Monitoreo multitemporal del humedal Pugllohuma, perteneciente al Área de Conservación Hídrica Antisana (ACHA), por medio de imágenes capturadas desde una aeronave no tripulada de ala fija (UAV).

Abstract

Effective regulation of Earth's resources requires the utilization of planning techniques within the domain of natural resource management. This approach ensures the continued availability of resources for future generations. Water, a vital natural resource, is found in several states on Earth. One method involves the retention of water by wetland ecosystems. Hence, it is vital to comprehend the current condition of natural wetlands. Nevertheless, alterations in land utilization, along with the expansion of agricultural and grazing practices, have resulted in a decline in the global wetland areas, especially those situated in the high Andes like the paramos of South America. This research presents a new methodology for analyzing vegetation phenology in a multi-temporal manner. The strategy involves the use of interactive map analysis and spectral indices derived from multispectral images captured by UAV. The selected research site for this study is the Pugllohuma Wetland, which is situated within the Antisana Water Conservation Area. Located in the northern Andes of Ecuador, slightly below the equator by a latitude of 0.5 degrees, this wetland has been chosen as the main area of focus for our research endeavor. The investigation resulted on vegetation indices (NDVI and SAVI) that rely on the phenological state of the vegetation present in the area. These indices have demonstrated their efficacy in assessing vegetation conditions and have successfully identified a 0.150 km2 region with high vegetative density. In contrast, the assessment of bodies of water and vegetation humidity was conducted using the NDWI spectral index, which yielded a surface water area parameter of 0.169 km2 . Furthermore, a maximum water saturation zone of 69.89% was determined in the wetland through the utilization of the water table, topographic maps, and spectral water indices. Through the utilization of multivariate analysis, a comprehensive equation was derived, establishing a connection between spectral indices and the groundwater table in relation to sea level.