Mapping tree species deciduousness of tropical dry forests combining reflectance, spectral unmixing, and texture data from high-resolution imagery

dc.creatorASTRID HELENA HUECHACONA RUIZ
dc.creatorJUAN MANUEL DUPUY RADA
dc.creatorNaomi Schwartz
dc.creatorJennifer Powers
dc.creatorCasandra Reyes García
dc.creatorFernando de Jesús Tun Dzul
dc.creatorJOSE LUIS HERNANDEZ STEFANONI
dc.date2020
dc.date.accessioned2023-07-21T19:19:25Z
dc.date.available2023-07-21T19:19:25Z
dc.identifierhttp://cicy.repositorioinstitucional.mx/jspui/handle/1003/1886
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7737438
dc.descriptionIn tropical dry forests, deciduousness (i.e., leaf shedding during the dry season) is an important adaptation of plants to cope with water limitation, which helps trees adjust to seasonal drought. Deciduousness is also a critical factor determining the timing and duration of carbon fixation rates, and affecting energy, water, and carbon balance. Therefore, quantifying deciduousness is vital to understand important ecosystem processes in tropical dry forests. The aim of this study was to map tree species deciduousness in three types of tropical dry forests along a precipitation gradient in the Yucatan Peninsula using Sentinel-2 imagery. We propose an approach that combines reflectance of visible and near-infrared bands, normalized difference vegetation index (NDVI), spectral unmixing deciduous fraction, and several texture metrics to estimate the spatial distribution of tree species deciduousness. Deciduousness in the study area was highly variable and decreased along the precipitation gradient, while the spatial variation in deciduousness among sites followed an inverse pattern, ranging from 91.5 to 43.3% and from 3.4 to 9.4% respectively from the northwest to the southeast of the peninsula. Most of the variation in deciduousness was predicted jointly by spectral variables and texture metrics, but texture metrics had a higher exclusive contribution. Moreover, including texture metrics as independent variables increased the variance of deciduousness explained by the models from R2 = 0.56 to R2 = 0.60 and the root mean square error (RMSE) was reduced from 16.9% to 16.2%. We present the first spatially continuous deciduousness map of the three most important vegetation types in the Yucatan Peninsula using high-resolution imagery. 
dc.formatapplication/pdf
dc.languageeng
dc.relationinfo:eu-repo/semantics/datasetDOI/10.3390/f11111234
dc.relationcitation:Huechacona-Ruiz, A. H., Dupuy, J. M., Schwartz, N. B., Powers, J. S., Reyes-García, C., Tun-Dzul, F., & Hernández-Stefanoni, J. L. (2020). Mapping Tree Species Deciduousness of Tropical Dry Forests Combining Reflectance, Spectral Unmixing, and Texture Data from High-Resolution Imagery. Forests, 11(11), 1234.
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.sourceForests, 11(11), 1234, 2020.
dc.subjectinfo:eu-repo/classification/Autores/PLANT PHENOLOGY
dc.subjectinfo:eu-repo/classification/Autores/RANDOM FOREST
dc.subjectinfo:eu-repo/classification/Autores/VEGETATION INDICES
dc.subjectinfo:eu-repo/classification/Autores/SPECTRAL MIXTURE ANALISIS
dc.subjectinfo:eu-repo/classification/Autores/IMAGE TEXTURE ANALYSIS
dc.subjectinfo:eu-repo/classification/cti/2
dc.subjectinfo:eu-repo/classification/cti/24
dc.subjectinfo:eu-repo/classification/cti/2417
dc.subjectinfo:eu-repo/classification/cti/241713
dc.subjectinfo:eu-repo/classification/cti/241713
dc.titleMapping tree species deciduousness of tropical dry forests combining reflectance, spectral unmixing, and texture data from high-resolution imagery
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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