Integration of UAV, Sentinel-1, and Sentinel-2 Data for Mangrove Plantation aboveground Biomass Monitoring in Senegal

Navarro Fernández, José Antonio and Algeet Abarquero, Nur and Fernández Landa, Alfredo and Esteban, Jessica and Rodríguez Noriega, Pablo and Guillén Climent, María Luz (2019). Integration of UAV, Sentinel-1, and Sentinel-2 Data for Mangrove Plantation aboveground Biomass Monitoring in Senegal. "Remote Sensing", v. 11 (n. 1); p. 77. ISSN 2072-4292. https://doi.org/10.3390/rs11010077.

Description

Title: Integration of UAV, Sentinel-1, and Sentinel-2 Data for Mangrove Plantation aboveground Biomass Monitoring in Senegal
Author/s:
  • Navarro Fernández, José Antonio
  • Algeet Abarquero, Nur
  • Fernández Landa, Alfredo
  • Esteban, Jessica
  • Rodríguez Noriega, Pablo
  • Guillén Climent, María Luz
Item Type: Article
Título de Revista/Publicación: Remote Sensing
Date: January 2019
ISSN: 2072-4292
Volume: 11
Subjects:
Freetext Keywords: Digital aerial photogrammetry; SAR; Model-assisted; Biomass estimation; Copernicus; Unmanned aerial vehicles
Faculty: E.T.S.I. Montes, Forestal y del Medio Natural (UPM)
Department: Sistemas y Recursos Naturales
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Due to the increasing importance of mangroves in climate change mitigation projects, more accurate and cost-effective aboveground biomass (AGB) monitoring methods are required. However, field measurements of AGB may be a challenge because of their remote location and the difficulty to walk in these areas. This study is based on the Livelihoods Fund Oceanium project that monitors 10,000 ha of mangrove plantations. In a first step, the possibility of replacing traditional field measurements of sample plots in a young mangrove plantation by a semiautomatic processing of UAV-based photogrammetric point clouds was assessed. In a second step, Sentinel-1 radar and Sentinel-2 optical imagery were used as auxiliary information to estimate AGB and its variance for the entire study area under a model-assisted framework. AGB was measured using UAV imagery in a total of 95 sample plots. UAV plot data was used in combination with non-parametric support vector regression (SVR) models for the estimation of the study area AGB using model-assisted estimators. Purely UAV-based AGB estimates and their associated standard error (SE) were compared with model-assisted estimates using (1) Sentinel-1, (2) Sentinel-2, and (3) a combination of Sentinel-1 and Sentinel-2 data as auxiliary information. The validation of the UAV-based individual tree height and crown diameter measurements showed a root mean square error (RMSE) of 0.21 m and 0.32 m, respectively. Relative efficiency of the three model-assisted scenarios ranged between 1.61 and 2.15. Although all SVR models improved the efficiency of the monitoring over UAV-based estimates, the best results were achieved when a combination of Sentinel-1 and Sentinel-2 data was used. Results indicated that the methodology used in this research can provide accurate and cost-effective estimates of AGB in young mangrove plantations.

More information

Item ID: 56282
DC Identifier: http://oa.upm.es/56282/
OAI Identifier: oai:oa.upm.es:56282
DOI: 10.3390/rs11010077
Official URL: https://www.mdpi.com/2072-4292/11/1/77
Deposited by: Memoria Investigacion
Deposited on: 04 Sep 2019 11:09
Last Modified: 04 Sep 2019 11:09
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