­Detection of Pinus monophylla forest in the Baja California desert by remote sensing


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Abstract

The Californian single-leaf pinyon (Pinus monophylla var. californiarum), a subspecies of the single-leaf pinyon (the world's only 1-needled pine), inhabits semi-arid zones of the Mojave Desert in southern Nevada and southeastern California (US) and also of northern Baja California (Mexico). This subspecies is distributed as a relict in the geographically isolated arid Sierra La Asamblea, between 1,010 and 1,631 m, with mean annual precipitation levels of between 184 and 288 mm. The aim of this research was i) to establish the distribution of Pinus monophylla var. californiarum in Sierra La Asamblea, Baja California (Mexico) using Sentinel-2 images, and ii) to test and describe the relationship between this distribution of Pinus monophylla and five topographic and 18 climate variables. We hypothesized that i) the Sentinel-2 images can be used to accurately detect the P. monophylla distribution in the study site due to higher resolution (x3) and increased number of bands (x2) relative to Landsat-8, and ii) the topographical variables aspect, ruggedness and slope are particularly influential because they represent important microhabitat factors that can affect where conifers can become established and persist.

Methods. It was used an atmospherically corrected a 12-bit Sentinel-2A MSI image with eleven spectral bands in the visible, near infrared, and short-wave infrared light region combined with the normalized differential vegetation index (NDVI). Supervised classification of this image was carried out using a backpropagation-type artificial neural network algorithm. Stepwise multivariate binominal logistical regression and Random Forest regression including cross valuation (10 fold) were used to model the associations between presence/absence of pines and the five topographical and 18 climate variables.

Results. Probably, P. monophylla covers 4,955 hectares in the isolated in Sierra La Asamblea, Baja California (Mexico) via supervised classification of Sentinel-2 satellite images. The NDVI was one of the variables that contributed to the detection and clearly separated the forest cover (NDVI > 0.35) from the other vegetation cover (NDVI < 0.20). The ruggedness was the best environmental predictor variable and indicated that the probability of P. monophylla occurrence was higher than 50% when the degree of ruggedness was greater than 17.5 m. When average temperature in the warmest month increased from 23.5 to 25.2 °C, the probability of occurrence of P. monophylla decreased.

Discussion. The classification accuracy (Kappa) was similar to other studies using Sentinel-2A MSI images. Ruggedness is known to generate microclimates and provides shade that decreases evapotranspiration from pines in desert environments. Identification of P. monophylla in Sierra La Asamblea as the most southern populations represents an opportunity for research on climatic tolerance and community responses to climatic variation and change.

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