Data/hora: 24/06/2024 19:24:49

Biblioteca(s): | Embrapa Unidades Centrais.
Tipo da produção científica: | Artigo em Periódico Indexado
Circulação/Nível: | A - 1
Data corrente: | 26/05/2017
Data da última atualização: | 26/05/2017
Autoria: | FENG, Y.; LU, D.; CHEN, Q.; KELLER, M.; MORAN, E.; SANTOS, M. N. dos S.; BOLFE, E. L.; BATISTELLA, M.
Afiliação: | YUNYUN FENG; DENGSHENG LU; QI CHEN; MICHAEL KELLER; EMILIO MORAN; MAIZA NARA DOS SANTOS; EDSON LUIS BOLFE, SIM; MATEUS BATISTELLA, SRI.
Título: | Examining effective use of data source and modeling algorithms for improving biomass estimation in a moist tropical forest of the brazilian Amazon.
Ano de publicação: | 2017
Fonte/Imprenta: | International Journal of Digital Earth, London, 2017.
DOI: | http://dx.doi.org/10.1080/17538947.2017.1301581
Idioma: | Inglês
Conteúdo: | Previous research has explored the potential to integrate lidar and optical data in aboveground biomass (AGB) estimation, but how different data sources, vegetation types, and modeling algorithms influence AGB estimation is poorly understood. This research conducts a comparative analysis of different data sources and modeling approaches in improving AGB estimation. RapidEye-based spectral responses and textures, lidar-derived metrics, and their combination were used to develop AGB estimation models. The results indicated that (1) overall, RapidEye data are not suitable for AGB estimation, but when AGB falls within 50?150 Mg/ha, support vector regression based on stratification of vegetation types provided good AGB estimation; (2) Lidar data provided stable and better estimations than RapidEye data; and stratification of vegetation types cannot improve estimation; (3) The combination of lidar and RapidEye data cannot provide better performance than lidar data alone; (4) AGB ranges affect the selection of the best AGB models, and a combination of different estimation results from the best model for each AGB range can improve AGB estimation; (5) This research implies that an optimal procedure for AGB estimation for a specific study exists, depending on the careful selection of data sources, modeling algorithms, forest types, and AGB ranges.
Palavras-Chave: | Algoritmo de modelagem.
Thesagro: | Biomassa; Solo; Vegetação.
Thesaurus Nal: | Aboveground biomass; Lidar; Tropical forests; Vegetation types.
Categoria do assunto: | --
Registro original: | Embrapa Unidades Centrais (AI-SEDE)
Exemplares: | AI-SEDE - (61310-1) - UPC - AP - DD -  -  -  - DIS