Biomass assessment in the Cameroon savanna using ALOS PALSAR data

Abstract In this paper, ALOS PALSAR data have been used to map above ground biomass (AGB) in savanna ecosystems in Cameroon. The study has been motivated by the need to have estimates of carbon in African savannas. The L-band PALSAR mosaic data are suitable for the retrieval of savanna biomass (typically less than 100 Mg.ha − 1 ) at national and continental scales. The retrieval methods have been developed using the following steps a) collection of in situ data and estimate of AGB and its uncertainties, b) pre-processing of SAR data, with an emphasis on the reduction of uncertainties due to speckle, while preserving the SAR resolution (25 m), c) development of a regression model with a reduced number of fitting parameters. The methodology is developed in a representative study area where in situ data are collected, using standard PALSAR Fine Beam Dual polarisation data, and d) pixel-to-pixel mapping of AGB over 259 228 km 2 of Cameroon savanna using PALSAR mosaic data. The dense tropical forest has been masked using the GlobCover 2009 land cover map. A value of AGB and its uncertainty has been assigned to each pixel. The results indicate a total AGB of 1.25 ± 0.04 Pg or 0.63 ± 0.02 PgC of above-ground carbon in the Cameroon savanna.

[1]  Manabu Watanabe,et al.  Forest Structure Dependency of the Relation Between L-Band$sigma^0$and Biophysical Parameters , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Mayaux Philippe,et al.  A First Look at Carbon Stocks and their Variation in Congo Basin Forests , 2009 .

[3]  P. Ciais,et al.  The carbon balance of Africa: synthesis of recent research studies , 2011, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[4]  Thomas L. Ainsworth,et al.  Improved Sigma Filter for Speckle Filtering of SAR Imagery , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[5]  M. Pettit.  Reducing emissions from deforestation and degradation: Human rights and the commodification of carbon , 2011 .

[6]  J. Bruniquel,et al.  Multi-variate optimal speckle reduction in SAR imagery , 1997 .

[7]  Sassan Saatchi,et al.  Estimation of Forest Fuel Load From Radar Remote Sensing , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Dirk H. Hoekman,et al.  Land cover type and biomass classification using AirSAR data for evaluation of monitoring scenarios in the Colombian Amazon , 2000, IEEE Trans. Geosci. Remote. Sens..

[9]  Masanobu Shimada,et al.  PALSAR Radiometric and Geometric Calibration , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[10]  Shaun Quegan,et al.  Filtering of multichannel SAR images , 2001, IEEE Trans. Geosci. Remote. Sens..

[11]  S. Saatchi,et al.  Impact of spatial variability of tropical forest structure on radar estimation of aboveground biomass , 2011 .

[12]  Maurizio Santoro,et al.  Signatures of ALOS PALSAR L-Band Backscatter in Swedish Forest , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[13]  J. Carreiras,et al.  Understanding the relationship between aboveground biomass and ALOS PALSAR data in the forests of Guinea-Bissau (West Africa) , 2012 .

[14]  R. Colwell.  Remote sensing of the environment , 1980, Nature.

[15]  F. Rocca,et al.  The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle , 2011 .

[16]  Sandra A. Brown,et al.  Sourcebook for land use, land-use change and forestry projects , 2013 .

[17]  G. Alexandrov,et al.  Who is Who in Carbon Balance and Management 2006 , 2007, Carbon Balance and Management.

[18]  Piermaria Corona,et al.  VALUTAZIONE DELLE RISORSE FORESTALI A LIVELLO GLOBALE , 2013 .

[19]  Sassan Saatchi,et al.  Measuring biomass changes due to woody encroachment and deforestation/degradation in a forest-savanna boundary region of central Africa using multi-temporal L-band radar backscatter , 2011 .

[20]  I. Woodhouse,et al.  Measuring biomass changes due to woody encroachment and deforestation/degradation in a forest-savanna boundary region of central Africa using multi-temporal L-band radar backscatter , 2011 .

[21]  J. Chave,et al.  Towards a Worldwide Wood Economics Spectrum 2 . L E a D I N G D I M E N S I O N S I N W O O D F U N C T I O N , 2022 .

[22]  Richard Condit,et al.  Error propagation and scaling for tropical forest biomass estimates. , 2004, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[23]  S. Fritz,et al.  A new land‐cover map of Africa for the year 2000 , 2004 .

[24]  Josep G. Canadell,et al.  Anthropogenic CO 2 emissions in Africa , 2008 .

[25]  D. F. Westlake.  The biomass and productivity of Glyceria maxima I Seasonal changes in biomass , 1966 .

[26]  Bicheron Patrice,et al.  GlobCover - Products Description and Validation Report , 2008 .

[27]  Christopher A Williams,et al.  Africa and the global carbon cycle , 2007, Carbon balance and management.

[28]  Lars M. H. Ulander,et al.  L- and P-band backscatter intensity for biomass retrieval in hemiboreal forest , 2011 .

[29]  J. Chambers,et al.  Tree allometry and improved estimation of carbon stocks and balance in tropical forests , 2005, Oecologia.

[30]  Masanobu Shimada,et al.  Generating Large-Scale High-Quality SAR Mosaic Datasets: Application to PALSAR Data for Global Monitoring , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[31]  Thuy Le Toan,et al.  Dependence of radar backscatter on coniferous forest biomass , 1992, IEEE Trans. Geosci. Remote. Sens..

[32]  Pierre Defourny,et al.  Mapping Congo Basin vegetation types from 300 m and 1 km multi-sensor time series for carbon stocks and forest areas estimation , 2012 .

[33]  Maurizio Santoro,et al.  Mapping forest aboveground biomass in the Northeastern United States with ALOS PALSAR dual-polarization L-band , 2012 .

[34]  Rasmus Fensholt,et al.  Evaluating MODIS, MERIS, and VEGETATION vegetation indices using in situ measurements in a semiarid environment , 2006, IEEE Transactions on Geoscience and Remote Sensing.