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Analysis of floristic diversity of restored forests using remote sensing

Grant number: 22/16261-7
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): April 01, 2023
Effective date (End): July 31, 2024
Field of knowledge:Agronomical Sciences - Forestry Resources and Forestry Engineering - Nature Conservation
Principal Investigator:Pedro Henrique Santin Brancalion
Grantee:Gustavo Fiedler Rossi
Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated research grant:18/18416-2 - Understanding restored forests for benefiting people and nature - NewFor, AP.BTA.TEM
Associated scholarship(s):23/08556-0 - Detecting floristic diversity of forests in restoration using remote sensing and machine learning, BE.EP.IC

Abstract

Forest restoration is considered one of the bets of several international institutions to mitigate the effects of climate change and reduce biodiversity loss. In the state of São Paulo, this is a technique increasingly widespread and studied, playing a crucial role in the protection of the Atlantic Forest. However, the methods for monitoring the success of restoration depend on field trips to analyze different factors, such as diversity and floristic composition, a time-consuming and costly process. With the use of remote sensing techniques, although there is still a need for field data, we can reduce the cost of monitoring by increasing the spatial and temporal scale, combining different sensors to detect various vegetation characteristics. The Sentinel 2A and 2B satellites and the Planet constellation generate images in different bands of the electromagnetic spectrum, between visible and infrared, where they highlight vegetation and water content. In addition, images derived from LiDAR sensor data, which is capable of providing a 3D view of forests, are useful for estimating different structural variables, which can be related to floristic variables. The focus of this project is to use remote sensing images (Sentinel 2, Planet and LiDAR), combined with forest inventory data obtained in the field (Newfor project - #FAPESP 2018/18416-2) to analyze the diversity and floristic composition of semideciduous seasonal forests under restoration in São Paulo state. The identification of floristic variables measured in the field with potential to be monitored by remote sensing will allow us to optimize the process of biodiversity study and monitoring of forest restoration.

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