Peer-Reviewed Articles
409 Size-constrained Region Merging (SCRM): An Automated
Delineation Tool for Assisted Photointerpretation
Guillermo Castilla, Geoffrey G.Hay, and Jose R. Ruiz-Gallardo
Abstract Download
Full Article
The manual delineation of vegetation patches or forest stands
is a costly and crucial stage in any land-cover mapping
project or forest inventory based upon photointerpretation.
Recent computer techniques have eased the task of the
interpreter; however, a good deal of craftsmanship is still
required in the delineation. In an effort to contribute to the
automation of this process, we introduce Size-Constrained
Region Merging (SCRM), a recently implemented software tool
that provides the interpreter with an initial template of the to be
mapped area that may reduce the manual digitization
portion of the interpretation. In essence, SCRM transforms
an ortho-rectified aerial or satellite image (single or multichannel)
into a polygon vector layer that resembles the work
of a human interpreter, whom with no a priori knowledge of
the scene, was given the task of partitioning the image into a
number of homogeneous polygons all exceeding a minimum
size. We provide background information on SCRM foundations
and workflow, and illustrate its application on three different
types of satellite images.
421 Integration of Landsat TM and SPOT HRG Images for
Vegetation Change Detection in the Brazilian Amazon
Dengsheng Lu, Mateus Batistella, and Emilio Moran
Abstract Download
Full Article
Traditional change detection approaches have been proven
to be difficult in detecting vegetation changes in the moist
tropical regions with multitemporal images. This paper
explores the integration of Landsat Thematic Mapper (TM)
and SPOT High Resolution Geometric (HRG) instrument data
for vegetation change detection in the Brazilian Amazon.
A principal component analysis was used to integrate TM
and HRG panchromatic data. Vegetation change/non-change
was detected with the image differencing approach based on
the TM and HRG fused image and the corresponding TM
image. A rule-based approach was used to classify the TM
and HRG multispectral images into thematic maps with three
coarse land-cover classes: forest, non-forest vegetation, and
non-vegetation lands. A hybrid approach combining image
differencing and post-classification comparison was used to
detect vegetation change trajectories. This research indicates
promising vegetation change techniques, especially for
vegetation gain and loss, even if very limited reference data
are available.
432 Reducing Edge Effects in the Classification of High
Resolution Imagery
Guiyun Zhou and Nina S.-N. Lam
Abstract Download
Full Article
Edge effects have been a problem in image classification
especially when scale-based textural methods were included
in the classification process. This paper proposes a new
approach to reducing edge effects. The essence of the new
approach is that all pixels in a moving window make use
of the textural information instead of only the center pixel
as in the traditional moving window method. The performance
of the new approach was tested in three classification
scenarios. The results show that the new approach generally
produced higher accuracy with larger window size and was
much less affected by the edge issues than the traditional
moving window method. The new approach yields satisfactory
results as long as the window size is smaller than the
land-use polygons and the class boundaries are not too
complex.
443 Generation of Advanced ERS and Envisat Interferometric
SAR Products Using the Stable Point Network
Technique
Michele Crosetto, Erlinda Biescas, Javier Duro, Josep Closa,
and Alain Arnaud
Abstract Download
Full Article
The advanced differential interferometric SAR techniques
(A-DINSAR), based on time series of SAR images, are powerful
geodetic tools for land deformation monitoring. This paper,
which is focused on a particular A-DINSAR technique, named
Stable Point Network, concisely outlines its characteristics
and describes its products: average deformation maps,
deformation time series, and the maps of the residual
topographic error used to precisely geocode the A-DINSAR
products. Furthermore, it illustrates the performance of the
technique on a test area located in Barcelona, Spain. From
this experiment, interesting features are highlighted: the
capability to cover wide areas and at the same time measuring
thin infrastructures, such as the main dike of the port;
the good agreement between the deformation velocities and
the reference values coming from leveling campaigns; the
high sensitivity of the A-DINSAR estimations, which can
measure millimeter-level periodical deformations due to
thermal dilation, and the precise geocoding of the A-DINSAR
products.
451 Land Surface Temperature Variation and Major Factors
in Beijing, China
Rongbo Xiao, Qihao Weng, Zhiyun Ouyang, Weifeng Li, Erich
W. Schienke, and Zhaoming Zhang
Abstract Download
Full Article
Land surface temperature (LST) is a significant parameter in
urban environmental analysis. Current research mainly
focuses on the impact of land-use and land-cover (LULC) on
LST. Seldom has research examined LST variations based on
the integration of biophysical and demographic variables,
especially for a rapidly developing city such as Beijing, China.
This study combines the techniques of remote sensing and
geographic information system (GIS) to detect the spatial
variation of LST and determine its quantitative relationship
with several biophysical and demographic variables based on
statistical modeling for the central area of Beijing. LST and
LULC data were retrieved from a Landsat Thematic Mapper
(TM) image. Building heights were delimited from the shadows
identified on a panchromatic SPOT image. The integration of
LULC and census data was further applied to retrieve gridbased
population density. Results indicate that the LST pattern
was non-symmetrical and non-concentric with high temperature
zones clustered towards the south of the central axis and
within the fourth ring road. The percentage of forest, farmland,
and water per grid cell were found to be most significant
factors, which can explain 71.3 percent of LST variance.
Principal component regression analysis shows that LST was
positively correlated with the percentage of low density builtup,
high density built-up, extremely-high buildings, low
buildings per grid cell, and population density, but was
negatively correlated with the percentage of forest, farmland,
and water bodies per grid cell. The findings of this study can
be applied as the theoretical basis for improving urban
planning for mitigating the effects of urban heat islands.
463 Per-pixel Classification of High Spatial Resolution Satellite
Imagery for Urban Land-cover Mapping
David Barry Hester, Halil I. Cakir, Stacy A.C. Nelson, and Siamak
Khorram
Abstract Download
Full Article
Commercial high spatial resolution satellite data now
provide a synoptic and consistent source of digital imagery
with detail comparable to that of aerial photography. In the
work described here, per-pixel classification, image fusion,
and GIS-based map refinement techniques were tailored to
pan-sharpened 0.61 m QuickBird imagery to develop a
six-category urban land-cover map with 89.3 percent overall
accuracy (k = 0.87). The study area was a rapidly developing
71.5 km2 part of suburban Raleigh, North Carolina,
U.S.A., within the Neuse River basin. “Edge pixels” were
a source of classification error as was spectral overlap
between bare soil and impervious surfaces and among
vegetated cover types. Shadows were not a significant source
of classification error. These findings demonstrate that
conventional spectral-based classification methods can be
used to generate highly accurate maps of urban landscapes
using high spatial resolution imagery.
473 Quantifying Multi-temporal Urban Development Characteristics
in Las Vegas from Landsat and ASTER Data
George Xian, Mike Crane, and Cory McMahon
Abstract Download
Full Article
Urban development has expanded rapidly in Las Vegas,
Nevada of the United States, over the last fifty years.
A major environmental change associated with this urbanization
trend is the transformation of the landscape from natural
cover types to increasingly anthropogenic impervious surface.
This research utilizes remote sensing data from both the
Landsat and Terra-Advanced Spaceborne Thermal Emission
and Reflection Radiometer (ASTER) instruments in conjunction
with digital orthophotography to estimate urban extent and
its temporal changes by determining sub-pixel impervious
surfaces. Percent impervious surface area has shown encouraging
agreement with urban land extent and development
density. Results indicate that total urban land-use increases
approximately 110 percent from 1984 to 2002. Most of the
increases are associated with medium-to high-density urban
development. Places having significant increases in impervious
surfaces are in the northwestern and southeastern parts
of Las Vegas. Most high-density urban development, however,
appears in central Las Vegas. Impervious surface conditions
for 2002 measured from Landsat and ASTER satellite data are
compared in terms of their accuracy.