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Detection and Prediction of Water Body and Aquatic Plants Cover Changes of Choghakhor International Wetland, Using Landsat Imagery and the Cellular Automata-Markov Model 期刊论文
发表期刊: CONTEMPORARY PROBLEMS OF ECOLOGY. 出版年: 2020, 卷号: 13, 期号: 5, 页码: 545-555
作者:  Reza, Pirali Zefrehei Ahmad;  Aliakba, Hedayati;  Saeid, Pourmanafi;  Omid, Beyraghdar Kashkooli;  Rasoul, Ghorbani
收藏  |  浏览/下载：7/0  |  提交时间：2021/01/07
Choghakhor International Wetland  Landsat imagery  remote sensing  water body  Wetland dynamics  Cellular Automata (CA)  
Analysis of past and future multi-temporal land use and land cover changes in the semi-arid Upper-Mzingwane sub-catchment in the Matabeleland south province of Zimbabwe 期刊论文
发表期刊: INTERNATIONAL JOURNAL OF REMOTE SENSING. 出版年: 2020, 卷号: 41, 期号: 14, 页码: 5206-5227
作者:  Maviza, Auther;  Ahmed, Fethi
收藏  |  浏览/下载：0/0  |  提交时间：2021/01/07
Land cover classification and change detection analysis of Qaroun and Wadi El-Rayyan lakes using multi-temporal remotely sensed imagery 期刊论文
发表期刊: ENVIRONMENTAL MONITORING AND ASSESSMENT. 出版年: 2019, 卷号: 191, 期号: 4
作者:  Mohamed, Soha A.;  El-Raey, Mohamed E.
收藏  |  浏览/下载：7/0  |  提交时间：2019/11/29
Remote sensing  Image classification  GIS  Digital change detection  Simulation  Prediction  Markov chain model  
Dramatic Loss of Agricultural Land Due to Urban Expansion Threatens Food Security in the Nile Delta, Egypt 期刊论文
发表期刊: REMOTE SENSING. 出版年: 2019, 卷号: 11, 期号: 3
作者:  Radwan, Taher M.;  Blackburn, G. Alan;  Whyatt, J. Duncan;  Atkinson, Peter M.
收藏  |  浏览/下载：8/0  |  提交时间：2019/11/29
land use/land cover  change detection  agricultural land sustainability  CA-Markov  remote sensing  
Reducing uncertainties in land cover change models using sensitivity analysis 期刊论文
发表期刊: KNOWLEDGE AND INFORMATION SYSTEMS. 出版年: 2018, 卷号: 55, 期号: 3, 页码: 719-740
作者:  Ferchichi, Ahlem;  Boulila, Wadii;  Farah, Imed Riadh
收藏  |  浏览/下载：6/0  |  提交时间：2019/11/29
LCC prediction models  Input parameters uncertainty  Model structure uncertainty  Belief function theory  Sensitivity analysis  Estimation  
Modeling the Land Use Change in an Arid Oasis Constrained by Water Resources and Environmental Policy Change Using Cellular Automata Models 期刊论文
发表期刊: SUSTAINABILITY. 出版年: 2018, 卷号: 10, 期号: 8
作者:  Hu, Xiaoli;  Li, Xin;  Lu, Ling
收藏  |  浏览/下载：6/0  |  提交时间：2019/11/29
land use/cover change  land use model  Markov model  cellular automata  artificial neural network  logistic regression  Zhangye oasis  Heihe River Basin  
Soil erosion vulnerability under scenarios of climate land-use changes after the development of a large reservoir in a semi-arid area 期刊论文
发表期刊: JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT. 出版年: 2016, 卷号: 59, 期号: 7, 页码: 1238-1256
作者:  Ferreira, Vera;  Samora-Arvela, Andre;  Panagopoulos, Thomas
Adobe PDF(1374Kb)  |  收藏  |  浏览/下载：12/7  |  提交时间：2020/03/23
land-use change  soil erosion  Revised Universal Soil Loss Equation (RUSLE)  scenarios  climate change  siltation  reservoir  
Application of a CA-based model to predict the fire front in Hyrcanian forests of Iran 期刊论文
发表期刊: ARABIAN JOURNAL OF GEOSCIENCES. 出版年: 2016, 卷号: 9, 期号: 17
作者:  Eskandari, Saeedeh
Adobe PDF(2443Kb)  |  收藏  |  浏览/下载：12/4  |  提交时间：2019/11/29
Cellular Automata (CA)  District Three of Neka-Zalemroud (DTNZ) forests  Fire front model  Fire simulation  Geographic Information System (GIS)  
Land cover change dynamics mapping and predictions using EO data and a GIS-cellular automata model: the case of Al-Baha region, Kingdom of Saudi Arabia 期刊论文
发表期刊: ARABIAN JOURNAL OF GEOSCIENCES. 出版年: 2016, 卷号: 9, 期号: 5
作者:  Mahmoud, Shereif H.;  Alazba, A. A.
Adobe PDF(3258Kb)  |  收藏  |  浏览/下载：15/8  |  提交时间：2019/11/29
Remote sensing  Land cover change (LCC)  GIS-cellular automata model  Markov model  GIS  
Land use/land cover change detection and prediction in the north-western coastal desert of Egypt using Markov-CA 期刊论文
发表期刊: APPLIED GEOGRAPHY. 出版年: 2015, 卷号: 63, 页码: 101-112
作者:  Halmy, Marwa Waseem A.;  Gessler, Paul E.;  Hicke, Jeffrey A.;  Salem, Boshra B.
收藏  |  浏览/下载：2/0  |  提交时间：2020/03/23
Markov-cellular automata  Land use/cover change  Prediction  Deserts