Spatio-Temporal Change Detection Analysis of Land Use Land Cover of Bathinda District, Punjab, India

Naseer Ahmad*

Department of Environmental Sciences and Technology, Central University of Punjab, VPO, Ghudda, Punjab 151401, India

corresponding Author E-mail:naseerevs@gmail.com

DOI : http://dx.doi.org/10.13005/bbra/3111

ABSTRACT: Due to rapid industrialization and urban sprawl in the last few decades, the land use pattern and its consumption takes place at a large scale that could lead to problems such as over-exploitation of land resources, food insecurity and pollution. It becomes imperative to carry out monitoring and subsequent modelling of land use land cover (LULC) changes. An attempt was made to study the changes in the LULC pattern of district of Bathinda, Punjab, India. Remote sensing (RS) and geographical information system (GIS) were used to perform the analysis of satellite data using image processing and classification procedures. For preparing LULC maps, supervised classification was carried out using maximum likelihood classification (MLC) algorithm, aided with Earth Resources Data Analysis System (ERDAS) Imagine 2014 and ArcGIS 10.3 software. Further, change detection study was done using multi-temporal Linear Imaging Self Scanning Sensor-III (LISS-III) data sets of the year 2006 and 2018 to analyze the temporal changes. It was observed that the region is occupied by various ground features such as water, built-up area, agricultural land, vegetation/trees and fallow land. The results revealed that the area under water bodies have increased by 0.413km² in 2018. The built-up areas including human settlements, commercial infrastructures, roads and other pavements, have increased from 584.448km² to 852.140km² between 2006 and 2018, whereas the agricultural land has reduced from 2686.121km² to 2398.384km² during the period. The area under vegetation (trees) indicated that there was an increasing trend from 28.490km² to 54.678km² during 12years of time span whereas, the fallow land/barren land showed a decreasing trend from 26.361km² to 18.367km². It is suggested that the LULC change detection studies are very significant to conserve the land resources and to avoid further degradation.

KEYWORDS: Built-up area; Classification; Climate; Monitoring; Management; Temporal; Urban; Vegetation

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