Characterization and monitoring of land surface phenology of natural vegetation in drylands

• Grant number: 23/02386-5
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Effective date (Start): June 15, 2023
• Effective date (End): April 14, 2024
• Field of knowledge: Agronomical Sciences - Forestry Resources and Forestry Engineering - Nature Conservation
• Principal Investigator: Yosio Edemir Shimabukuro
• Grantee: Andeise Cerqueira Dutra
• Supervisor: Alfredo Huete
• Host Institution: Instituto Nacional de Pesquisas Espaciais (INPE). Ministério da Ciência, Tecnologia e Inovações (Brasil). São José dos Campos , SP, Brazil
• Research place: University of Technology, Sydney (UTS), Australia
• Associated to the scholarship: 22/01746-5 - The impact of climate change on drylands vegetation phenology in the Southern Hemisphere, BP.DR

Abstract

Vegetation phenology is the recurring periodic patterns of plant growth and development and is linked to many key processes in the respective ecosystem. Vegetation phenology studies can, therefore, provide information on the effects of climate and environmental changes. In this context, natural vegetation in drylands plays an important role as it is directly related to food security, biodiversity, and socio-economic factors. Phenology based on remote sensing (also known as Land Surface Phenology - LSP) has received prominent attention in recent decades. However, the applicability of the LSP must take into account the variability of factors such as vegetation characteristics, primary remote sensing observations, and methods of smoothing and retrieval of phenological metrics. The main goal of this project is to improve the knowledge of how drylands vegetation phenology is detected by Earth's observation platforms and to develop a validated methodological framework for retrieving LSP metrics. It is intended to use local data from pre-existing phenological cameras (PhenoCams) covering forests, shrubs, and grass formations in Brazil and Australia, and optical time series from orbital remote sensing (possibly including daily reflectance and Solar induced chlorophyll fluorescence data). Phenological metrics will be retrieved from different algorithms. The research group abroad will contribute significantly to knowledge about the integration of orbital and near remote sensing, and consequently improve scientific knowledge about relationship models between climate and plant phenology. (AU)