Introductory Digital Image Processing: A Remote Sensing Perspective
Introductory Digital Image Processing: A Remote Sensing Perspective
Remote Sensing and Image Interpretation
Remote Sensing and Image Interpretation
Quantile estimation in two-phase sampling
Computational Statistics & Data Analysis
Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter
Computational Statistics & Data Analysis
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Due to the progressive increase in development of desert land in Egypt, the demand for efficient and accurate land cover change information is increasing. In this study, we apply the methodology of post-classification change detection to map and monitor land cover change patterns related to agricultural development and urban expansion in the desert fringes of the Eastern Nile Delta region. Using a hybrid classification approach, we employ multitemporal Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images from 1984, 1990 and 2003 to produce three land cover/land-use maps. Post-classification comparison of these maps was used to obtain 'from-to' statistics and change detection maps. The change detection results show that agricultural development increased by 14% through the study period. The average annual rate of land reclamation during 1990-2003 (4511 ha a-1) was comparable to that during 1984-1990 (4644 ha a-1), reflecting a systematic national plan for desert reclamation that went into effect. We find that the increase in urbanization (by ca 21 300 ha) during 1990-2003 was predominantly due to encroachment into traditionally cultivated land at the fringes of urban centres. Our results accurately quantify the land cover changes and delineate their spatial patterns, demonstrating the utility of Landsat data in analysing landscape dynamics over time. Such information is critical for making efficient and sustainable policies for resource management.