UAV RGB, thermal infrared and multispectral imagery used to investigate the control of terrain on the spatial distribution of dryland biocrust.

UAV apparent inertia biocrusts biological soil crusts drylands lichen moss multispectral thermal

Journal

Earth surface processes and landforms
ISSN: 1096-9837
Titre abrégé: Earth Surf Process Landf
Pays: England
ID NLM: 101729938

Informations de publication

Date de publication:
30 Sep 2021
Historique:
received: 09 11 2020
revised: 16 06 2021
accepted: 17 06 2021
entrez: 25 10 2021
pubmed: 26 10 2021
medline: 26 10 2021
Statut: ppublish

Résumé

Biocrusts (topsoil communities formed by mosses, lichens, bacteria, fungi, algae, and cyanobacteria) are a key biotic component of dryland ecosystems. Whilst climate patterns control the distribution of biocrusts in drylands worldwide, terrain and soil attributes can influence biocrust distribution at landscape scale. Multi-source unmanned aerial vehicle (UAV) imagery was used to map and study biocrust ecology in a typical dryland ecosystem in central Spain. Red, green and blue (RGB) imagery was processed using structure-from-motion techniques to map terrain attributes related to microclimate and terrain stability. Multispectral imagery was used to produce accurate maps (accuracy > 80%) of dryland ecosystem components (vegetation, bare soil and biocrust composition). Finally, thermal infrared (TIR) and multispectral imagery was used to calculate the apparent thermal inertia (ATI) of soil and to evaluate how ATI was related to soil moisture (

Identifiants

pubmed: 34690397
doi: 10.1002/esp.5189
pii: ESP5189
pmc: PMC8518773
doi:

Types de publication

Journal Article

Langues

eng

Pagination

2466-2484

Informations de copyright

© 2021 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

Déclaration de conflit d'intérêts

The authors declare there is no conflict of interest.

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Auteurs

Javier Blanco-Sacristán (J)

Remote Sensing of Environmental Dynamics Lab University of Milano-Bicocca Milan Italy.

Cinzia Panigada (C)

Remote Sensing of Environmental Dynamics Lab University of Milano-Bicocca Milan Italy.

Rodolfo Gentili (R)

Remote Sensing of Environmental Dynamics Lab University of Milano-Bicocca Milan Italy.

Giulia Tagliabue (G)

Remote Sensing of Environmental Dynamics Lab University of Milano-Bicocca Milan Italy.

Roberto Garzonio (R)

Remote Sensing of Environmental Dynamics Lab University of Milano-Bicocca Milan Italy.

M Pilar Martín (MP)

Environmental remote sensing and spectroscopy laboratory (SpecLab) Spanish National Research Council (CSIC) Madrid Spain.

Mónica Ladrón de Guevara (M)

Universidad Rey Juan Carlos Móstoles Spain.
Centre for Ecological Research and Forestry Applications, CREAF-CSIC-UAB Barcelona Spain.

Roberto Colombo (R)

Remote Sensing of Environmental Dynamics Lab University of Milano-Bicocca Milan Italy.

Thomas P F Dowling (TPF)

United Nations Environment Programme World Conservation Monitoring Centre Cambridge UK.

Micol Rossini (M)

Remote Sensing of Environmental Dynamics Lab University of Milano-Bicocca Milan Italy.

Classifications MeSH