Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm

Climate change increases extreme whether events such as floods, hailstorms, or storms, which can affect agriculture, causing damages and economic loss within the agro-food sector. Optical remote sensing data have been successfully used in damage detections. Cloud conditions limit their potential, es...

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Main Authors: Samuele De Petris, Filippo Sarvia, Michele Gullino, Eufemia Tarantino, Enrico Borgogno-Mondino
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/5/1030
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spelling doaj-fd9ba4d22c4948e9b29e75a85cc315412021-03-10T00:01:36ZengMDPI AGRemote Sensing2072-42922021-03-01131030103010.3390/rs13051030Sentinel-1 Polarimetry to Map Apple Orchard Damage after a StormSamuele De Petris0Filippo Sarvia1Michele Gullino2Eufemia Tarantino3Enrico Borgogno-Mondino4Department of Agriculture, Forest and Food sciences—University of Torino, L.go Braccini 2, Grugliasco 10095, ItalyDepartment of Agriculture, Forest and Food sciences—University of Torino, L.go Braccini 2, Grugliasco 10095, ItalyAz. Agr. Fessia Franca, v. Lagnasco 6, 12030 Manta, ItalyDICATECh, Politecnico di Bari, Via Orabona 4, 70125 Bari, ItalyDepartment of Agriculture, Forest and Food sciences—University of Torino, L.go Braccini 2, Grugliasco 10095, ItalyClimate change increases extreme whether events such as floods, hailstorms, or storms, which can affect agriculture, causing damages and economic loss within the agro-food sector. Optical remote sensing data have been successfully used in damage detections. Cloud conditions limit their potential, especially while monitoring floods or storms that are usually related to cloudy situations. Conversely, data from the Polarimetric Synthetic Aperture Radar (PolSAR) are operational in all-weather conditions and are sensitive to the geometrical properties of crops. Apple orchards play a key role in the Italian agriculture sector, presenting a cultivation system that is very sensitive to high-wind events. In this work, the H-α-A polarimetric decomposition technique was adopted to map damaged apple orchards with reference to a stormy event that had occurred in the study area (NW Italy) on 12 August 2020. The results showed that damaged orchards have higher H (entropy) and α (alpha angle) values compared with undamaged ones taken as reference (Mann–Whitney one-tailed test U = 14,514, <i>p </i>< 0.001; U = 16604, <i>p</i> < 0.001 for H and α, respectively). By contrast, A (anisotropy) values were significantly lower for damaged orchards (Mann–Whitney one-tailed test U = 8616, <i>p</i> < 0.001). Based on this evidence, the authors generated a map of potentially storm-damaged orchards, assigning a probability value to each of them. This map is intended to support local funding restoration policies by insurance companies and local administrations.https://www.mdpi.com/2072-4292/13/5/1030Sentinel-1apple orchard damagepolarimetric decompositionentropyanisotropyalpha angle
collection DOAJ
language English
format Article
sources DOAJ
author Samuele De Petris
Filippo Sarvia
Michele Gullino
Eufemia Tarantino
Enrico Borgogno-Mondino
spellingShingle Samuele De Petris
Filippo Sarvia
Michele Gullino
Eufemia Tarantino
Enrico Borgogno-Mondino
Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm
Remote Sensing
Sentinel-1
apple orchard damage
polarimetric decomposition
entropy
anisotropy
alpha angle
author_facet Samuele De Petris
Filippo Sarvia
Michele Gullino
Eufemia Tarantino
Enrico Borgogno-Mondino
author_sort Samuele De Petris
title Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm
title_short Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm
title_full Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm
title_fullStr Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm
title_full_unstemmed Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm
title_sort sentinel-1 polarimetry to map apple orchard damage after a storm
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-03-01
description Climate change increases extreme whether events such as floods, hailstorms, or storms, which can affect agriculture, causing damages and economic loss within the agro-food sector. Optical remote sensing data have been successfully used in damage detections. Cloud conditions limit their potential, especially while monitoring floods or storms that are usually related to cloudy situations. Conversely, data from the Polarimetric Synthetic Aperture Radar (PolSAR) are operational in all-weather conditions and are sensitive to the geometrical properties of crops. Apple orchards play a key role in the Italian agriculture sector, presenting a cultivation system that is very sensitive to high-wind events. In this work, the H-α-A polarimetric decomposition technique was adopted to map damaged apple orchards with reference to a stormy event that had occurred in the study area (NW Italy) on 12 August 2020. The results showed that damaged orchards have higher H (entropy) and α (alpha angle) values compared with undamaged ones taken as reference (Mann–Whitney one-tailed test U = 14,514, <i>p </i>< 0.001; U = 16604, <i>p</i> < 0.001 for H and α, respectively). By contrast, A (anisotropy) values were significantly lower for damaged orchards (Mann–Whitney one-tailed test U = 8616, <i>p</i> < 0.001). Based on this evidence, the authors generated a map of potentially storm-damaged orchards, assigning a probability value to each of them. This map is intended to support local funding restoration policies by insurance companies and local administrations.
topic Sentinel-1
apple orchard damage
polarimetric decomposition
entropy
anisotropy
alpha angle
url https://www.mdpi.com/2072-4292/13/5/1030
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