Examining effective use of data sources and modeling algorithms for improving biomass estimation in a moist tropical forest of the Brazilian Amazon-Reference-Cited by-同舟云学术

Examining effective use of data sources and modeling algorithms for improving biomass estimation in a moist tropical forest of the Brazilian Amazon

Published:2017-03-13 Issue:10 Volume:10 Page:996-1016
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Feng Yunyun¹²,Lu Dengsheng¹²^ORCID,Chen Qi¹³,Keller Michael⁴⁵,Moran Emilio²,dos-Santos Maiza Nara⁴,Bolfe Edson Luis⁶,Batistella Mateus⁷

Affiliation:

1. The Nurturing Station for the State Key Laboratory of Subtropical Silviculture, Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, School of Environmental & Resource Sciences, Zhejiang Agriculture and Forestry University, Lin An, People’s Republic of China

2. Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI, USA

3. Department of Geography, University of Hawaii at Manoa, Honolulu, HI, USA

4. Brazilian Agricultural Research Corporation – Embrapa Informática Agropecuária, Campinas, Brazil

5. USDA Forest Service, International Institute of Tropical Forestry, Rio Piedras, PR, USA

6. Brazilian Agricultural Research Corporation – Embrapa, Secretariat of Intelligence and Macro Strategy, Brasília, Brazil

7. Brazilian Agricultural Research Corporation (Embrapa), Brasília, Brazil

Funder

National Natural Science Foundation of China

Research and Development

Brazilian Agricultural Research Corporation (EMBRAPA)

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2017.1301581

Reference70 articles.

1. Capabilities and limitations of Landsat and land cover data for aboveground woody biomass estimation of Uganda

2. A first map of tropical Africa’s above-ground biomass derived from satellite imagery

3. Remotely sensed biomass over steep slopes: An evaluation among successional stands of the Atlantic Forest, Brazil

4. Agroforestry in Tomé-Açu: An Alternative to Pasture in the Amazon

5. Análise florística e estrutural de sistemas silviagrícolas em Tomé-Açu, Pará

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