Estimated Surface Temperature Variation of the Earth (LST) in the National Park Yasuní - Ecuador with Remote Sensor Techniques and Cloud Computing.

Abstract:

There are vast areas of the Amazon region that lack basic climate information, and as a result, it has become difficult to study and monitor the effects of climate change in these tropical forest ecosystems. A prime example is the current situation of the Ecuadorian Amazon region, where there are only 5 climate stations. Although two stations are located within the Yasuní National Park, only one is operational at km 53 (Napo Rocafuerte - M0007), while the other is not (Napo in Nuevo Rocafuerte - H1136). It is our overarching objective to fill the gaps in climatic information, particularly in temperature and humidity, using innovative time-series and cloud based remote sensing strategies in a quick and efficient way.

The research will be carried out over period of past 30 years using Landsat satellite images or more sophisticated new imagery available. This study will use an estimation used by Sobrino (2003). Sobrino’s method relates the normalized vegetation index and the brightness temperature with data calculated and provided by the Google Earth Engine platform. These Lansat images are transformed into Surface Reflectance data. Then the proportion of vegetation in the Yasuni National Park will be determined, estimate the emissivity, and finally surface temperature. This transformation is part of a cyclical process that will allow annual mosaics formation.

A total of 726 Landsat satellite images will be analyzed for an 103,007 km². Based on these Landsat images, annual mosaics will be to visually identify the variation in surface temperature. Finally, a spatial statistical analysis will be carried out to identify areas where a greater change in the LST.