A novel linear spectral unmixing-based method for tree decline monitoring by fusing UAV-RGB and optical space-borne data

Author:

Ghasemi Marziye1ORCID,Latifi Hooman12ORCID,Shafeian Elham3,Naghavi Hamed4ORCID,Pourhashemi Mehdi5ORCID

Affiliation:

1. Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran

2. Department of Remote Sensing, University of Würzburg, Würzburg, Germany

3. Institute of Geography and Geoecology, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

4. Faculty of Natural Resources, Lorestan University, Khorramabad, Lorestan, Iran

5. Research Institute of Forests and Rangelands (RIFR), Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran

Funder

Research Institute of Forests and Rangelands

Publisher

Informa UK Limited

Reference113 articles.

1. Airbus group 2021. SPOT 6 & SPOT 7 Imagery User Guide. https://www.intelligence-airbusds.com/en/8718-user-guides#spot6.

2. Alsdorf J. 2007. “Using Remote Sensing to Determine Differences in Soybean Seeding Rates”. Doctoral dissertation Purdue University.

3. Armando A. A. Held S. Phinn and J. Markley. Formulation and Assessment of Narrow-Band Vegetation Indices from EO-1 Hyperion Imagery for Discriminating Sugarcane Disease. Paper presented at the Proceedings of the Spatial Sciences Institute Biennial Conference (SSC 2003): Spatial Knowledge Without Boundaries. 2003

4. A review of vegetation indices

5. Relevance of UAV and sentinel-2 data fusion for estimating topsoil organic carbon after forest fire

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