Monitoring forest landscape restoration through Light Detection and Ranging (LiDAR).

• Grant number: 16/05219-9
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: September 01, 2016
• End date: January 02, 2019
• Field of knowledge: Biological Sciences - Ecology - Ecosystems Ecology
• Principal Investigator: Pedro Henrique Santin Brancalion
• Grantee: Danilo Roberti Alves de Almeida
• Host 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): 17/03867-6 - Towards universal biological structural assessment of forests with LiDAR remote sensing for vegetation monitoring in a changing world, BE.EP.DR

Abstract

We live in an era of unprecedented environmental change, with extensive degraded landscapes and great opportunities to transform these unproductive lands in functional landscapes and restore ecosystems that provide multiple benefits to society and future generations from processes such as the Forest Landscape Restoration (FLR), seeking the restoration of forests along with food production, carbon sequestration, soil and water protection and conservation of biodiversity, providing a good quality of life for people living in these landscapes. To meet these ambitious processes is necessary to adopt a rich concept of "Forest", performing a structural previous survey the landscape, distinguishing forest types (natural or planted, native or exotic species, continuous or fragmented among others) for the monitoring and success activity. However, perform the measurement of structural attributes in the field, able to distinguish these types, it is unworkable and some remote passive sensors have low accuracy in tropical forest classification due to high rates of leaf area. Active remote sensing, LiDAR, produce three-dimensional images of the landscape enabling direct or indirect estimate important structural physical attributes of vegetation with high accuracy. The objective of this study is to evaluate what are the opportunities that LiDAR has to monitor landscape restoration programs in tropical forests with the distinction of forest types, biomass estimates and biodiversity.

Scientific publications

(16)

(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)

ALMEIDA, D. R. A.; STARK, S. C.; CHAZDON, R.; NELSON, B. W.; CESAR, R. G.; MELI, P.; GORGENS, E. B.; DUARTE, M. M.; VALBUENA, R.; MORENO, V. S.; et al. The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration. FOREST ECOLOGY AND MANAGEMENT, v. 438, p. 34-43, APR 15 2019. (14/14503-7, 16/00052-9, 16/05219-9)

KRAINOVIC, PEDRO MEDRADO; ALVES DE ALMEIDA, DANILO ROBERTI; DESCONCI, DIEGO; DA VEIGA-JUNIOR, VALDIR FLORENCIO; BARBOSA SAMPAIO, PAULO DE TARSO. Sequential Management of Commercial Rosewood (Aniba rosaeodora Ducke) Plantations in Central Amazonia: Seeking Sustainable Models for Essential Oil Production. FORESTS, v. 8, n. 12, DEC 2017. (16/05219-9)

ALVES DE ALMEIDA, DANILO ROBERTI; STARK, SCOTT C.; SHAO, GANG; SCHIETTI, JULIANA; NELSON, BRUCE WALKER; SILVA, CARLOS ALBERTO; GORGENS, ERIC BASTOS; VALBUENA, RUBEN; PAPA, DANIEL DE ALMEIDA; SANTIN BRANCALION, PEDRO HENRIQUE. Optimizing the Remote Detection of Tropical Rainforest Structure with Airborne Lidar: Leaf Area Profile Sensitivity to Pulse Density and Spatial Sampling. REMOTE SENSING, v. 11, n. 1, JAN 1 2019. (17/03867-6, 16/05219-9)

KRAINOVIC, PEDRO; ALMEIDA, DANILO; SAMPAIO, PAULO. New Allometric Equations to Support Sustainable Plantation Management of Rosewood (Aniba rosaeodora Ducke) in the Central Amazon. FORESTS, v. 8, n. 9, SEP 2017. (16/05219-9)

COSTA, FLAVIA R. C.; LANG, CARLA; ALMEIDA, DANILO R. A.; CASTILHO, CAROLINA V.; POORTER, LOURENS. Near-infrared spectrometry allows fast and extensive predictions of functional traits from dry leaves and branches. Ecological Applications, v. 28, n. 5, p. 1157-1167, JUL 2018. (16/05219-9)

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.; et al. 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. (18/21338-3, 16/05219-9)

AMAZONAS, NINO TAVARES; FORRESTER, DAVID I.; SILVA, CARINA CAMARGO; ALVES ALMEIDA, DANILO ROBERTI; RODRIGUES, RICARDO RIBEIRO; BRANCALION, PEDRO H. S.. High diversity mixed plantations of Eucalyptus and native trees: An interface between production and restoration for the tropics. FOREST ECOLOGY AND MANAGEMENT, v. 417, p. 247-256, MAY 15 2018. (13/50718-5, 14/02070-9, 16/05219-9, 16/07498-2)

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; et al. Persistent effects of fragmentation on tropical rainforest canopy structure after 20 yr of isolation. Ecological Applications, v. 29, n. 6, JULY 2019. (18/21338-3, 16/05219-9)

BRANCALION, PEDRO H. S.; DE ALMEIDA, DANILO R. A.; VIDAL, EDSON; MOLIN, PAULO G.; SONTAG, VANESSA E.; SOUZA, SAULO E. X. F.; SCHULZE, MARK D.. Fake legal logging in the Brazilian Amazon. SCIENCE ADVANCES, v. 4, n. 8, AUG 2018. (13/50718-5, 16/05219-9)

MEDEIROS, RAQUEL DA SILVA; VIEIRA, GIL; ALVES DE ALMEIDA, DANILO ROBERTI; FO, MARIO TOMAZELLO. New information for managing Copaifera multijuga Hayne for oleoresin yield. FOREST ECOLOGY AND MANAGEMENT, v. 414, p. 85-98, APR 15 2018. (16/05219-9)

KRAINOVIC, PEDRO MEDRADO; ALVES DE ALMEIDA, DANILO ROBERTI; DA VEIGA JUNIOR, VALDIR FLORENCIO; BARBOSA SAMPAIO, PAULO DE TARSO. Changes in rosewood (Aniba rosaeodora Ducke) essential oil in response to management of commercial plantations in Central Amazonia. FOREST ECOLOGY AND MANAGEMENT, v. 429, p. 143-157, DEC 1 2018. (16/05219-9)

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. (18/21338-3, 16/05219-9)

KRAINOVIC, PEDRO MEDRADO; BASTOS, RODRIGO PINHEIRO; DE ALMEIDA, DANILO ROBERTI; NEVES JUNIOR, AFRANIO FERREIRA; BARBOSA SAMPAIO, PAULO DE TARSO; GOMES DE SOUZA, LUIZ AUGUSTO; DE SOUZA FALCAO, NEWTON PAULO. Effect of rosewood plantation chronosequence on soil attributes in Central Amazonia. Geoderma, v. 357, JAN 1 2020. (16/05219-9)

SHAO, GANG; STARK, SCOTT C.; DE ALMEIDA, DANILO R. A.; SMITH, MARIELLE N.. Towards high throughput assessment of canopy dynamics: The estimation of leaf area structure in Amazonian forests with multitemporal multi-sensor airborne lidar. REMOTE SENSING OF ENVIRONMENT, v. 221, p. 1-13, FEB 2019. (17/03867-6, 16/05219-9)

VALBUENA, R.; HERNANDO, A.; MANZANERA, J. A.; GORGENS, E. B.; ALMEIDA, D. R. A.; MAURO, F.; GARCIA-ABRIL, A.; COOMES, D. A.. Enhancing of accuracy assessment for forest above-ground biomass estimates obtained from remote sensing via hypothesis testing and overfitting evaluation. ECOLOGICAL MODELLING, v. 366, p. 15-26, DEC 24 2017. (16/05219-9)

LANG, CARLA; ALMEIDA, DANILO R. A.; COSTA, FLAVIA R. C.. Discrimination of taxonomic identity at species, genus and family levels using Fourier Transformed Near-Infrared Spectroscopy (FT-NIR). FOREST ECOLOGY AND MANAGEMENT, v. 406, p. 219-227, DEC 15 2017. (16/05219-9)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

ALMEIDA, Danilo Roberti Alves de. Assessing tropical forest degradation and restoration through lidar remote sensing. 2018. Doctoral Thesis - Universidade de São Paulo (USP). Escola Superior de Agricultura Luiz de Queiroz (ESALA/BC) Piracicaba.