Analysis of drought effect over vegetation through a time series of Landsat images

• Grant number: 22/14014-2
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: December 01, 2022
• End date: November 30, 2023
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Geophysics
• Principal Investigator: Fernanda Sayuri Yoshino Watanabe
• Grantee: Luana Sacuman Floriano
• Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil

Abstract

One of the most evident impacts of climate change is the alteration of the rainfall regime in a region, increasing or decreasing precipitation levels, which lead to flooding or drought events more recurrent, respectively. Such changes have direct effects on health, housing and food production. The implementation of actions to combat climate change and its impacts is one of the Sustainable Development Goals (SDG-13), of the 2030 Agenda of the United Nations (UN). In this context, agricultural production is strongly threatened, and public policies need to be taken in order to guarantee food security for the population. Remote sensing images have been widely used in the monitoring of droughts and floods. Data of optical and thermal sensors have been widely used to analyze vegetation water stress conditions, evapotranspiration and surface temperature elevation. The western region of the State of São Paulo has agriculture and livestock as the basis of its economy, and in recent years, it has been suffering from drought events, with records of maximum temperature and low precipitation. In this sense, the present project aims to analyze the effect of drought on vegetation in Western São Paulo State based on a historical series of Landsat images. A time series analysis of vegetation spectral indices will be performed together with meteorological data. It is expected that the results of this work will contribute to the analysis of climate dynamics on vegetation, which can support the agricultural and environment sectors.