High-quality land use and land cover data are important for monitoring and analyzing environmental changes in the background of global warming. This study assessed the spatial and areal inconsistencies in the four most recent multiresources land cover products in a complex manner using the common classification systems of International Geosphere-Biosphere Program (IGBP)-17, IGBP-9, IPCC-5, and TC (vegetation, wetlands, and others only). Based on inconsistencies and multitemporal land cover datasets, a synthesis of the study was triggered out on land use and land cover dynamics during 2001 to 2017 in the southeastern region of Bangladesh. The overall areal and spatial inconsistencies decreased from high to low levels of aggregation (IGBP-17 to TC), indicating that the inconsistencies are not only influenced by the level of thematic detail and landscape complexity but also related to the conversion uncertainties. Overall, areal inconsistency in the comparison of the FROM-GLC and GlobeLand30 datasets was the smallest among the six pairs, whereas the pair of MODISLC and LULC was observed the highest inconsistencies. Based on an overall lower inconsistencies classification system (IGBP-9), the synthetic land use cover changes in the study area were assessed. During the period of study, the areal distribution of forest cover, built-up areas, and water increased annually by 0.4%, 1.32%, and 0.3% respectively, whereas the croplands and wetlands decreased by 0.5% and 0.3%, respectively. The dynamic changes of croplands, forest, and artificial surface were identified the prime cyclic land cover change. This research is helpful in providing training areas for the producer of land cover products. |
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CITATIONS
Cited by 11 scholarly publications.
Classification systems
Earth observing sensors
Landsat
Agriculture
Spatial resolution
Vegetation
Image classification