4.7 Article

Predicting the future land use and land cover changes for Bhavani basin, Tamil Nadu, India, using QGIS MOLUSCE plugin

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 29, Issue 57, Pages 86337-86348

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-021-17904-6

Keywords

Land use and Land cover; Multilayer Perceptron MLP-ANN; Predicted LULC; Bhavani basin; MOLUSCE; QGIS

Ask authors/readers for more resources

This study used the QGIS 2.18.24 version MOLUSCE plugin (MLP-ANN) model to analyze land-use changes in the Bhavani basin and forecast future changes. The study found that DEM, distance from the road, and distance from builtup areas have significant effects on land-use changes. The projections indicate a continued increase in cropland and builtup areas in the coming years.
Human population growth, movement, and demand have a substantial impact on land use and land cover dynamics. Thematic maps of land use and land cover (LULC) serve as a reference for scrutinizing, source administration, and forecasting, making it easier to establish plans that balance preservation, competing uses, and growth compressions. This study aims to identify the changeover of land-use changes in the Bhavani basin for the two periods 2005 and 2015 and to forecast and establish potential land-use changes in the years 2025 and 2030 by using QGIS 2.18.24 version MOLUSCE plugin (MLP-ANN) model. The five criteria, such as DEM, slope, aspect, distance from the road, and distance from builtup, are used as spatial variable maps in the processes of learning in MLP-ANN to predict their influences on LULC between 2005 and 2010. It was found that DEM, distance from the road, and distance from the builtup have significant effects. The projected and accurate LULC maps for 2015 indicate a good level of accuracy, with an overall Kappa value of 0.69 and a percentage of the correctness of 76.28%. MLP-ANN is then used to forecast changes in LULC for the years 2025 and 2030, which shows a significant rise in cropland and builtup areas, by 20 km(2) and 10 km(2), respectively. The findings assist farmers and policymakers in developing optimal land use plans and better management techniques for the long-term development of natural resources.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available