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International Journal of Remote Sensing Volume 29, 2008 - Issue 5: 3D Remote Sensing in Forestry
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Original Articles

Assessing the influence of flight parameters, interferometric processing, slope and canopy density on the accuracy of X‐band IFSAR‐derived forest canopy height models

H.‐E. Andersen USDA Forest Service Pacific Northwest Research Station, Anchorage Forestry Sciences Laboratory, 3301 C Street, Suite 200, Anchorage, AK 99503, USACorrespondence[email protected]
,
R. J. Mcgaughey USDA Forest Service Pacific Northwest Research Station, University of Washington, Box 352100, Seattle, WA 98195, USA
&
S. E. Reutebuch USDA Forest Service Pacific Northwest Research Station, University of Washington, Box 352100, Seattle, WA 98195, USA
Pages 1495-1510 | Received 11 Oct 2006, Accepted 26 May 2006, Published online: 25 Feb 2008

Citations (15)

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C. Stone, M. Webster, J. Osborn & I. Iqbal. (2016) Alternatives to LiDAR-derived canopy height models for softwood plantations: a review and example using photogrammetry. Australian Forestry 79:4, pages 271-282.
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. (2008) Preface: 3D Remote Sensing in Forestry. International Journal of Remote Sensing 29:5, pages 1239-1242.
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Vandna Bansla, Sandeep Kumar, Vibhoo Sharma, Girish Singh Bisht & Akanksha Srivastav. 2024. Advances in Aerial Sensing and Imaging. Advances in Aerial Sensing and Imaging 313 331 .
Udayalakshmi Vepakomma, Denis Cormier, Linnea Hansson & Bruce Talbot. 2023. Boreal Forests in the Face of Climate Change. Boreal Forests in the Face of Climate Change 657 682 .
Benjamin L. Branoff & Sebastián Martinuzzi. (2020) The Structure and Composition of Puerto Rico’s Urban Mangroves. Forests 11:10, pages 1119.
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Nathalie Guimarães, Luís Pádua, Pedro Marques, Nuno Silva, Emanuel Peres & Joaquim J. Sousa. (2020) Forestry Remote Sensing from Unmanned Aerial Vehicles: A Review Focusing on the Data, Processing and Potentialities. Remote Sensing 12:6, pages 1046.
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Angela Lausch, Marco Heurich, Paul Magdon, Duccio Rocchini, Karsten Schulz, Jan Bumberger & Doug J. King. 2020. Remote Sensing of Plant Biodiversity. Remote Sensing of Plant Biodiversity 309 348 .
Dion J. Wiseman & Jurjen van der Sluijs. 2019. Unmanned Aerial Vehicles. Unmanned Aerial Vehicles 249 270 .
Dion J. Wiseman & Jurjen van der Sluijs. 2019. Geospatial Intelligence. Geospatial Intelligence 1175 1196 .
Cian Desmond, Simon Watson, Christiane Montavon & Jimmy Murphy. (2018) Modelling Uncertainty in t-RANS Simulations of Thermally Stratified Forest Canopy Flows for Wind Energy Studies. Energies 11:7, pages 1703.
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Angela Lausch, Stefan Erasmi, Douglas King, Paul Magdon & Marco Heurich. (2017) Understanding Forest Health with Remote Sensing-Part II—A Review of Approaches and Data Models. Remote Sensing 9:2, pages 129.
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Dion J. Wiseman & Jurjen van der Sluijs. (2015) Alternative Methods for Developing and Assessing the Accuracy of UAV-Derived DEMs. International Journal of Applied Geospatial Research 6:3, pages 58-77.
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Hassan Ahmadi, Arun Das, Mehdi Pourtaheri, Chooghi Bairam Komaki & Houshang Khairy. (2014) Redefining the watershed line and stream networks via digital resources and topographic map using GIS and remote sensing (case study: the Neka River’s watershed). Natural Hazards 72:2, pages 711-722.
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Veronica Prush & Rowena Lohman. (2014) Forest Canopy Heights in the Pacific Northwest Based on InSAR Phase Discontinuities across Short Spatial Scales. Remote Sensing 6:4, pages 3210-3226.
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Todd L. Erdody & L. Monika Moskal. (2010) Fusion of LiDAR and imagery for estimating forest canopy fuels. Remote Sensing of Environment 114:4, pages 725-737.
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