Monitoring the quality of forest remnants through novel remote sensing approaches

• Grant number: 23/05751-6
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: July 01, 2023
• End date: April 30, 2024
• Field of knowledge: Agronomical Sciences - Forestry Resources and Forestry Engineering - Nature Conservation
• Principal Investigator: Aline Ribeiro Machado
• Grantee: Laura Barbosa Vedovato
• Host Institution: Instituto de Pesquisas Tecnológicas S/A (IPT). Secretaria de Desenvolvimento Econômico (São Paulo - Estado). São Paulo , SP, Brazil
• Associated research grant: 17/50343-2 - Institutional development plan in the area of digital transformation: advanced manufacturing and smart and sustainable cities (PDIp), AP.PDIP

Abstract

Tropical forest cover is now composed of a heterogeneous mosaic of forests with different origins (i.e. natural regeneration, restoration plantations, commercial monocultures), varying ages, composition and structure, with market impacts on their biodiversity and ecosystem services. Transformations in forest cover occurred intensely in space and time, challenging monitoring. Monitoring restored areas with different previous land uses and with different restoration strategies is of great importance to quantify carbon stock and evaluate ecosystem services, such as biodiversity, and soil and water protection. New remote sensing approaches have revolutionised how we monitor forest diversity, structure and functioning, and can play a key role in tracking the progress of restoration programs. The rapid advancement of technology focused on improving sensors and their products at different scales of temporal, spatial and spectral resolution promises to transform the methodologies used in monitoring forest cover. In this project, we will explore new remote sensing technologies, especially lidar, and modelling approaches to assess forest quality. A variety of analytical and modelling approaches will be taken to assess forest quality attributes, including aboveground biomass, tree diversity, and various other variables related to biodiversity and ecosystem services. These analyses will be undertaken to compare restoration strategies, assess drivers of biodiversity and biomass recovery, and produce large-scale maps to guide policy and market interventions. The postdoctoral researcher will conduct the following activities: (1) organise a geospatial database of remote sensing data (mainly lidar); (2) analyse remote sensing data along with field data; (3) harmonise the structure of the spatial databases presented above (e.g., time and space scale, scope) and results in the multifunctionality of different land uses and forest types to allow the development of an analysis system that allows combining these databases to obtain impact products for decision making; (4) improvement and integration of geospatial databases for the production of thematic maps.