iEarth

Acquire high-quality global seamless remote sensing data cubes to advance Earth science research.

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Global Computable Seamless Data Cube

Global 30-m Seamless Data Cube of Land Surface Reflectance

The Global 30-m Seamless Data Cube (SDC) (2000–2022) integrates Landsat 5/7/8/9 and MODIS Terra data to produce a gap-free surface reflectance product. Unlike other Landsat-based datasets, it offers improved land change detection and spatiotemporal consistency, making it ideal for large-scale land cover and land use change studies.

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Global Artificial Impervious Area (GAIA) data (Version 2024)

The overall accuracy of GAIA data for representative years (1985, 1990, 1995, 2000, 2005, 2010, and 2015) exceeds 90%. The temporal trend in GAIA agrees well with other datasets at the local, regional, and global scales.

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Global Daily 500m Waterbody

Daily global inland surface water maps are produced from more than 2 million frames of satellite images for the period of 2001–2022 with a spatial resolution of 500 m.

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Global Wetland Dynamics Dataset

Global wetland dynamics dataset is based on 30-meter resolution seamless data cube and deep learning, with 3 level-1 categories and 14 level-2 categories, first revealing the fine-grained wetland dynamic changes since the 21 century.

Publications

A total of 8 papers were found.

Chen, S., Wang, J., Liu, Q., Liang, X., Liu, R., Qin, P., Yuan, J., Wei, J., Yuan, S., Huang, H., and Gong, P. (2024). Global 30 m seamless data cube (2000–2022) of land surface reflectance generated from Landsat 5, 7, 8, and 9 and MODIS Terra constellations. Earth System Science Data, 16, 5449–5475, https://doi.org/10.5194/essd-16-5449-2024.

SDC30

Chen, S., Wang, J., & Gong, P. (2023). ROBOT: A spatiotemporal fusion model toward seamless data cube for global remote sensing applications. Remote Sensing of Environment, 294, 113616.

SDC30

Liang, X., Liu, Q., Wang, J., Chen, S., and Gong, P. (2024). Global 500 m seamless dataset (2000–2022) of land surface reflectance generated from MODIS products. Earth System Science Data, 16, 177–200, https://doi.org/10.5194/essd-16-177-2024.

SDC500