气候变化领域集成服务门户(CCPortal): Spatiotemporal LULC change detection and future prediction for the Mand catchment using MOLUSCE tool

CCPortal

DOI	10.1007/s12665-023-11381-5
	Spatiotemporal LULC change detection and future prediction for the Mand catchment using MOLUSCE tool
	Baghel, Shreeya; Kothari, M. K.; Tripathi, M. P.; Singh, Pradeep Kumar; Bhakar, Sita Ram; Dave, Vikramaditya; Jain, S. K.
发表日期	2024
ISSN	1866-6280
EISSN	1866-6299
起始页码	83
结束页码	2
卷号	83 期号:2
英文摘要	The changes in land use and land cover (LULC) are one of the primary forces for the worldwide climate, ecosystem, and environmental changes. A detail understanding of the dynamics of LULC changes is requisite for natural resource management and sustainable development. The present study region is the Mand catchment situated in Chhattisgarh, which has witnessed changes in LULC due to a rise in anthropogenic activities, such as an increase in population, urbanization, mining activity, and agriculture, as well as natural causes, such as climate change. The present study focused on spatiotemporal LULC change analysis and the subsequent prediction of future LULC patterns. A supervised image classification method in Geographic Information System (GIS) was used to analyze decadal LULC changes from 2001 to 2021. The Cellular Automata-Artificial Neural Network (CA-ANN) model, incorporated in the MOLUSCE (Modules of Land Use Change Evaluation) plugin of QGIS, was used for the future prediction of LULC from 2030 to 2040. The overall accuracy of LULC for 2001, 2010, and 2021 was obtained as 82, 86, and 90%, respectively, and the overall kappa coefficient was obtained as 0.79, 0.84, and 0.88, respectively. The decadal study of LULC change concludes that the agricultural land counts highest area of 29.21% as compared to other LULCs in 2001 which was further increased 31.76% in 2021. Increasing trend were also noticed for the open forest, shallow waterbody, fallow land, and settlement for the decadal years 2001 to 2021 by 1.7, 7.41, 7.57, and 2.55%, respectively. A decreasing trend was observed in LULC changes during the decadal years 2001 to 2021 for dense forest, deep water body, and barren land by 10.28, 0.66, and 10.24%, respectively. The LULC predictions for 2030 and 2040 indicate a similar trend to the prior years, with an increase in settlement, fallow land, agricultural land, open forests, shallow waterbodies, scrubland, and a decrease in dense forests, deep waterbodies, and barren land. This comprehensive analysis of the changes in LULC over an extended period will prove to be a valuable resource for policymakers and planners seeking to achieve sustainable development and effective management of the ecosystem within the study area.
英文关键词	LULC; Remote sensing and GIS; CA-ANN; Accuracy assessment
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Water Resources
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Water Resources
WOS记录号	WOS:001136874800001
来源期刊	ENVIRONMENTAL EARTH SCIENCES
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/305487
作者单位	College of Technology & Engineering Udaipur; College of Technology & Engineering Udaipur; College of Technology & Engineering Udaipur; College of Technology & Engineering Udaipur
推荐引用方式 GB/T 7714	Baghel, Shreeya,Kothari, M. K.,Tripathi, M. P.,et al. Spatiotemporal LULC change detection and future prediction for the Mand catchment using MOLUSCE tool[J],2024,83(2).
APA	Baghel, Shreeya.,Kothari, M. K..,Tripathi, M. P..,Singh, Pradeep Kumar.,Bhakar, Sita Ram.,...&Jain, S. K..(2024).Spatiotemporal LULC change detection and future prediction for the Mand catchment using MOLUSCE tool.ENVIRONMENTAL EARTH SCIENCES,83(2).
MLA	Baghel, Shreeya,et al."Spatiotemporal LULC change detection and future prediction for the Mand catchment using MOLUSCE tool".ENVIRONMENTAL EARTH SCIENCES 83.2(2024).