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Prediction of spatio-temporal land use/land cover dynamics in rapidly developing Varanasi district of Uttar Pradesh, India, using geospatial approach: a comparison of hybrid models

机译:印度北方邦快速发展瓦拉纳西区快速发展的时空土地利用/土地覆盖动态预测,采用地理空间方法:混合模型的比较

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摘要

Land use/land cover changes (LULCC) are one of the foremost aspects of environmental changes caused by human-induced activities mainly in rapidly developing areas. This study endeavors to evaluate and compare three hybrid models: stochastic Markov chain (ST-MC), cellular automata-Markov chain (CA-MC), and multi-layer perceptron-Markov chain (MLP-MC) to predict future land use/land cover (LULC) scenario in Varanasi district. LULC information extracted for years 1988 and 2001 was first employed to predict LULC scenario for 2015 using three hybrid models. The predicted results were compared with the observed LULC information for the year 2015 to appraise the validity of models through kappa index statistics. The MLP-MC model yielded reliable and best results. Finally, based on this consequence, the prediction of future LULC scenarios for years 2030 and 2050 was performed. The findings of this study exhibited the constant but overall increase of built up area and a considerable reduction in agricultural land. The results also demonstrate the potentiality of MLP-MC hybrid model for better understanding of spatio-temporal dynamics and predicting future landsacpe?scenario in Varanasi district of Uttar Pradesh, India.
机译:土地使用/土地覆盖变更(LULCC)是人类诱导的活动主要在快速发展领域的环境变化的最重要方面之一。本研究努力评估和比较三种混合模型:随机马尔可夫链(ST-MARCAV),蜂窝自动机 - 马尔可夫链(CA-MC),以及多层Perceptron-Markov链(MLP-MC),以预测未来的土地使用/瓦拉纳西区的陆地封面(LULC)情景。第1988年和2001年提取的Lulc信息首先是使用三种混合模型预测2015年的Lulc场景。将预测结果与2015年度观察到的Lulc信息进行了比较,以评估模型的有效性通过Kappa指数统计数据。 MLP-MC模型产生可靠和最佳结果。最后,基于这一后果,执行了几年2030和2050的未来LULC情景的预测。该研究的结果表现出恒定但整体增加的建筑面积和农业土地相当减少。结果还展示了MLP-MC混合模型的潜力,以便更好地了解时空动态和预测未来Landsacpe的情况?在印度北方邦瓦拉纳西区的场景。

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