Agricultural Lands Risk Assessment Using Geo-spatial Techniques A Case Study of Victoria Catchment Area (VCA), Sri Lanka

Siri Karunaratne BATUGODA GEDARA; Takehiro Morimoto

doi:10.14866/ajg.2023s.0_210

Annual Meeting of the Association of Japanese Geographers, Spring 2023

Session ID : 617

DOI https://doi.org/10.14866/ajg.2023s.0_210

Conference information

Host: The Association of Japanese Geographers

Name : Annual Meeting of the Association of Japanese Geographers, Spring 2023

Date : March 25, 2023 - March 27, 2023

Agricultural Lands Risk Assessment Using Geo-spatial Techniques

A Case Study of Victoria Catchment Area (VCA), Sri Lanka

*Siri Karunaratne BATUGODA GEDARA, Takehiro Morimoto

Author information

Keywords: Machine Learning Technique, Support Vector Machine, AHP Analysis, Micro Study, Agriculture Risk

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Abstract

Intensive land use/cover changes can be detcted in the Victoria catment area in Sri Lanka during last two decades. In this study, Land use land cover classification was conducted by using Machine Learning Techniques. “r “ software was used to classify the LANDSAT satellite images (30mX30m). Aging the agriculture community was also mandatory. 60% of fertile lands has been utilized to build houses. It is better to make necessary adjustments to policy regulatory system related to agricultural promotion while mitigating agricultural vulnerability proved through the risk map generated..

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