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Monitoring forest landscape restoration from unmanned aerial vehicles using LIDAR and hyperspectral remote sensing

Grant number: 18/21338-3
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): February 01, 2019
Status:Discontinued
Field of knowledge:Agronomical Sciences - Forestry Resources and Forestry Engineering
Principal Investigator:Pedro Henrique Santin Brancalion
Grantee:Danilo Roberti Alves de Almeida
Home Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated research grant:13/50718-5 - Ecological restoration of riparian forests, native forest of economic production and of degraded forest fragments (in APP and RL) based on restoration ecology of reference ecosystems in order to scientifically test the precepts of the New Brazilian Forest Code, AP.BTA.TEM
Associated scholarship(s):19/14697-0 - Monitoring the demography and diversity of forests undergoing restoration using a drone-lidar-hyperspectral system, BE.EP.PD

Abstract

Several countries have submitted ambitious international pledges to restore by 2030 over 350 million hectares of degraded and deforested landscapes into multi-functional landscapes. Planning and monitoring forest and landscape restoration programs requires more comprehensive information at large scale using cost-effective methodologies to distinguish forest typologies and assess the recovery of forest structure and functions. This proposal will advance our understanding of restoration of tropical forests and their functions using several crucial variables derived by an unmanned aerial vehicle (UAV) using 3-D Lidar (Light Detection and Ranging) and HSI (hyperspectral imaging). The information offered by these remote sensors in such low cost platforms will revolutionize measurement and understanding of tropical forests restoration success, bringing detailed information from broad areas such as restoration, management and conservation, to significantly improve decision making in forestry. More specifically, we will investigate the potential of a UAV-based Lidar-HIS fusion approach to (i) distinguish forest types, tree diversity, above-ground biomass, (ii) identify tree species and predict (iii) microclimate, light and water environments and (iv) tree demography. These contributions may be key to advance monitoring of restoration programs implemented in the contexts of the Native Vegetation Protection Law (which replaced the Forest Code), the Brazilian commitments to the Paris Climate Agreement and Bonn Challenge, and national coalitions as such the Atlantic Forest Restoration Pact.

Articles published in other media outlets: (3 total)

Scientific publications (6)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
PAPA, DANIEL DE ALMEIDA; ALVES DE ALMEIDA, DANILO ROBERTI; SILVA, CARLOS ALBERTO; FIGUEIREDO, EVANDRO ORFANO; STARK, SCOTT C.; VALBUENA, RUBEN; ESTRAVIZ RODRIGUEZ, LUIZ CARLOS; NEVES D'OLIVEIRA, MARCUS VINICIO. Evaluating tropical forest classification and field sampling stratification from lidar to reduce effort and enable landscape monitoring. FOREST ECOLOGY AND MANAGEMENT, v. 457, FEB 1 2020. Web of Science Citations: 0.
DE ALMEIDA, DANILO R. A.; STARK, SCOTT C.; VALBUENA, RUBEN; BROADBENT, EBEN N.; SILVA, THIAGO S. F.; DE RESENDE, ANGELICA F.; FERREIRA, MATHEUS P.; CARDIL, ADRIAN; SILVA, CARLOS A.; AMAZONAS, NINO; ZAMBRANO, ANGELICA M. A.; BRANCALION, PEDRO H. S. A new era in forest restoration monitoring. RESTORATION ECOLOGY, v. 28, n. 1 NOV 2019. Web of Science Citations: 0.
SILVA, CARLOS A.; VALBUENA, RUBEN; PINAGE, EKENA R.; MOHAN, MIDHUN; DE ALMEIDA, DANILO R. A.; NORTH, EBEN; JAAFAR, WAN SHAFRINA WAN MOHD; PAPA, DANIEL DE A. MEIDA; CARDIL, ADRIAN; KLAUBERG, CARINE. ForestGapR: An r Package for forest gap analysis from canopy height models. METHODS IN ECOLOGY AND EVOLUTION, v. 10, n. 8, p. 1347-1356, AUG 2019. Web of Science Citations: 0.
ALMEIDA, D. R. A.; BROADBENT, E. N.; ZAMBRANO, A. M. A.; WILKINSON, B. E.; FERREIRA, M. E.; CHAZDON, R.; MELI, P.; GORGENS, E. B.; SILVA, C. A.; STARK, S. C.; VALBUENA, R.; PAPA, D. A.; BRANCALION, P. H. S. Monitoring the structure of forest restoration plantations with a drone-lidar system. International Journal of Applied Earth Observation and Geoinformation, v. 79, p. 192-198, JUL 2019. Web of Science Citations: 5.
ALMEIDA, DANILO R. A.; STARK, SCOTT C.; SCHIETTI, JULIANA; CAMARGO, JOSE L. C.; AMAZONAS, NINO T.; GORGENS, ERIC B.; ROSA, DIOGO M.; SMITH, MARIELLE N.; VALBUENA, RUBEN; SALESKA, SCOTT; ANDRADE, ANA; MESQUITA, RITA; LAURANCE, SUSAN G.; LAURANCE, WILLIAM F.; LOVEJOY, THOMAS E.; BROADBENT, EBEN N.; SHIMABUKURO, YOSIO E.; PARKER, GEOFFREY G.; LEFSKY, MICHAEL; SILVA, CARLOS A.; BRANCALION, PEDRO H. S. Persistent effects of fragmentation on tropical rainforest canopy structure after 20 yr of isolation. Ecological Applications, v. 29, n. 6 JULY 2019. Web of Science Citations: 1.
VALBUENA, RUBEN; HERNANDO, ANA; MANZANERA, JOSE ANTONIO; GORGENS, ERIC B.; ALMEIDA, DANILO R. A.; SILVA, CARLOS A.; GARCIA-ABRIL, ANTONIO. Evaluating observed versus predicted forest biomass: R-squared, index of agreement or maximal information coefficient?. EUROPEAN JOURNAL OF REMOTE SENSING, v. 52, n. 1, p. 345-358, 2019. Web of Science Citations: 2.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.