Luiz de Queiroz College of Agriculture - University of São Paulo

Homepage: https://en.esalq.usp.br/

FAPESP Project: RedeFloresta: Geospatial decision support platform for the restoration of landscapes and ecosystems in the state of São Paulo (Public Policy Research Program – PPPP)
FAPESP process number: 2023/09862-7
Supervisor: Prof. Pedro Henrique Santin Brancalion
Co-Supervisors: Profª. Catherine Torres de Almeida (UFPR in Curitiba/PR/Brazil), Prof. Paulo Guilherme Molin (UFSCar Lagoa do Sino in Buri/SP/Brazil)

The ReflorestaSP program, from the Secretariat of Environment, Infrastructure and Logistics of the state of São Paulo (SEMIL), aims to increase the vegetation coverage of the state by 700 thousand hectares by 2050. To achieve this goal in order to optimize the socio-ecological benefits of landscape and ecosystem restoration and minimize its costs, it is necessary to adopt a strategic plan to prioritize areas to be restored and monitor the effectiveness of interventions.
The RedeFloresta project aims to develop an online decision-making support platform for the ReflorestaSP program, which will allow the generation of interactive maps identifying priority areas for landscape and ecosystem restoration in the state, as well as monitoring areas with remote sensing data.
We are seeking 2 postdoctoral candidates with a consistent history of scientific publications and advanced theoretical and practical knowledge in geospatial modeling (PD#1) and remote sensing (PD#2), to create and analyze scenarios and models that support decision-making in the ReflorestaSP program. We also have 1 TT4 (technical training) position for professionals interested in contributing to the technical-scientific development of the platform, through the creation and organization of geospatial databases and field data collection with drones and GNSS.
The selected candidates will work with interdisciplinary teams of researchers from ESALQ/USP, UFPR, UFSCar, UNESP, and other research institutions, in addition to working directly with public managers from SEMIL and professionals from NGOs, such as PACTO, SOS Mata Atlântica, WWF, IPE, and TNC, to create and organize the geospatial data and models needed to feed the online platform. The workplace will be in person at ESALQ/USP, in Piracicaba/SP, with the possibility of occasional travel to São Paulo/SP and/or Curitiba/PR for meetings with partners.
The FAPESP postdoctoral fellowship (R$12,000/month) will last 36 months, have a technical reserve of 10% of the fellowship’s annual value, and require a doctorate degree. The FAPESP TT4 fellowship (R$4,320/month) will last 24 months and require a 40-hour weekly dedication, a bachelor’s degree with at least 2 years of experience, or a master’s degree in related areas. The positions are open to Brazilian and foreign researchers. Proficiency in Portuguese is required to facilitate the discussion and co-production environment with the different stakeholders involved in the project.
The selection process will include analysis of the letter of interest/presentation (with information on 2 professional references for contact), curriculum summary (https://fapesp.br/sumula), and online interview, in addition to documents proving the required degree. To apply, interested candidates must fill out the form for postdoc positions or the form for TT4 position”. If you have any questions, please contact us by email at redefloresta.br@gmail.com.

Positions:
PD#1 – Multicriteria modeling to prioritize areas for landscape and ecosystem restoration
The fellow will develop a multicriteria spatial modeling approach that combines ecological and socioeconomic indicators to prioritize areas for landscape and ecosystem restoration in the state of SP. The proposed approach will be implemented in an online geospatial platform to support the ReflorestaSP program. Knowledge of geospatial modeling and programming (e.g. Python and SQL) is required. Experience with geospatial databases (e.g. PostgreSQL and Postgis) and webGIS development (e.g. Mapserver and Geoserver) is desirable.

PD#2 – Remote sensing applied to multiscale monitoring of landscape and ecosystem restoration
The fellow will work on collecting data from various remote sensors on board drones (RGB, LiDAR and multispectral) and integrating them with satellite images using machine learning and deep learning techniques to generate indicators that allow remote monitoring of restoration. Knowledge of remote sensing (e.g. GEDI, LiDAR, multispectral) and programming (e.g. Python and SQL) is required. Experience in forest inventory, geospatial databases, deep learning and WebGIS is desirable.

TT4 – WebGIS and geospatial databases
Main activities include creating and organizing geospatial databases (e.g. PostGIS) and collecting data in the field with drones (LiDAR/RGB/Multispectral) and GNSS. Knowledge of WebGIS development (e.g. MapServer/GeoServer) is also desirable.