Remote Sensing-Based Urban Sprawl Modeling Using Multilayer Perceptron Neural Network Markov Chain in Baghdad, Iraq

被引:21
|
作者
Al-Hameedi, Wafaa Majeed Mutashar [1 ]
Chen, Jie [1 ]
Faichia, Cheechouyang [2 ]
Al-Shaibah, Bazel [2 ]
Nath, Biswajit [3 ]
Abdulla-Al Kafy [4 ,5 ]
Hu, Gao [1 ]
Al-Aizari, Ali [2 ]
机构
[1] Cent South Univ, Sch Geosci & Infophys, Changsha 410083, Peoples R China
[2] Northeast Normal Univ, Sch Environm, Inst Nat Disaster Res, Changchun 130024, Peoples R China
[3] Univ Chittagong, Dept Geog & Environm Studies, Chittagong 4331, Bangladesh
[4] Rajshahi City Corp, Int Council Local Environm Initiat ICLEI South As, Rajshahi 6203, Bangladesh
[5] Rajshahi Univ Engn & Technol RUET, Dept Urban & Reg Planning, Rajshahi 6204, Bangladesh
关键词
GIS; remote sensing; MLP neural network method; Markov chain model; land use/cover change; future urban simulation; Baghdad; LAND-USE CHANGE; COVER CHANGE; PREDICTION; CITY; GROWTH; ENVIRONMENT; REGRESSION; GIS;
D O I
10.3390/rs13204034
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The global and regional land use/cover changes (LUCCs) are experiencing widespread changes, particularly in Baghdad City, the oldest city of Iraq, where it lacks ecological restoration and environmental management actions at present. To date, multiple land uses are experiencing urban construction-related land expansion, population increase, and socioeconomic development. Comprehensive evaluation and understanding of the effect of urban sprawl and its rapid LUCC are of great importance to managing land surface resources for sustainable development. The present research applied remote sensing data, such as Landsat-5 Thematic Mapper and Landsat-8 Operation Land Imager, on selected images between July and August from 1985 to 2020 with the use of multiple types of software to explore, classify, and analyze the historical and future LUCCs in Baghdad City. Three historical LUCC maps from 1985, 2000, and 2020 were created and analyzed. The result shows that urban construction land expands quickly, and agricultural land and natural vegetation have had a large loss of coverage during the last 35 years. The change analysis derived from previous land use was used as a change direction for future simulation, where natural and anthropogenic factors were selected as the drivers' variables in the process of multilayer perceptron neural network Markov chain model. The future land use/cover change (FLUCC) modeling results from 2030 to 2050 show that agriculture is the only land use type with a massive decreasing trend from 1985 to 2050 compared with other categories. The entire change in urban sprawl derived from historical and FLUCC in each period shows that urban construction land increases the fastest between 2020 and 2030. The rapid urbanization along with unplanned urban growth and rising population migration from rural to urban is the main driver of all transformation in land use. These findings facilitate sustainable ecological development in Baghdad City and theoretically support environmental decision making.
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页数:26
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