Extraction of Urban Area

1
Extraction of Urban Area Using ASTER Imagery and
the Existing Land Cover Data
Shibasaki-Lab, the University of Tokyo.
Ayako TANAKA, Koki IWAO, Ryosuke
SHIBASAKI Center for Spatial Information
Science, The University of Tokyo, Grid
Technology Research Center, National Institute of
Advanced Industrial Science and Technologiy
Backgrounds
Social background !!
Problems !!
Urban Area Mapping using ASTER images and the
Existing Land Cover Data
Riyadh, Saudi Arabia
Urban population growth
MOD12 Land cover 2
GRUMP Urban extents Grid 1
ASTER image
Important points in developing urban mapping
method 1, Global !! 2, Automatic and Simple 3,
Better Resolution and Accuracy
Urban expansion
urban area
GRUMP/ urban extent http//bet.sedac.ciesin.columb
ia.edu/gpw/
urban area
Climate change
Overestimate!!
non-urban area
Coarse!!
vegetation
To analyze and evaluate effects for human
activities
More accurate!!
ASTER GRUMP urban extents Grid (city
lights) MOD12 (seasonal change)
We need New Global Urban Area Map !!
urban area
MOD12 http//www-modis.bu.edu/landcover/
1 GRUMP urban extents grid Urban extents
grid is a data set resulting from GRUMP (Global
Rural-Urban Mapping Project) include a 30
arc-second land area grid showing urban areal
extents worldwide produced by the Center for
International Earth Science Information Network
(CIESIN) of the Earth Institute at Columbia
University. 2 MOD12 This is one of the Land
cover products generated by BOSTON University
using MODIS Data include a 30 arc-second land
area grid. Urban areas are one of the land cover
category.
Methodology
Images in each Process Case study of Asahikawa
Urban area (detected by visual interpretation)
GRUMP/urban extent
thin2
thin1
urban
MOD12
urban
buffer
urban
urban
ASTER classification
?ASTER image
?GRUMP/ urban extent
?MOD12/ urban
OverlayRegion Segmentation
Urban area detected by visual interpretation
(pink) Area of each segmentation
(gray)
?GRUMP/ thin
?MOD12/ buffer
?ASTER classification
Probability of each segment as urban
Thinning is a morphological operation that is
used to remove selected foreground pixels from
binary images (3km, 5km)
Buffering is a morphological operation that is
used to remove selected background pixels from
binary images (2km)
Classify the urban area using unsupervised
classification method for the automatic data
processing
Calculate probabilities of each segment as
urban in 6cities (Asahikawa, Oita, Manaus,
Hailar, Dubai). Average ? 80 classified as
urban Average lt 80 classified as others
?Overlay/ MOD12Result of visual interpretation
?Overlay/ GRUMPResult of visual interpretation
? Results of visual interpretation
Probability of each segment as urban
Accuracy
Result
?? Urban Map (Detected by this method)
??
?Apply this method to 4 cities in different
climatic zones
? Temperate ZoneAsahikawa
? Desert AreaDubai, UAE
? Steppe AreaHailar,China
? Tropical ZoneManaus, Brazil
Hit Rate ()
Results of urban classification
Results of visual interpretation
Detection Rate()
Detection Rate() Urban area (overlap) /
Urban area (detected by visual interpretation)
100 Hit Rate() Urban area (overlap) / Urban
area (detected by this method) 100 Detection
Rate(???) The rate of urban area detected by
visual interpretation in the urban area in the
results Hit Rate(???) The rate of urban area
detected by visual interpretation in the urban
area in the results
?test area ?Asahikawa (Japan), ?Dubai(UAE),
?Hailar(China), ?Manaus(Brazil),
(?Oita(Japan),?Ulaanbaatar(Mongolia))
Study Area

• Urban areas are tend to be overestimated in the
  results.
• Detection Rates of the results 60 95
  (Higher than that of MOD12)
• Hit Rates of the results 50 70 (Higher than
  that of GRUMP/ urban extent)
• This method improves
• detection rates compared with MOD12
• hit rates compared with GRUMP/ urban extent

?
?
?

• Apply this method to various cities and
  assessing the accuracy
• Generate a global urban map using this method
• Classify small villages accurately using
• Gazetteer a dictionary of place-names
• slope data

?
?
?
What is a Gazetteer? A Gazetteer is a
geographical dictionary. Instead of including
lists of words, it includes lists of places.
These places can be settlements (cities, towns,
villages) or geographical features (hills,
rivers, regions, parks, tourist attractions
etc.). We have extended the concept of a
Gazetteer to include famous people and family
names.