Name: Dr. Ravinder Dhiman
Department: Centre for Urban Science and Engineering
Program: Ph D. (PhD awarded (2015 - 2020)
Name of supervisor: Prof. Pradip Kalbar
Topic of research: Geospatial approaches for land-use planning of coastal urban regions
Description of research work:
Coastal cities are witnessing unprecedented growth caused by urbanization and industrialization. This uncontrolled growth exerts enormous stress on natural resources of coastal regions. Therefore, land-use planning of the coastal zones is a priority issue with regard to coastal zone management and sustainable development. The process of land-use planning in coastal regions involves the classification of areas into different categories by retaining the synergy between environmental conservation and urban development. Coastal Regulation Zone (CRZ) guidelines are currently being practiced for the management of the Indian coastal zone. These guidelines are difficult to implement and do consider the variation of physical characteristics of the coast.
In this research work, the issues related to current CRZ practices were identified through expert surveys as well as from the literature. Major challenges with current CRZ guidelines are – subjectivity in interpretations of definitions, conflicts in decision-making criteria in the demarcation of coastal area boundaries, and lack of scientific rationale. To address these shortcomings and challenges of existing CRZ practices, a Geographical Information System (GIS) coupled Multiple Criteria Decision Making (MCDM) framework based Coastal Area Index (CAI) was developed in this research work (Figure 1). The GIS-MCDM approach is quantitative in nature and demonstrated the applicability and validation considering Mumbai city as a realistic case. The CAI integrates the spatial variation of the physical characteristics of the coast. The CAI based on the GIS-MCDM approach was developed by applying utility functions to subclasses of physical coastal features for classification of coastal areas according to their importance towards coastal conservation and sensitivity towards developmental activities (Figure 2).
Physical coastal features in the form of raster layers (Land Use Land Cover, Geology, Soil, Normalized Difference Vegetation Index, Slope, and Elevation) were used for deriving the CAI. Linear Weighted Sum (LWS) from MCDM approaches was used to derive the CAI. A sensitivity analysis was also carried to identify the best suitable weighting scheme for LWS based CAI (LWS-CAI). Further, the LWS-CAI based classification of coastal urban regions was compared quantitatively at spatial scale with prevailing CRZ classification approach at three distinct urban coastal sites in Mumbai, and results are validated by field visits. The results of comparative assessment showed that GIS-MCDM based approaches such as LWS-CAI are more suitable for effective and transparent decision making for coastal conservation and development. The LWS-CAI method allows for better utilization of land parcels and conservation of coastal resources at the same time.
In addition to LWS-CAI, another potential GIS-MCDM based Ideal Point (IP) method was also established and demonstrated. Further, the weight elicitation of the physical coastal features using the Analytic Hierarchy Process (AHP) method was carried out to incorporate experts’ opinions. The GIS-MCDM approaches were found useful for identifying the coastal stretches which need special consideration by planning authorities for the application of inclusive coastal management measures. The CAI based on the GIS-MCDM approach is modular, where other relevant criteria can be incorporated for complex decision problems. Therefore, the CAI will facilitate the land-use planning of coastal urban regions based on scientific principles (Figure 3). The CAI synergizes the urban development and conservational activities in complex coastal urban settings such as in case of Mumbai. Further, the CAI is a potential science-policy instrument which is easy in application for land-use planning of urban coastal regions, and will also reduce the gap between technology advancement and possible users for planning of coastal urban regions.
Recognitions of the work