DOI: 10.3390/rs12030584
论文题名: Mapping and quantifying the human-environment interactions in middle Egypt using machine learning and satellite data fusion techniques
作者: Blasco J.M.D. ; Cian F. ; Hanssen R.F. ; Verstraeten G.
刊名: Remote Sensing
ISSN: 20724292
出版年: 2020
卷: 12, 期: 3 语种: 英语
英文关键词: AI4EO
; Egypt
; Google earth engine
; Land reclamation
; Landscape dynamics
; Machine learning
; Multi-temporal land cover mapping
; Satellite data fusion
; Urban growth
Scopus关键词: Agriculture
; Climate change
; Data fusion
; Land reclamation
; Learning systems
; Machine learning
; Mapping
; Neural networks
; Population statistics
; Remote sensing
; Rural areas
; Satellites
; Structures (built objects)
; AI4EO
; Egypt
; Google earths
; Land cover mapping
; Landscape dynamics
; Satellite data
; Urban growth
英文摘要: Population growth in rural areas of Egypt is rapidly transforming the landscape. New cities are appearing in desert areas while existing cities and villages within the Nile floodplain are growing and pushing agricultural areas into the desert. To enable control and planning of the urban transformation, these rapid changes need to be mapped with high precision and frequency. Urban detection in rural areas in optical remote sensing is problematic when urban structures are built using the same materials as their surroundings. To overcome this limitation, we propose a multi-temporal classification approach based on satellite data fusion and artificial neural networks. We applied the proposed methodology to data of the Egyptian regions of El-Minya and part of Asyut governorates collected from 1998 until 2015. The produced multi-temporal land cover maps capture the evolution of the area and improve the urban detection of the European Space Agency (ESA) Climate Change Initiative Sentinel-2 Prototype Land Cover 20 m map of Africa and the Global Human Settlements Layer from the Joint Research Center (JRC). The extension of urban and agricultural areas increased over 65 km2 and 200 km2, respectively, during the entire period, with an accelerated increase analysed during the last period (2010-2015). Finally, we identified the trends in urban population density as well as the relationship between farmed and built-up land. © 2020 by the authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/159734
Appears in Collections: 气候变化与战略
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作者单位: Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, 2628 CN, Netherlands; Department of Earth and Environmental Sciences, Leuven, Division of Geography and Tourism, KU Leuven-University of Leuven, Leuven, B-3001, Belgium; Department of Economics, Ca' Foscari University Venice, Venice, 30121, Italy; The World Bank Group, Washington, DC 20433, United States
Recommended Citation:
Blasco J.M.D.,Cian F.,Hanssen R.F.,et al. Mapping and quantifying the human-environment interactions in middle Egypt using machine learning and satellite data fusion techniques[J]. Remote Sensing,2020-01-01,12(3)