Inferência do estado geral da umidade superficial do solo pelo índice de seca temperatura-vegetação e por imagens do satélite NOAA-17: aplicações no semiárido do Ceará

Abstract

The observation of the Earth's surface by satellites orbiting our planet has become commonplace in the contemporary world. Inferences of various environmental variables made from images and satellite data increasingly increase in quality and applicability so that an increasing number of hydrologists, meteorologists, climatologists and other professional and general lay-intensive use of them in studies and research in government policy or decision making. One such variable is the surface soil moisture, which is an important component of the Earth's water cycle, which is essential in many natural environmental processes and whose knowledge is important in the management of water and land resources, agricultural management and modeling of the environment and agriculture. The information derived from satellites, though still present some technical limitations, can greatly facilitate environmental monitoring to become often more agile and more economical than local in situ measurements. In developing countries and limited financial resources, such as ours, the information satellite grows in value. In the state of Ceará, it further emerges because of their economic and social difficulties. In view of this, it is proposed in this paper, the application in this northeastern state of a method of inference, satellite, the general state of surface soil moisture expressed by Drought Temperature-Vegetation Index (ISTV), which is indicative of the degree moisture and is related to it. This index is derived from the combination of information from the Continental Surface Temperature (TSC) and the Vegetation Index Normalized Difference (NDVI), inferred through images in the visible and infrared which can be provided by operational meteorological satellites, polar orbit, such as the NOAA (National Oceanic and Atmospheric Administration, USA). In the method, it was chosen from the literature, a TSC calculation algorithm that presents a certain ease of use, being directly dependent on the vegetation coverage fraction (FCV) and can provide good inferences that temperature. In this algorithm, were tested in an unprecedented way, some different formulations of FCV found in the literature, representing one state of the art in the subject. Were used images from the NOAA-17 satellite, received at FUNCEME, and specific software, this Foundation to process the images and implement the methodology addressed. Some tests were done to two relatively small regions of Ceará semiarid region, especially one comprising the Experimental Basin Aiuaba (BEA), comparing the NOAA-17 satellite information with in situ data (from probes in the soil) and with data coming from the environmental satellite Earth (TSC data available on the Internet) and Aqua (data surface soil moisture). He tried to show the qualitative differences between the mappings obtained from surface soil moisture, and between them and those offered by modeling in general. The results proved promising for use in cearense territory ISTV (in trapezoidal model) by NOAA, with the Kerr algorithm for calculating the TSC and FCV given by Scaled Difference Vegetation Index (SDVI) in order to estimate the overall state of the surface soil moisture over large areas. However, it is recommended rearmost local validation of the method used to detect possible errors or limitations not envisioned in these first tests, aiming its final operational implementation in Ceará and even in the semi-arid Northeast.