Construction of LAI and fAPAR maps of the Monarch Butterfly Biosphere Reserve and comparison with global maps
The Monarch Butterfly Biosphere Reserve (MBBR) is in a critical situation with levels of deforestation that threaten butterfly migration. Biophysical variables such as the leaf area index (LAI) and the fraction of photosynthetically active radiation absorbed by plants (fAPAR), can help diagnose the...
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Universidad Autónoma de Tamaulipas
2014
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España-Boquera, María Luisa Champo-Jiménez, Omar Sánchez-Vargas, Nahum Lobit, Philippe López-Pérez, Luis Cruz-de-León, José |
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España-Boquera, María Luisa Champo-Jiménez, Omar Sánchez-Vargas, Nahum Lobit, Philippe López-Pérez, Luis Cruz-de-León, José Construction of LAI and fAPAR maps of the Monarch Butterfly Biosphere Reserve and comparison with global maps |
author_facet |
España-Boquera, María Luisa Champo-Jiménez, Omar Sánchez-Vargas, Nahum Lobit, Philippe López-Pérez, Luis Cruz-de-León, José |
author_sort |
España-Boquera, María Luisa |
title |
Construction of LAI and fAPAR maps of the Monarch Butterfly Biosphere Reserve and comparison with global maps |
title_short |
Construction of LAI and fAPAR maps of the Monarch Butterfly Biosphere Reserve and comparison with global maps |
title_full |
Construction of LAI and fAPAR maps of the Monarch Butterfly Biosphere Reserve and comparison with global maps |
title_fullStr |
Construction of LAI and fAPAR maps of the Monarch Butterfly Biosphere Reserve and comparison with global maps |
title_full_unstemmed |
Construction of LAI and fAPAR maps of the Monarch Butterfly Biosphere Reserve and comparison with global maps |
title_sort |
construction of lai and fapar maps of the monarch butterfly biosphere reserve and comparison with global maps |
description |
The Monarch Butterfly Biosphere Reserve (MBBR) is in a critical situation with levels of deforestation that threaten butterfly migration. Biophysical variables such as the leaf area index (LAI) and the fraction of photosynthetically active radiation absorbed by plants (fAPAR), can help diagnose the state of a forest. These variables can be measured in the field or, in case of a wide area, estimated from a linear regression fit between satellite images and field data, constructing high-resolution maps. There are also time series of low-resolution global maps of these variables available. In this work, we present the construction of LAI and fAPAR maps of the MBBR, using a SPOT image with spatial resolution of 20 m and field data. We compared them with GEOV1 maps of spatial resolution of 1 km, of the same variables and dates in order to assess the possibility of using them together. To build high-resolution maps, a field sampling was conducted in the summer of 2007, at 62 forest sites in the MBBR. Radiometric data of the corresponding pixel of a SPOT image of August 2007 were associated to each sample point; the areas with clouds were replaced by the same pixels in images taken on close dates. For each variable, 45 linear models were adjusted, from which the one with the highest concordance index was selected (0.45). These functions were applied to each pixel of the SPOT image to construct the maps, which were validated with field data, presenting acceptable relative errors (RMSEr, LAI: 20 %; fAPAR: 8 %). Comparison of these maps with GEOV1 maps of the same date, showed a significant correlation (r > 0.5) and an acceptable relative error (RMSEr, LAI: 19 %; fAPAR: 8 %). This result encourages the joint use of high resolution maps and time series. |
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Universidad Autónoma de Tamaulipas |
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2014 |
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https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/293 |
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oai:ojs.pkp.sfu.ca:article-2932015-09-30T12:09:00Z Construction of LAI and fAPAR maps of the Monarch Butterfly Biosphere Reserve and comparison with global maps Construcción de mapas de LAI y fAPAR de la Reserva de la Biósfera Mariposa Monarca y su comparación con mapas globales España-Boquera, María Luisa Champo-Jiménez, Omar Sánchez-Vargas, Nahum Lobit, Philippe López-Pérez, Luis Cruz-de-León, José Biophysical variable SPOT GEOLAND2 GEOV1 time series. Variable biofísica SPOT GEOLAND2 GEOV1 serie de tiempo. The Monarch Butterfly Biosphere Reserve (MBBR) is in a critical situation with levels of deforestation that threaten butterfly migration. Biophysical variables such as the leaf area index (LAI) and the fraction of photosynthetically active radiation absorbed by plants (fAPAR), can help diagnose the state of a forest. These variables can be measured in the field or, in case of a wide area, estimated from a linear regression fit between satellite images and field data, constructing high-resolution maps. There are also time series of low-resolution global maps of these variables available. In this work, we present the construction of LAI and fAPAR maps of the MBBR, using a SPOT image with spatial resolution of 20 m and field data. We compared them with GEOV1 maps of spatial resolution of 1 km, of the same variables and dates in order to assess the possibility of using them together. To build high-resolution maps, a field sampling was conducted in the summer of 2007, at 62 forest sites in the MBBR. Radiometric data of the corresponding pixel of a SPOT image of August 2007 were associated to each sample point; the areas with clouds were replaced by the same pixels in images taken on close dates. For each variable, 45 linear models were adjusted, from which the one with the highest concordance index was selected (0.45). These functions were applied to each pixel of the SPOT image to construct the maps, which were validated with field data, presenting acceptable relative errors (RMSEr, LAI: 20 %; fAPAR: 8 %). Comparison of these maps with GEOV1 maps of the same date, showed a significant correlation (r > 0.5) and an acceptable relative error (RMSEr, LAI: 19 %; fAPAR: 8 %). This result encourages the joint use of high resolution maps and time series. La Reserva de la Biosfera Mariposa Monarca (RBMM) presenta un nivel crítico de deforestación que pone en peligro el fenómeno migratorio de la mariposa. Variables biofísicas, como el índice de área foliar (LAI) y la fracción de radiación fotosintéticamente activa absorbida por las plantas (fAPAR), pueden ayudar en el diagnóstico del estado de una masa forestal. Es posible construir mapas de alta resolución de estas variables con imágenes satelitales y datos de campo; también existen series de mapas globales de baja resolución. En el presente trabajo se construyeron mapas de LAI y fAPAR de la RBMM, a partir de una imagen SPOT-4 con resolución espacial de 20 m y datos de campo, y se compararon con los mapas de la serie GEOV1 con resolución espacial de 1 km, de las mismas variables y fecha, con el fin de valorar la posibilidad de utilizarlos conjuntamente. Para construir los mapas de alta resolución, se realizó un muestreo en el verano de 2007, en 62 sitios de bosque en la RBMM. A cada sitio se asociaron los datos radiométricos del pixel correspondiente de una imagen SPOT de agosto de 2007, en la que las zonas con nubes se sustituyeron por los mismos pixeles de imágenes de fechas cercanas. Para cada variable, se ajustaron 45 modelos lineales, entre los que se eligió el de mayor índice de concordancia (0.45). Estas funciones se aplicaron a cada pixel de la imagen SPOT para construir los mapas, que se validaron con datos de campo, presentando errores relativos aceptables (RMSEr, LAI: 20 %; fAPAR: 8 %). La comparación de los mapas con los GEOV1 mostró una correlación significativa (r > 0.5) y un error relativo aceptable (RMSEr, LAI: 19 %; fAPAR: 8 %). Este resultado alienta la utilización conjunta de mapas de alta resolución y series de tiempo Universidad Autónoma de Tamaulipas 2014-07-09 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/293 10.29059/cienciauat.v8i2.293 CienciaUAT; Vol. 8 No. 2: January-June 2014; 22-31 CienciaUAT; Vol. 8 No. 2: Enero-Junio 2014; 22-31 2007-7858 2007-7521 spa https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/293/156 |