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

By Alessandro Baccini, N. Laporte, Scott J. Goetz, M. Sun, H. Dong. 2008

184 citations recorded by the source corpus.

Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000–2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha−1 for a range of biomass between 0 and 454 Mg ha−1. Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate that the model successfully captured the regional distribution of AGB. The results showed a strong positive correlation (R2 = 0.90) between the GLAS height metrics and predicted AGB.

Subfields: Ecology, Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/1612caca0c6ed06d483fd901b83a8a647f0c3869

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Matthew C. Hansen
2. Martin Herold
3. Scott J. Goetz
4. Svetlana Turubanova
5. Dengsheng Lu
6. Qi Chen
7. M. Skutsch
8. Alessandro Baccini

In Environmental Engineering

1. Martin Herold
2. Scott J. Goetz
3. Svetlana Turubanova
4. Dengsheng Lu
5. M. Day
6. Qi Chen
7. Lijuan Liu
8. Guiying Li

In Nature and Landscape Conservation

1. Martin Herold
2. Dengsheng Lu
3. M. Day
4. Qi Chen
5. Lijuan Liu
6. Guiying Li
7. M. Skutsch
8. E. Rutishauser

Citations in the corpus

• Relationships between tree species diversity and above-ground biomass in Central African rainforests: implications for REDD (2013, background): “The rainforests of West and Central Africa are the second largest block of rainforest in the world (Baccini et al. 2008) and contain the highest levels of biomass per hectare (c. 250 t ha−1) worldwide (Lewis et al. 2009; FAO 2010).”
• Monitoring, reporting and verification for national REDD + programmes: two proposals (2011, background): “…approaches depends on a number of factors including the type of degradation, available (historical) data, capacities and resources and the potentials and limitations of various measurement and monitoring approaches (Asner et al 2005, Laporte et al 2007, Souza et al 2005, Baccini et al 2008).”
• A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems (2016, methodology): “…for comparative analysis of different algorithms such as regression tree, random forest, and ANN to identify the most appropriate algorithm for establishing biomass estimation models (Moisen and Frescino 2002; Labrecque et al. 2006; Baccini et al. 2008; Goetz et al. 2009; Latifi et al. 2010).”
• Mapping and monitoring deforestation and forest degradation in Sumatra (Indonesia) using Landsat time series data sets from 1990 to 2010 (2012, methodology): “Canopy height was useful for assessing differences between primary intact and degraded forest classes and the HOME metric was also used given previous evidence of its relationship to forest canopy structure and aboveground biomass (Drake et al 2002a, Baccini et al 2008).”