Large-Scale Forest Height Mapping by Combining TanDEM-X and GEDI Data

被引:14
|
作者
Choi, Changhyun [1 ]
Cazcarra-Bes, Victor [2 ]
Guliaev, Roman [1 ]
Pardini, Matteo [3 ]
Papathanassiou, Konstantinos P. P. [3 ]
Qi, Wenlu [3 ]
Armston, John [3 ]
Dubayah, Ralph O. O. [4 ]
机构
[1] Deutsch Zentrum Luft & Raumfahrt Standort Oberpfaf, HR, D-82234 Wessling, Germany
[2] Capella Space Corp, InSAR SAR Applicat, San Francisco, CA 94110 USA
[3] Deutsch Zentrum Luft & Raumfahrt DLR, Microwaves & Radar Inst, D-82234 Wessling, Germany
[4] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
关键词
Forestry; Laser radar; Estimation; Atmospheric modeling; Decorrelation; Synthetic aperture radar; Coherence; Forest height; GEDI; SAR interferometry; synthetic aperture radar (SAR); TanDEM-X; waveform lidar; POL-INSAR; ABOVEGROUND BIOMASS; SAR INTERFEROMETRY; LIDAR; MISSION; PERFORMANCE;
D O I
10.1109/JSTARS.2023.3244866
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The present study addresses the development, implementation, and validation of a forest height mapping scheme based on the combination of TanDEM-X interferometric coherence and GEDI waveform measurements. The very general case where only a single polarisation TanDEM-X interferogram, a set of spatially discrete GEDI waveform measurements, and no DTM are available is assumed. The use of GEDI waveforms to invert the TanDEM-X interferometric measurements is described together with a set of performance criteria implemented to ensure a certain performance quality. The emphasis is set on developing a methodology able to invert forest height at large scales. Combining 595 TanDEM-X scenes and about 15 million GEDI waveforms, a spatially continuous 25-m resolution forest height map covering the whole of Tasmania Island is achieved. The derived forest height map is validated against an airborne lidar-derived canopy height map available across the whole island.
引用
收藏
页码:2374 / 2385
页数:12
相关论文
共 50 条
  • [1] Mapping large-scale pantropical forest canopy height by integrating GEDI lidar and TanDEM-X InSAR data
    Qi, Wenlu
    Armston, John
    Choi, Changhyun
    Stovall, Atticus
    Saarela, Svetlana
    Pardini, Matteo
    Fatoyinbo, Lola
    Papathanassiou, Konstantinos
    Pascual, Adrian
    Dubayah, Ralph
    REMOTE SENSING OF ENVIRONMENT, 2025, 318
  • [2] FUSION OF TANDEM-X AND GEDI DATA FOR MAPPING FOREST HEIGHT IN THE BRAZILIAN AMAZON
    Choi, Changhyun
    Pardini, Matteo
    Guliaev, Roman
    Papathanassiou, Konstantinos P.
    2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 5429 - 5431
  • [3] Combining Tandem-X InSAR and simulated GEDI lidar observations for forest structure mapping
    Qi, Wenlu
    Dubayah, Ralph O.
    REMOTE SENSING OF ENVIRONMENT, 2016, 187 : 253 - 266
  • [4] Improved forest height estimation by fusion of simulated GEDI Lidar data and TanDEM-X InSAR data
    Qi, Wenlu
    Lee, Seung-Kuk
    Hancock, Steven
    Luthcke, Scott
    Tang, Hao
    Armston, John
    Dubayah, Ralph
    REMOTE SENSING OF ENVIRONMENT, 2019, 221 : 621 - 634
  • [5] Experiences from Large-Scale Forest Mapping of Sweden Using TanDEM-X Data
    Persson, Henrik J.
    Olsson, Hakan
    Soja, Maciej J.
    Ulander, Lars M. H.
    Fransson, Johan E. S.
    REMOTE SENSING, 2017, 9 (12):
  • [6] SPACEBORNE DATA FUSION FOR LARGE-SCALE FOREST PARAMETER ESTIMATION: GEDI LIDAR & TANDEM-X INSAR MISSIONS
    Lee, Seung-Kuk
    Fatoyinbo, Temilola
    Marselis, Suzanne M.
    Qi, Wenlu
    Hancock, Steven
    Armston, John
    Dubayah, Ralph
    2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 4491 - 4494
  • [7] Forest Height Estimation by Means of TanDEM-X InSAR and Waveform Lidar Data
    Guliaev, Roman
    Cazcarra-Bes, Victor
    Pardini, Matteo
    Papathanassiou, Konstantinos
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 14 : 3084 - 3094
  • [8] A Deep Learning Framework for the Estimation of Forest Height From Bistatic TanDEM-X Data
    Carcereri, Daniel
    Rizzoli, Paola
    Ienco, Dino
    Bruzzone, Lorenzo
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2023, 16 : 8334 - 8352
  • [9] Large-Scale Biomass Classification in Boreal Forests With TanDEM-X Data
    Caicoya, Astor Torano
    Kugler, Florian
    Hajnsek, Irena
    Papathanassiou, Konstantinos P.
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2016, 54 (10): : 5935 - 5951
  • [10] FOREST STRUCTURE MODELING OF A CONIFEROUS FOREST USING TANDEM-X INSAR AND SIMULATED GEDI LIDAR DATA
    Qi, Wenlu
    Dubayah, Ralph O.
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 914 - 917