Assessing Consistency of Five Global Land Cover Data Sets in China

Yan Bai,Yingzhen Liu,Juanle Wang,Yunqiang Zhu,Min Feng,Hao Jiang

doi:10.3390/rs6098739

Abstract

Global land cover mapping with high accuracy is essential to downstream researches. Five global land cover data sets derived from moderate-resolution satellites, i.e., Global Land Cover Characterization (GLCC), University of Maryland land cover product (UMd), Global Land Cover 2000 project data (GLC2000), MODIS Land Cover product (MODIS LC), and GLOBCOVER land cover product (GlobCover), have been widely used in many researches. However, these data sets were produced using different data sources and class definitions, which led to high uncertainty and inconsistency when using them. This study looked into the consistencies and discrepancies among the five data sets in China. All of the compared data sets were aggregated to consistent spatial resolution and extent, along with a 12-class thematic classification schema; intercomparisons among five datasets and each with reference data GLCD-2005 were performed. Results show reasonable agreement across the five data sets over China in terms of the dominating land cover types like Grassland and Cropland; while discrepancies of Forest classes, particularly Shrubland and Wetland among them are great. Additionally, GLC2000 has the highest agreement with GLCD-2005; MODIS LC gets the highest map-specific consistency compared with others; whereas UMd has the lowest agreement with GLCD-2005, but also has the lowest map-specific consistency.

Highlights

Land cover, the observedphysical cover on the earth’s surface [1], is important ecosystem-based information
A total percent area comparison of Global Land Cover Characterization (GLCC), University of Maryland land cover product (UMd), Global Land Cover 2000 project data (GLC2000), MODIS LC, and GlobCover that assigned to each with twelve target classes was performed in China (Figure 2), and the result suggests that there is reasonable agreement across the five products for Grassland, Cropland, and
When classification scheme transformation was performed, differences and uncertainties were already introduced. This effort has been the first investigation of the consistencies and differences of all the five global land cover data sets (i.e., GLCC, UMd, GLC2000, MODIS LC, and GlobCover) for

Summary

Introduction

The observed (bio)physical cover on the earth’s surface [1], is important ecosystem-based information. It is essential for scientific studies, sustainable management of land resources, and political purposes [2]. One of the major data sources for producing land cover datasets is satellite data, which provides a synoptic view of earth surface at various spatial scales and regular time intervals [12], and facilitates mapping and monitoring areas where are difficult or unable to access as well. Land cover maps at different scales have been generated from satellite data [13,14,15,16,17,18,19,20,21,22,23,24], of which five available global land cover data sets have been widely used in a variety of applications: (i) Global Land Cover

Methods

Results

Conclusion