The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration
Ambitious pledges to restore over 400 million hectares of degraded lands by 2030 have been made by several countries within the Global Partnership for Forest Landscape Restoration (FLR). Monitoring restoration outcomes at this scale requires cost-effective methods to quantify not only forest cover,...
| Autor principal: | Almeida, Danilo Roberti Alves de |
|---|---|
| Outros Autores: | Stark, Scott C., Chazdon, Robin L., Nelson, Bruce Walker, César, Ricardo Gomes, Meli, Paula, Görgens, Eric Bastos, Duarte, Marina Melo, Valbuena, Rubén, Moreno, Vanessa Sousa, Mendes, Alex Fernando, Amazonas, Nino Tavares, Gonçalves, Nathan Borges, Silva, Carlos Alberto, Schietti, Juliana, Brancalion, Pedro Henrique Santin |
| Grau: | Artigo |
| Idioma: | English |
| Publicado em: |
Forest Ecology and Management
2020
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| Assuntos: | |
| Acesso em linha: |
https://repositorio.inpa.gov.br/handle/1/16700 |
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oai:repositorio:1-16700 |
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dspace |
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oai:repositorio:1-16700 The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration Almeida, Danilo Roberti Alves de Stark, Scott C. Chazdon, Robin L. Nelson, Bruce Walker César, Ricardo Gomes Meli, Paula Görgens, Eric Bastos Duarte, Marina Melo Valbuena, Rubén Moreno, Vanessa Sousa Mendes, Alex Fernando Amazonas, Nino Tavares Gonçalves, Nathan Borges Silva, Carlos Alberto Schietti, Juliana Brancalion, Pedro Henrique Santin Biodiversity Cost Effectiveness Land Reclamation Optical Radar Reforestation Remote Sensing Restoration Atlantic Forest Forest Canopies Forest Regeneration Forest Succession Tropical Forest Conservation Forest Canopy Forest Cover Forest Ecosystem Landscape Laser Method Leaf Area Lidar Remote Sensing Restoration Ecology Secondary Forest Species Diversity Species Richness Tree Tropical Forest Biodiversity Cost Effectiveness Land Reclamation Reforestation Remote Sensing Restoration Atlantic Forest Brasil Ambitious pledges to restore over 400 million hectares of degraded lands by 2030 have been made by several countries within the Global Partnership for Forest Landscape Restoration (FLR). Monitoring restoration outcomes at this scale requires cost-effective methods to quantify not only forest cover, but also forest structure and the diversity of useful species. Here we obtain and analyze structural attributes of forest canopies undergoing restoration in the Atlantic Forest of Brazil using a portable ground lidar remote sensing device as a proxy for airborne laser scanners. We assess the ability of these attributes to distinguish forest cover types, to estimate aboveground dry woody biomass (AGB) and to estimate tree species diversity (Shannon index and richness). A set of six canopy structure attributes were able to classify five cover types with an overall accuracy of 75%, increasing to 87% when combining two secondary forest classes. Canopy height and the unprecedented “leaf area height volume” (a cumulative product of canopy height and vegetation density) were good predictors of AGB. An index based on the height and evenness of the leaf area density profile was weakly related to the Shannon Index of tree species diversity and showed no relationship to species richness or to change in species composition. These findings illustrate the potential and limitations of lidar remote sensing for monitoring compliance of FLR goals of landscape multifunctionality, beyond a simple assessment of forest cover gain and loss. © 2019 Elsevier B.V. 2020-06-15T21:35:49Z 2020-06-15T21:35:49Z 2019 Artigo https://repositorio.inpa.gov.br/handle/1/16700 10.1016/j.foreco.2019.02.002 en Volume 438, Pags. 34-43 Restrito Forest Ecology and Management |
| institution |
Instituto Nacional de Pesquisas da Amazônia - Repositório Institucional |
| collection |
INPA-RI |
| language |
English |
| topic |
Biodiversity Cost Effectiveness Land Reclamation Optical Radar Reforestation Remote Sensing Restoration Atlantic Forest Forest Canopies Forest Regeneration Forest Succession Tropical Forest Conservation Forest Canopy Forest Cover Forest Ecosystem Landscape Laser Method Leaf Area Lidar Remote Sensing Restoration Ecology Secondary Forest Species Diversity Species Richness Tree Tropical Forest Biodiversity Cost Effectiveness Land Reclamation Reforestation Remote Sensing Restoration Atlantic Forest Brasil |
| spellingShingle |
Biodiversity Cost Effectiveness Land Reclamation Optical Radar Reforestation Remote Sensing Restoration Atlantic Forest Forest Canopies Forest Regeneration Forest Succession Tropical Forest Conservation Forest Canopy Forest Cover Forest Ecosystem Landscape Laser Method Leaf Area Lidar Remote Sensing Restoration Ecology Secondary Forest Species Diversity Species Richness Tree Tropical Forest Biodiversity Cost Effectiveness Land Reclamation Reforestation Remote Sensing Restoration Atlantic Forest Brasil Almeida, Danilo Roberti Alves de The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration |
| topic_facet |
Biodiversity Cost Effectiveness Land Reclamation Optical Radar Reforestation Remote Sensing Restoration Atlantic Forest Forest Canopies Forest Regeneration Forest Succession Tropical Forest Conservation Forest Canopy Forest Cover Forest Ecosystem Landscape Laser Method Leaf Area Lidar Remote Sensing Restoration Ecology Secondary Forest Species Diversity Species Richness Tree Tropical Forest Biodiversity Cost Effectiveness Land Reclamation Reforestation Remote Sensing Restoration Atlantic Forest Brasil |
| description |
Ambitious pledges to restore over 400 million hectares of degraded lands by 2030 have been made by several countries within the Global Partnership for Forest Landscape Restoration (FLR). Monitoring restoration outcomes at this scale requires cost-effective methods to quantify not only forest cover, but also forest structure and the diversity of useful species. Here we obtain and analyze structural attributes of forest canopies undergoing restoration in the Atlantic Forest of Brazil using a portable ground lidar remote sensing device as a proxy for airborne laser scanners. We assess the ability of these attributes to distinguish forest cover types, to estimate aboveground dry woody biomass (AGB) and to estimate tree species diversity (Shannon index and richness). A set of six canopy structure attributes were able to classify five cover types with an overall accuracy of 75%, increasing to 87% when combining two secondary forest classes. Canopy height and the unprecedented “leaf area height volume” (a cumulative product of canopy height and vegetation density) were good predictors of AGB. An index based on the height and evenness of the leaf area density profile was weakly related to the Shannon Index of tree species diversity and showed no relationship to species richness or to change in species composition. These findings illustrate the potential and limitations of lidar remote sensing for monitoring compliance of FLR goals of landscape multifunctionality, beyond a simple assessment of forest cover gain and loss. © 2019 Elsevier B.V. |
| format |
Artigo |
| author |
Almeida, Danilo Roberti Alves de |
| author2 |
Stark, Scott C. Chazdon, Robin L. Nelson, Bruce Walker César, Ricardo Gomes Meli, Paula Görgens, Eric Bastos Duarte, Marina Melo Valbuena, Rubén Moreno, Vanessa Sousa Mendes, Alex Fernando Amazonas, Nino Tavares Gonçalves, Nathan Borges Silva, Carlos Alberto Schietti, Juliana Brancalion, Pedro Henrique Santin |
| author2Str |
Stark, Scott C. Chazdon, Robin L. Nelson, Bruce Walker César, Ricardo Gomes Meli, Paula Görgens, Eric Bastos Duarte, Marina Melo Valbuena, Rubén Moreno, Vanessa Sousa Mendes, Alex Fernando Amazonas, Nino Tavares Gonçalves, Nathan Borges Silva, Carlos Alberto Schietti, Juliana Brancalion, Pedro Henrique Santin |
| title |
The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration |
| title_short |
The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration |
| title_full |
The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration |
| title_fullStr |
The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration |
| title_full_unstemmed |
The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration |
| title_sort |
effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration |
| publisher |
Forest Ecology and Management |
| publishDate |
2020 |
| url |
https://repositorio.inpa.gov.br/handle/1/16700 |
| _version_ |
1787141769992863744 |
| score |
11.755432 |