Contrastive Analysis and Accuracy Assessment of Three Global 30 m Land Cover Maps Circa 2020 in Arid Land

Qiang Bie (), Ying Shi, Xinzhang Li and Yueju Wang
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Qiang Bie: Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
Ying Shi: Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
Xinzhang Li: Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
Yueju Wang: Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China

Sustainability, 2022, vol. 15, issue 1, 1-17

Abstract: Fine-resolution land cover (LC) products are critical for studies of urban planning, global climate change, the Earth’s energy balance, and the geochemical cycle as fundamental geospatial data products. It is important and urgent to evaluate the performance of the updated global land cover maps. In this study, three widely used LC maps with 30 m spatial resolution (FROM-GLC30-2020, GLC_FCS30, and GlobeLand30) published around 2020 were evaluated in terms of their degree of consistency and accuracy metrics. First, we compared their similarities and difference in the area ratio and spatial patterns over different land cover types. Second, the sample and response protocol was proposed and validation samples were collected. Based on this, the overall accuracy, producer’s accuracy, and user’s accuracy were analyzed. The results revealed that: (1) the consistent areas of the three maps accounted for 65.96% of the total area and that two maps exceeded 75% of it. (2) The dominant land cover types, bare land and grassland, were the most consistent land cover types across the three products. In contrast, the spatial inconsistency of the wetland, shrubland, and built-up areas were relatively high, with the disagreement mainly occurring in the heterogeneous regions. (3) The overall accuracy of the GLC_FCS30 map was the highest with a value of 87.07%, which was followed by GlobeLand30 (85.69%) and FROM-GLC30 (83.49%). Overall, all three of the LC maps were found to be consistent and have a good performance in classification in the arid regions, but their ability to accurately classify specific types varied.

Keywords: land cover map; consistency analysis; accuracy assessment; error matrix; northwestern China (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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