Studying land use dynamics using decadal satellite images and Dyna-CLUE model in the Mahanadi River basin, India (original) (raw)
2024
Aims: This study was conducted to examine Land Use Land Cover (LULC) dynamics in Maharashtra's sub-upper Krishna basin from 2009 to 2019 using remote sensing and geographical information system (GIS), focusing on water bodies, vegetation, soil, settlements, and their changes. Study Design: Employing remote sensing and GIS for LULC mapping (2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019) the study used a maximum likelihood classifier in supervised classification, identifying six land use categories: water bodies, open shrubs, forests, agricultural land, settlements, and fallow land. Place and Duration of Study: It was conducted in the sub-upper Krishna basin, Maharashtra, over ten years ' data (2009-2019). Methodology: The study utilised satellite remote sensing and GIS tools for LULC mapping. A supervised classification was applied with a maximum likelihood classifier to categorize land. The changes in water bodies, open shrubs, forests, agricultural land, settlements, and fallow land were analysed using GIS approach. Results: It was seen that, over the decade, fallow land decreased by 3.03%, while agricultural land and settlements grew by 7.32% and 4.3%, respectively. Tree cover increased by 9.85%, water bodies by 0.93%, and open scrubland decreased by 1.77%. Institutional factors, easier water access, and technological and economic factors drove these changes. The study advocates the effective use of satellite remote sensing to monitor LULC changes, identifying key drivers, including institutional and technological factors, contributes to sustainable development planning. The findings aid predictions for future land use changes, supporting effective land management and conservation strategies in the region.
Land use land cover dynamics as a function of changing demography and hydrology
GeoJournal, 2013
This paper describes the spatiotemporal changes pertaining to land use land cover (LULC) and the driving forces behind these changes in Doodhganga watershed of Jhelum Basin. An integrated approach utilizing remote sensing and geographic information system (GIS) was used to extract information pertaining to LULC change. Multi-date LULC maps were generated by analyzing remotely sensed images of three dates which include LandSat TM 1992, LandSat ETM? 2001 and IRS LISS-III 2005. The LULC information was extracted by adopting onscreen image interpretation technique in a GIS environment at 1:25,000 scale. Based on the analysis, changes were observed in the spatial extent of different LULC types over a period of 13 years. Significant changes were observed in the spatial extent of forest, horticulture, built-up and agriculture. Forest cover in the watershed has decreased by 1.47 %, Agricultural by 0.93 % while as built-up area has increased by 0.92 %. The net decrease in forest cover and agriculture land indicate the anthropogenic interference into surrounding natural ecosystems. From the study it was found that the major driving forces for these changes were population growth and changes in the stream discharge. The changes in the stream discharge were found responsible for the conversion of agricultural land into horticulture, as horticulture has increased by 1.14 % in spatial extent. It has been found that increasing human population together with decreasing stream discharge account for LULC changes in the watershed. Therefore, the existing policy framework needs to focus upon mitigating the impacts of forces responsible for LULC change so as to ensure sustainable development of land resources.
Development of Decadal (1985–1995–2005) Land Use and Land Cover Database for India
India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for Remote Sens. 2015, 7 2403 comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study.
Land use and land cover (LULC) change has been recognized as a key driver of global climate change by influencing land surface processes. Being in constant change, river basins are always subjected to LULC changes, especially decline in forest cover to give way for agricultural expansion, urbanization, industrialization etc. We used on-screen digital interpretation technique to derive LULC maps from Landsat images at three decadal intervals i.e., 1985, 1995 and 2005 of two major river basins of India. Rain-fed, Mahanadi river basin (MRB) attributed to 55% agricultural area wherein glacier-fed, Brahmaputra river basin (BRB) had only 16% area under agricultural land. Though conversion of forest land for agricultural activities was the major LULC changes in both the basins, the rate was higher for BRB than MRB. While water body increased in MRB could be primarily attributed to creation of reservoirs and aquaculture farms; snow and ice melting attributed to creation of more water bodies in BRB. Scrub land acted as an intermediate class for forest conversion to barren land in BRB, while direct conversion of scrub land to waste land and crop land was seen in MRB. While habitation contributed primarily to LULC changes in BRB, the proximity zones around habitat and other socio-economic drivers contributed to LULC change in MRB. Comparing the predicted result with actual LULC of 2005, we obtained >97% modelling accuracy; therefore it is expected that the Dyna-CLUE model has very well predicted the LULC for the year 2025. The predicted LULC of 2025 and corresponding LULC changes in these two basins acting as early warning, and with the past 2-decadal change analysis this study is believed to help the land use planners for improved regional planning to create balanced ecosystem, especially in a changing climate.
2014
Mapping of land use land cover (LULC) change is fundamental method for assessment, managing and protection of natural resources of a region and the information on the existing land use is one of the prime pre-requisites for suggesting better use of terrain. Remote sensing and Geographical Information system (GIS) provide fundamental tools which can be useful in the investigation of LULC changes at all levels viz, watershed and catchment as well as at basin levels. Remote sensing becomes useful as it provides synoptic view and multi-temporal land uses land cover data that are often required. In the present study, spatio-temporal changes has been studied in the Romshi watershed of Jhelum basin that has been experiencing a lot of land use land cover changes due to both socioeconomic and natural factors. Spatial extent changes in forest cover (8640.239 to 6756.592 ha), horticulture (6891.458 to 8519.483 ha), built-up (858.91 to 2830.438 ha) and agriculture (19483.05 to 18060.83 ha) were...
GEO-EYE, 2021
Analysis of land use and land cover dynamics in the Sind watershed of Kashmir provides valuable insights into the changes that have occurred in the region over the past three decades. The use of satellite images from Landsat 5 TM in 1995, 2005, and Landsat 8 TM in 2015 and 2019 with a spatial resolution of 30m allows for a comprehensive and detailed analysis of the changes in the study area. The images were processed using ArcGIS 10.2.2 and ERDAS Imagine 14, and land use classes identified. The results of the study showed that there has been a significant increase in farmland and settlement areas in the past 25 years. This increase can be attributed to the growing population and the increasing demand for agricultural production and urbanization. These changes have important implications for the ecosystem and the environment, as well as for the livelihoods of the local people. The conversion of natural lands, such as forests and grasslands, into agricultural or urban areas can lead to habitat loss and degradation, soil erosion, and increased runoff and pollution. The retrospective analysis of land use and land cover dynamics in the Sind watershed of Kashmir provides important information for decision-makers and highlights the need for sustainable land use practices to ensure the protection of the ecosystem and the livelihoods of the local people. The findings of this study can inform policies aimed at promoting sustainable land use and environmental management in the region.
Http Dx Doi Org 10 1080 10106049 2013 776641, 2013
An attempt has been made to explore and evaluate the Cellular Automata (CA) Markov modelling to monitor and predict the future land use and land cover (LULC) scenario in a part of Brahmaputra River basin using LULC maps derived from multi-temporal satellite images. CA Markov is a combined cellular automata/Markov chain/multi-criteria/multi-objective land allocation (MOLA) LULC prediction procedure that adds an element of spatial contiguity as well as knowledge base of the likely spatial distribution of transitions to Markov chain analysis. Evidence likelihood map was used for as knowledge base of the likely spatial procedure in CA Markov model. The predicting quantity and predicting location change have been analysed and statistically evaluated. The validation statistics indicated how well the comparison map agreed and disagreed with the reference map. Predicted results accuracy is slightly higher when compare to others studies of LULC change using CA Markov approaches.
Assessment of Land Use Land Cover and River Dynamics of Himalaya: Seti River Sub-Basin of Nepal
The Geographic Base
In rapidly growing areas, land use land cover (LULC) change is one of the most pre-eminent features of environmental changes produced by human-induced activities. LULC changes are critical issues and challenges for environmentally friendly and sustainable development. Understanding land-use and land-cover (LULC) changing patterns is critical for sustainable environmental management, particularly effective water management. This study was focused on the assessment of LULC and sinuosity of the Seti River sub-Basin over 28 years. Satellite imagery of Landsat series (MS, TM, and OLI) were classified using maximum likelihood classifier to create LULC maps for 1991, 2004 and 2019. The LULC change was assessed using change detection analysis and verified the result by confuse matrix. The results showed that forest cover is regaining its original status with the increasing rate of 1.31%. In the meantime, built-up areas are expanding with the rate of 2.62% while agricultural land has decreas...
Applied Ecology and Environmental Research, 2022
The impact of land use and land cover changes (LULCC) is one of the major contributors to increasing greenhouse gas emissions to the atmosphere. At the terrestrial surface, the impact of LULCC is realized in altered hydrology. Conversion of cultivable lands into fallow lands severely affects crop production in agriculturally dominant basins such as the Vaigai River Basin (VRB) in Tamil Nadu, India. Considered as a granary of South Tamil Nadu, any LULCC in VRB results in uncertainty in food production. Therefore, in this study, Landsat images were used to evaluate changes in land use and MODIS NDVI images to estimate changes in browning and greening in VRB during 2001-2020. We also analyzed the rainfall and river discharge in the basin to understand the variations from 2001 to 2019 concerning LULCC. The results showed an increase of seventy-seven percent in fallow lands between 2010 and 2020 and a forty-one to fifty-nine percent increase in urban settlements between 2001 and 2020 in the basin. The impacts of LULCC were realized in monsoon rainfall with no change in river discharge in the lower Vaigai Basin. The study results will aid regulated land use planning and encourage further research on feedback between terrestrial and atmospheric water fluxes for ensuring food security.
Indian Journal of Spatial Science Winter Issue, 2022:13(4) pp.37 - 42 , 2022
This study considered the change in land use and land cover for the last 20 years (2000-2020) in the Kalinjar river basin, using geospatial techniques. For sustainable development, planning, and management mapping and observing the land use and land cover (LULC) changes in the Kalinjar river basin is very important. Images from Landsat-7 Enhanced Thematic Mapper (ETM+) and Landsat-8 Operational Land Imager (OLI) data were used to extract land cover maps. To prepare LULC maps of the basin supervised classification was used. Realities of the ground have been verified and determined through field verifications and specific interviews and thus the accuracy of the classified map was assessed. Eight major LULC classes viz; agricultural land, wasteland, built-up area, natural vegetation, scrubland, gullied area, plantation area, and water bodies have been recognized, which indicate that the main land use of the basin is agriculture. The result shows that the built-up area, scrubland, wasteland, gullied area, plantation, and water bodies increased in the last 20 years, while agricultural land and natural vegetation decreased. Agricultural lands were therefore transformed into built-up areas, scrubland, wasteland, and plantation areas during this period. The growth of the built-up area, wasteland, and scrubland and the reduction of natural vegetation, and agricultural lands are therefore drivers of gully erosion. The findings and analysis of the study emphasize significant policy recommendations for sustainable land use management in the Kalinjar river basin of Odisha.