Abstract

Land cover changes in tropical rainforest climate zones play an important role in global climate change and the functioning of the Earth’s natural system. Existing research on the consistency of different land cover products has mainly focused on administrative divisions (continental or national scales). However, the ongoing production of large regional or global land cover products with higher resolutions requires us to have a better grasp of confusing land types and their geographical locations for different zoning (e.g., geographical zoning) in order to guide the optimization of strategies such as zoning and sample selection in automated land cover classification. Therefore, we selected the GlobeLand30-2010, GLC_FCS30-2015, and FROM_GLC2015 global land cover products with a 30-m resolution covering Indonesia, which has a tropical rainforest climate, as a case study, and then analyzed these products in terms of areal consistency, spatial consistency, and accuracy evaluation. The results revealed that (a) all three land cover products revealed that forest is the main land cover type in Indonesia. The area correlation coefficient of any two products is better than 0.89; (b) the areas that are completely consistent among the three products account for 58% of the total area of Indonesia, mainly distributed in the central and northern parts of Kalimantan and Papua, which are dominated by forest land types. The spatial consistency of the three products is low, however, due to the complex surface types and staggered distributions of grassland, shrub, cultivated land, artificial surface, and other land cover types in Java, eastern Sumatra, and the eastern, southern, and northwestern sections of Kalimantan, where the elevation is less than 200 m. Given these results, land cover producers should take heed of the classification accuracy of these areas; (c) the absolute accuracy evaluation demonstrated that the GLC_FCS30-2015 product has the highest overall accuracy (65.59%), followed by the overall accuracy of the GlobeLand30-2010 product (61.65%), while the FROM_GLC2015 exhibits the lowest overall accuracy (57.71%). The mapping accuracy of the three products is higher for forests and artificial surfaces. The cropland mapping accuracy of the GLC_FCS30-2015 product is higher than those of the other two products. The mapping accuracy of all products is low for grassland, shrubland, bareland, and wetland. The classification accuracy of these land cover types requires further improvement and cannot be used directly by land cover users when conducting relevant research in tropical rainforest climate zones, since the utilization of these products could lead to serious errors.

Highlights

  • Land cover classification and mapping is an important basic goal in global change research and provides a data source for many studies on global change [1,2,3]

  • Where Ri is the area correlation coefficient of two land cover data, i is the land cover type, Xi is the total area of type i in land cover dataset X, Yi is the total area of type i in land cover dataset Y, X is the average of the total area of all types in land cover dataset X, Y is the average of the total area of all types in land cover dataset Y, and n is the total number of land cover types

  • The results revealed that the overall accuracy and kappa coefficient of the GLC_FCS30-2015 product were the highest, with values of 65.59% and 0.55, respectively (Table 9), followed by the GlobeLand30-2010 product, with overall accuracy and kappa coefficient values of 61.65% and 0.49, respectively (Table 10)

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Summary

Introduction

Land cover classification and mapping is an important basic goal in global change research and provides a data source for many studies on global change [1,2,3]. There are many sets of land cover products with different resolutions, such as the Global Land Cover Fine Surface Covering 30-2015 (GLC_FCS30-2015), produced by the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences [17], the GlobeLand30-2010, produced by the National Geomatics Center of China [18], the Fine Resolution Observation and Monitoring of Global Land Cover (FROM_GLC), produced by Tsinghua University [19], the Moderate-resolution Imaging Spectroradiometer (MODIS) of Boston University [20], the GLC2000 of the European Union [21], and others The emergence of these remote sensing products provides basic data for industry and academia that can be utilized to perform relevant production research [22]. The reason for this variety is that these remote sensing land cover products lack consistent benchmarks, and land cover users do not understand the spatial accuracy characteristics of these products in different regions and the advantages and disadvantages of specific field applications

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