Forest biomass assessment combining field inventorying and remote sensing data

Author:

Qasim Mohammad1,Csaplovics Elmar1,Villegas Mike Harvey Salazar12

Affiliation:

1. Chair of Remote Sensing, Faculty of Environmental Sciences, Technische Universität Dresden , Helmholtz straße 10, 01069 Dresden , Germany

2. Facultad de Ciencias Sociales y Humanas, Institución Universitaria Antonio José Camacho , Cali 25663 , Colombia

Abstract

Abstract Forests offer high potential for the fight against climate change. However, forests are faced with increased deforestation. REDD+ is a financial mechanism that offers hope to developing countries for tackling deforestation. Aboveground (AGB) estimation, however, is necessary for such financial mechanisms. Remote sensing methods offer various advantages for AGB estimation. A study, therefore, was conducted for the estimation of AGB using a combination of remote sensing Sentinel-1 (S1) and Sentinel-2 (S2) satellite data and field inventorying. The mean AGB for Sub-tropical Chir Pine Forest was recorded as 146.73 ± 65.11 Mg ha−1, while for Sub-tropical Broadleaved Evergreen Forest it was 33.77 ± 51.63 Mg ha−1. Results revealed weak associations between the S1 and S2 data with the AGB. Nonetheless, S1 and S2 offer advantages such as free data resources that can be utilized by developing countries for forest biomass and carbon monitoring.

Publisher

Walter de Gruyter GmbH

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

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