Semantic Scholar Open Access 2021 170 sitasi

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

Manikandan Kamaraj S. Rangarajan

Abstrak

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 km2 and 10 km2, 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.

Topik & Kata Kunci

Penulis (2)

M

Manikandan Kamaraj

S

S. Rangarajan

Format Sitasi

Kamaraj, M., Rangarajan, S. (2021). Predicting the future land use and land cover changes for Bhavani basin, Tamil Nadu, India, using QGIS MOLUSCE plugin. https://doi.org/10.1007/s11356-021-17904-6

Akses Cepat

Lihat di Sumber doi.org/10.1007/s11356-021-17904-6
Informasi Jurnal
Tahun Terbit
2021
Bahasa
en
Total Sitasi
170×
Sumber Database
Semantic Scholar
DOI
10.1007/s11356-021-17904-6
Akses
Open Access ✓