Open AccessLand use/Land Cover and Change Detection in Chikodi Taluk, Belagavi District, Karnataka using Object based Image Classification
Author(s) -
S. C.,
C. Krishnaiah,
Praveen G. Deshbhandari
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a1290.109119
Subject(s) - land cover , land use , urbanization , agricultural land , change detection , cohen's kappa , agriculture , geography , environmental science , computer science , environmental resource management , remote sensing , civil engineering , archaeology , machine learning , engineering , economics , economic growth
The study examines land use land cover and change detection in Chikodi taluk, Belagavi district, Karnataka. Land use land cover plays an important role in the study of global change. Due to fast urbanization there is variation in natural resources such as water body, agriculture, wasteland land etc. These environment problems are related to land use land cover changes. And for the sustainable development it is mandatory to know the interaction of human activities with the environment and to monitor the change detection. In present study for image classification Object Based Image Analysis (OBIA) method was adapted using multi-resolution segmentation for the year 1992, 1999 and 2019 imagery and classified into four different classes such as agriculture, built-up, wasteland and water-body. Random points (200) were generated in ArcGIS environment and converted points into KML layer in order to open in Google Earth. For the accuracy assessment confusion matrix was generated and result shows that overall accuracy of land use land cover for 2019 is 83% and Kappa coefficient is 0.74 which is acceptable. These outcomes of the result can provide critical input to decision making environmental management and planning the future.