通过随机森林和 CA-Markov 模型分析马尤拉克希河流域的土地/使用土地/覆盖动态和未来情景

IF 3 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
D. D. L. Soren, K. C. Roy, B. Biswas
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引用次数: 0

摘要

研究重点是分析印度东部恰尔肯德邦和西孟加拉邦马尤拉克希盆地的土地利用和土地覆被状况、变化模式和未来情景。用于图像分类的数据集包括大地遥感卫星 5 号(TM)(1991-2008 年)和大地遥感卫星 8 号(OLI)(2020 年)。使用 QGIS 3.16 和 ArcGIS 10.8 软件进行了各种连续的预处理步骤,如大气校正、图像增强、镶嵌、屏蔽和剪切。研究区域的土地利用和土地覆被类别为水域、植被、裸地、农业和建筑区,采用随机森林机器学习算法进行分类。1991 年、2005 年和 2020 年的 Kappa 值分别为 0.89、0.85 和 0.88,验证并接受了土地利用和土地覆被分类的准确性。在整个研究期间,农业是最主要的土地利用类别,其次是植被和裸地。在 1991-2005 年和 2005-2020 年期间,水域、植被和裸地等土地利用和土地覆被类别的面积持续减少,而农业区和建筑区的面积则分别增加了 4.49%、0.76%、17.81% 和 2.04%。为了预测未来的土地利用和土地覆被状况,我们采用了流行的细胞自动机马尔可夫链模型。预测结果表明,农业仍将是最主要的土地覆被,占 70.24%,其次是植被(17.72%)和建筑区(5.09%)。不过,预计农业和建筑区的比例都会略有下降。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Land/use land /cover dynamics and future scenario of Mayurakshi river basin by random forest and CA–Markov model

Land/use land /cover dynamics and future scenario of Mayurakshi river basin by random forest and CA–Markov model

The study was focused on analyzing the land use and land cover status, change patterns, and future scenarios in the Mayurakshi basin in Jharkhand and West Bengal state of eastern India. The dataset collected for image classification included Landsat 5 (TM) (1991–2008) and Landsat 8 (OLI) (2020). Various sequential preprocessing steps such as atmospheric correction, image enhancement, mosaicking, masking, and clipping were performed using QGIS 3.16 and ArcGIS 10.8 software. The land use and land cover classes found in the study area were water, vegetation, bare land, agriculture, and built-up, and classification was executed by using the Random Forest machine learning algorithm. The accuracy of the classified land use and land cover was validated and accepted with Kappa agreements of 0.89, 0.85, and 0.88 for the years 1991, 2005, and 2020, respectively. Throughout the study period, agriculture emerged as the dominant land use class, followed by vegetation and bare land. The area under the land use and land cover categories of water, vegetation, and bare land continuously decreased between the years 1991–2005 and 2005–2020, while agriculture and built-up areas recorded an increase of 4.49%, 0.76%, 17.81%, and 2.04%, respectively. To project future land use and land cover status, the popular Cellular Automata Markov Chain Model was employed. The projected results indicate that agriculture will remain the dominant land cover with a share of 70.24%, followed by vegetation at 17.72% and built-up areas at 5.09%. However, a marginal decline is expected in both the agriculture and built-up classes.

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来源期刊
CiteScore
5.60
自引率
6.50%
发文量
806
审稿时长
10.8 months
期刊介绍: International Journal of Environmental Science and Technology (IJEST) is an international scholarly refereed research journal which aims to promote the theory and practice of environmental science and technology, innovation, engineering and management. A broad outline of the journal''s scope includes: peer reviewed original research articles, case and technical reports, reviews and analyses papers, short communications and notes to the editor, in interdisciplinary information on the practice and status of research in environmental science and technology, both natural and man made. The main aspects of research areas include, but are not exclusive to; environmental chemistry and biology, environments pollution control and abatement technology, transport and fate of pollutants in the environment, concentrations and dispersion of wastes in air, water, and soil, point and non-point sources pollution, heavy metals and organic compounds in the environment, atmospheric pollutants and trace gases, solid and hazardous waste management; soil biodegradation and bioremediation of contaminated sites; environmental impact assessment, industrial ecology, ecological and human risk assessment; improved energy management and auditing efficiency and environmental standards and criteria.
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