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Analyzing and modeling of a large river basin dynamics applying integrated cellular automata and Markov model

机译:基于集成元胞自动机和马尔可夫模型的大型流域动力学分析与建模。

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Historical and exact information about the land use/land cover change is very important for regional sustainable development. The aim of this paper is to determine the rapid changes in land use/land cover (LULC) pattern due to agriculture expansion, environmental calamities such as flood and government policies over Upper Narmada basin, India. Multi-temporal Landsat satellite images for years 1990, 2000, 2010 and 2015 were used to analyze and monitor the changes in LULC with an overall accuracy of more than 85%. Results revealed a potential decrease in natural vegetation (-9.52%) due to the expansion of settlement (+ 0.52%) and cropland (+ 9.43%) from 1990 to 2015. In the present study, Cellular Automata and Markov (CA-Markov), an integrated tool was used to project the short-term LULC map of year 2030. The projected LULC ( 2030) indicated the expansion of built-up area along with the cropland and degradation in the vegetation area. The outcomes from the study can help as a guiding tool for protection of natural vegetation and the management of the built-up area. Additionally, it will help in devising the strategies to utilize every bit of land in the study area for decision makers.
机译:有关土地利用/土地覆被变化的历史和确切信息对于区域可持续发展非常重要。本文的目的是确定由于农业扩张,环境灾难(例如洪水)和印度上纳尔默达盆地的政府政策而导致的土地利用/土地覆被(LULC)模式的快速变化。使用1990年,2000年,2010年和2015年的多时相Landsat卫星图像分析和监测LULC的变化,总体精度超过85%。结果显示,从1990年到2015年,由于定居点(+ 0.52%)和农田(+ 9.43%)的扩大,自然植被的潜在减少量(-9.52%)。在本研究中,Cellular Automata和Markov(CA-Markov) ,则使用集成工具来投影2030年的短期LULC图。预测的LULC(2030年)表明,随着耕地面积的增加,耕地面积的增加以及植被区域的退化。这项研究的结果可作为指导性工具,以保护自然植被和管理建筑面积。此外,这将有助于制定决策者利用研究区域内所有土地的策略。

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