Spatio-temporal variation in land use/land cover pattern and channel migration in Majuli River Island, India

2021 ◽  
Vol 193 (12) ◽  
Author(s):  
Shehnaj Ahmed Pathan ◽  
Kumar Ashwini ◽  
Briti Sundar Sil
2020 ◽  
Vol 66 (1) ◽  
pp. 51-58
Author(s):  
Chnadrakesh Maurya ◽  
◽  
V. N. Sharma ◽  

Land use is a man-made dynamic process in which human uses land resource to fulfil their various economic, social and cultural needs and at the same time it also provides a base for development. The proper management needed for sustainable development of land can improve the eco-system and its productivity in a particular geographical region. The present study focuses on spatio-temporal changes in land use and land cover pattern in Auranga river basin of Jharkhand using geospatial approach. Supervised classification technique was applied in this study to detect land use/ land cover changes. The main objective of the study is to analyse temporal change of land use/ land cover pattern during 1996, 2007 and 2018 using various dataset as well as other ancillary data. The result reveales both increase and decrease of the different land use/ land cover classes from 1996 to 2018.


2018 ◽  
Vol 10 (3) ◽  
pp. 257-276 ◽  
Author(s):  
Varun Narayan Mishra ◽  
Praveen Kumar Rai ◽  
Rajendra Prasad ◽  
Milap Punia ◽  
Mărgărit-Mircea Nistor

2020 ◽  
Vol 4 (2) ◽  
pp. 55-78
Author(s):  
Modibbo Babagana-Kyari ◽  
Babagana Boso

The fragile Sudano-Sahelian ecological zone of Nigeria has been classified as a hotspot of land cover change (LCC) that has been suffering from serious anthropogenic and biophysical stresses. Damaturu, being the fastest growing town situated in the region happened to be a victim of this negative development. The purpose of this study is to remotely observe and assess the prevailing land-use/land-cover (LULC) dynamics of Damaturu town and its delicate surrounding lands from the year 1987-2017 study periods. To achieve this, a supervised image classification technique with Maximum Likelihood Classifier (MLC) algorithm was used in ERDAS Imagine version 15 software to classify the three epochs multi-temporal and multi-spectral Landsat imageries (TM 1987, ETM+7 2000 and OLI 2017). The classified LULC maps and their resulting statistics were then used to assess the spatio-temporal aspects of the observed changes by placing the results within the wider context of previous related literature and evidences. Findings revealed that the built-up area has been expanding since 1987 with an annual change rate of 4.5% between 1987-2000, and 5.3% during 2000-2017 respectively. The growth of the town is being accompanied by massive farmlands expansion and vegetal cover (trees and shrubs) lost making the surrounding arable lands seriously disturbed. Thus, if the observed trends continue, the entire studied region will be subjected to severe environmental hazard such as desertification. Overall, the study provides valuable information required for sustainable  environmental management.


Sign in / Sign up

Export Citation Format

Share Document