The Role of Remote Sensing Data in Habitat Suitability and Connectivity Modeling: Insights from the Cantabrian Brown Bear
Ecological modeling requires sufficient spatial resolution and a careful selection of environmental variables to achieve good predictive performance. Although national and international administrations offer fine-scale environmental data, they usually have limited spatial coverage (country or contin...
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2021
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ftdoajarticles:oai:doaj.org/article:7d2f7e2402804ed6b089d74f175bac91 2023-05-15T18:42:10+02:00 The Role of Remote Sensing Data in Habitat Suitability and Connectivity Modeling: Insights from the Cantabrian Brown Bear Pablo Cisneros-Araujo Teresa Goicolea María Cruz Mateo-Sánchez Juan Ignacio García-Viñás Miguel Marchamalo Audrey Mercier Aitor Gastón 2021-03-01T00:00:00Z https://doi.org/10.3390/rs13061138 https://doaj.org/article/7d2f7e2402804ed6b089d74f175bac91 EN eng MDPI AG https://www.mdpi.com/2072-4292/13/6/1138 https://doaj.org/toc/2072-4292 doi:10.3390/rs13061138 2072-4292 https://doaj.org/article/7d2f7e2402804ed6b089d74f175bac91 Remote Sensing, Vol 13, Iss 1138, p 1138 (2021) ecological modeling landscape connectivity species–habitat relationships spatial resolution thematic resolution Ursus arctos Science Q article 2021 ftdoajarticles https://doi.org/10.3390/rs13061138 2022-12-30T20:20:01Z Ecological modeling requires sufficient spatial resolution and a careful selection of environmental variables to achieve good predictive performance. Although national and international administrations offer fine-scale environmental data, they usually have limited spatial coverage (country or continent). Alternatively, optical and radar satellite imagery is available with high resolutions, global coverage and frequent revisit intervals. Here, we compared the performance of ecological models trained with free satellite data with models fitted using regionally restricted spatial datasets. We developed brown bear habitat suitability and connectivity models from three datasets with different spatial coverage and accessibility. These datasets comprised (1) a Sentinel-1 and 2 land cover map (global coverage); (2) pan-European vegetation and land cover layers (continental coverage); and (3) LiDAR data and the Forest Map of Spain (national coverage). Results show that Sentinel imagery and pan-European datasets are powerful sources to estimate vegetation variables for habitat and connectivity modeling. However, Sentinel data could be limited for understanding precise habitat–species associations if the derived discrete variables do not distinguish a wide range of vegetation types. Therefore, more effort should be taken to improving the thematic resolution of satellite-derived vegetation variables. Our findings support the application of ecological modeling worldwide and can help select spatial datasets according to their coverage and resolution for habitat suitability and connectivity modeling. Article in Journal/Newspaper Ursus arctos Directory of Open Access Journals: DOAJ Articles Remote Sensing 13 6 1138 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
ecological modeling landscape connectivity species–habitat relationships spatial resolution thematic resolution Ursus arctos Science Q |
spellingShingle |
ecological modeling landscape connectivity species–habitat relationships spatial resolution thematic resolution Ursus arctos Science Q Pablo Cisneros-Araujo Teresa Goicolea María Cruz Mateo-Sánchez Juan Ignacio García-Viñás Miguel Marchamalo Audrey Mercier Aitor Gastón The Role of Remote Sensing Data in Habitat Suitability and Connectivity Modeling: Insights from the Cantabrian Brown Bear |
topic_facet |
ecological modeling landscape connectivity species–habitat relationships spatial resolution thematic resolution Ursus arctos Science Q |
description |
Ecological modeling requires sufficient spatial resolution and a careful selection of environmental variables to achieve good predictive performance. Although national and international administrations offer fine-scale environmental data, they usually have limited spatial coverage (country or continent). Alternatively, optical and radar satellite imagery is available with high resolutions, global coverage and frequent revisit intervals. Here, we compared the performance of ecological models trained with free satellite data with models fitted using regionally restricted spatial datasets. We developed brown bear habitat suitability and connectivity models from three datasets with different spatial coverage and accessibility. These datasets comprised (1) a Sentinel-1 and 2 land cover map (global coverage); (2) pan-European vegetation and land cover layers (continental coverage); and (3) LiDAR data and the Forest Map of Spain (national coverage). Results show that Sentinel imagery and pan-European datasets are powerful sources to estimate vegetation variables for habitat and connectivity modeling. However, Sentinel data could be limited for understanding precise habitat–species associations if the derived discrete variables do not distinguish a wide range of vegetation types. Therefore, more effort should be taken to improving the thematic resolution of satellite-derived vegetation variables. Our findings support the application of ecological modeling worldwide and can help select spatial datasets according to their coverage and resolution for habitat suitability and connectivity modeling. |
format |
Article in Journal/Newspaper |
author |
Pablo Cisneros-Araujo Teresa Goicolea María Cruz Mateo-Sánchez Juan Ignacio García-Viñás Miguel Marchamalo Audrey Mercier Aitor Gastón |
author_facet |
Pablo Cisneros-Araujo Teresa Goicolea María Cruz Mateo-Sánchez Juan Ignacio García-Viñás Miguel Marchamalo Audrey Mercier Aitor Gastón |
author_sort |
Pablo Cisneros-Araujo |
title |
The Role of Remote Sensing Data in Habitat Suitability and Connectivity Modeling: Insights from the Cantabrian Brown Bear |
title_short |
The Role of Remote Sensing Data in Habitat Suitability and Connectivity Modeling: Insights from the Cantabrian Brown Bear |
title_full |
The Role of Remote Sensing Data in Habitat Suitability and Connectivity Modeling: Insights from the Cantabrian Brown Bear |
title_fullStr |
The Role of Remote Sensing Data in Habitat Suitability and Connectivity Modeling: Insights from the Cantabrian Brown Bear |
title_full_unstemmed |
The Role of Remote Sensing Data in Habitat Suitability and Connectivity Modeling: Insights from the Cantabrian Brown Bear |
title_sort |
role of remote sensing data in habitat suitability and connectivity modeling: insights from the cantabrian brown bear |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doi.org/10.3390/rs13061138 https://doaj.org/article/7d2f7e2402804ed6b089d74f175bac91 |
genre |
Ursus arctos |
genre_facet |
Ursus arctos |
op_source |
Remote Sensing, Vol 13, Iss 1138, p 1138 (2021) |
op_relation |
https://www.mdpi.com/2072-4292/13/6/1138 https://doaj.org/toc/2072-4292 doi:10.3390/rs13061138 2072-4292 https://doaj.org/article/7d2f7e2402804ed6b089d74f175bac91 |
op_doi |
https://doi.org/10.3390/rs13061138 |
container_title |
Remote Sensing |
container_volume |
13 |
container_issue |
6 |
container_start_page |
1138 |
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1766231787118264320 |