TY - JOUR
T1 - Assessment of land use/land cover changes for Kafr El-Sheikh governorate, Egypt, utilizing remote sensing
AU - Alkhawaga, Abdalmonem
AU - Mohamed, Mohamed
AU - Zeidan, Bakenaz
AU - Elshemy, Mohamed
AU - Elshinnawy, Ahmed
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - Egypt is experiencing considerable changes in its agricultural areas primarily due to unorganized urban sprawl. These changes can lead to reducing area of the highly productive fertile lands, posing major threats to food security and impacting the regional environment and society. This study assesses land use and land cover (LULC) changes in Kafr El-Sheikh Governorate, Nile Delta, Egypt, from 1990 to 2018, proposing a technique that considers cropping seasons using the normalized difference vegetation index (NDVI) for classification enhancement. Supervised classification using the maximum likelihood algorithm was applied to spectral bands for Landsat satellite images covering the study period. Results revealed that the area of the natural reserve of Lake Burullus decreased by approximately 6.3% and that Kafr El-Sheikh Governorate lost approximately 91.5 km2 of agricultural land between 2010 and 2018. This indicates that Kafr El-Sheikh currently suffers from rapid unorganized urban sprawl, leading to a loss of agricultural area at an annual rate of approximately 0.4%. Using the NDVI enhanced the overall classification accuracy by 4.4%. Regular assessment of LULC incorporating higher-resolution data sources is essential in the future for planning, mitigation, and adaptation strategies.
AB - Egypt is experiencing considerable changes in its agricultural areas primarily due to unorganized urban sprawl. These changes can lead to reducing area of the highly productive fertile lands, posing major threats to food security and impacting the regional environment and society. This study assesses land use and land cover (LULC) changes in Kafr El-Sheikh Governorate, Nile Delta, Egypt, from 1990 to 2018, proposing a technique that considers cropping seasons using the normalized difference vegetation index (NDVI) for classification enhancement. Supervised classification using the maximum likelihood algorithm was applied to spectral bands for Landsat satellite images covering the study period. Results revealed that the area of the natural reserve of Lake Burullus decreased by approximately 6.3% and that Kafr El-Sheikh Governorate lost approximately 91.5 km2 of agricultural land between 2010 and 2018. This indicates that Kafr El-Sheikh currently suffers from rapid unorganized urban sprawl, leading to a loss of agricultural area at an annual rate of approximately 0.4%. Using the NDVI enhanced the overall classification accuracy by 4.4%. Regular assessment of LULC incorporating higher-resolution data sources is essential in the future for planning, mitigation, and adaptation strategies.
KW - Food security
KW - Land use changes
KW - Landsat, Maximum likelihood algorithm
KW - Nile Delta
KW - Normalized difference vegetation index
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U2 - 10.1038/s41598-025-96601-7
DO - 10.1038/s41598-025-96601-7
M3 - Article
C2 - 40221455
AN - SCOPUS:105003132359
SN - 2045-2322
VL - 15
JO - Scientific reports
JF - Scientific reports
IS - 1
M1 - 12600
ER -