RESIDENTIAL LAND SUITABILITY MODEL FOR RESETTLEMENT PLAN OF ENVIRONMENTAL IMPACT ASSESSMENT A CASE STUDY – KALU GANGA DEVELOPMENT PROJECT

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Year:
2016
Type of Publication:
Proceedings
Keywords:
Geographic Information Systems, Multi Criteria Analysis, Social Environmental Assessment, Model Builder
Authors:
Samarakoon, S. M. D.; Gunatilake, Jagath; Withanage, K. K. S. A.
Abstract:
Kalu Ganga Environmental Impact Assessment (EIA) project is a part of one of the major agricultural development projects started in 2006, which comes along with the Mahaweli Development Projects launched by Mahaweli Authority of Sri Lanka. Resettlement is a very complicated process due to real world complexities. Most of the resettlement sites choose according to the availability of lands. But according to legal acts and policies, the lives of affected people should be better off than they were before. So this contradictory situation has created long term effects on people as well as environment in the past. This study is an attempt to integrate Geographic Information Systems (GIS) and resettlement process under EIA to minimize the social and environmental impacts, to design a methodology of GIS-based residential land suitability assessment, to identify the most suitable residential areas and to integrate GIS and community participation in the resettlement process. The study area was in Laggala Pallegama Divisional Secretariat Division in Matale District. The tool spatial analyst used to perform a multi criteria analysis through model builder in Arc GIS 9.3. Fourteen parameters selected for the model as, slope, landslide susceptibility, water reservation, water availability, mineral resources, road reservation, road accessibility, soil type, hazard prone areas, forest reservation, service centers, land use, archaeological sites, and community participation. With the guidance of subject specialist and legal aspects different weights and influences were decided for each parameter of the model. Also, the Information Value Method (IVM) used to find landslide susceptibility. Most of the data layers were derived from 1: 10, 000 topographic maps. Accordingly, the study reveals that 2%, 14%, 65%, 17%, and 2% found as highly, moderately, low, very low and not suitable for residential lands respectively. Most suitable areas are laid in the South East area of the resettlement area. Thus, this integration of EIA and GIS gives a contribution in decision making, while minimizing social and environmental impacts.
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