Article, 2024

High-resolution canopy height map in the Landes forest (France) based on GEDI, Sentinel-1, and Sentinel-2 data with a deep learning approach

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, ISSN 1569-8432, Volume 128, 10.1016/j.jag.2024.103711

Contributors

Schwartz, Martin 0009-0001-9929-4410 (Corresponding author) [1] [2] [3] [4] Ciais, Philippe [1] [2] [3] [4] Ottle, Catherine [1] [2] [3] [4] [5] De Truchis, Aurelien [6] Vega, Cedric [7] Fayad, Ibrahim [8] [9] [10] Brandt, M. 0000-0001-9531-1239 [5] Fensholt, Rasmus 0000-0003-3067-4527 [5] Baghdadi, Nicolas 0000-0002-9461-4120 [8] [9] [10] Morneau, Francois [11] Morin, David 0000-0001-7711-2770 [4] [10] [12] [13] [14] Guyon, D. [10] Dayau, Sylvia [10] Wigneron, Jean-Pierre [10]

Affiliations

  1. [1] Univ Paris Saclay, CEA CNRS UVSQ, LSCE IPSL, Lab Sci Climat & Environm, F-91191 Gif Sur Yvette, France
    2. [NORA names: France; Europe, EU; OECD];
  2. [2] Univ Paris Saclay, CEA CNRS UVSQ, LSCE IPSL, Lab Sci Climat & Environm, F-91191 Gif Sur Yvette, France
    3. [NORA names: France; Europe, EU; OECD];
  3. [3] Univ Paris Saclay, CEA CNRS UVSQ, LSCE IPSL, Lab Sci Climat & Environm, F-91191 Gif Sur Yvette, France
    4. [NORA names: France; Europe, EU; OECD];
  4. [4] Univ Paris Saclay, CEA CNRS UVSQ, LSCE IPSL, Lab Sci Climat & Environm, F-91191 Gif Sur Yvette, France
    5. [NORA names: France; Europe, EU; OECD];
  5. [5] Univ Copenhagen, Dept GeoSci & Nat Resource Management, Copenhagen, Denmark
    6. [NORA names: KU University of Copenhagen; University; Denmark; Europe, EU; Nordic; OECD];

Abstract

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Keywords

3D Stereo, Deep Learning, Forest Inventory, Forest height, GEDI, Landes forest, Sentinel-1, Sentinel-2, U-Net

Data Provider: Clarivate

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