Exploring TanDEM-X Interferometric Products for Crop-Type Mapping

Exploring TanDEM-X Interferometric Products for Crop-Type Mapping

This article belongs to the Special Issue Feature-Based Methods for Remote Sensing Image Classification.

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Bibliographic Details
Main Authors: Busquier, Mario, López-Sánchez, Juan M., Mestre-Quereda, Alejandro, Navarro, Elena, González-Dugo, María P., Mateos, Luciano
Other Authors: Agencia Estatal de Investigación (España)
Format: artículo biblioteca
Published: Multidisciplinary Digital Publishing Institute 2020-06-01
Subjects:TanDEM-X, Agriculture, Classification, SAR, Interferometry, Polarimetry,
Online Access:http://hdl.handle.net/10261/227046
http://dx.doi.org/10.13039/501100000780
http://dx.doi.org/10.13039/501100011033
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spelling dig-ias-es-10261-2270462021-01-26T04:32:45Z Exploring TanDEM-X Interferometric Products for Crop-Type Mapping Busquier, Mario López-Sánchez, Juan M. Mestre-Quereda, Alejandro Navarro, Elena González-Dugo, María P. Mateos, Luciano Agencia Estatal de Investigación (España) European Commission Ministerio de Ciencia, Innovación y Universidades (España) TanDEM-X Agriculture Classification SAR Interferometry Polarimetry This article belongs to the Special Issue Feature-Based Methods for Remote Sensing Image Classification. The application of satellite single-pass interferometric data to crop-type mapping is demonstrated for the first time in this work. A set of nine TanDEM-X dual-pol pairs of images acquired during its science phase, from June to August 2015, is exploited for this purpose. An agricultural site located in Sevilla (Spain), composed of fields of 13 different crop species, is employed for validation. Sets of input features formed by polarimetric and interferometric observables are tested for crop classification, including single-pass coherence and repeat-pass coherence formed by consecutive images. The backscattering coefficient at HH and VV channels and the correlation between channels form the set of polarimetric features employed as a reference set upon which the added value of interferometric coherence is evaluated. The inclusion of single-pass coherence as feature improves by 2% the overall accuracy (OA) with respect to the reference case, reaching 92%. More importantly, in single-pol configurations OA increases by 10% for the HH channel and by 8% for the VV channel, reaching 87% and 88%, respectively. Repeat-pass coherence also improves the classification performance, but with final scores slightly worse than with single-pass coherence. However, it improves the individual performance of the backscattering coefficient by 6–7%. Furthermore, in products evaluated at field level the dual-pol repeat-pass coherence features provide the same score as single-pass coherence features (overall accuracy above 94%). Consequently, the contribution of interferometry, both single-pass and repeat-pass, to crop-type mapping is proved. This work was funded by the Spanish Ministry of Science and Innovation, the State Agency of Research (AEI) and the European Funds for Regional Development (EFRD) under Project TEC2017-85244-C2-1-P, and by the European Commission, H2020 Programme, under Project MOSES (Managing crOp water Saving with Enterprise Services). 2021-01-19T10:50:23Z 2021-01-19T10:50:23Z 2020-06-01 2021-01-19T10:50:24Z artículo http://purl.org/coar/resource_type/c_6501 doi: 10.3390/rs12111774 e-issn: 2072-4292 Remote Sensing 12(11): 1774 (2020) http://hdl.handle.net/10261/227046 10.3390/rs12111774 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100011033 #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/TEC2017-85244-C2-1-P info:eu-repo/grantAgreement/EC/H2020/642258 Publisher's version http://doi.org/10.3390/rs12111774 Sí open Multidisciplinary Digital Publishing Institute
institution IAS ES
collection DSpace
country España
countrycode ES
component Bibliográfico
access En linea
databasecode dig-ias-es
tag biblioteca
region Europa del Sur
libraryname Biblioteca del IAS España
topic TanDEM-X
Agriculture
Classification
SAR
Interferometry
Polarimetry
TanDEM-X
Agriculture
Classification
SAR
Interferometry
Polarimetry
spellingShingle TanDEM-X
Agriculture
Classification
SAR
Interferometry
Polarimetry
TanDEM-X
Agriculture
Classification
SAR
Interferometry
Polarimetry
Busquier, Mario
López-Sánchez, Juan M.
Mestre-Quereda, Alejandro
Navarro, Elena
González-Dugo, María P.
Mateos, Luciano
Exploring TanDEM-X Interferometric Products for Crop-Type Mapping
description This article belongs to the Special Issue Feature-Based Methods for Remote Sensing Image Classification.
author2 Agencia Estatal de Investigación (España)
author_facet Agencia Estatal de Investigación (España)
Busquier, Mario
López-Sánchez, Juan M.
Mestre-Quereda, Alejandro
Navarro, Elena
González-Dugo, María P.
Mateos, Luciano
format artículo
topic_facet TanDEM-X
Agriculture
Classification
SAR
Interferometry
Polarimetry
author Busquier, Mario
López-Sánchez, Juan M.
Mestre-Quereda, Alejandro
Navarro, Elena
González-Dugo, María P.
Mateos, Luciano
author_sort Busquier, Mario
title Exploring TanDEM-X Interferometric Products for Crop-Type Mapping
title_short Exploring TanDEM-X Interferometric Products for Crop-Type Mapping
title_full Exploring TanDEM-X Interferometric Products for Crop-Type Mapping
title_fullStr Exploring TanDEM-X Interferometric Products for Crop-Type Mapping
title_full_unstemmed Exploring TanDEM-X Interferometric Products for Crop-Type Mapping
title_sort exploring tandem-x interferometric products for crop-type mapping
publisher Multidisciplinary Digital Publishing Institute
publishDate 2020-06-01
url http://hdl.handle.net/10261/227046
http://dx.doi.org/10.13039/501100000780
http://dx.doi.org/10.13039/501100011033
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