NDVI - alpha diversity relationship in tropical montane cloud forest of Ecuador; [Соотношение NDVI и альфа-разнообразия в тропических влажных горных лесах Эквадора]

In tropical forest the biodiversity is in a constant threat, some species are listed in the IUCN as vulnerable, endangered or threatened with extinction. Thus, a fast method for biodiversity determination or monitoring can contribute to its conservation. Remote sensing has demonstrated to be a powerful tool, and together with the vegetation indexes, can determine the vegetation state of forest. Recently researches have correlated the normalized differentiated vegetation index (NDVI) with species richness, structure and biodiversity of forests obtaining successful results. This study, conducted in a Tropical Montane Cloud Forest (TMCF) of Ecuador, aims to correlate NDVI with alpha diversity estimators to understand its relationships. NDVI of Landsat OLI 8 Level 1 images in five months was determined. We considered a scene as valid in case of cloud coverage in the areas of interest below 25%. Radiometric and atmospheric corrections, with flaash tool, and the delimitation of the study site (ROI) were developed in ENVI 5.3 program. NDVI was calculated with ENVI 5.3 program (histograms allowed the determination of mean, maximum and minimum NDVI), and with ArcGIS 10.3 (for classification index). In field, species richness, Chao1, Shannon index, Simpson index, and biomass of three plots were quantified for trees with DBH ≥ 10 cm. Then, we calculate Pearson coefficient to correlate and disentangle the effects of altitude, diversity, richness, biomass and NDVI. A positive relationship was observed between Mean NDVI and Chao1 (p < 0.10) and Mean NDVI - richness (p < 0.05). In conclusion, NDVI can be considered useful to estimate richness and biodiversity and even to detect ecotone as was the case in this research. The application of this methodology could allow biodiversity assessment and monitoring in real time and low cost, which contributes in forest conservation programs. © 2022.