Abstract
Land cover plays an important role in the climate and biogeochemistry of the Earth system. It is of great significance to produce and evaluate the global land cover (GLC) data when applying the data to the practice at a specific spatial scale. The objective of this study is to evaluate and validate the consistency of the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product (MCD12Q1) at a provincial scale (Anhui Province, China) based on the Chinese 30 m GLC product (GlobeLand30). A harmonization method is firstly used to reclassify the land cover types between five classification schemes (International Geosphere Biosphere Programme (IGBP) global vegetation classification, University of Maryland (UMD), MODIS-derived Leaf Area Index and Fractional Photosynthetically Active Radiation (LAI/FPAR), MODIS-derived Net Primary Production (NPP), and Plant Functional Type (PFT)) of MCD12Q1 and ten classes of GlobeLand30, based on the knowledge rule (KR) and C4.5 decision tree (DT) classification algorithm. A total of five harmonized land cover types are derived including woodland, grassland, cropland, wetland and artificial surfaces, and four evaluation indicators are selected including the area consistency, spatial consistency, classification accuracy and landscape diversity in the three sub-regions of Wanbei, Wanzhong and Wannan. The results indicate that the consistency of IGBP is the best among the five schemes of MCD12Q1 according to the correlation coefficient (R). The “woodland” LAI/FPAR is the worst, with a spatial similarity (O) of 58.17% due to the misclassification between “woodland” and “others”. The consistency of NPP is the worst among the five schemes as the agreement varied from 1.61% to 56.23% in the three sub-regions. Furthermore, with the biggest difference of diversity indices between LAI/FPAR and GlobeLand30, the consistency of LAI/FPAR is the weakest. This study provides a methodological reference for evaluating the consistency of different GLC products derived from multi-source and multi-resolution remote sensing datasets on various spatial scales.
Highlights
Land use/land cover change (LUCC) is closely related to climate change, terrestrial ecosystem, geophysical and chemical cycles, human life, etc. [1,2,3,4,5,6]
The results indicate that the consistency of IGBP is the best among the five schemes of MCD12Q1 according to the correlation coefficient (R)
The “woodland” area derived from the five classification schemes of MCD12Q1 is, respectively, 42.75 km2 of IGBP, 53.50 km2 of UMD, 8.75 km2 of LAI/FPAR, 52.75 km2 of net primary productivity (NPP) and 57.00 km2 of Plant Functional Type (PFT) in Wanbei, while it is 106.25 km2 of GlobeLand30 and is much closer to the yearbook statistics
Summary
Land use/land cover change (LUCC) is closely related to climate change, terrestrial ecosystem, geophysical and chemical cycles, human life, etc. [1,2,3,4,5,6]. Remote sensing technology has the ability to produce land cover products at different spatial resolutions, especially at a global scale. Global land cover (GLC) mapping has been given much attention by the international scientific community since the 1990s. Some scholars have paid more attention to assessing and validating the consistency, accuracy and suitability among different GLC products [7,8,9,10,11,12]. GLC products have been distributed to the scientific community, non-governmental organizations, individuals and governments. It is of great significance to evaluate and validate the quality and consistency of these GLC products [13]. Several GLC products have been produced, including the International Geosphere-Biosphere Programme
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