Remote Sensing Assessment of the Impact of Land Use and Land Cover Change on the Environment of Barddhaman District, West Bengal, India

Abstract

Land transformation is caused by natural as well as anthropogenic driving forces and its impact on the regional environment is a key issue in understanding the relationship between society and the environment. Here, we investigate Land Use Land Cover (LULC) change over four decades, based on Landsat satellite imagery for 1987, 1997, 2007, and 2017, for the Barddhaman district of West Bengal, India. In total, six land use and land cover types have been identified. Over the period in question, there are notable increases in the area under built-up land, plantations and water bodies, whereas there has been a marked decrease in forest cover, agricultural land, and in bare land. The diverse effects of land transformation on the natural environment have been assessed using Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Leaf Area Index (LAI), Effective Roughness Length (ERL), and Surface Albedo (SA). Overall, mean annual LST increased by 2.91 • C during the study period, while there were reduced values for vegetation indices and an increase in the water index over the period 1987-2017. LAI and ERL both exhibit notable decreases, although the pattern was not uniform across the study area. For example, LAI values increased over time in the Kalna, Memari, Jamalpur, Ausgram, and Kanksa regions. In Faridpur-Durgapur, Raniganj, Asansol, and Raina, increases in surface albedo and ERL were more marked than in other regions. Negative correlations are found between LST-NDVI and NDVI-NDWI, while there is no correlation between LST and NDWI. During the period 1987-2017, NDVI values have declined, although the NDWI shows no clear trend. LULC change is shown to have had a series of negative impacts on the environment of the Barddhaman district. In response, technological, economic, policy, or legislation measures are needed to restore degraded ecosystem services in the district as well as other areas where similar impacts are experienced.

Assessing the Relationship among the Land Surface Features: A Geographic Information System (GIS) and Remote Sensing (RS) Based Approach for City Area

“…It was the ratio between the NIR and SWIR raster bands [31]. Here, NIR means Near-Infrared and SWIR means short weave Infra-Red [5]. The NDMI calculation is shown in equation (2).…”

“…Due to urbanization and industrialization, substantial environmental and ecological changes have occurred over the last century, particularly in the last 20 years, raising societal concerns [4]. Land transformation is an important issue in understanding the interaction between humans and the environment since it is driven by both natural and anthropogenic driving forces [5]. The widespread urbanization has harmful repercussions on the Earth's surface, resulting in significant environmental changes [6][7].…”

“…Several methods have been used to evaluate the various environmental implications of LULC, including remote sensing assessments of surface changes utilizing, for example, LST, NDVI, and NDBI. [5,[11][12]. LST was frequently used in global temperature change research studies, as well as hydrological, geo-biophysical, and LULC studies [13].…”

A Structural Equation Modeling Approach to Disentangling Regional-Scale Landscape Dynamics in Ghana

“…There is therefore considerable interest in studying the intersections between environmental, socioeconomic, and climatic data as causes or consequences of LCC. For example, changes in land cover (LC) have been found to be correlated to measurable indicators such as erosion, population expansion, industrial growth, surface heating, and soil quality (Teuling et al, 2010;Kuenzer et al, 2014;Rahaman et al, 2020). Direct human activity, such as increased agricultural land use, has been a significant component of change throughout history in natural LC dynamics (Malhi et al, 2013;Lewis et al, 2015;Addo-Fordjour and Ankomah, 2017).…”

Natural And Human-Induced Land Degradation And Its Impact Using Geospatial Approach In The Kallar Watershed Of Tamil Nadu, India

“…unpredicted rainfall, seasonal variation, and human activity (landuse). Change detection studies of LULC have proven to be effective in assessing the potential adverse impacts on the environment (Leh et al 2013;Pankaj, et al 2019;Rahaman et al 2020). Through LULC Dynamics and simulation models, the extent of land degradation at the landscape level can be evaluated and effective strategies for land management can be developed (Gessesse et al 2015;Rahaman et al 2017a).…”