In 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.
Bibliographical noteFunding Information:
The study was financially supported by CICY and Ecometrica LTD and the United Kingdom Space Agency as part of the project Forests 2020. This study is part of the first author’s Ph.D. dissertation which was supported by a grant from IICA-CONACYT. We thank James Callaghan and Kaxil Kiuic A. C. for providing logistic support and the community of Xkobenhaltun for their continued support with fieldwork. Finally, we want to thank FiligonioMay-Pat for their help in the fieldwork and their identification of foliar habitat of the species.
Funding: The study was financially supported by CICY and Ecometrica LTD and the United Kingdom Space Agency as part of the project Forests 2020. This study is part of the first author’s Ph.D. dissertation which was supported by a grant from IICA-CONACYT.
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
- Image texture analysis
- Plant phenology
- Random forest
- Spectral mixture analysis
- Vegetation indices