Extrapolating forest canopy cover by combining airborne LiDAR and Landsat data: The case of the Yeste fire (Spain)

Alba Viana-Soto, Mariano Garcia, Inmaculada Aguado, Javier Salas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Wildfires play a key role on forest composition and structure in the Mediterranean biomes. Hence, Mediterranean species are adapted to fire, developing ecological strategies to naturally recover. Nevertheless, climate change impacts and land use changes are expected to increase the frequency and intensity of extreme wildfire events, endangering forest resilience to fire. Combining LiDAR and Landsat data provides a valuable opportunity to temporally extend detailed information on the forest structure. This study attempts to evaluate the feasibility of extrapolating LiDAR-derived canopy cover variables, as indicators of vegetation recovery, to Landsat time-series using Support Vector Regression (SVR) in a large forest fire. Canopy Cover (CC) and Canopy Cover above 2 m (CC2m) were derived from LiDAR data acquired in 2009 and 2016 from the National Plan for Aerial Orthophotography of Spain (PNOA) and time-series of annual Landsat composites for the period 1990-2020 were generated through the Google Earth Engine platform. We calibrated a SVR model from a stratified random sample using a 60% of the sample from 2016 for calibrating and the remaining 40% from both 2016 and 2009 for spatial and temporal validation, respectively. The two canopy cover variables yielded highly acceptable accuracy, with an R2 of 0.78 (CC) and 0.64 (CC2m), and an RMSE around 12.5-15% for the spatial validation, and with an R2 of 0.74 (CC) and 0.51 (CC2m), and an RMSE around 14-16.5% for the temporal validation. These results ensure the applicability of the extrapolation of the LiDAR-derived canopy cover variables to Landsat timeseries.

Original languageEnglish
Title of host publicationEarth Resources and Environmental Remote Sensing/GIS Applications XII
EditorsKarsten Schulz, Ulrich Michel, Konstantinos G. Nikolakopoulos
PublisherSPIE
ISBN (Electronic)9781510645707
DOIs
StatePublished - 2021
Externally publishedYes
EventEarth Resources and Environmental Remote Sensing/GIS Applications XII 2021 - Virtual, Online, Spain
Duration: 13 Sep 202117 Sep 2021

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11863
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceEarth Resources and Environmental Remote Sensing/GIS Applications XII 2021
Country/TerritorySpain
CityVirtual, Online
Period13/09/2117/09/21

Keywords

  • Canopy cover
  • Landsat
  • LiDAR
  • Mediterranean region
  • post-fire recovery
  • Support vector regression

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