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A multi-resolution global land cover dataset through multisource data aggregation

  • Research Paper
  • Special Topic: Remote Sensing and Global Change
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Abstract

Recent developments of 30 m global land characterization datasets (e.g., land cover, vegetation continues field) represent the finest spatial resolution inputs for global scale studies. Here, we present results from further improvement to land cover mapping and impact analysis of spatial resolution on area estimation for different land cover types. We proposed a set of methods to aggregate two existing 30 m resolution circa 2010 global land cover maps, namely FROM-GLC (Finer Resolution Observation and Monitoring-Global Land Cover) and FROM-GLC-seg (Segmentation), with two coarser resolution global maps on development, i.e., Nighttime Light Impervious Surface Area (NL-ISA) and MODIS urban extent (MODIS-urban), to produce an improved 30 m global land cover map—FROM-GLC-agg (Aggregation). It was post-processed using additional coarse resolution datasets (i.e., MCD12Q1, GlobCover2009, MOD44W etc.) to reduce land cover type confusion. Around 98.9% pixels remain 30 m resolution after some post-processing to this dataset. Based on this map, majority aggregation and proportion aggregation approaches were employed to create a multi-resolution hierarchy (i.e., 250 m, 500 m, 1 km, 5 km, 10 km, 25 km, 50 km, 100 km) of land cover maps to meet requirements for different resolutions from different applications. Through accuracy assessment, we found that the best overall accuracies for the post-processed base map (at 30 m) and the three maps subsequently aggregated at 250 m, 500 m, 1 km resolutions are 69.50%, 76.65%, 74.65%, and 73.47%, respectively. Our analysis of area-estimation biases for different land cover types at different resolutions suggests that maps at coarser than 5 km resolution contain at least 5% area estimation error for most land cover types. Proportion layers, which contain precise information on land cover percentage, are suggested for use when coarser resolution land cover data are required.

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Authors and Affiliations

  1. Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing, 100084, China

    Le Yu, XueCao Li, YuanYuan Zhao & Peng Gong

  2. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China

    Jie Wang & Peng Gong

  3. State Key Laboratory of Remote Sensing Science, and College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China

    CongCong Li

  4. Joint Center for Global Change Studies, Beijing, 100875, China

    Peng Gong

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  1. Le Yu
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  2. Jie Wang
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  3. XueCao Li
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  4. CongCong Li
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  5. YuanYuan Zhao
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Correspondence to Peng Gong.

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Yu, L., Wang, J., Li, X. et al. A multi-resolution global land cover dataset through multisource data aggregation. Sci. China Earth Sci. 57, 2317–2329 (2014). https://doi.org/10.1007/s11430-014-4919-z

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  • DOI: https://doi.org/10.1007/s11430-014-4919-z

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