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Springer Geography
Youjia Liang
Lijun Liu
Jiejun Huang
Integrated
Modelling of
Ecosystem Services
and Land-Use
Change
Case Studies of Northwestern Region of
China

Springer Geography

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Youjia LiangLijun LiuJiejun Huang
IntegratedModelling
ofEcosystemServices
andLand-UseChange
Case Studies of Northwestern Region
of China
123

Youjia Liang
Department of Resources
and Environmental Engineering
Wuhan University of Technology
Wuhan, China
Lijun Liu
Department of Navigation
Wuhan University of Technology
Wuhan, China
Jiejun Huang
Department of Resources
and Environmental Engineering
Wuhan University of Technology
Wuhan, China
ISSN 2194-315X ISSN 2194-3168 (electronic)
Springer Geography
ISBN 978-981-13-9124-8 ISBN 978-981-13-9125-5 (eBook)
https://doi.org/10.1007/978-981-13-9125-5
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Singapore

Preface
Humankind depends on land system of nature for its existence; its well-being and
related economic activity is connected with land system by numerous direct and
indirect ties. In addition, ecosystem services have become popular as the desig-
nation for all these beneﬁts that are useful to people in recent years. Land system
not only provides goods for the social-ecological system, such as food, energy, and
water for our daily existence, and industry products and medicinal plants for
healthcare, but also protect us against soil erosion and extreme climate events,
create the oxygen, and bind greenhouse gases by climate regulation, and provide
spiritual inspiration by diverse landscapes with esthetic pleasure, rest, and recre-
ation. However, people often are not even aware of the important role of ecosystem
services, or they see the land-based supply of nature simply as an endlessly bub-
bling without any restrictions and negative consequences. The assessment of
Millennium Ecosystem Assessment (2005) summarized that many types of
ecosystem services have reached their critical thresholds over the past decades.
Subsequently, integrated analysis with land system and ecosystem services supply
has become an important interdisciplinary researchﬁeld to provide the beneﬁts of
ecosystem services for human well-being.
In general, intensive Land-Use and Cover Change (LUCC) involves a complex
spatio-temporal change of the regulatory and sociocultural services rendered in a
typical human-activity area. It is important to identify and improve the available
standing of the nonmarketable and intermediate services by improving the under-
standing for the land-based social-ecological system and the dynamics between
diverse land properties, landscape functions and services, natural capital and their
various beneﬁcial effects at multiple spatio-temporal scales, and in connection with
their different driving forces. Integrated modeling and assessing the ecosystem
services provided by land-based landscapes is in accordance with the widespread
tendency of our society development. The arguments for integrated analysis of
ecosystem services need to be developed to persuade local stakeholders and policy
makers, and also to gain acceptance and support by business and social groups.
Generally, the quantitative results of integrated modeling of ecosystem service are
the standard is easily understood and spread (e.g., economical valuation of
v

ecosystem service) by land-use planning and eco-policy management, especially
outside of the scientiﬁc community.
This book prepared from the case studies provides to related readers with a
multiple view of integrated modeling of ecosystem services and land-use change in
different typical areas. The case studies were mainly conducted in the Zhangye
oasis of the Hexi corridor and the upper reaches of the Heihe river basin, also
including typical Loess plateau region (for wind power) and the inland waterways
of the Yangtze River (for the regulation of extreme events). The research in this
book is relevant to both local policy makers and scientists as issues faced by similar
areas such as ecosystem degradation under rapid economic development. The main
objectives of this book are as follows: (1) Analyzes the land-use change based on
different spatial and explicit LULC models; (2) Identiﬁes and simulates the different
change of ecosystem services from existing experiences by integrating the scientiﬁc
knowledge in theﬁelds of ecosystem assessment and integrated environment
modeling; and (3) Demonstrates how to integrate ecosystem services and land-use
change in different typical areas.
The authors hope that the present case studies based on our researches will
contribute the methodologies and application practices of integrated modeling of
ecosystem services and land-use change. The length of the book was limited, so
that, while some very essential aspects of this complex topic have been addressed in
our research, others, unfortunately, have not. In addition, we sincerely apologize to
those of our potential colleagues working in these similar researchﬁelds whom we
were unable to exchange academic views for reasons of space and limited time,
although the key references were summarized in every chapter of the book, and we
want to thank all for their contribution.
Tokyo, Japan Youjia Liang
[email protected] 2019
AcknowledgementsMost case studies in this book were supported by the National Natural
Science Foundation of China (NNSFC, 41601184). We are very grateful for the support from
NNSFC and related individuals. We also are very grateful for all the help from Springer and
related individuals in publishing the book. Finally, my grandmother passed away suddenly on 8th
of August 2017, with the book, I want to say thanks to you, for the wonderful years of care and
company.
vi Preface

Contents
Part I Integrated Modelling of Land-Use and Cover Change
1 An Integrated Modeling Analysis to LUCC Dynamic
at Regional Scale
....................................... 3
1.1 Integrated Analysis Approach of LUCC
.................. 4
1.2 Study Area and Data
................................ 5
1.2.1 Study Area
................................ 5
1.2.2 Data Processing
............................. 6
1.3 Description of the IA Method
......................... 6
1.3.1 SD Model
................................. 7
1.3.2 CLUE-S Model
............................. 11
1.4 Application of the Integrated Model
..................... 12
1.4.1 Demand Simulation of Land-Use Types
........... 12
1.4.2 Spatial Distribution of Land-Use Pattern
........... 14
1.4.3 Assessment of Landscape Pattern Change
.......... 14
1.5 Discussion and Conclusion
........................... 16
References
............................................ 17
2 Modeling Urban Growth with CA Model at Regional Scale
......19
2.1 Urban Growth Modeling with CA Model
................. 19
2.2 Description of Urban Growth Model
.................... 21
2.2.1 Study Area
................................ 21
2.2.2 Data
..................................... 23
2.2.3 SLEUTH Model
............................. 24
2.3 Application of SLEUTH Model
........................ 29
2.3.1 Calibration of SLEUTH
....................... 29
2.3.2 Accuracy Validation
.......................... 32
2.3.3 Simulation of SLEUTH
....................... 33
2.4 Discussion and Conclusion
........................... 35
References
............................................ 37
vii

3 Vegetation Change Detection Using Trend Analysis
and Remote Sensing
.................................... 39
3.1 Detection of Vegetation Change
....................... 39
3.2 NDVI Time Series Analysis
.......................... 41
3.2.1 Study Area
................................ 41
3.2.2 Data Processing
............................. 43
3.2.3 Trend Analysis of Vegetation Change
............. 44
3.2.4 Assessment of Spatial NDVI Change
............. 46
3.3 Application of NDVI Time Series Analysis
............... 48
3.3.1 NDVI Trends from 1975 to 2010
................ 48
3.3.2 Spatio-Temporal Relationship of NDVI,
Precipitation, and Temperature
.................. 50
3.3.3 Spatial Patterns of NDVI Change Using Landscape
Metrics
................................... 52
3.4 Discussion and Conclusions
.......................... 54
References
............................................ 55
Part II Integrated Modelling of Ecosystem Services
4 Modeling of Wind Power Service with CFD and Kalman
Filtering
............................................. 61
4.1 Introduction of Wind Power Service
.................... 61
4.2 Modeling Framework of Wind Power Service
............. 63
4.2.1 Data Processing
............................. 63
4.2.2 CFD Model
................................ 65
4.2.3 Kalman Filter Model
......................... 66
4.2.4 Statistical Analysis
........................... 67
4.2.5 Beneﬁt Assessment of Wind Power Service
.........69
4.3 Application of Wind Power Service Models
............... 71
4.3.1 Analysis on the Characteristics of Wind Power
......71
4.3.2 CFD-Based Simulation of Spatial Wind Speed
.......72
4.3.3 Correction of Wind Speed Using Kalman Filtering
....75
4.3.4 Assessment of Wind Power Supply
............... 76
4.4 Discussion and Conclusion
........................... 79
References
............................................ 80
5 Modeling of Hydrologic Regulating Service at Regional Scale
....83
5.1 Introduction of Hydrologic Regulating Service
............. 83
5.2 Integrated Modeling of Hydrologic Regulating Service
.......84
5.2.1 Study Area
................................ 84
5.2.2 Data Processing
............................. 85
5.2.3 Hydrology Unit Model
........................ 86
viii Contents

5.2.4 Opportunity Cost Model....................... 89
5.2.5 MD Model
................................ 89
5.3 Application of Integrated Hydrologic Regulating Service
Model
.......................................... 90
5.3.1 Application of Hydrology Model
................ 90
5.3.2 Assessment of Hydrology Regulating Service
.......92
5.4 Discussion and Conclusions
.......................... 93
References
............................................ 94
6 Assessing Climate Regulating Service for Extreme Weather
......95
6.1 Introduction of Extreme Weather Processes
............... 96
6.2 Integrated Assessment Method of Extreme Weather
.........97
6.2.1 Study Area
................................ 97
6.2.2 Identiﬁcation of the Impact Indices
............... 98
6.2.3 Data Analysis
.............................. 101
6.3 Analysis of the Extreme Weather Phenomena
.............. 102
6.3.1 Heavy Rainfall
.............................. 102
6.3.2 Heat Wave
................................. 104
6.3.3 Cold Spell
................................. 105
6.3.4 Wind Gust
................................. 106
6.3.5 Storm
.................................... 107
6.4 Discussion and Conclusions
.......................... 108
References
............................................ 112
7 Assessing the Valuation of Multiple Ecosystem Services
.........115
7.1 Economic Valuation of Multiple Ecosystem Services
........115
7.1.1 Introduction of Ecosystem Service Valuation
........115
7.1.2 Method of Ecosystem Service Valuation
...........116
7.1.3 Application of Ecosystem Service Valuation
........117
7.1.4 Discussion and Conclusion
..................... 119
7.2 Assessing the Relationship Between Urbanization
and Carbon Sequestration/Loss
........................ 122
7.2.1 Introduction of Urbanization and Carbon
Sequestration/Loss
........................... 122
7.2.2 Integrated Assessing Method of Urbanization
and Carbon Change
.......................... 123
7.2.3 Application of Integrated Assessment Between
Urbanization and Carbon Change
................ 126
7.2.4 Sensitivity Analysis of LUCC Patterns on Carbon
Change
................................... 128
7.2.5 Conclusion
................................ 130
References
............................................ 131
Contents ix

Part III Integrated Modelling of Ecosystem Services
and Land-Use Change
8 Simulating Land-Use Change and Its Effect on Biodiversity
......135
8.1 Introduction of Biodiversity Conservation
................ 135
8.2 Integrated Modeling of Land-Use and Biodiversity
..........136
8.2.1 Study Area
................................ 136
8.2.2 Data
..................................... 138
8.2.3 Simulating Method of Biodiversity Conservation
.....139
8.2.4 Land Management Scenarios in the Watershed
......140
8.3 Application of the Integrated Modeling of Land-Use
and Biodiversity
................................... 140
8.3.1 Changes of Land-Use/Cover Pattern
.............. 140
8.3.2 Changes in Biodiversity
....................... 145
8.3.3 LUCC Pattern Impact on Biodiversity
.............147
8.4 Discussion and Conclusions
.......................... 148
References
............................................ 150
9 Integrated Ecosystem Services Assessment in Urbanizing
Regions
.............................................. 153
9.1 Introduction of Integrated Ecosystem Services Assessment
....153
9.2 Integrated Modeling of Ecosystem Services Assessments
.....154
9.2.1 Study Area
................................ 154
9.2.2 Land Management Scenarios
.................... 155
9.2.3 Data
..................................... 156
9.2.4 Ecosystem Services Assessment
................. 156
9.3 Application of Integrated Ecosystem Services Assessments
....162
9.4 Discussion and Conclusions
.......................... 164
References
............................................ 166
10 Impact Assessment of LUCC on Ecosystem Services
...........169
10.1 Integrated Impact Assessment of LUCC and Ecosystem
Services
......................................... 169
10.2 Method of the Integrated Impact Assessment
.............. 171
10.2.1 Study Area
................................ 171
10.2.2 Methodological Overview
...................... 172
10.3 Application of the Integrated Impact Assessment
...........175
10.3.1 Spatiotemporal change in LUCC Patterns
..........175
10.3.2 Assessment of Supply of ESs from LUCC
dynamics
.................................. 176
10.3.3 Potential Impacts of Land-Use Forms
on LUCC-ESs Nexus
......................... 178
10.4 Discussion and Conclusion
........................... 180
References
............................................ 181
x Contents

Part I
Integrated Modelling of Land-Use
and Cover Change

Chapter 1
An Integrated Modeling Analysis
to LUCC Dynamic at Regional Scale
Land-use and cover-change (LUCC) models are useful tools for analyzing different
LUCC dynamic and their driving forces, also in assessing ecological impacts and
consequences of LUCC dynamics and decision-making for land-use planning. How-
ever, single model is not able to capture all the essential key processes to explore
LUCC dynamic at different spatial-temporal scales and make a full assessment of
driving factors and macro-ecological impacts. An integrated analysis (IA) approach
was developed to analyze land-use dynamics at multiple spatio-temporal scales, by
integrating system dynamics (SD) model, the Conversion of Land-Use and its Effects
at Small regional extent (CLUE-S) model and landscape indices method. The SD
model was used to calculate and predict quantity demands for the area of differ-
ent land-use types at the macro-scale as a whole during the research period. Then,
the LUCC process was simulated at a high spatial resolution using the CLUE-S
model, considering the spatial land-use policies and restrictions to satisfy the bal-
ance between demand and supply of LUCC dynamic. Kappa values of the map
simulation are used to reﬂect the accuracy of the integrated model. We also evalu-
ated the macro-ecological effect of LUCC and optimized scenario managements of
land-use by using landscape indices method. The IA approach could be used for bet-
ter understanding the complexity of land-use change and provide scientiﬁc support
for land-use planning and management, and the simulation results also could be used
as source data for scenario analysis of different ecosystem service processes based
on different underlying surface of LUCC dynamic. We selected Ganzhou District
of Zhangye oasis in northwest China as a case study for the application of the IA
method.
© Springer Nature Singapore Pte Ltd. 2020
Y. L i a n g e t a l . ,Integrated Modelling of Ecosystem Services
and Land-Use Change, Springer Geography,
https://doi.org/10.1007/978-981-13-9125-5_1
3

4 1 An Integrated Modeling Analysis …
1.1 Integrated Analysis Approach of LUCC
Increased effort has been made to understand the process trends and driving forces
of LUCC dynamic and its ecological consequences in fragile ecological regions (Liu
and Deng2010; Ojima et al.2002; Turner et al.2007). Simulating the processes
of LUCC are crucial for land-use planning and environment management (Lambin
and Geist2006). LUCC process is determined by the spatio-temporal interactions
between natural and human driving factors at different scales (Julie et al.2005;
Verburg et al.2008).
LUCC models are useful quantitative tools for analyzing driving forces and change
of LUCC dynamic. In the past decades, scientists have developed different spatial
explicit models for LUCC simulation in different case studies (Verburg et al.2004),
but no single model is capable of seizing all processes of LUCC dynamic at the
different spatio-temporal scales (He et al.2005; Liu et al.2002; Verburg et al.2008).
Such spatial explicit models have their own potential advantages and shortcomings
in the different applications of case studies. Some LUCC models only can be used
to represent single LUCC process or cannot show the quality evaluation of model
results. In order to address the gap for these important aspects to LUCC modeling,
it is necessary to develop an IA approach which can better reﬂect multi-scale LUCC
characteristics, and explicitly simulate spatial-temporal dynamics of LUCC (Ye et al.
2002). In addition, the IA approach also can be used to evaluate the quality of LUCC
results (Liang et al.2010). Developing an integrated modeling framework is the
fundamental requirement for integrating existing LUCC models and other available
approaches, which also could be a feasible and potential solution for improving the
methodology of land-use science (Ewers2006; Kalnay and Cai2003; Quang et al.
2008; Verburg et al.2004).
SD method can be used to analyze various complex problems in different disci-
plines (Forrester1971). Further, SD model can be used to simulate system change
with computer models for solving complicated management problems, which also
can predict different land-use demands based on speciﬁc socioeconomic conditions
in land-use science (Rizzo et al.2006;Stave2003). It is important to develop a SD
model for reﬂecting human activities and corresponding change in land-use demands
caused by their potential consequences. However, the ability of SD model to reﬂect
spatial change in different land-use types is still limited (Liang and Xu2011).
CLUE-S model is speciﬁcally developed for spatially explicit simulation of land-
use change based on an empirical analysis of location suitability, by combining with
dynamic simulation of competition and interactions between spatial and temporal
dynamics of land-use systems (Kok et al.2007; Veldkamp and Fresco1996;Verburg
et al.1999). Existing researches also have well documentation that the model is
available for multiple scenarios setting under different social-ecological conditions
of future land-use (Castella et al.2007; Eickhout et al.2007). However, the model
lacks the ability to represent the macro-demand for land-use. In such cases, other
available models were introduced to calculate macro-land-use demands at speciﬁc

1.1 Integrated Analysis Approach of LUCC 5
spatio-temporal scale, which have become a feasible solution for improving the
limitation of the CLUE-S model (Aspinall2004; Liang et al.2010;Wuetal.2010).
In this case study, an IA approach was developed by the combination of CLUE-S
model and SD model at regional scale, and then integrating with landscape indices to
evaluate the macro-ecological effect of spatio-temporal LUCC dynamic. The main
objectives of the case study are as follows: (1) developing a SD model to calculate
and predict demands of different land-use types at the macro-scale as a whole, which
are based on the inﬂuence of different human driving factors; (2) simulating explicit
LUCC processes using CLUE-S model based on demand-driven at a temporal scale;
and (3) evaluating the macro-ecological effect of LUCC dynamic to optimize scenario
management, and also discuss the uncertainty of the integrated analysis approach.
1.2 Study Area and Data
1.2.1 Study Area
Ganzhou District was selected as the study area, which is located in Zhangye City
of Gansu Province, with a total area of 4240 km
2
(Fig.1.1), and it is also famous
as a typical desert oasis located in the middle reaches of the Heihe River in north-
western China (38°39

–39°24

W, 100°6

–100°52

E). In administrative division, it is
Fig. 1.1Location of the study area

6 1 An Integrated Modeling Analysis …
adjacent to Shandan, Gaotai, Linze, Minle, and Sunan counties, and is the economic
and cultural center of Zhangye City. The landform of this area is about an average
elevation of 1474 m above sea level. The average annual precipitation of the region is
113–120 mm, and annual evaporation is 2047 mm. Over the past few decades, local
vegetation and soil have changed signiﬁcantly due to large-scale land cultivation
and irrigation activities. Thus, the most typical LUCC pattern in the study area is
farm-based land-use with large-scale intensiﬁed agricultural activities.
1.2.2 Data Processing
First, Remote Sensing (RS) data was used to characterize LUCC pattern in the study
area, including three Landsat Thematic Mapper (TM) images in August 1996, July
2000 and July 2005 separately, and the initial data was obtained from the Digital River
Basin website (http://heihe.westgis.ac.cn/). Geo-rectiﬁcation and mosaic of these
images were conducted using ERDAS image processing software and 1:50,000 scale
topographic maps. And then, we obtained three land-use maps, identifying six general
land-use type, including farmland, woodland, grassland, water area, construction
land, and unused land. Based on the information provided by local residents and
on-site visits, the classiﬁcation accuracy of the land-use types was estimated to be
94, 96, and 95% for 1996, 2000, and 2005, respectively.
Besides RS data, other auxiliary data also were collected for the IA modeling,
mainly including Digital Elevation Model (DEM) data with 100 m resolution, slope
and aspect maps created by DEM data using ArcGIS software, depth and quality
of groundwater in 2000, hydro-geological map (dividing into two types plain–pore
water of the quaternary loose deposits; and mountain–former quaternary bedrock ﬁs-
sures, karsts erosion water and layered water), and soil map at the scale of 1:100,000
(including four categories: desert soil, chestnut soil, gray calcium soil, and meadow
soil). Road and boundary maps came from Chinese basic geographic information at
the scale of 1:4,000,000 (http://nfgis.nsdi.gov.cn/). Population density map was built
by statistical population data of 2000, and the socioeconomic data mainly obtained
from the Statistical Yearbook of Ganzhou District during 1996–2005.
All of these raster data uniformly projected into Transverse Mercator projection,
and reproduced with 500 m resolution by ArcGIS. Based on the aforementioned
data, an integrated GIS database for the study area was developed by merging RS,
biophysical, and census data in the raster or vector format.
1.3 Description of the IA Method
We mainly developed an IA approach by integrating the SD and CLUE-S models to
simulate the spatial-temporal LUCC processes in the study area. SD model was used
to simulate the demand for land-use types as a whole at the temporal scale. CLUE-S

1.3 Description of the IA Method 7
Fig. 1.2Methodological framework of the case study
model was used to simulate spatial dynamics and conduct top-down implementation
for the spatial allocation of land-use types. Finally, the macro-ecological effect and
scenario managements of land-use pattern was conducted by using landscape indices
(Fig.1.2).
1.3.1 SD Model
The SD model has been proven to be a useful tool for analyzing the complex con-
nection between LUCC dynamics and socioeconomic development, and it also was
used to reﬂect different socioeconomic development scenarios at speciﬁc temporal
scales (Deng et al.2004; Fang and Bao2004; Hilty et al.2006).
The SD model in this case study was divided into two sections, including the
modules of driving forces and land-use change. The driving force module dealt with
the impact of nonspatial human factors on land-use change. The land-use part focused
on the interaction and conversion between LUCC types driven by nonspatial human
and natural factors, which was built based on Markov transition matrix by contrasting
two images in 1996–2000, and connected with driving force by using two driving
force coefﬁcientsKandM, indicating the change of farmland and construction land,
respectively.
Finally, the SD modeling software STELLA7.0 was used to design the stock and
ﬂow diagram according to the causal loop diagram of SD model which automatically
generated the corresponding equations based on the designed stock and ﬂow diagram
(Fig.1.3). The main variables in this model were shown in Table1.1.Themain
equations of SD model are as follows:
A(t)=A(t−dt)+(A5+A3+A2+A4+A1−A6−A8−A9−A10−A7)∗dt
(1.1)

8 1 An Integrated Modeling Analysis …
Fig. 1.3Feedback relationships between different LUCC types in SD model (Dashed shows driving
forces)
Table 1.1The main parameters used in the SD model
Factors AbbreviationsFactors Abbreviations
Farmland A Speciﬁc investment SI
Woodland B Water investment WI
Grassland C Mining land M_area
Water area D Speciﬁcally land S_area
Construction land E Trafﬁc land T_area
Unused land F Demand for A F_area
Change of E E_sum Rural habitation C_area
GDP growth G_add Urban land Uarea
Demand for food F_demand Water land W_area
Trafﬁc investment TI Rural population C_pop
Mining investment MI Total population Totalpop
Demand for W_area W_occupy Food self-sufﬁciency rateCrop_ratio
Demand for S_area S_occupy Gross Domestic ProductGDP
Demand for T_area T_occupy Mechanical pop growth rateMg_rate
Urban population Urban_pop Growth rate of nature popNg_rate
Growth rate of GDP G_ratio Urban land per capita U_per_area
Residential land per capitaC_per_area

1.3 Description of the IA Method 9
B(t)=B(t−dt)+(B 4+B6+B3+B1+B2−A5−B7−B8−B5−B6)∗dt
(1.2)
C(t)=C(t−dt)+(B
7+C2+C3+C1+A10−B4−C6−C4−C5−A1)∗dt
(1.3)
D(t)=D(t−dt)+(C
6+D1+D2+A9+B6−C2−D4−A2−D3−B2)∗dt
(1.4)
E(t)=E(t−dt)+(D
4+E1+A8+B5+C5−D1−A3−E2−C1−B1)∗dt
(1.5)
F(t)=F(t−dt)+(C
4+E2+D3+B8+A7−C3−D2−E1−A4−B3)∗dt
(1.6)
A
0=1140.9249∗K+F_demand∗Crop_ratio∗F_area/Yield∗(1−K)
(1.7)
E
0=E_sum∗M+10.0922∗(1−M) (1.8)
E_sum=M_area+S_area+T_area+W_area+C_area+U_area
(1.9)
IM_area(t)=MI_area(t−dt)+MI∗I_occupy∗dt (1.10)
S_area(t)=S_area(t−dt)+SI∗S_occupy∗dt (1.11)
T_area(
t)=T_area(t−dt)+TI∗T_occupy∗dt (1.12)
W_area(t)=W_area(t−dt)+WI∗W_occupy∗dt (1.13)
C_area=C_pop∗C_per_area (1.14)
U_area=Urban_pop∗U_per_area (1.15)
Total_pop(t)=Total_pop(t−dt)+Total_pop∗(Ng_rate
+Mg_rate)∗dt
(1.16)
GDP(t)=GDP(t−dt)+GDP∗G_ratio∗dt (1.17)
The area values of six land-use types at timetare shown in Eqs.1.1–1.6, and
A
x−Eyare conversion coefﬁcients of different land-use types in these equations.
The initial value of farmlandA
0and construction landE 0which are directly linked
to human activities, and they were calculated using Eqs.1.7–1.8.E_sumindicates

10 1 An Integrated Modeling Analysis …
construction area under the disturbance of human activities, which are generated in
Eqs.1.9–1.15. The change in population and GDP are calculated in Eqs.1.16–1.17.
We selected the data of 1996 as a baseline for the simulation of SD model. The
model was calibrated with historical land-use data in 2000 and 2005. The values of
KandMis 0.81 and 0.35, respectively. The SD model is reliable with <4.5% relative
errors of simulation results compared with reference data (Table1.2), and this model
can be used to simulate future macro-demand for LUCC types in the study area.
Based on local statistical social-economic information from 1996 to 2005, and
related macro-economic planning and policies at the provincial and national level,
ﬁve aspects were deﬁned to reﬂect the key inﬂuence factors of macro-scale land-
use demands, including economic growth, population increase, urbanization, food
supply, and technology development (representing as the indicator of growth rate of
food production) (Table1.3). Then, according to the combination of these variable
settings, three future socioeconomic scenarios have been deﬁned and their demand
for speciﬁc land-use areas can be predicted during 2005–2035 using the SD model.
Scenario 1 shows the potential speed-up development of socioeconomic aspects.
Scenario 2 is the reference which basically keeps the present pace with social and
economic development. Scenario 3 is ecological which is favorable to ecological
improvement.
Table 1.2The precision and validation of SD model
LUCC types
(hm
2
)
2000 2005
ObservationSimulationErrors (%)ObservationSimulationErrors (%)
Farmland 95,116 94,303 −0.85 92,345 93,093 0.81
Woodland 2861 2850 −0.38 572 564 −1.39
Grassland41,975 42,280 0.72 56,574 57,194 1.09
Water area 2788 2663 −4.49 4393 4537 3.27
Construction
land
12,181 12,223 0.34 31,574 32,151 1.82
Unused land 210,526 211,142 0.29 179,989 179,078 −0.49
Table 1.3Scenarios design based on the key indicators of social-economic condition in the study
area
Indicators 1996–2000Scenario 1Scenario 2Scenario 3
Growth rate of GDP (%) 8.81 10 8.5 7
Growth rate of nature pop (‰)6.23 8 6 4
Urbanization (%) 23.29 40 30 20
Food self-sufﬁciency rate (%)95 110 100 90
Growth rate of food production (%)1 1.3 1 0.7

1.3 Description of the IA Method 11
1.3.2 CLUE-S Model
Given its ability to represent multi-scale land change, the CLUE-S model has been
applied in case studies with high-resolutions at local or regional scales (Huang and
Cai2005; Verburg and Overmars2009). The CLUE-S model considers the following
four parts which contain land-use demand, spatial policy and restrictions, location
characters and speciﬁc conversion settings of land-use types (Fig.1.4).
(1) Land-use demand: land demand for different land-use types are calculated using
the SD model (see detail in Fig.1.3).
(2) Spatial policy and restrictions: the model accounts for spatial policy and restric-
tions for the speciﬁc land-use type that affects the conversion and causes differ-
ences in spatial-temporal behavior. Spatial change from farmland area into other
LUCC types are usually restricted, particularly due to the protection policy of
basic farmlands in China. In the case study, the large farmland and construction
land are not allowed to be converted to other land-use types.
(3) Location characters: demand for land by different land-use types determines
the overall competitive capacity of the different LUCC types. The location
characters in this study include 12 driving factors (Table1.4). Logistic regression
method is used to indicate the probability of a certain grid cell to be devoted to
a land-use type given a set of potential driving factors following:
ln
β
Pi
1−Pi
∗
=β0+β1X1,i+β2X2,i···+βnXn,i (1.18)
wherePiis the probability of a grid cell for the occurrence of the considered land-
use typei, andXiindicating the driving factors. The value of Relative Operating
Characteristics (ROC) is used to indicate the validation of the model (Hanley and
McNeil1982; Pontius and Schneider2001).
By using ArcGIS, the raster maps were generated into ASCII ﬁles for analyses
with SPSS software 14.0. The coefﬁcient value of driving factors of different land-
use types in 2000 is presented in Table1.4. The order of different ROC curve values
Fig. 1.4Modeling framework of the CLUE-S model

12 1 An Integrated Modeling Analysis …
Table 1.4Theβvalue of the logit model for different land-use types in the study area (p< 0.01)
Driving
force
FarmlandWoodlandGrasslandWater ConstructionUnused land
Population density 0.0165 −0.3155
Desert soil−0.6737 1.3471−0.2052
Chestnut soil 0.9816 1.1937
Gray
calcium soil
−1.0417 0.4998
Meadow soil
Altitude 0.00340.0042 −0.0036 −0.0027
Slope −0.0061−0.0897−0.0405 −0.3625
Aspect −0.3545 −0.0025 0.0020
Road
accessibility
−0.0013 −0.0002−0.0002 0.0001
Groundwater
depth
−0.0002−3.2908 −0.0118 0.0092
Piedmont 0.5312−2.87343.7850 −1.1643
Mountain 3.3113 −3.8755 1.1811
Constant 7.2465−10.8617−9.6972−0.7181−0.4024 4.4578
are: farmland (0.880) > unused land (0.84) > construction land (0.830) > water area
(0.808) > grassland (0.774) > woodland (0.739). The best performance with selected
factors is farmland; the spatial distribution of all land types could well be explained
by the selected driving variables when all the ROC curve values are more than 0.7.
(4) Land-use type speciﬁc conversion setting: because of the different conversion
possibilities among land-use types, conversion coefﬁcient is usually from 0 to
1. 1 means that the conversion barely occurs, such as urban land convert to
agricultural land; 0 means that the type can convert to any other land type, the
higher the deﬁned elasticity, the more difﬁcult it is to convert this land-use type.
1.4 Application of the Integrated Model
1.4.1 Demand Simulation of Land-Use Types
SD model was used to simulate demand of land-use types under three scenarios (see
Table1.3) with yearly time steps during 2000–2035, and the results were shown in
Table1.5and Fig.1.5.
The results showed that there are no obvious differences in LUCC types of wood-
land, water area, and construction land under different scenarios, especially, there

1.4 Application of the Integrated Model 13
Table 1.5Simulation of land-use types demand in typical years of 2015, 2025, and 2035 (units:
hm
2
)
ScenariosFarmlandWoodlandGrasslandWater
area
ConstructionUnused land
2015Scenario 189,492296 61,2564965 45,158 164,295
Scenario 296,466289 59,4124979 45,843 158,473
Scenario 3101,115284 58,1774990 46,322 154,574
2025Scenario 185,712236 62,5495434 60,840 150,691
Scenario 291,437230 60,6775447 61,714 145,957
Scenario 395,254225 59,4225456 62,314 142,789
2035Scenario 182,599222 61,4015740 73,087 142,412
Scenario 287,311217 59,6635754 74,069 138,448
Scenario 390,453213 58,4995763 74,738 135,795
Fig. 1.5Simulation of land-use types demand with SD model during 2000–2035 (units: hm
2
)
is an obvious collinear character between woodland and water area. The possible
reason is the areas of two land-use types are very small which is difﬁcult to reﬂect
the difference by interpretation data.

14 1 An Integrated Modeling Analysis …
1.4.2 Spatial Distribution of Land-Use Pattern
The Kappa statistic was employed to evaluate the accuracy of CLUE-S model results,
which was ﬁrst proposed in 1960, and it is usually used to evaluate the accuracy of
remote sensing image classiﬁcation (Bai et al.2005; Liu et al.2009; Zeledon and
Kelly2009). In this study, the Kappa values of LUCC maps are 0.86 and 0.81 in
2000 and 2005 separately. For different land-use types, the relative differences of
the simulation by CLUE-S model and the actual areas are 0.29–4.49% from 2000 to
2005.
Figure1.6shows the explicit simulation result of future LUCC pattern based on
three scenarios in 2015, 2025 and 2035. The central parts in the study area have obvi-
ous changes under different scenarios, which is the key area of the Zhangye oasis,
and is famous as the national production base of corn seed under complete irrigation
agriculture system. Such an area was affected by insensitive human activities under
different socioeconomic development scenarios. In addition, grassland in the north-
east region of the study area also has obvious change at the pixel scale, because of
the dominant human activity for grazing, which also affected by the local land-use
planning and ecosystem management. Changes in different LUCC types under three
scenarios showed that the scenario design can be used to reﬂect different developing
pathways in the study area.
1.4.3 Assessment of Landscape Pattern Change
According to landscape pattern change analysis, we can understand macro-ecology
effect of LUCC progress in the study area and optimize the land-use management
based on optional scenarios (Cushman and David2000). In this study, we evaluated
the simulation results at landscape scale based on three scenarios by using two
landscape indices which are the interspersion and juxtaposition index (IJI) and the
contagion index (CONTAG). IJI index can reﬂect the constrained distribution variety
of ecosystems (Wu2007). IJI value is generally low in the mountain’s vertical zones
and high in the arid region. In this case study, the values of IJI are generally higher
than 66% and the basic trend is similar during the study period (Fig.1.7).
CONTAG index can describe the landscape in different types of agglomeration
patch (Wu2007). In general, a high value means the spread of the landscape patch
types has good connectivity, and low value means a higher landscape fragmentation.
It can be seen from Fig.1.7, the CONTAG value of scenario 3 signiﬁcantly increased
from 97.3 after 2030, showing the ecological protection characteristic of the speciﬁc
scenario. By using different prediction indices, different scenario managements of
land-use can be chosen for better understanding of the macro-ecological effect in the
speciﬁc study area. The landscape indices approach can forecast accurate results of
different scenarios.

1.4 Application of the Integrated Model 15
2015 2015 2015
2025
2025
Scenario2
Scenario
1
Scenario3
2025
2035 2035 2035
Woodland Grassland Construction landFarmland Water area Unused land
Fig. 1.6Simulated LUCC dynamics in the study area based on three scenarios during 2015–2035
Fig. 1.7Changes of IJI (left) and CONTAG (right) on landscape pattern in 2000–2035

16 1 An Integrated Modeling Analysis …
1.5 Discussion and Conclusion
It is important to realize that no single model is able to reﬂect all key LUCC processes
at different spatial-temporal scales (Verburg et al.2008), and also can not include
all relevant driving factors to make a full assessment of LUCC. Each LUCC model
has its own potential and constraints. Based on multi-scale characteristics, this study
accounted for an IA approach by combining of SD, CLUE-S, and landscape indices
methods, which could improve the level of LUCC analyses, and also better predict
future changes of LUCC based on different scenarios.
Integrating SD modeling technology and methodology of land surface process
research is an important issue worthy of future research. The human factors analysis
can be added into the evolution research of ecosystems for achieving the combination
of human factors and the natural elements by using SD modeling approach, which
can fully reﬂect the evolution of the system architecture, and integrated analysis for
different factors of ecological-economics system is very signiﬁcance. The SD model
is used to calculate demand of areas change for different land-use types as a whole,
while the CLUE-S model was used to transfer the demand to spatially explicit LUCC
patterns at a reasonable scale with the spatial consideration of land-use suitability
in the study area, landscape indices approach evaluated the LUCC simulation result
that could help choose a special management scenario of LUCC.
By setting different development scenarios, changes can be found especially for
hot spot areas. The performance of integrated LUCC model does not work well for
urban areas, considering the study area is located in the northwest inland river basin of
China, and urban areas are small. In addition, the deﬁnition of conversion coefﬁcient
in the CLUE-S model is based on the user’s knowledge of the study area, and settings
of the coefﬁcient have an important inﬂuence on the results. The prepared resolution
of map data is 500 m, and running time is reasonable (about half an hour) in Windows
XP PC. Sensitivity issues based on scale changes could be devoted to research in
future research.
This paper developed an IA approach to understand the characterization and pre-
sentation of LUCC processes by combining CLUE-S, SD and landscape indices
methods, which gave insight into a better understanding of the possible impacts of
LUCC on terrestrial ecosystems and provided scientiﬁc support for land-use plan-
ning and scenario management. The simulation results also could be used as a source
data for scenario analysis of different hydrological and ecological processes based
on different underlying surface of LUCC.
The successful application of the IA approach proves that the integration of exist-
ing models and approaches based on the multi-scale characteristics of LUCC within
a single modeling framework could be a feasible solution because it is able to reﬂect
the complexity of the land-use system and capture key processes of land-use change
at different scales. Furthermore, the identiﬁcation and spatialization of driving fac-
tors (especially human factors, such as social capital, cultural types) of LUCC is
an important issue, and integrate these factors into the IA framework, which can
enhance the simulation accuracy of LUCC based on IA approach.

References 17
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Chapter 2
Modeling Urban Growth with CA Model
at Regional Scale
In recent years, arid areas in northwest China has witnessed rapid urban growth
and excessive agricultural activities, mainly because of its economic development
and increasing population pressure. In this study, a typical arid area was selected as
the case study area, and aimed to understand the growth dynamics of the region, to
forecast its future expansion, and to provide a basis for regional management. We
calibrated and validated a SLEUTH model with historical data derived from different
sources, which comprised remotely sensed and strategic planning data records from
1995 to 2009. Further, three scenarios based on local regional ecological planning
were designed to simulate the spatial pattern of urban growth in different condi-
tions. The ﬁrst scenario allowed urban expansion without any additional managed
growth limitations and the continuation of the actual historical trend. The second sce-
nario was limited based on environmental considerations and managed growth was
assumed with moderate protection. The third scenario simulated managed growth
with strict protection on wetland reserves and productive agricultural areas in the
study area. We consider that the results of these models of growth in the study
area obtained under different scenarios are of great potential use to city managers
and stakeholders. We also suggest that scale sensitivity and spatial accuracy are
among the factors that must be considered in practical applications. We urge future
researchers to build on the present study to produce models for similar regions in
northwest China.
2.1 Urban Growth Modeling with CA Model
Urban growth is among the most signiﬁcant processes that shape the earth’s ecosys-
tems (Ahern2013; Seto and Fragkias2005), particularly in regions where rapid
economic and population development have reduced the amount and distribution of
natural resources that provide vital services to society (Tian et al.2014). In addition,
© Springer Nature Singapore Pte Ltd. 2020
Y. L i a n g e t a l . ,Integrated Modelling of Ecosystem Services
and Land-Use Change, Springer Geography,
https://doi.org/10.1007/978-981-13-9125-5_2
19

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Kagayan Sulu, by a separate treaty in November, 1900. Its close proximity to Borneo
renders it a convenient stopping place for small Moro boats navigating between Borneo
and Sulu. Sitanki, an island and town, is the trade center of this group, and has just lately
been made an open port.
Island of Sulu
Geographical features
Sulu is an island of irregular shape and among the islands of the Archipelago is next in
size to Basilan. Its longest diameter runs east and west and approximates 37 miles, while
its average length does not exceed 32 miles. Its greatest width is 14 miles and its average
width about 10 miles. The main structure of the island is volcanic, but it is surrounded
with a coral reef formation, which is most extensive in the bays and on the south.
Two indentations of the northern shore at Jolo and Si’it and two corresponding
indentations of the southern shore at Maymbung and Tu’tu’, divide the island into three
parts—western, middle, and eastern.
The Bay of Jolo is quite open and faces the northwest. It is very shallow near the shore
and its head constitutes the roadstead of Jolo. The Bay of Maymbung is a deeper
indentation, but it is narrower and shallower than the Bay of Jolo. The town of
Maymbung lies at the head of the bay and is about 9 miles south of Jolo in a direct line.
The Bays of Si’it and Tu’tu’ indent the island to such an extent as to leave only a neck of
land, less than 4 miles wide, connecting the middle and eastern parts of the island. The
settlement of Si’it lies at the head of the bay and in the immediate vicinity of a small
lake of the same name. The shores of the Bay of Tu’tu’ are marshy and are covered with
mangrove trees. The bay is very shallow to a considerable distance from shore. Tu’tu’ is
the principal settlement near the head of the bay.

Sulu Island.
The backbone of the island is a mountain range which runs east and west and lies nearer
to the northern shore. The highest point is Mount Tumangtangis, at the western extremity
of the range. This mountain reaches a height of 853 meters above sea level and descends
very rapidly to the western coast near Timahu. A spur of the mountain terminates in
Point Pugut at the northwestern extremity of the island.5
Toward the east, the ridge descends to a much lower level at Bud Datu, Bud Agad, and
Bud Pula, which lie immediately to the south of Jolo. It rises again in Mount Dahu to an
altitude of 716 meters. Mount Dahu is a prominent landmark and forms the most
picturesque landscape in the background of Jolo. It is a steep and conical extinct
volcano, similar to, but smaller and more regular in form than Mount Tumangtangis.
East of Mount Dahu is another gap in which lies Tambang Pass. Beyond this the range
rises again at Mount Tambang and continues uninterrupted to Mount Sinuma’an, at the
extreme end of Lati, and Mount Bagshag. After Mount Bagshag the range descends
gradually toward Su’ and Si’it. The northern slopes of Mount Tumangtangis and Mount
Dahu, and the crest of Bud Datu are covered with grand forests, while the crests and
lower slopes of Bud Agad and Bud Pula are partly cultivated and partly covered with tall
grass.
From the shores of the Bay of Jolo the land rises gradually and presents a beautiful green
appearance. The northern aspect of this whole range and its beauty were appropriately
described by Mr. Hunt, as follows:
There are few landscapes in the world that exhibit a more delightful appearance than the
seacoasts of Sulu; the luxuriant variety of the enchanting hills exhibits a scenery hardly ever
equaled and certainly never surpassed by the pencil of the artist. Some with majestic woods that

wave their lofty heads to the very summits; others with rich pasturage delightfully verdant, with
here and there patches burnt for cultivation, which form an agreeable contrast with enameled
meads; others, again, exhibit cultivation to the mountain top, checkered with groves affording a
grateful variety to the eye—in a word, it only requires the decorations of art and civilized life to
form a terrestrial paradise.6
To the south of Bagshag7 lies a small extinct volcano called Panamaw or Pandakan,
whose crater is now a lake. East of Si’it rise the Lu’uk mountains of Urut, Upao, and
Tayungan. From these the range extends to Bud Tandu at the eastern extremity of the
island.
The highlands near the southern coast of the island divide into three separate regions.
The first and westernmost lies west of Maymbung and forms the principal highlands of
Parang. The highest points in this region are Mount Tukay, east of the town of Parang,
and Mount Mabingkang, east of Tukay. To the east of Maymbung rise Mount Talipao
and Mount Kumaputkut, which form the middle and second region. The third region is
the southern part of the Lu’uk country. Its highest point is Mount Bulag, to the north of
Tandu-Panu’an.
Between Mount Tukay and Mount Tumangtangis lies Bud Gapang. Midway between
Mount Talipao and Bud Datu is Mount Kumuray, in the neighborhood of Langhub.
The largest streams on the island are Tubig Palag and Bina’an. The first is generally
known as the Maymbung River. It passes through the settlement of Maymbung and
empties into the head of the bay of the same name. It drains the southern slopes of
Mounts Tumangtangis, Pula, Dahu, and Kumuray. The Bina’an stream drains the
southern slopes of Mount Sinuma’an and the northern slopes of Mounts Talipao and
Kumaputkut and empties into the Bay of Tu’tu’.
Principal coast settlements
Beginning at Jolo and going west along the northern coast we pass the following points
of interest: The first is Point Baylam, the western limit of the Bay of Jolo. At the head of
the small bay that follows lies the settlement of Matanda, where a Spanish blockhouse
marks the western limit of the Jolo line of fortifications. Next comes Point Mangalis and
the receding beach of Bwansa, the old capital of Sulu. Here and in the next bay, at
Malimbay and Kansaya, Samal boats assemble in favorable weather for fishing. Back of
these settlements the land rises rapidly to Mount Tumangtangis. A teak forest of
considerable size lies between Tumangtangis and Jolo.

Outside of the wall of Jolo and to the east lies the settlement of Busbus, where criminals
formerly were chopped to death after being tied to a tree. A mile beyond is Mubu, where
the old residence of Sultan Harun stands out prominently. Copious springs of fresh water
issue at this place at a point near the high-water mark. A mile farther east we come to
Tandu (point or cape), where Datu Kalbi lives. This point is generally known as Tandu
Dayang Ipil8 and marks the eastern limit of the Bay of Jolo. The isolated hill of Patikul
rises immediately behind Tandu. The settlement of Patikul lies still farther away on the
beach. Here lives Datu Julkarnayn (Alexander the Great), the brother of Datu Kalbi. The
beautiful region lying between Patikul and the mountains of Tambang and Sinuma’an is
called Lati.
Buhanginan lies about midway between Patikul and Higasan. At the latter place or Tandu
Manuk-manuk the shore line recedes toward the south. Opposite this point lies the Island
of Bakungan. Next comes the larger settlement of Taglibi, above which rises Mount
Ta’ung; then Bunbun, near a point which marks the western entrance into the Bay of
Si’it. Midway between Bunbun and the head of the bay is Su’, which may be said to
mark the boundary line between Lati and Lu’uk. Si’it is a small settlement near the head
of the bay. Beyond Si’it the shore line turns north until it reaches Kansipat. About 2
miles farther, a semicircular reef off the shore makes the excellent and well-protected
small harbor of Bwal. A large spring of pure, fresh water adds to this place another
natural advantage, one which gave it the prominence it had in former days. The entrance
into the harbor is very shallow and allows only sailboats of light draft. The channel lies
close to the shore on the west side. Opposite the Island of Tulayan lie Tandu-batu and a
little farther inland Kuta Makis. Limawa lies about 3 miles farther on near a point
opposite the Island of Bŭli Kuting. Behind this island and at the head of a shallow cove
lies Patutul, the chief settlement of Tandu. East of Bud Tandu is Tandu Pansan, the
easternmost point of the island. The eastern coast is exposed to storms and appears rocky
and barren, though the hills behind it are well cultivated.
The first point on the southern coast is Tandu Panu’an, behind which lies the settlement
of Sukuban. This marks the southern extremity of the boundary line between Tandu and
Lu’uk. The country behind Kuta Sihi’ and Pitugu appears rich and well tilled. The hills
come down to the beach. Near the point at the eastern limit of Tu’tu’ Bay lies Kambing.
The neighboring country is rich and prosperous. It is governed by Maharaja Bayrula,
one of the wisest and best chiefs of Sulu. West of Kambing lie Pandang-pandang, Tŭbu-
manuk, and Tu’tu’. The shore is a continuous mangrove marsh, while the country behind
is about the richest and best tilled land on the whole island. The western side of Tu’tu’
Bay has few places of importance. The country behind is picturesque and hilly, but not
as well populated as other parts of the island. Lubuk, Kabungkul, and Lumapit are the
chief settlements.

Beyond the point of Buhangin Puti’, the shore line bends again north and the Bay of
Maymbung begins. Here mangrove swamps are extensive and extend a good distance
inland. The greater part of Maymbung is built on piles over the water. It is surrounded by
swamps on all sides. After the tide recedes, strong odors arise from the muddy bottom to
such an extraordinary degree as to render the atmosphere of the place very disagreeable
and often unbearable to strangers. The center of the town is a small, open square of
reclaimed land filled with coral rocks. Around this square were built the houses of Sultan
Jamalul Aʿlam and his ministers of state. The present sultan lives on a hill about half a
mile inland from the town. The square was probably the site of the Maymbung fort
which was destroyed by General Arolas in 1887. Some Chinese traders live in the town
and export hemp, pearls, pearl shells, etc., through Jolo. The population of the town and
its immediate suburbs varies considerably, but it is generally estimated at 1,000. Beyond
Maymbung the coast bends sharply to the south. In the immediate vicinity of Maymbung
lies Bwalu. A mile west of this place begins the district of Parang. After Lipid and Lapa
comes Kabali’an, the western limit of the Bay of Maymbung. The shore line then takes a
more westerly direction. Passing Dandulit and Lakasan, we reach Tandu Pūt, where the
western coast of the island begins. This southern region of Parang is well populated and
is very pretty and productive. Cultivated areas are seen on the side of the mountains
everywhere and they reach the very summit of Mount Tukay.
The town of Parang is one of the largest settlements on the island and has, at present, an
estimated population of 1,000. It is situated at the head of a small open bay facing the
southwest and commands a beautiful view of Tapul and Lugus and the intervening sheet
of water. It is the capital of the district and has one of the best markets in the Archipelago
for fish, shells, and pearls. The drinking water in this neighborhood is brackish.
An islet lies off the shore near Tandu Bunga. Beyond this point the shore line turns north
to Bwisan, which is one of the most prosperous settlements in the district. Beyond Alu
Pangku’ the coast inclines a little east and runs to Silankan and Timahu. Extensive
coconut groves and well-cultivated fields and fruit trees of various kinds abound all
along the coast from Parang to Timahu.
Districts of the island
The districts of the island conform in a great measure to its natural divisions. However,
political reasons have modified the natural boundaries and increased the districts to six
by division. These districts are Parang, Pansul, Lati, Gi’tŭng, Lu’uk and Tandu. The first
district on the west is Parang. A line joining the western limit of Bwalu on the south
coast, with a point slightly east of the summit of Mount Tumantangis, and projected to
the sea on the north, delimits this district on the east and carves out of the western

natural division the district of Pansul. The eastern boundary of Pansul is a line running
from a point 2 or 3 miles east of Maymbung to Mount Pula and Busbus. The chief
reason for separating Pansul from Parang was to reserve for the sultan direct control over
Jolo and Maymbung. This district has more foreigners residing in it than any other.
A line joining Su’ and Lubuk marks the eastern limit of both Lati and Gi’tŭng, the third
and fourth districts. The watershed line joining the summits of Mounts Dahu, Tambang,
and Sinuma’an and falling on the east to the vicinity of Su’, divides Lati on the north
from Gi’tŭng on the south. For all practical purposes the district of Lati may be said to
lie between Jolo and Su’, and the district of Gi’tŭng or Talipao between Maymbung and
Tu’tu’. The land joining Si’it and Tu’tu’ is low. Sulu traditions say that when the Samals
arrived in the island this neck of land was submerged and the island was divided by a
channel of water. The extinct volcano of Pandakan, generally spoken of as the “Crater
Lake,” which lies in this vicinity, may be of late origin and may have been the source of
the geologic deposits which helped to fill the channel. Spanish records speak of a
volcanic eruption in the vicinity of Jolo as late as 1840, and it is very likely that other
volcanic action occurred prior to that date and after the arrival of the Samals in the
fourteenth century.
A line joining Limawa on the north and Sukuban or Tandu Panu’an on the south, divides
Lu’uk from Tandu, thus forming the fifth and sixth districts respectively. A line joining
Mount Tayungan and Bud Tandu divides both Lu’uk and Tandu into a northern and a
southern part. In both cases the southern parts are more fertile and better cultivated and
probably more thickly populated than the northern.
The Sulus are principally agriculturists. The greater part of the people are farmers and a
considerable portion of the interior of the island is under cultivation. They raise a good
number of cattle, carabaos, and horses, which they utilize for tilling the soil and
transporting its products. Trails cross the island in all directions and the interior is in
easy communication with the sea. Fruits are good and abundant. The forests are rich in
jungle products and in timber. Some copra and hemp is raised and the amount is being
increased annually. The staples are tapioca, rice, and corn. Sugar cane is raised in small
quantities. Ubi and taro are fairly abundant. Some coffee is produced, but disease
destroyed most of the plantations. Some tobacco and vegetables are raised for home
consumption only.
Jolo is one of the best fish markets in the Philippine Islands. The varieties of fish in Sulu
waters are innumerable and of excellent quality. The Island of Sulu surpasses Mindanao
in the quality and proportional amount of its fruit. There is an abundance of mangostins,
durians, nangkas (jack-fruit), lançones,9 marangs,9 mangos of several varieties
(mampalam, bawnu, and wanni), oranges, custard apples, pineapples, bananas, etc.

In the extent and quality of cultivation the district of Lu’uk ranks first, Parang second,
and Lati third. Good fresh water abounds everywhere except on the western coast.
Considerable irrigation is possible in many localities.
Town of Jolo.
General plan, buildings and streets
Jolo is the Spanish representation (or rather misrepresentation) of the word Sulu,
sometimes written Sooloo. The early Spaniards wrote it “Xolo,” which later changed to
Joló. The complete form of the word is Sulug, as it is rendered in Magindanao. The
Sulus pronounce it and write it Sūg. Sūg means a sea current. The flow of the tide
through the innumerable narrow channels separating the numerous islands of the
Archipelago gives rise to unusually strong currents which figure prominently in the
seafaring life of the people. Therefore the term is an appropriate designation for the
Archipelago as a whole.
The rulers of the island state have changed their capital four times. The most ancient
capital was Maymbung, the second was Bwansa, which lies on the north coast of the
island about 3 miles west of Jolo. Here ruled Raja Baginda and the first three sultans of
Sulu. The fourth sultan moved to Sūg, the third capital, and the town remained the
capital of the sultanate until 1876, the date of the Spanish conquest and occupation.
Sultan Jamalul Aʿlam then moved to Maymbung and the Spaniards occupied the town.
Since then the term Jolo has become so intimately associated with it, that it is deemed
preferable to use it as a name for the town, while the term Sulu, which is more correct
and more commonly used, is retained in all other applications.
The town of Jolo has been so closely identified with the history of the sultanate as to
claim considerable attention. The Spanish buildings and improvements were sufficiently
extensive to obscure the ancient landmarks of the town and to render a complete and
intelligent understanding of the early history and traditions of the place impracticable. A
few words describing the location of Jolo, its ancient landmarks, and the Spanish
improvements will therefore be of primary interest.

The town as it stands at present is divided into four distinct parts. The main or central
part is Jolo proper or the “walled town.” This is known to the Moros as Tiyangi Sūg
meaning the “shops or market of Sulu.” The western half of this part bordering on Suba’
Bawang formerly was termed Luway. The second part, called San Remondo, lies back
and south of the walled town and is separated from it by a little stream called Tubig
Hasa’an. The third part is Tulay and lies on the west side; the fourth is Busbus, on the
east side.
At the head of the roadstead separating the Pueblo nuevo or Tulay from Jolo proper or
Luway is a small tidal stream formerly called Suba’ Bawang. Some maps designate it as
Rio del Sultan. This stream extends back into a swamp and divides into two branches.
The main or direct branch extends in a more or less southerly direction to a point about
700 meters from the mouth of the stream, where it rises in copious springs of fresh water
at the edge of the swamp. The other branch is formed by the junction of the rivulet that
rises in the springs of San Remondo with Tubig Hasa’an. The latter has its origin at the
foot of the hills above the cemetery and Blockhouse No. 2. Hasa’an means grindstone,
and the springs are said to have burst out of the spot where a grindstone was set for use.
Another stream, termed Suba’ Ligayan, drains the northern slopes of Buds Datu and
Agad, and running north, passes by Fort Asturias and through Tulay, and empties into the
roadstead of Jolo at a point about 250 meters west of the mouth of Suba’ Bawang. A
branch of this stream formerly issued at Asturias and connected with the main stream of
Suba’ Bawang. The land which thus lay between Suba’ Bawang and Suba’ Ligayan was
a delta. It was called by the Moros ū-laya (that is, the head of the net) because of its
triangular shape. It was mostly marshy, but it had a central longitudinal strip of dry land
which practically connected Tulay with the base of the hills, at Asturias. At the upper
end of this strip there existed at one time a well-defined, sandy spot, different in
formation from the surrounding land, which was considered sacred and was supposed to
be the first land formed on the island. This spot was Sūg proper; after it was named the
whole settlement which was built along the banks of Suba’ Bawang and at the head of
the roadstead.

Sketch of Jolo before 1888.

Sketch of Jolo at the present time.
The Sultan’s palace, termed istana, his kuta (fort) and stockades were built along the
lower left bank of the stream Bawang; hence the name Rio del Sultan. On the right bank
lay the houses and stockades of the other datus of high rank. Two bridges connected one
side of the stream with the other.
On the outskirts of the town lay various kuta belonging to subordinate datus, which
defended the approaches to the town. The most famous of these kuta was Daniel’s Fort,
the best stronghold of Sulu. On the site of this fort was built in 1878 the fort or redoubt
of Alfonso XII, which was lately replaced by the present headquarters building of the
military post of Jolo. Another strong fort was built at the foot of the hills just above the
head of the delta above described; it defended the inland approach to the town. This was
Panglima Arabi’s kuta, on the site of which Fort Asturias was erected. Another kuta was
located on Point Baylam.
The principal part of the town was formerly built over the shoal and beach at the head of
the bay. Extensive rows of buildings stretched out into the roadstead and in front of the
buildings now occupied as the clubhouse and military hospital. The present “Chinese
pier” is constructed on the same plan. This extensive row of houses and shops begins at

the lower point of the Tulay delta and stretches straight out into the sea. The bay is very
shallow here and appears to be fairly well protected from severe storms. A variety of fish
called tulay, after which the Moro town of Tulay is named, is caught in the bay. A
swamp bounds the town on the south and west, affording it considerable protection from
assault. However, it is open to attack from the sea and from the east. The land on the east
is high and affords the only desirable site for residences. Here the strongest forts and
defenses were erected.
The Spaniards built the central part of Jolo first. They raised it considerably above sea
level by extensive fillings, and surrounded it by a loop-holed wall, 8 feet high and 1½
feet thick, for protection from Moro assaults. The new town was beautifully laid out with
broad, clean streets lined with double rows of arbol de fuego (fire trees), ylang-ylang,10
acacia, and other varieties of trees, some of which are large and magnificent. Three
parks, each one block in size, added considerable picturesqueness to the place.
Substantial quarters were built for the officers, all houses were painted white or
whitewashed, and none of them had the nipa roofs so common in the Archipelago.
Business places, storehouses, a large market place, a church, a theater, two schoolhouses,
and a hospital were erected and a public water supply provided. A stone pier was built
extending 120 meters into the sea, and provided with a light-house at its outer end.
The town wall had five gates, two of which lay on the northwest or sea front, one at the
foot of the pier, and the other close to it. Through the latter gate cargo was admitted from
small boats, which can always come up to this point at high water. The three other gates
lay on the land side, one at the south end of the town toward Tulay, another at the
opposite extremity facing Busbus, and a third one at the southern end of Calle11 Buyon,
directly facing San Remondo. This last is the only gate of the three kept open at present
and is the only entrance into the town from the land side. A tower called Torre de la
Farola surmounts the gate. Near the Busbus gate and forming the northeast angle of the
town was the fort or redoubt termed Alfonso XII. It was built on a prominent eminence
and commanded an extensive view of the bay, the town, and the surrounding country.
In the immediate vicinity lay the Cuartel España, which was a large and substantial
building occupying the northern extremity of the town, facing the bay on the side of
Busbus. At the extreme end of the wall beyond the barracks was the tower or blockhouse
called Torre Norte. Another similar tower at the south gate was termed Torre Sur. At the
intersection of the south wall and the beach line was a strong building called Cuartel
Defensivo de las Victorias. The block lying diagonally between this cuartel and the
market had eight buildings which were known as Casas de la Colonia para Deportados.
Two roads and two bridges connected the south and southeast gates with San Remondo.
The continuation of these roads formed the two main streets of this part of the town. San
Remondo has six small town blocks, nearly all of which are on reclaimed swamp land.

The buildings here are mere nipa huts and the streets are muddy and narrow, unlike those
of the walled town. Back of the town lies a large coconut grove which extends to
Blockhouse No. 2 on one side and Asturias on the other. A straight and well laid out road
directly connects these two latter points and marks the southern limit of the town.
A good road runs outside the wall connecting Busbus and Tulay. Later usage has applied
the term Tulay to all parts of the town lying west of Suba’ Bawang. Formerly the name
Tulay was applied only to that part lying west of Suba’ Ligayan, while the intermediate
section was known as Pueblo nuevo. The bridge across the mouth of Suba’ Bawang was
termed puente del sultan. On the other side of the bridge this street extends through
Pueblo nuevo and along the central strip of ū-laya, or the delta, to Fort Asturias, thus
separating the waters of Suba’ Bawang from Suba’ Ligayan. Midway between Tulay and
Asturias stands an obelisk-like monument erected by General Arolas and bearing the
date 1892. Further fillings in Tulay have provided for several streets, the chief one of
which is the direct street running to the Chinese pier and then on to the blockhouse of
the playa12 and the Ligayan River. A large bridge crosses this river to Tulay proper. The
road ends at the beach a little beyond the bridge. In the central plaza at Tulay stands a
monument erected by General Arolas in 1891 in memory of the three renowned
conquerors of Jolo. On one side the monument bears the inscription “A la gloria de los
que con su esfuerzo hicieron esta tierra Española;” the second side bears the inscription
“Corcuera, 17 de Abril de 1638;” the third side, “Urbistondo, 28 de Febrero de 1851;”
the fourth side, “Malcampo, 29 de Febrero de 1876.” A straight road about three-fourths
of a mile long called the Asturias Road directly connects Asturias with the main entrance
of the walled town. Another road starts at this latter point and running along the right
bank of Tubig Hasa’an reaches the cemetery on the opposite side of Blockhouse No. 2.
The old bridge connecting a branch of this road with the one running from Asturias to
Blockhouse No. 2 was washed away by a severe freshet in 1904, thus breaking what had
formerly been a complete circle of roads around the town.
Busbus is wholly occupied by Moros. Its houses are dilapidated nipa huts built on piles
over the water. Back of the town is a marsh which extends a little way toward the base of
the hills. The water from the marsh escapes into the bay by two rivulets, the first of
which runs through the settlement and is known as Tubig Uhang; the other is artificial,
forms the outer limit of the town, and is called Buyung Canal. Persons convicted of
capital crimes in the days of the independent sultanate were tied to a tree at this place
and there their bodies were chopped to pieces; hence the name “Busbus” which means to
“chop up” or “dress wood.”
Trade

Jolo lies about 4 miles from the point of intersection of latitude 6° north and longitude
121° east. It is about 540 nautical miles due south from Manila and 81 nautical miles
distant from Zamboanga. The harbor is deep and free from currents. The bay is well
protected on the north by the Islands of Pangasinan and Marongas and is safe from all
storms except those from the northwest.
Sulu occupies the most nearly central position of any island in eastern Malaysia. It lies
between Mindanao on the east and Borneo on the west, and separates the Sulu Sea from
the Celebes Sea. The commercial advantages of this position are unique. To the north lie
the Bisayas, Palawan, Luzon, Formosa, China, and Japan; to the east Mindanao and
Basilan; to the south, the Moluccas, Celebes, and Java; to the west, Borneo, Sumatra,
and the Malay Peninsula. Besides, the Sulus are natural-born sailors, and their famous
pearl industry has prompted them to trade since time immemorial. Their boats brought
silk, amber, silver, scented woods, and porcelain from China and Japan; gold dust, wax,
dyes, saltpeter, slaves, and food stuffs from Luzon, the Bisayas, and Mindanao;
gunpowder, cannon, brass, copper, iron, rubies, and diamonds from Malacca and
Bruney;13 pepper and spices from Java, the Moluccas, and Celebes. Chinese merchants
traded with Sulu long before the arrival of Legaspi, and while Manila and Cebu were
still small and insignificant settlements Jolo had reached the proportions of a city and
was, without exception, the richest and foremost settlement in the Philippine Islands.
Jolo, with the exception of Bruney, had no rival in northeast Malaysia prior to the
seventeenth century.
Such commercial importance naturally attracted the attention of the early Spanish
Governors-General and was one of the causes which led to the early invasion of Sulu.
The long period of warfare which followed this invasion retarded the progress of Jolo
and reduced its trade. Again, the rise of Spanish commerce in the north tended to restrict
the trade of Jolo. The growth of Manila, Cebu, and Iloilo naturally diverted the
commerce of Luzon and the Bisayas and the north coast of Mindanao to those cities. The
later commercial decline of Jolo was probably brought about more in this way than as a
result of actual clash of arms. Jolo, however, remained an important port and a
transshipping station to Mindanao until a late date.
At present trade has assumed new proportions and is following new routes. Zamboanga,
Kotabato, and Davao are directly connected with Manila by regular steamship lines, and
Jolo is fast losing its importance as a transshipping port. Zamboanga, on the other hand,
is rising in importance and seems destined to become the port of Mindanao. It is the
capital of the Moro Province and lies in the direct route connecting China, Manila, and
Australia. It has direct communication with Manila, Hongkong, Singapore, and
Australia, and is gradually diverting the trade of Mindanao from Jolo.

In spite of overwhelming odds, however, Jolo will maintain considerable commercial
importance. It has well-established trade relations with Borneo, the Malay Peninsula,
China, and Luzon, and is connected by regular steamship lines with Sandakan,
Singapore, Manila, and Zamboanga. Practically the whole trade of the Sulu Archipelago
passes through this port, and it stands now, as ever before, as the center of business,
power, and importance of the whole district of Sulu.
In the early days the trade of Sulu was carried on by Moros and Chinese. The Chinese
appear to have entered the Archipelago prior to its mohammedanization, and the
commercial relations of China and Sulu are really prehistoric. As hostilities between
Spain and Sulu increased, Sulu traders became less daring and grew fewer and fewer.
Chinese traders, on the other hand, were less molested and conditions encouraged their
increase. The “Chinese pier” is a very old business establishment, and Chinese traders
and merchants have resided in Jolo for many generations. Their number, in 1851,
exceeded 500. At present Chinese merchants have complete control of the trade of the
Sulu Archipelago. They are found everywhere and command all the avenues of
commerce. The Sulus have abandoned commerce as a trade and apparently have no
inclination to resume it on any large scale. This is due mainly to the decline of their
power and the present abeyance of their national life. A new political revival will no
doubt change their attitude and may bring about a surprising development in arts and
trades as well as of commerce.
The trade between Jolo and various islands and settlements of the Archipelago is carried
on by means of innumerable small Moro boats and sloops termed sapits. Formerly such
boats traded with Bruney, Sandakan, the Celebes, Java, and all the various islands of the
Philippine Archipelago, but the stricter enforcement of the customs regulations, which
followed the establishment of open ports at Sitanki, Bangao, and Kagayan Sulu, had the
effect of checking trade with foreign countries in such small boats and tended to
concentrate the whole trade of the Archipelago at Jolo. A review of the imports and
exports of the port of Jolo will therefore throw considerable light on the material
resources of the Archipelago, its industries, and the enterprise of the natives.
Port of Jolo
IMPORTS
Fiscal year—
1905 1906
Animals, etc $214 $71
Brass, manufactures of 6,4022,548
Breadstuffs 4,8813,870

Fiscal year—
1905 1906
Cement 745 989
Coal 4,208
Coffee 621 872
Cotton cloths, close woven 82,99980,381
Cotton cloths, loose woven 14,05314,338
Carpets 5,379
Yarn and thread 18,05919,594
Knit fabrics 2,6883,564
Cotton cloths, all other manufactures of949 2,079
Dyes 2,6913,807
Opium 14,5786,601
Earthen and stone ware 1,4942,419
Fibers, vegetable 308 153
Dried fish 216 456
Shell fish 375 497
Fruits, canned 272 254
Fruits, not canned 362 407
Glass and glassware 694 415
Iron, steel, and manufactures of3,6402,916
Malt liquors 2,020822
Matches 956 372
Mineral oils 742 1,339
Vegetable oils 536 503
Paints 979 299
Paper and manufactures of 2,1231,816
Condensed milk 1,5161,363
Rice 76,17257,416
Silk and manufactures of 1,6141,318
Soap 724 610
Spirits, distilled 1,6431,108
Sugar, refined 4,3142,987
Tea 646 489
Tobacco and manufactures of 586 367
Vegetables 1,2041,919

Fiscal year—
1905 1906
Wearing apparel 3,699
Wood and manufactures of 2,2701,646
Wool and manufactures of 2,282206
All others 8,1267,262
Total in U. S. currency $274,281$231,772
Total in Philippine currency ₱548,562₱463,544
EXPORTS
Commodity Fiscal year—
1905 1906
Animals $42 $70
Hemp 486 5,561
Cordage 5,0845,054
Fish 7,89313,151
Copra 17,87030,052
Copal 3,7934,458
Gutta-percha 108 3,939
Hides 839 867
Mother-of-pearl (shells)88,51660,051
Tortoise shell 1,9712,856
Shells, all others 4,24911,864
All others 8,0334,610
Total in U. S. currency$138,884$142,533
Total in Philippine currency₱277,768₱285,066
Port of Zamboanga14
IMPORTS
Agricultural imports ₱250₱40
Wheat flour 6,04818,378
Cement 3,08812,966
Coffee 5,65610,646
Copper, manufactures of838686

Cotton cloths, close woven92,25497,866
Cotton cloths, loose woven9,62833,714
Cotton wearing apparel2,1365,152
Cotton yarn and thread25,03234,862
Cotton, knit fabrics 6,2784,380
Cotton, all other manufactures1,8405,118
Opium 8,92826,254
Earthen and stone ware1,4065,016
China ware 262388
Hats and caps 1,164598
Iron, sheet 6,47012,786
Cutlery, table 76 142
Cutlery, all other 12096
Nails, wire 500530
Boots and shoes 7622,884
Beer in wood None.198
Beer in bottles 8,41042,618
Other malt liquors 1,902548
Matches 60 988
Tin, manufactures of 18840
Oil, petroleum 4,8508,600
Milk, condensed 3,2005,972
Rice, husked 119,572161,642
Brandy 8143,212
Whiskey, bourbon 8221,240
Whiskey, rye 1,030376
Whiskey, all other 6,66819,566
Sugar, refined 3,5665,488
Tea 1,3462,484
Zinc, manufactures of880834
All other imports 49,71286,807
Total in Philippine currency375,756613,115
EXPORTS

Commodity Fiscal year—
19051906
Bejuco (rattan) ₱700₱1,594
Fish 60 1,886
Coconuts None.2,258
Copra 125,734157,398
Almaciga15 632288
Copal 19,90631,582
Gutta-percha 2,28228,370
Rubber None.None.
All other gums and resins910None.
Hides, carabao 362316
Beeswax None.3,024
Shells, mother-of-pearl2,4402,420
Shells, tortoise 8,7087,638
Shells, all other 2,22410,320
Salt None.1,508
Wood, all kinds 1,3461,076
All other exports 9,5909,860
Total in Philippine currency174,894259,538
The above statements of the imports and exports of the port of Jolo for the fiscal years
1905 and 1906 have been obtained through the kindness and help of Mr. E. B. Cook,
collector of customs for Jolo. They represent the total value of the imports and exports of
the town to and from foreign ports only. They do not, however, give an idea of the grand
total of the imports and exports of the Archipelago. Account must also be taken of the
large amount of commodities smuggled into the country by means of small boats which
continually run between the Tawi-tawi Group and Kagayan Sulu on the one side and
Borneo and Palawan on the other. Moreover, it is difficult to tell what part of the trade of
Basilan and the Samal group of islands is retained by Jolo and what part has lately been
drawn away by Zamboanga. Besides, some trade between Sulu and Basilan, on one side,
and Mindanao, Negros, and Cebu on the other, is carried on by sailing craft; no account
of this is taken either at Jolo or Zamboanga. Since July 1, 1905, all boats under 15 tons
register have not been required to present at the custom-house manifests of goods
carried. It is clear, therefore, that no correct estimate or opinion can be rendered on the
strength of these figures, unless one is aided by personal observation and knowledge of
actual conditions previous to July 1, 1903.

Estimating the population affected by the trade of Jolo, at 100,000, we note that the
importation of cloths and woven materials amounted to ₱204,431 in 1905 and ₱196,836
in 1906, or 37 per cent and 42 per cent of total imports, respectively. There is no doubt
that the weaving industry among Sulus and Samals is far from being adequate to furnish
clothing material, and European cotton cloths are therefore extensively used throughout
the Archipelago.
The importation of rice amounted to ₱152,344 in 1905 and ₱114,832 in 1906, or 27 and
24 per cent of the total imports, respectively. The Sulus are agriculturists and should be
able to raise sufficient rice for themselves and the Samals. The islands most fitted for
this purpose are Sulu, Basilan, Tapul, Siasi, Pata, and Pandami. The Samals are not
agriculturists as a rule and seldom raise anything except tapioca and corn. They
generally live on flat, low islands, unfit for the cultivation of rice. The Archipelago as a
whole should produce sufficient rice, tapioca, corn, and camotes to feed the whole
population. The importation of rice in 1905 was probably in excess of the average
amount; less rice was raised that year because of war and general disturbances.
The commodities of next importance are yarn and thread for weaving purposes.
Importation of these articles amounted to ₱36,118 in 1905 and ₱39,188 in 1906, or 7 and
8 per cent, respectively. The country does not produce silk, cotton, or wool.
All other imports may be regarded as accessories. Of these opium comes first, then dyes,
breadstuffs, sugar, iron, steel, brass, paper, and earthenware. A considerable amount of
tobacco is imported by the government free of duty, and quantities of tobacco, opium,
and cloths formerly were smuggled in. The reduction of imports in 1906 may be due to
increased production, to the depression that followed the disturbances of 1904 and 1905,
and to a diversion of certain parts of the trade to Zamboanga.
The exports, on the other hand, show a light increase in 1906. They distinctly represent
those resources of the country which are most capable of development. At the head of
the list stands the shell industry, particularly the pearl shell, which amounted to
₱189,472 in 1905 and ₱149,542 in 1906, or 64 and 52 per cent of total exports,
respectively. The exportation of shell has lately been greatly affected by the falling of the
price of pearl shell in the market of Singapore. The exportation of other shells seems, on
the contrary, to have increased. Pearl fishing is the principal industry of the country and
forms the main source of its riches. The fishing is done exclusively by natives, but the
trade seems to be wholly in the hands of Chinese. The figures given above do not
include pearls. It is very difficult to obtain any statistics for this valuable product, but on
the whole it is reckoned by merchants as equivalent to the whole output of shell.
Second in importance comes copra, which amounted to ₱35,740 in 1905 and ₱60,104 in
1906, or 12 and 21 per cent of total exports, respectively. The marked increase of this

export in 1906 may be explained partly by increased production and partly by the
general damage done to the trees in 1905 by locusts. Increase in the cultivation of
coconut trees is not perceptible and can not account for the increase in exportation.
Dried fish comes third in order, amounting to ₱15,786 in 1905 and ₱26,302 in 1906.
This industry is capable of unlimited development. The fertility of the Sulu Sea is
unusual and can hardly be surpassed. Nothing but enterprise and organized effort is
needed to render this trade a source of enormous wealth to the country. The natives are
exceedingly skillful in fishing, but lack ambition and initiative. The trade in fish is
mostly in the hands of Chinese merchants.
Fourth in importance comes hemp. Both in fiber and cordage its exports amounted to
₱11,140 in 1905 and ₱21,230 in 1906. Hemp culture has markedly improved during the
last year, and the increased production is sufficient to explain the increase in exportation.
Coconut trees and hemp grow splendidly on all the larger islands of the Archipelago, and
their cultivation is capable of extensive development.
Copal and gutta-percha are the products of Sulu, Basilan, and the Tawi-tawi Islands.
Although sufficiently important in themselves, they sink into insignificance when
compared with the four primary staple products and the immense possibilities that lie in
the line of their development.
The greater part of the trade of Jolo is handled by the Jolo Trading Company, the firm of
Hernandez & Co., and the commercial houses of Chaun Lee and Ban Guan, all of which
are controlled and managed by Chinese merchants. The following list compiled in the
office of the Jolo Trading Company, for the Far Eastern Review, is a fair estimate of the
prospective exports of the town for the coming two years:
Article AmountPriceTotal
Piculs.
Hemp 1,000₱21₱21,000
Pearl shells 150456,750
Trepang or beche-de-mar 50 301,500
Shark fins 20 45900
Hemp rope 30 25750
Caracoles (sea shells for buttons, etc.)40 12480
Black shells 10 880
Copra 50073,500
Seaweeds 40 4160
Hides 10 20200

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Integrated Modelling of Ecosystem Services and Land Use Change Case Studies of Northwestern Region of China Youjia Liang

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