Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Mais filtros

Bases de dados
País/Região como assunto
Ano de publicação
Tipo de documento
País de afiliação
Intervalo de ano de publicação
1.
Sci Data ; 11(1): 334, 2024 Apr 04.
Artigo em Inglês | MEDLINE | ID: mdl-38575638

RESUMO

Accurate mapping and monitoring of tropical forests aboveground biomass (AGB) is crucial to design effective carbon emission reduction strategies and improving our understanding of Earth's carbon cycle. However, existing large-scale maps of tropical forest AGB generated through combinations of Earth Observation (EO) and forest inventory data show markedly divergent estimates, even after accounting for reported uncertainties. To address this, a network of high-quality reference data is needed to calibrate and validate mapping algorithms. This study aims to generate reference AGB datasets using field inventory plots and airborne LiDAR data for eight sites in Central Africa and five sites in South Asia, two regions largely underrepresented in global reference AGB datasets. The study provides access to these reference AGB maps, including uncertainty maps, at 100 m and 40 m spatial resolutions covering a total LiDAR footprint of 1,11,650 ha [ranging from 150 to 40,000 ha at site level]. These maps serve as calibration/validation datasets to improve the accuracy and reliability of AGB mapping for current and upcoming EO missions (viz., GEDI, BIOMASS, and NISAR).


Assuntos
Florestas , Árvores , Clima Tropical , África Central , Ásia Meridional , Biomassa , Reprodutibilidade dos Testes
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA