Generation of High-Resolution Land Use and Land Cover Maps in JAPAN Version 21.11

DOI JASI Web Site 2 Citations
  • HIRAYAMA Sota
    Earth Observation Research Center, Japan Aerospace Exploration Agency
  • TADONO Takeo
    Earth Observation Research Center, Japan Aerospace Exploration Agency
  • OHKI Masato
    Earth Observation Research Center, Japan Aerospace Exploration Agency
  • MIZUKAMI Yousei
    Earth Observation Research Center, Japan Aerospace Exploration Agency
  • NISHIDA NASAHARA Kenlo
    Earth Observation Research Center, Japan Aerospace Exploration Agency Faculty of Life and Environmental Sciences, University of Tsukuba
  • IMAMURA Koichi
    Remote Sensing Technology Center of Japan, Tsukuba Station
  • HIRADE Naoyoshi
    Remote Sensing Technology Center of Japan, Tsukuba Station
  • OHGUSHI Fumi
    Remote Sensing Technology Center of Japan, Tsukuba Station
  • DOTSU Masanori
    Remote Sensing Technology Center of Japan, Tsukuba Station
  • YAMANOKUCHI Tsutomu
    Remote Sensing Technology Center of Japan, Tsukuba Station

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Other Title
  • JAXA高解像度土地利用土地被覆図日本域21.11版（HRLULC-Japan v21.11）の作成
  • JAXA コウカイゾウド トチ リヨウ トチ ヒフクズ ニホンイキ 21.11ハン(HRLULC-Japan v21.11)ノ サクセイ

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<p>Land use and land cover (LULC) maps provide essential data for ecosystem service assessment, agriculture, resource management, disaster management, etc. We have developed a multi-temporal LULC classification algorithm called "SACLASS2" based on a convolutional neural network (CNN) in a two-dimensional space spanned by a temporal axis and a feature axis. This allows for better generalizability and lowers computational costs through a simple treatment of the characteristics of time-series remote sensing data. Moreover, it can keep fine spatial patterns that may be lost when CNN is used in a geographic space. Using this algorithm in combination with a well-qualified training dataset, we took data from Sentinel-2 and ALOS-2/PALSAR-2 together with some ancillary data as input and created a new LULC map of all of Japan for the period from 2018 to 2020. The Japan Aerospace Exploration Agency (JAXA) has released this product free of charge under the title of "JAXA HRLULC version 21.11". It has been greatly improved in terms of both number of categories (12 categories, 88.85 %) and overall accuracy from the earlier version (JAXA HRLULC v18.03; 10 categories, 81.62 %), which used a previous algorithm, SACLASS, based on a kernel density estimator. Compared to other LULC maps of Japan (made by the European Space Agency, Esri, the Ministry of the Environment, and the Ministry of Land, Infrastructure, Transportation and Tourism), HRLULC-Japan v21.11 has the multiple advantages of high-spatial resolution, description of the most recent situation, suitable categories for typical LULC maps of Japan (rice paddy fields, solar panels, bamboo forests, etc.), and overall accuracy.</p>

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