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The purpose of the study is to analyze changes in land use, specifically residential area expansion, in South Tangerang City and identify the factors that influence land use change.

The study used remote sensing methods in ArcGIS 10.8 for data analysis and processing, including spatial analysis and identification of land use changes. The study analyzed satellite images from 2010 and 2020 to identify changes in land use in South Tangerang City over the ten-year period.

The study found that the most significant land use changes in South Tangerang City between 2010 and 2020 were the reduction of mixed plantation area and the expansion of residential areas. The study identified the development of small townships by private developers as the main factor that influenced land use change in South Tangerang City.

The study has several limitations, including a focus on only one aspect of land use change (i.e. residential area expansion), limited scope of the study area (South Tangerang City) and a reliance on remote sensing methods for data analysis.

The findings of the study can be used by policymakers and city planners to develop sustainable land use planning strategies that balance the need for urban development with environmental and social concerns. By understanding the factors that drive land use changes in South Tangerang City, policymakers can develop policies that encourage sustainable urban growth and development while preserving natural resources and protecting the environment.

The study has social implications as the expansion of residential areas in South Tangerang City indicates a growing demand for housing in the area. The study highlights the importance of developing affordable and sustainable housing solutions to meet the needs of the growing population in South Tangerang City. Additionally, the study emphasizes the importance of understanding the social and economic factors that drive land use change and their implications for the well-being of local communities.

The residential area development in South Tangerang City is driven by private developers who make small independent cities that have all facilities in one area. These small cities attract people to reside and also drive high population growth in South Tangerang City, considering it is a buffer city of Jakarta that has good infrastructure development.

In this chapter, the authors contribute toward building a better understanding of farmers’ responses to behavioral drivers of land-use decision by establishing an alternative analytical procedure, which can overcome various drawbacks suffered by methods currently used in existing studies. Firstly, our procedure makes use of spatially high-resolution data, so that idiosyncratic effects of physical environment drivers, e.g., soil textures, can be explicitly modeled. Secondly, we address the well-known censored data problem, which often hinders a successful analysis of land-use shares. Thirdly, we incorporate spatial error dependence (SED) and heterogeneity in order to obtain efficiency gain and a more accurate formulation of variances for the parameter estimates. Finally, the authors reduce the computational burden and improve estimation accuracy by introducing an alternative generalized method of moments (GMM)–quasi maximum likelihood (QML) hybrid estimation procedure. The authors apply the newly proposed procedure to spatially high-resolution data in England and found that, by taking these features into consideration, the authors are able to formulate conclusions about causal effects of climatic and physical environment, and environmental policy on land-use shares that differ significantly from those made based on methods that are currently used in the literature. Moreover, the authors show that our method enables derivation of a more effective predictor of the land-use shares, which is utterly useful from the policy-making point of view.

This paper aims to explore the role of participatory governance to actors’ participation in land use planning for tenure security in rural Tanzania. Three case studies where land use planning project implemented were selected to make assessment on how local actors were involved in the process.

This paper uses qualitative research methods, whereby semi-structured interviews with village landholders and key informants were conducted to get their perspectives on land use decisions and land tenure (in)security. Besides, focus group discussions with the village landholders were also used.

The research findings indicate low participation of local actors in land use planning process. Decisions on land use by the local actors were very minimal. Further, communication between the involved actors was also difficult.

The study offers insights on participatory governance into land use planning for tenure security. The study develops a framework to improve land use planning process toward tenure security outcome. A tri-partite strategy consisting of enabling mechanisms of governance capacity, institutional capacity and converging discourses articulates a framework for the evolution in the degree of local actors’ participation to improve security of land rights through land use planning process in rural Tanzania.

The purpose of the study is to assess the environmental and socio‐economic impacts and risks of climate change through GIS database management system (DBMS) on land use‐informatics and climate‐informatics. The Dabka watershed constitutes a part of the Kosi Basin in the Lesser Himalaya, India in district Nainital has been selected for the case illustration.

Land use‐informatics consists of land use mapping and change diction, i.e. decadal changes and annual changes. Climate‐informatics consists of climate change detection through daily, monthly and annual weather data for a period of 25 years.

The exercise revealed that oak and pine forests have decreased, respectively, by 25 percent (4.48 km²) and 3 percent (0.28 km²) thus bringing a decline of 4.76 km² forest in the watershed during 1990 to 2010. But, due to climate change the mixed forest taking place of oak forest in certain pockets and consequently the mixed forest in the catchment increased by 18 percent (2.3 km²) during the same period which reduced the overall loss of forests in the region but its not eco‐friendly as the oak forest. Barren land increased 1.21 km² (56 percent), riverbed increased 0.78 km² (52 percent) and cultivated land increased about 0.63 km² (3 percent) during the period of 1990 to 2010. Out of the total seven classes of the land use land cover, five classes (i.e. Oak, Pine, Mixed, Barren and Riverbed) are being changed dominantly due to climate change factor and anthropogenic factors plays a supporting role whereas only two classes (scrub land and agricultural land) are being changed dominantly by anthropogenic factors and climate change factors plays a supporting role. Expansion of mixed forest land brought out due to upslope shifting of existing forest species due to climate change factor only because upslope areas getting warmer than past with the rate of 9°C‐12°C/two decades. Consequently, the results concluded that the high rate of land use change accelerating several environmental problems such as high runoff, flash flood, river‐line flood and soil erosion during monsoon season and drought during non‐monsoon period. These environmental problems cause great loss to life and property and poses serious threat to the process of development with have far‐reaching economic and social consequences.

This study generated primary data on land use‐informatics and climate‐informatics to integrate each‐other for impact assessment and mitigation through sustainable land use as constitutes a part of a multidisciplinary project, Department of Science and Technology (D.S.T.) Government of India.

Major land use changes can have a significant impact on the environment, e.g. increased leaching and run‐off losses of nutrients and water contamination. Nitrate (NO₃^–) can be easily leached and, when present at high concentrations in drinking water, can be a health hazard. This paper seeks to report an easy‐to‐use computer model designed to provide predictions of possible impacts on groundwater NO₃^– concentration on a regional scale.

The model takes into account NO₃^–‐N concentrations from various land use activities, land surface recharge rates (as affected by soil water retention capacity, land management, irrigation and rainfall), and mixing of surface recharge and river recharge. Spatial information on land use and groundwater recharge sources are lumped into groundwater management zones (100‐500 km²), and vertical concentration profiles of NO₃^– in groundwater are estimated from a one‐dimensional dispersion model. The model is applied to the 2,300 km² Central Canterbury Plains of New Zealand.

A scenario analysis for the Bankside groundwater management zone showed that the NO₃^–‐N concentration at the groundwater surface could increase from 7.8 mg N L^‐1 to 11.3 mg N L^‐1 if all the land used for sheep farming is replaced by dairy farming (increasing dairy land from 21 per cent to 64 per cent of the total land area). However, the impact of such land use changes on the NO₃^–‐N concentration 50 m below the groundwater surface was relatively small, resulting in an increase of NO₃^–‐N concentration from 0.4 to 0.5 mg N L^‐1. This is because of the significant mixing of surface recharge with river recharge at this depth.

The model can serve as a useful tool for first‐order estimation of possible trends of NO₃^–‐N concentration profiles in aquifers as a result of land use changes.