mapping of fractional woody cover using full, dual and...

$: Mapping of fractional woody cover using full, dual and ...seom.esa.int/LPS13/5867d0b0/LP_2013_Urbazaev.pdf · radarsat-2 hh/hv/vh/vv 21-02-2010 fq13 radarsat-2 hh/hv/vh/vv 09-05-2009$
http://www.eo.uni-jena.de

Jena

Stu

dy a

rea &

Data

sets

Mapping of fractional woody cover using full, dual and single polarimetric

L- and C-band datasets in the Kruger National Park region, SA

Mikhail Urbazaev1, Christian Thiel1, Christiane Schmullius1, Renaud Mathieu², Laven Naidoo²,

Shaun Levick ³, Izak Smit4, Gregory Asner5, Brigitte Leblon6

1 Friedrich-Schiller-University Jena Jena, Germany [email protected] [email protected]

2 Council for Scientific and Industrial Research Pretoria, South Africa

Co

nta

ct

Ab

str

act

Woody vegetation cover affects a range of ecosystem processes such as carbon and water cycling, energy fluxes, and fire regimes. Information on the spatial distribution of woody vegetation over large area is needed to understand the dynamics of savanna ecosystems. In this study the mapping of fractional woody cover using full, dual and single polarimetric L- (ALOS PALSAR) and C-band (RADARSAT-2) imageries is investigated. From both sensors different SAR-parameters, e.g. multipolarized intensities and polarimetric decompositions, were extracted and compared with woody cover obtained from 1-m airborne LiDAR data using a semi-empirical exponential model. The SAR data were acquired at different seasonal cycles between 2007 and 2010. The LiDAR survey was carried out in April-May 2008 with the LiDAR component of the CAO (Carnegie Airborne Observatory, USA) at a frequency of 50 kHz. The overall aim of the study was to analyze the capabilities and limitations of SAR data for woody cover mapping and the investigation of the potential synergic uses of LiDAR and SAR systems. Furthermore we investigated the influence of seasonality for mapping of woody vegetation. The LiDAR based woody cover was used for training and validation of SAR data. The woody cover map based on SAR backscatter was calculated using Random Forest algorithm. The results show that L-band backscatter is sensitive to map woody cover in Southern Africa. The highest correlation to the reference data was obtained from the dry season backscatter. In general, there was an increase in correlation between the SAR and LiDAR datasets with an increase in resolution coarseness. The calculated map was validated at a resolution of 50 m with R² of 0.73 and RMSE of 7.62%.

Sensor Polarisation Acq. date Mode

PALSAR HH/HV/VH/VV 14-04-2007 PLR

PALSAR HH/HV/VH/VV 19-04-2007 PLR

PALSAR HH/HV 06-08-2007 FBD




PALSAR HH 03-02-2007 FBS




Sensor Polarisation Acq. date FQ

RADARSAT-2 HH/HV/VH/VV 02-06-2009 FQ13









An

aly

sis

I. SAR-Parameters • Backscatter intensity most correlated SAR-parameter to woody cover • Weaker correlation of polarimetric decomposition parameters to woody cover

than backscatter

III. Spatial resolution • Increase of correlation with coarser resolutions (e.g. R² for L-band datasets)

IV. Seasonality • Highest correlation in winter at all scales (e.g. correlation for L-band datasets at

50m resolution)

3 Max Planck Institute for Biogeochemistry Jena, Germany

4 SANParks Skukuza, South Africa 5 Carnegie Institution for Science Stanford, USA

6 University of New Brunswick New Brunswick, Canada

Methodology

A fractional map of woody cover was produced using • PALSAR FBD from 6th Aug 2007, 23rd Sep 2008, 29th Sep 2010 • random forest algorithm (BREIMAN 2001) • spatial resolution = 50 m • 60% of random points from LiDAR woody cover for data training, 40%

for validation

II. Wavelength • L-band data better correlated to LiDAR woody cover than C-band data at all

scales (e.g. PALSAR and RADARSAT-2 data with highest r² at 50m resolution)

𝜎0 = 𝛽𝑠 + 𝛽𝑛 − 𝛽𝑠 ∙ 𝑒𝑥𝑝 −𝑘 ∙ 𝑊

Re

su

lts &

Va

lid

ati

on

Val

idat

ion

of

pro

du

ced

map

I. Conclusions • Resulting map in agreement with woody cover obtained

from CAO LiDAR • Underestimation in high woody cover values (from ca.

50% cover) • Basis for development of an operational monitoring

program of woody cover over the whole area of the Kruger National Park

• Basis for development of the first SAR-based biomass map for the Kruger National Park

II. Further steps • Integration of C-band data for better modelling of small

vegetation (shrubs, small trees) • Obtain and investigate fully polarimetric L-band data

(polarimetric decompositions) from winter period • Investigation of scale effects

Acknowledgements: This scientific research is supported by the SANPark Project

SARvanna, NRF/BMBF-Project SUA 08/54 and has been undertaken within the framework of the JAXA Kyoto & Carbon Initiative. ALOS PALSAR data have been provided by JAXA EORC. Scientific research in Kruger National Park is supported by the Andrew Mellon Foundation. The Carnegie Airborne Observatory is made possible by the Gordon and Betty Moore Foundation, the Grantham Foundation for the Protection of the Environment, Avatar Alliance Foundation, W. M. Keck Foundation, the Margaret A. Cargill Foundation, Mary Anne Nyburg Baker and G. Leonard Baker Jr., and William R. Hearst III.

(MDRY: middle of dry season (winter); MWET: middle of rainy season (summer); EWET: end of rainy season (autumn))

mapping of fractional woody cover using full, dual and...

Documents