Impact of Land Use and Land Cover Changes on Urban Ecosystem Service Value in Dhaka, Bangladesh

Assessing climate and land use impacts on surface water yield using remote sensing and machine learning

Climate and land use changes are critical factors affecting watershed water yields, with significant implications for water resources at both local and regional levels. This study examined the combined effects of temporal and spatial climate variability and land use/land cover (LULC) changes on surface water yield and availability in the Gilgel Gibe watershed, Ethiopia, from 1993 to 2023. Utilizing the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) hydrological models, machine learning, and remote sensing techniques, this study assessed variations in water resources and their impacts on basin water yield. This study utilized Landsat (30 m), MODIS (500 m-1 km), and 4 km resolution climate datasets from the United States Geological Survey (USGS) and NASA POWER for large-scale climate and land-use analyses from 1993 to 2023. An ensemble of machine learning models, including Random Forest (RF), Support Vector Machine (SVM), and XGBoost (XGB), were used to evaluate the effects of climate variability and land use on annual water yield. The study revealed significant land cover changes over a 30-year period. Shrubland decreased from 1,108.37 km2 (21.54%) in 1993 to 295.22 km2 (5.74%) in 2023. Grasslands and wetlands also showed declining trends. In contrast, water bodies increased from 12.51 km2 (0.24%) to 41.57 km2 (0.81%), primarily due to the construction of the Gilgel Gibe hydroelectric dam, and forested areas slightly decreased from 626.73 km2 (12.18%) to 534.18 km2 (10.38%). The surface runoff decreased to 15.78% in 2021 and 15.28% in 2022, whereas the water yield dropped from 1.22% in 1993 to 0.83% by 2023. This study also showed a reduction in lateral flow and higher evapotranspiration levels in 2000 and 2017. The decrease in runoff can be attributed to the loss of wetlands and grasslands, reduced precipitation, and regulatory effects of hydropower operations. In contrast, elevated evapotranspiration levels were primarily attributed to temperature extremes, vegetation stress, and potential increases in irrigation practices. These findings underscore the importance of climatic elements in regulating river discharge and the necessity for smart land use planning to prevent negative environmental consequences on water resources.

Impacts of rapid urbanization on long-term water quality of the peripheral River of Dhaka, Bangladesh

This study was carried out to determine the current state of the physicochemical water quality parameters and the effects of urbanization over 50 years in the peripheral rivers by using primary and secondary data adjacent to Dhaka city. These rivers and waterways had DO levels much below the recommended standard of Bangladesh, and occasionally, they even approached 0. This suggests that the water in these rivers is highly polluted and unfit for aquatic life. For the most part, high rates of pollution also contribute to high BOD readings. Besides, the weighted arithmetic method discovered that the urban rivers have deficient water quality, which requires immediate attention. Compared to the seasonal variations, the water quality is worse in the dry season compared to the wet season. Among all the rivers, the lowest WQI found was 11.89 in the wet season and 123.65 in the dry season. Moreover, the Heavy Metal Pollution Index (HPI) calculation was done, with data from 1 to 3797 indicating that most heavy metal data sets are unsuitable for drinking and household uses. The current study found that built-up areas have grown 288%, and the water bodies have declined by 60% over the last 30 years. This study shows that the quality of peripheral river water in Dhaka city hinders the objectives of the SDG 6 Goal: Clean Water and Sanitation. Revitalizing the water supply requires the attention of the city authorities. PRACTITIONER POINTS: Rapid urbanization has made Dhaka one of the least habitable cities, with industrial growth contributing significantly to pollution. DO levels are far below than Bangladesh's standards, sometimes approaching zero, making the water unfit for aquatic life. The study reveals a decline in water quality, especially during the dry season, and WQI indicates extremely low standards. Built-up areas have increased by 288%, while water bodies have decreased by 60% over the past 30 years.

Ecosystem health assessment of East Kolkata Wetlands, India: Implications for environmental sustainability

The East Kolkata Wetlands (EKW) in Kolkata, India, span 12,500 ha and are a vital ecological zone providing several benefits, including water purification, flood control, and biodiversity support. This study investigated land use and land cover (LULC) alterations in the EKW from 1991 to 2023, using a random forest (RF) machine learning model. Significant LULC changes were observed over the 32 years, with wetland areas decreasing from 91.2 km2 in 1991 to 33.4 km2 in 2023, reflecting substantial habitat loss and reduced ecosystem services. Conversely, agricultural land expanded from 27.8 km2 to 58.7 km2, driven by economic and food production needs, and built-up areas increased dramatically from 0.2 km2 to 10.5 km2, indicating rapid urbanization. This study evaluated the health, resilience, and ecosystem functionality of EKW by analysing human-induced land use changes and using ecological indicators and landscape metrics. Landscape and class level metrics such as PLAND, largest patch index (LPI), total edge (TE), edge density (ED), number of patches (NP), and patch density (PD) were used to analyse the spatiotemporal dynamics of the wetlands. This study revealed a significant increase in fragmentation, with the number of patches increasing from 2689 in 1991 to 4532 in 2023, despite a consistent decrease in core wetland areas. Ecosystem health indicators, such as the ecosystem structure index (ESI) and landscape deviation degree (LDD), were used to assess landscape metrics and fragmentation changes. The ESI and other metrics revealed significant temporal fluctuations, providing insights into landscape structure, connectivity, and heterogeneity. The ESI improved from 0.87 in 1991 to 1.03 in 2023, indicating enhanced connectivity and diversity. Conversely, the LDD increased from 20.6% to 56.85%, indicating a shift towards impervious surfaces. The vegetation productivity and ecosystem health index (EHI) decreased, indicating biodiversity loss and reduced carbon sequestration. The EHI also dropped from 0.67 to 0.55, signifying ongoing environmental stress. This study emphasizes the need for conservation efforts to maintain the ecological integrity of the EKW amidst urbanization and land use changes and recommends a balanced approach for sustainable urban development and enhanced wetland resilience.

GIS based method for mapping actual LULC by combining seasonal LULCs

One of the most significant applications of remote sensing data is to prepare land use and land cover (LULC) maps. LULC maps are always affected by seasonality and a single LULC map of a particular month is prepared to represent a year in most of the research, especially in change detection research. This does not represent the real view of the landscape because the seasonal variation of different LULC types is always overlooked. Considering the issue, the current method aims to solve the problem by incorporating seasonal LULC using the raster overlay method to remove the seasonality effect on LULC classification. To apply this method, a minimum of two seasonal LULC maps is required for a single study year. The map needs to overlay and then reclassify according to the stable and rotational LULC pattern of the study area. This method will replicate the actual LULC pattern of a study area from satellite images. Summary of the method is as follows:•LULC of each season was classified using image classification technique.•LULC of each seasons are coded and combined using overlay technique.•Combined map is reclassified to prepare the actual LULC map.

Changes in the economic value of ecosystem services in rapidly growing urban areas: the case of Dhaka, Bangladesh

Assessing the effects of land use patterns on ecosystem services can provide a conceptual foundation and point of reference for spatial planning strategies. The benefits ecosystems bring to individuals' lives and general well-being are referred to as ecosystem services. Land use/land cover (LULC) could influence various ecosystems and have implications for natural habitats and the quality of life. LULC has changed dramatically in Bangladesh during the past few decades, notably in the Dhaka Metropolitan Area. However, no attempt has been made to examine the co-evolution of LULC variations and values of ecosystem services (ESV) in the Dhaka Metropolitan Area. The study's objective is to evaluate the impact of LULC changes and different socio-demographic factors on ESV. LULC data sets were extracted from Landsat OLI and TIRS images using maximum likelihood classification. Analyses were conducted on both ESV estimations and driving forces, and the influence of LULC dynamics on the ESV was assessed. Data from 1991, 2001, 2011, and 2021 were used to estimate ESVs. LULC in the major metropolitan area of Dhaka has seen considerable changes between 1991 and 2021, with the most important change being the declination of water bodies, vegetation, and agricultural land. Vegetation and agricultural land proportions dropped from 22.50% and 19.29%, respectively, to 6.45% and 10.60%. Overall, there was a US$25.11M drop in ESV during 1991-2021. The study emphasizes the value of integrated land use planning for tightly regulating and controlling the growth of built-up regions. This will be essential for maintaining ecological sustainability and contributing to ecosystem resilience.

Impact of land use and land cover on urban ecosystem service value in Chandigarh, India: a GIS-based analysis

Assessing the effects of land use and land cover (LULC) on ecosystem service values (ESVs) is critical for public understanding and policymaking. This study evaluated the impacts of LULC dynamics on ESVs in Chandigarh city of India. The assessment of LULC changes was performed by analyzing the satellite imagery of the study area for the years 1990 and 2020 with different band combinations in ArcGIS (10.8 version software). In addition, we analyzed ecosystem services changes which were based on the LULC classes of the study area. Five LULC classes were identified in the present study area (Water bodies, forest and vegetation, built-up, agriculture and shrubland and open spaces). The results demonstrated (from 1990 to 2020) that the forest cover and agricultural areas decreased by 4.19% and 37.01%, respectively, whereas the built-up area substantially increased by 104.61%. Overall, ESV decreased by 2.54% from 1990 to 2020 due to rapid urbanization. The combination of LULC and ecosystem services valuation can increase our understanding of different issues of an urban ecosystem. Hence, we recommend the integration of LULC and ecosystem services valuation as a tool that could provide information to policymakers, urban planners and land managers for sustainable use in future.

Use of cellular automata-based artificial neural networks for detection and prediction of land use changes in North-Western Dhaka City

The purpose of this study was to analyze the trend of change in land use land cover (LULC) and land surface temperature (LST) in Mirpur and its surrounding area over the last 30 years using Landsat satellite images and remote sensing indices, and to develop relationships between LULC types and LST, as well as to analyze their impact on local warming. Using this analyzed data, a further projection of LULC and LST change over the next two decades was made. From 1989 to 2019, 5-year intervals of Landsat 4-5 TM and Landsat 8 OLI images were utilized to track the relationship between LULC changes and LST. The modeled LST was validated with MODIS-derived LST within the study area. Cellular automata-based artificial neural network (CA-ANN) algorithm was used to model the LULC and LST maps for the year 2039. The Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-up Index (NDBI) were analyzed to determine their link with LST. The relation between LST and LULC types indicates that built-up area raises LST by substituting non-evaporating surfaces for natural vegetation. The average surface temperature was increasing steadily for the last 30 years. For the year 2019, it was determined that roughly 86% of total land area has been converted to built-up area and that 89% of land area had an LST greater than 28 °C. According to the study, if the current trend continues, 72% of the Mirpur area is predicted to see temperatures near 32 °C in 2039. Additionally, LST had a significant positive association with NDBI and a negative correlation with NDVI. The overall accuracy of LULC was greater than 90%, with a kappa coefficient of 0.83. The study may assist urban planners and environmental engineers in comprehending and recommending effective policy measures and plans to mitigate the consequences of LULC.

Research on land-use evolution and ecosystem services value response in mountainous counties based on the SD-PLUS model

Rapid urbanization has caused changes in climate and environment and threatened the ecosystem with multiple risks. The ecosystem services capacity has shown a downward trend accordingly. It is significant to explore the spatio-temporal evolution of land use and ecosystem services value (ESV) in mountainous counties at small scales, as it coordinates economic growth and ecological protection, and promotes sustainable and high-quality development. Based on the SD-PLUS model, the study simulated three scenarios of land-use change in Qianshan city from 2019 to 2035: high-growth rate, medium-growth rate, and low-growth rate, and studied the impacts of land-use change on the ESV. Results showed that: (1) Under the three scenarios, the construction land in the study area increased significantly, the forest and water have a decreasing trend, and the scale of gardens partly increased. (2) In the urban built-up areas, a significant amount of construction land is centrally expanded, whereas, in mountainous regions, construction land exhibits sporadic point expansion. And among the various factors that influence land-use change, the impact of roads at all levels is the most significant, followed by elevation. (3) The overall ESV shows a downward trend, with the low-growth rate scenario dropping the least (4.91%). The value distribution changes little at the space scale, and different regions demonstrate different degrees of change. From the perspective of value type, the service values of water conservation and waste treatment are significantly reduced, while that of food production is relatively stable; from the perspective of various lands with their ESV, cultivated land and forest remain stable. The study results can provide technical ideas for the coordinated economic development and ecological protection of mountainous cities and boost the implementation of green development.

Quantifying the Relationship between Land Use Intensity and Ecosystem Services' Value in the Hanjiang River Basin: A Case Study of the Hubei Section

An increased land use intensity due to rapid urbanization and socio-economic development would alter the structure and function of regional ecosystems and cause prominent environmental problems. Revealing the impact of land use intensity on ecosystem services (ES) would provide guidance for more informed decision making to promote the sustainable development of human and natural systems. In this study, we selected the Hanjiang River Basin (HRB) in Hubei Province (China) as our study area, explored the correlation between land use intensity and ecosystem Services' Value (ESV), and investigated impacts of natural and socio-economic factors on ESV variations based on the Geographical Detector Model (GDM) and Geographically Weighted Regression (GWR). The results show that (1) from 2000 to 2020, land use intensity in HRB generally showed an upward trend, with a high spatial agglomeration in the southeast and low in the northwest; (2) the total ESV increased from 295.56 billion CNY in 2000 to 296.93 billion CNY in 2010, and then decreased to 295.63 CNY in 2020, exhibiting an inverted U-shaped trend, with regulation services contributing the most to ESV; (3) land use intensity and ESV had a strong negative spatial correlation, with LH (low land use intensity vs. high ESV) aggregations mainly distributed in the northwest, whereas HL (high land use intensity vs. low ESV) aggregations were located in the southeast; (4) natural factors, including annual mean temperature, the percentage of forest land, and slope were positively associated with ESV, while socio-economic factors, including GDP and population density, were negatively associated with ESV. To achieve the coordinated development of the socio-economy and the environment, ES should be incorporated into spatial planning and socio-economic development policies.

The Evolution and Determinants of Ecosystem Services in Guizhou—A Typical Karst Mountainous Area in Southwest China

Due to rapid urbanization and economic development, the natural environment and ecological processes have been significantly affected by human activities. Especially in ecologically fragile karst areas, the ecosystems are more sensitive to external disturbances and have a hard time recovering, thus studies on the ecosystem services in these areas are significant. In view of this, we took Guizhou (a typical karst province) as the research area, evaluated the ecosystem service value (ESV) according to reclassified land uses and revised equivalent factors, and investigated the determinants of ecosystem services based on geographic detection. It was found that the total ESV showed a prominent increase trend, increasing from 152.55 billion CNY in 2000 to 285.50 billion CNY in 2020. The rise of grain prices due to growing social demands was the main factor in driving the increase of ESV. Spatially, the ESVs of central and western Guizhou were lower with cold spots appearing around human gathering areas, while that of southern and southeastern Guizhou were higher with hot spots that formed in continually distributed woodland. Moreover, the ESV per unit area and its change rate in karst regions were always lower than that in non-karst areas. Precipitation and temperature were the dominant nature factors while cultivation and population density were the main anthropogenic effects driving the evolution of ecosystem services. Therefore, positive human activities as well as rational and efficient land-use should be guided to promote the coordinated and high-quality development of ecology and the economy.

Spatial and Temporal Evolution of Ecosystem Service Value in Shaanxi Province against the Backdrop of Grain for Green

The Grain for Green Project (GGP) has influenced Shaanxi Province’s land-use pattern, resulting in a shift in ecosystem service value (ESV). Exploring the spatial and temporal evolution of the pattern of land use and ESV in Shaanxi Province, before and after the project’s implementation, can give a theoretical foundation for regional land-use planning. For this study, we used the transfer matrix and the value equivalent approaches to investigate the influence of project implementation on the spatial distribution and evolution of patterns of land use and ESV in Shaanxi Province based on four periods of land-use data from 1990 to 2020. The results suggest the following: (1) Farmland, forestland, and grassland were the most common land-types in Shaanxi Province. Farmland, forestland, and grassland in Shaanxi Province were all altered dramatically over the research period due to the GGP. Farmland was turned mostly into forestland and grassland, and forestland and grassland areas progressively grew. (2) The ESVs in Shaanxi Province were USD 3802.82, 3814.90, 3836.20, and 3806.50 billion in 1990, 2000, 2010, and 2020, respectively. The most value was supplied by hydrological management, while water resources provided the lowest value. Forestland and grassland were the most valuable land-types in high-value locations, whereas built-up land was the most valuable land-type in low-value areas. (3) While the GGP has increased the ESV of forestland and grassland, it has harmed the acreage of other land-types, resulting in a decline in the total ESV in Shaanxi Province.

Monitoring of Land Desertification Changes in Urat Front Banner from 2010 to 2020 Based on Remote Sensing Data

Monitoring the spatio-temporal dynamics of desertification is critical for desertification control. Using the Urat front flag as the study area, Landsat remote sensing images between 2010 and 2020 were selected as data sources, along with MOD17A3H as auxiliary data. Additionally, RS and GIS theories and methods were used to establish an Albedo–NDVI feature space based on the normalized difference vegetation index (NDVI) and land surface albedo. The desertification difference index (DDI) was developed to investigate the dynamic change and factors contributing to desertification in the Urat front banner. The results show that: ① the Albedo–NDVI feature space method is effective and precise at extracting and classifying desertification information, which is beneficial for quantitative analysis and monitoring of desertification; ② from 2010 to 2020, the spatial distribution of desertification degree in the Urat front banner gradually decreased from south to north; ③ throughout the study period, the area of moderate desertification land increased the most, at an annual rate of 8.2%, while the area of extremely serious desertification land decreased significantly, at an annual rate of 9.2%, indicating that desertification degree improved during the study period; ④ the transformation of desertification types in Urat former banner is mainly from very severe to moderate, from severe to undeserted, and from mild to undeserted, with respective areas of 22.5045 km2, 44.0478 km2, and 319.2160 km2. Over a 10-year period, the desertification restoration areas in the study area ranged from extremely serious desertification to moderate desertification, from serious desertification to non-desertification, and from weak desertification to non-desertification, while the desertification aggravation areas ranged mainly from serious desertification to moderate desertification; ⑤ NPP dynamic changes in vegetation demonstrated a zonal increase in distribution from west to east, and significant progress was made in desertification control. The change in desertification has accelerated significantly over the last decade. Climate change and irresponsible human activities have exacerbated desertification in the eastern part of the study area.

Sustainable Urban Land-Use Optimization Using GIS-Based Multicriteria Decision-Making (GIS-MCDM) Approach

Land-use optimization is an effective technique to produce optimal benefits in urban land-use planning. There are many approaches and methods to optimize land-use allocation. However, the focus on addressing urban sustainability in land-use optimization is very limited. In this study, we presented a GIS-based multicriteria decision-making (GIS-MCDM) approach to optimize the location of a new residential development considering sustainability dimensions (social, economic, and environmental benefits). Rajshahi City in Bangladesh was taken as a case study. Different types of data, including land use, land cover, ecosystem service value, land surface temperature, and carbon storage, were used to define sustainability criteria. Five physical criteria, three sustainability criteria, and two constraints were used to optimize residential land. Fuzzy membership functions were used to standardize the criteria. The ordered weighted averaging (OWA) was used to produce a residential suitability map. Finally, the multiobjective land allocation (MOLA) module of TerrSet v 19.0 was used to generate optimal locations under an alternative decision scenario. The findings suggest that about 9.00% more sustainability benefits can be achieved using our approach. Using our proposed approach, we also generated six alternative decision scenarios. Among the alternative decision strategies, “high risk–no trade-off” proved to be the most optimal decision strategy that generated the highest sustainability benefit in our case.

A Novel Composite Index to Measure Environmental Benefits in Urban Land Use Optimization Problems

In urban land use optimization problems, different conflicting objectives are applied. One of the most significant goals in urban land use optimization problems is to maximize environmental benefits. To quantify environmental benefits in land use optimization, many researchers have employed a variety of methodologies. According to previous studies, there is no standard approach for calculating environmental benefits in urban land use allocation problems. Against this background, this study aims to (a) identify indicators of environmental benefits and (b) propose a novel composite index to measure environmental benefits in urban land use optimization problems. This study identified four indicators as a measure of environmental benefits based on a literature assessment and expert opinion. These are spatial compactness, land surface temperature, carbon storage, and ecosystem service value. In this work, we proposed a novel composite environmental benefits index (EBI) to quantify environmental benefits in urban land use allocation problems using an ordered weighted averaging (OWA) method. The study results showed that land surface temperature (LST) is the most influential indicator of environmental benefit while carbon storage is the least important factor. Finally, the proposed method was applied in Rajshahi city in Bangladesh. This study identified that, in an average-risk decision, most of the land (64.55%) of the study area falls within the low-environmental-benefit zone due to a lack of vegetated land cover. The result suggests the potential of using EBI in the land use allocation problem to ensure environmental benefits.

Disturbances Brought about by Human Activities in Relation to the Eco-Environment of the Main Stream of the Tarim River, 2000–2020

The main stream of the Tarim River in China is typical of ecologically sensitive areas that have been heavily disturbed by human activities; as such, the monitoring of the quality of its eco-environment constitutes an important task for researchers. By using GlobeLand30 data and applying the disturbance degree model and revised ecosystem service value (ESV) model, the study presented in this paper undertook a quantitative estimation of the effects of the disturbance impacts of human activities on the eco-environment of this area in the period of 2000 to 2020. The main conclusions are as follows: (1) disturbance index values, which reflect disturbance to the local ecosystem by human activities, increased over the study period. Further, cultivated land experienced the largest increase, which, in turn, brought about the most significant disturbance to the eco-environment. High disturbance index values presented a patchy distribution in the west of the main stream of the Tarim River and formed bands and dots in the east; the area of land characterized by high and moderate disturbance index values increased, with growth areas taking on a scattered distribution of patches, bands, and dots without significant spatial continuity. (2) The total ESV increased, indicating the quality of the eco-environment improved. The increase of cultivated land offset the increase in ESV, which counteracted the effects of ecological governance measures. Areas with high ESV values were mainly located in the western and central parts of the study area, while low values were found in the middle east and east. Areas with higher increases in ESV were mainly located in the western and the western part of the middle reaches and took on a zonal distribution, while areas of decrease followed a scattered distribution, presenting as dots or patches. Using the quantitative analysis methods and high-resolution remote sensing data to evaluate the changes in the eco-environment was considered as the innovation of this study, and the findings are useful in exploring the influence of human activities on ecosystems and evaluating the eco-environment in the minor watershed of an arid area. This piece of quantitative research contributes to the task of monitoring eco-environmental changes using remote sensing techniques in ecologically sensitive areas.

Strategies to Mitigate the Deteriorating Habitat Quality in Dong Trieu District, Vietnam

Dong Trieu district is a vital connection for territorial ecological security and human welfare between Hanoi (the capital of Vietnam) and Quang Ninh province. Therefore, habitat quality (HQ) is of extraordinary importance to the area’s sustainable development. The ArcGIS platform, Dyna-CLUE, and InVEST models were utilized in this study to assess the spatial and temporal transformations of land use and the changes of HQ in 2030 under various scenarios, with intentions to find strategies that may mitigate the HQ’s deteriorating trend in the district. Simulated results indicated that, assuming the development is maintained as usual, the average HQ of the District at 2030 could diminish by 0.044 from that of 2019 (a four-times decrease compared to the previous decade). Cases comprised of four basic scenarios, including development as usual, built-up expansion slowdown, forest protection emphasized, and agricultural land conversion, were used to identify potential strategies to mitigate the deteriorating trend. Simulated results revealed that keeping the built-up expansion rate lower than 100 ha y−1, the deforestation rate lower than 20 ha y−1, and preferring orchards over agricultural land conversion is required to limit the drop in HQ to within 0.01 in the next decade. Other than the existing population growth control policy, new guidelines such as (1) changing urban expansion type from outward to upward to control the built-up expansion rate, (2) substituting forest-harming industries to forest-preservation industries to reduce deforestation rate, (3) encouraging orchards preferred over agricultural land conversion to increase incomes while maintaining higher habitat quality, (4) practicing better farming technologies to improve crop production and to alleviate potential food security issues due to considerable reduction in cropland, and (5) promoting Green Infrastructure and the Belt and Road Initiative to increase urban green cover and raise residents’ income should be considered in designing the new mitigation strategies.

Performance Evaluation of Land Administration System (LAS) of Nairobi Metropolitan Area, Kenya

This paper aims to evaluate the internal processes of the current land administration in Kenya based on the following parameters that include ownerships, transactions, transfers, inquiries, public records of maps as attributes, issues, and customer satisfaction using stakeholder surveys and focused group discussions. A framework tool was developed for evaluation and shared with potential respondents who were either clients or staff working at the Ministry of Lands to obtain an overview of the performance of the documentation and registration processes of the land administration system (LAS). Data collected were processed and analysed using SPSS 26. To ascertain data reliability, the Cronbach’s alpha test was performed, and a coefficient of 0.908 was calculated, which indicated the presence of high internal consistency of the questions and relevance of the study subjects for the participants. The findings revealed the presence of emerging issues where an average of approximately 28% of clients do not have an idea of land registration transactions. In addition, in Kenya, similarly to other national mapping agencies in the developing world, pre-independence laws have begun, which need to be upscaled or revised to sustain and effectively address issues noted on land administration and policy.

Spatial Responses of Ecosystem Service Value during the Development of Urban Agglomerations

This study analyzed data from 1995, 2005, and 2015 using mathematical calculations, spatial analysis, and a geographically weighted regression model. The results showed that from 1995 to 2015, the comprehensive regional development degree (RDD) of urban agglomeration in the middle of Jilin Province increased overall, with the average RDD increasing from 0.250 in 1995 to 0.323 in 2015. Especially in Changchun, a sub-provincial city, the RDD increased by nearly one-third, and the gap between this and other cities has been increasing. However, the ecosystem service value (ESV) decreased overall, with the average ESV decreasing from 108.3 in 1995 to 105.4 in 2015, and showed a strong spatial correlation. The maximum quantile in southeast–northwest direction was 1.712, with good homogeneity. The spatial influence coefficient of the RDD on the ESV showed a trend from positive to negative in the northwest–southeast direction. This value decreased continuously while the negative agglomeration area was gradually expanding, corresponding to the stressful effects of the RDD on ESV. The results of this study can provide a reference for urban planning and development as well as encourage reasonable regional spatial planning to ensure the sustainable development of urban agglomerations.

A Geospatial Approach to Measure Social Benefits in Urban Land Use Optimization Problem

Different conflicting objectives are used in urban land use optimization problems. The maximization of social benefit is one of the important objectives in urban land use optimization problems. Many researchers have used different methods to measure social benefits in land use optimization. Studies show that there is no established method to measure social benefit in the urban land use allocation game. Against this background, this study aims to (a) identify the appropriate indicators as a measure of social benefit, and (b) propose a composite index to measure social benefit in urban land use optimization problems. Based on the literature review and expert opinion, this study identifies four indicators as a measure of social benefit. These are spatial compactness, land use compatibility, land use mix, and evenness of population distribution. Using the weighted sum approach, this study proposes a composite social benefit index (SBI) to measure social benefit in urban land use allocation/optimization problems and planning. The study suggests that spatial compactness is the most influential indicator to the SBI, but the most critical indicator is compatibility, whose 11.60% value reduction from 0.5 alters the decision of choice. Finally, the proposed method was applied in Rajshahi city in Bangladesh. The result suggests the potential of using SBI in the land use allocation problem. It is expected that the proposed social benefit index (SBI) will help the land use optimization and planning and will be helpful for decision makers.