21 results on '"Laurin, Gaia Vaglio"'
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2. Corrigendum to “Validating GEDI tree canopy cover product across forest types using co-registered aerial LiDAR data” [ISPRS J. Photogramm. Remote Sens. 207 (2024) 326–337]
3. SnowWarp: An open science and open data tool for daily monitoring of snow dynamics
4. A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps
5. Inferring plant functional diversity from space: the potential of Sentinel-2
6. Characteristics of Tropical Tree Species in Hyperspectral and Multispectral Data
7. Vegetation structure derived from airborne laser scanning to assess species distribution and habitat suitability: The way forward
8. Space For The Unccd And The Desertwatch Project
9. Prospects for monitoring bird migration along the East Asian‐Australasian Flyway using weather radar.
10. Imperfect detection and wildlife density estimation using aerial surveys with infrared and visible sensors.
11. Space For The Unccd And The Desertwatch Project
12. Global Airborne Laser Scanning Data Providers Database (GlobALS)—A New Tool for Monitoring Ecosystems and Biodiversity
13. Satellite open data to monitor forest damage caused by extreme climate-induced events: a case study of the Vaia storm in Northern Italy.
14. Above-ground biomass prediction by Sentinel-1 multitemporal data in central Italy with integration of ALOS2 and Sentinel-2 data
15. An integrated pan‐tropical biomass map using multiple reference datasets
16. COSMO-SkyMed potential to detect and monitor Mediterranean maquis fires and regrowth: a pilot study in Capo Figari, Sardinia, Italy.
17. Tree species diversity of three Ghanaian reserves.
18. Potential of ALOS2 and NDVI to Estimate Forest Above-Ground Biomass, and Comparison with Lidar-Derived Estimates.
19. Does degradation from selective logging and illegal activities differently impact forest resources? A case study in Ghana.
20. Airborne LiDAR Detects Selectively Logged Tropical Forest Even in an Advanced Stage of Recovery.
21. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estiates.
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