印度旁遮普巴欣达地区土地利用、土地覆盖时空变化检测分析

N. Ahmad
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引用次数: 1

摘要

摘要:近几十年来,由于工业化的快速发展和城市的无序扩张,土地利用模式和消费呈现大规模变化,导致土地资源过度开发、粮食不安全和环境污染等问题。对土地利用和土地覆被变化进行监测和建模已成为当务之急。本文对印度旁遮普邦巴欣达地区土地利用价值变化模式进行了研究。利用遥感(RS)和地理信息系统(GIS)对卫星数据进行图像处理和分类分析。为了编制LULC地图,利用最大似然分类(MLC)算法,在地球资源数据分析系统(ERDAS) Imagine 2014和ArcGIS 10.3软件的辅助下进行监督分类。此外,利用2006年和2018年的多时相线性成像自扫描传感器- iii (LISS-III)数据集进行变化检测研究,分析时间变化。据观察,该区域被各种地面特征所占据,例如水、建筑面积、农业用地、植被/树木和休耕地。结果表明,2018年水体面积增加了0.413km2。2006年至2018年,包括人类住区、商业基础设施、道路和其他路面在内的建成区面积从584.448km2增加到852.140km2,而同期农业用地从2686.121km2减少到2398.384km2。植被(乔木)覆盖面积从28.490km2增加到54.678km2,休耕/荒地面积从26.361km2减少到18.367km2。土地利用价值变化检测研究对保护土地资源和防止土地进一步退化具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatio-Temporal Change Detection Analysis of Land Use Land Cover of Bathinda District, Punjab, India
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.
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