2022
DOI: 10.3390/rs14195053
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A Field-Data-Aided Comparison of Three 10 m Land Cover Products in Southeast Asia

Abstract: To study global and regional environment protection and sustainable development and also to optimize mapping methods, it is of great significance to compare three existing 10 m resolution global land cover products in terms of accuracy: FROM-GLC10, the ESRI 2020 land cover product (ESRI2020), and the European Space Agency world cover 2020 product (ESA2020). However, most previous validations lack field collection points in large regions, especially in Southeast Asia, which has a cloudy and rainy climate, creat… Show more

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Cited by 13 publications
(11 citation statements)
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“…It is possible to determine whether the classification results are sourced from two separate classes by comparing the derivatives of each predicted class in the matrix to the derivative of the actual class in each row. For remote sensing picture classification, the most effective and practical validation tool is the confusion matrix method 52 . The vast majority of operations are consolidated into the error matrix, which use producer accuracy (PA), user accuracy (UA), and overall accuracy (OA) as indicators; this method is therefore successful 53 .…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…It is possible to determine whether the classification results are sourced from two separate classes by comparing the derivatives of each predicted class in the matrix to the derivative of the actual class in each row. For remote sensing picture classification, the most effective and practical validation tool is the confusion matrix method 52 . The vast majority of operations are consolidated into the error matrix, which use producer accuracy (PA), user accuracy (UA), and overall accuracy (OA) as indicators; this method is therefore successful 53 .…”
Section: Methodsmentioning
confidence: 99%
“…For remote sensing picture classification, the most effective and practical validation tool is the confusion matrix method. 52 The vast majority of operations are consolidated into the error matrix, which use producer accuracy (PA), user accuracy (UA), and overall accuracy (OA) as indicators; this method is therefore successful. 53 A test of the classification results' Fig.…”
Section: Field Datamentioning
confidence: 99%
“…LUCAS [15,[39][40][41].In particular, based on the CHINA2000 reference dataset, Song et al identified obvious confusion of grass in China within GLOBCOVER, MODIS2005, MODIS2000, and GLC2000 products . Gao et al evaluated the capability of three LC datasets by comparing them to the LUCAS reference dataset across the European Union, and showed that disagreement primarily occurred in regions characterized by heterogeneity [27].…”
Section: Study Areamentioning
confidence: 99%
“…For example, ESRI has released the 2020 Land Cover product. It has good classification results for agricultural land, forests, water bodies, and building sites, but poor classification results for shrubs, wetlands, or fallow lands [27]. Additionally, Myanmar is relatively backward.…”
Section: Introductionmentioning
confidence: 99%