Automatic Recognition of Built-up Areas in China Using CBERS-2B HR Data
The study presented here evaluates the possibility to
map the human settlement patterns in China using CBERS-2B
2.36m-resolution single-band panchromatic images as input. The
automatic image information extraction workflow designed by
the Joint Research Center, European Commission (JRC) is used
for the global human settlement layer (GHSL) production. The
classification methodology relies on textural and multi-scale
morphological image feature retrieval and automatic learning
and classification from low resolution globally-available
reference layers. According to the experimental results, the most
promising learning and classification option is the one using perscene
area-matching techniques with MODIS 500 “urban areas”
as training layer. This option provides an average accuracy of
98.13% with 5.66% of standard deviation. More refined analysis
is necessary using detailed reference datasets in order to
understand the value added to the propose methodology.
LU Linlin;
GUO Huadong;
PESARESI Martino;
SOILLE Pierre;
FERRI Stefano;
2014-08-25
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
JRC86187
978-1-4799-0211-8,
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