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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorHasan, S-
dc.creatorShi, WZ-
dc.creatorZhu, XL-
dc.creatorAbbas, S-
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
dc.rightsThe following publication Hasan, S.; Shi, W.; Zhu, X.; Abbas, S. Monitoring of Land Use/Land Cover and Socioeconomic Changes in South China over the Last Three Decades Using Landsat and Nighttime Light Data. Remote Sens. 2019, 11, 1658, 1-23 is available at
dc.subjectLand use land coveren_US
dc.subjectLight indexen_US
dc.subjectNighttime light dataen_US
dc.titleMonitoring of land use/land cover and socioeconomic changes in South China over the last three decades using landsat and nighttime light dataen_US
dc.typeJournal/Magazine Articleen_US
dcterms.abstractLand use and land cover changes (LULCC) are prime variables that reflect changes in ecological systems. The Guangdong, Hong Kong, and Macau (GHKM) region located in South China has undergone rapid economic development and urbanization over the past three decades (1986-2017). Therefore, this study investigates the changes in LULC of GHKM based on multi-year Landsat and nighttime light (NTL) data. First, a supervised classification technique, i.e., support vector machine (SVM), is used to classify the Landsat images into seven thematic classes: forest, grassland, water, fishponds, built-up, bareland, and farmland. Second, the demographic activities are studied by calculating the light index, using nighttime light data. Third, several socioeconomic factors, derived from statistical yearbooks, are used to determine the impact on the LULCC in the study area. The post-classification change detection shows that the increase in the urban area, from 0.76% (1488.35 km(2)) in 1986 to 10.31% (20,643.28 km(2)) in 2017, caused GHKM to become the largest economic segment in South China. This unprecedented urbanization and industrialization resulted in a substantial reduction in both farmland (from 53.54% (105,123.93 km(2)) to 33.07% (64,932.19 km(2))) and fishponds (from 1.25% (2463.35 km(2)) to 0.85% (1674.61 km(2))) during 1986-2017. The most dominant conversion, however, was of farmland to built-up area. The subsequent urban growth is also reflected in the increasing light index trends revealed by NTL data. Of further interest is that the overall forest cover increased from 33.24% (65,257.55 km(2)) to 45.02% (88,384.19 km(2)) during the study period, with a significant proportion of farmland transformed into forest as a result of different afforestation programs. An analysis of the socioeconomic indicators shows that the increase in gross domestic product, total investment in real estate, and total sales of consumer goods, combined with the overall industrialization, have led to (1) urbanization on a large scale, (2) an increased light index, and (3) the reduction of farmland. The speed of development suggests that opportunistic development has taken place, which requires a pressing need to improve land policies and regulations for more sustainable urban development and protection of farmland.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationRemote sensing, 2 July 2019, v. 11, no. 14, 1658, p. 1-23-
dcterms.isPartOfRemote sensing-
dc.description.validate201909 bcrc-
dc.description.oaVersion of Recorden_US
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