Dataset for "Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series"

Employed dataset for a research work development. Crop mapping with remote sensing data is a valuable tool for monitoring global food security, economic stability, and environmental conditions. This work aimed to evaluate the added value of Repeat-Pass interferometric coherence to backscatter for...

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Detalles Bibliográficos
Autor principal: Amherdt, Sebastian
Otros Autores: Bolsa de Comercio de Rosario
Formato: other conjunto de datos publishedVersion
Lenguaje:Inglés
Publicado: 2022
Materias:
InSAR coherence
Crop mapping
Time series
https://biblioteca.mincyt.gob.ar/ford/2.7
Acceso en línea:http://hdl.handle.net/2133/23194
http://hdl.handle.net/2133/23194
Aporte de:
Repositorio Hipermedial de la Universidad Nacional de Rosario (UNR) de Universidad Nacional de Rosario
id I15-R121-2133-23194
record_format dspace
institution Universidad Nacional de Rosario
institution_str I-15
repository_str R-121
collection Repositorio Hipermedial de la Universidad Nacional de Rosario (UNR)
language Inglés
orig_language_str_mv eng
topic InSAR coherence
Crop mapping
Time series
https://biblioteca.mincyt.gob.ar/ford/2.7
spellingShingle InSAR coherence
Crop mapping
Time series
https://biblioteca.mincyt.gob.ar/ford/2.7
Amherdt, Sebastian
Dataset for "Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series"
topic_facet InSAR coherence
Crop mapping
Time series
https://biblioteca.mincyt.gob.ar/ford/2.7
description Employed dataset for a research work development. Crop mapping with remote sensing data is a valuable tool for monitoring global food security, economic stability, and environmental conditions. This work aimed to evaluate the added value of Repeat-Pass interferometric coherence to backscatter for soybean and corn mapping, which are the most significant grain crops in Argentina. In addition, it was proposed the analysis of crops’ growth stages SAR information as well as the accuracy of in-season crop classifications. A complete 1-year time series of dual polarization Sentinel-1 (A and B) images was used. High accuracies were obtained with backscatter coefficients for both polarizations (higher than 95%) and interferometric coherence (88%). The work showed that coherence addition to single VV polarization backscatter yielded an improvement of 2-3% in general precision and 2-4 in kappa index score. Such result suggests the added value of interferometric coherence to backscattering coefficient, being a valuable source for single polarization SAR data.
author2 Bolsa de Comercio de Rosario
author_facet Bolsa de Comercio de Rosario
Amherdt, Sebastian
format other
conjunto de datos
publishedVersion
author Amherdt, Sebastian
author_sort Amherdt, Sebastian
title Dataset for "Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series"
title_short Dataset for "Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series"
title_full Dataset for "Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series"
title_fullStr Dataset for "Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series"
title_full_unstemmed Dataset for "Assessment of interferometric coherence contribution to corn and soybean mapping with Sentinel-1 data time series"
title_sort dataset for "assessment of interferometric coherence contribution to corn and soybean mapping with sentinel-1 data time series"
publishDate 2022
url http://hdl.handle.net/2133/23194
http://hdl.handle.net/2133/23194
work_keys_str_mv AT amherdtsebastian datasetforassessmentofinterferometriccoherencecontributiontocornandsoybeanmappingwithsentinel1datatimeseries
bdutipo_str Repositorios
_version_ 1764820411845967872

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