Peer-Reviewed Articles
513 Multi-Band Wavelet for Fusing SPOT
Panchromatic and Multispectral Images
Wenzhong Shi, Changqing Zhu, Caiying Zhu, and Xiaomei Yang
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With the development of remote sensing technology, fusion of remotely sensed
images, such as SPOT panchromatic (SPOT P) with SPOT multispectral images
(SPOT XS) or Landsat Thematic Mapper (TM), has become more important in order
to obtain richer information in the spatial and spectral domains simultaneously.
Many fusion methods have been developed based on the two-band wavelet transformation.
However, due to the limitations of the transformation characteristics themselves,
the two-band wavelet is not very ef.cient for the fusion of images whose
ratio of spatial resolutions is not 2n (n _ 1, 2, 3, ...), e.g., for fusing
a 10-m resolution panchromatic SPOT image and with 30-m resolution multispectral
TM images. However, a recently developed new wavelet branch—multi-band
wavelet—can potentially be applied to solve this problem.
In this paper, we develop a new approach for fusing SPOT P images with multispectral TM images based on multi-band wavelet transformation. First, the theoretical basis of multi-band wavelet is presented and its transformation properties are analyzed. Second, a new method for fusing a SPOT P image with multispectral images using the multi-band wavelet is proposed. Speci.cally, the threeband wavelet is implemented to fuse 10-m SPOT panchromatic and 30-m multispectral TM images. Third, this new method is compared with previous methods such as the two-band wavelet and IHS methods for image fusion. The proposed multi-band wavelet approach demonstrates an improvement in spatial and spectral characteristics for fusing SPOT P and multispectral TM images.
521 A Simplified Atmospheric Correction
Procedure for the Normalized Difference Vegetation Index
Jie Song, Duanjun Lu, and M.L. Wesely
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Accurate corrections of the Normalized Difference Vegetation Index (NDVI) for
atmospheric effects are currently based on modeling the physical behavior
of radiation as it passes through the atmosphere. An important requirement
for application of the physical models is detailed information on atmospheric
humidity and particles. Here, a method is described for making atmospheric
corrections without the need for detailed atmospheric observations. A simpli.ed
procedure for making atmospheric corrections to re.ectances observed from
satellites is developed by using the unique spectral signature of water pixels
in satellite images. A radiative transfer model is applied to a variety of
clear-sky conditions to generate functional relationships between the radiation
due to the atmospheric scattering above water bodies and atmospheric radiative
properties. Test cases indicate that the resulting estimates of surface re.ectances
and NDVI agree well with estimates made using a radiative transfer model
applied independently and with measurements made at the surface.
529 Comparison of Gray-Level Reduction
and Different Texture Spectrum Encoding Methods for Land-Use Classification
Using a Panchromatic Ikonos Image
Bing Xu, Peng Gong, Edmund Seto, and Robert Spear
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In this paper, we evaluate the potential of a frequencybased contextual classi.er
(FBC) for land-use classi.cation with a panchromatic Ikonos image. To capture
the spatial arrangement of image gray-level values and use such information
in image classi.cation, we applied texture spectrum (TS) directly in the
FBC. The effects of several data preprocessing and reduction methods on the
performance of the FBC are also evaluated. The methods include four gray-level
reduction (GLR) techniques and several modi.cations to the TS technique.
The purpose of data reduction is to improve the classi.cation ef.ciency of
the FBC. The GLR schemes were min-max linear compression (LC), gray level
binning (BN), histogram equalization (HE), and piece-wise nonlinear compression
(PC). Instead of using the texture measures derived from the texture spectrum,
we directly applied texture spectra of various sizes in the classi.cation.
We modi.ed the encoding algorithm in the TS and were able to reduce the number
of texture units from its original 6561 to 256, 81, and 16, leading to as
much as a 410 times computation ef.ciency. The original image and GLR images
were subsequently classi.ed with the FBC. We compared the classi.cation accuracies
and found that the GLR methods resulted in accuracies similar to that of
the original image (within 0.03 kappa value). There was little difference
in classi.cation accuracy (within 0.03 kappa value) among the three modi.ed
TS methods, which were all outperformed by the original TS method. All TS
methods performed considerably better than the use of the original image
and the GLR methods.
537 Use of Multispectral Ikonos Imagery
for Discriminating between Conventional and Conservation Agricultural
Tillage Practices
Andrés Viña, Albert J. Peters, and Lei Ji
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There is a global concern about the increase in atmospheric concentrations
of greenhouse gases. One method being discussed to encourage greenhouse gas
mitigation efforts is based on a trading system whereby carbon emitters can
buy effective mitigation efforts from farmers implementing conservation tillage
practices. These practices sequester carbon from the atmosphere, and such
a trading system would require a low-cost and accurate method of veri.cation.
Remote sensing technology can offer such a veri.cation technique. This paper
is focused on the use of standard image processing procedures applied to
a multispectral Ikonos image, to determine whether it is possible to validate
that farmers have complied with agreements to implement conservation tillage
practices. A principal component analysis (PCA) was performed in order to
isolate image variance in cropped .elds. Analyses of variance (ANOVA) statistical
procedures were used to evaluate the capability of each Ikonos band and each
principal component to discriminate between conventional and conservation
tillage practices. A logistic regression model was implemented on the principal
component most effective in discriminating between conventional and conservation
tillage, in order to produce a map of the probability of conventional tillage.
The Ikonos imagery, in combination with ground-reference information, proved
to be a useful tool for veri.cation of conservation tillage practices.
545 Building and Evaluating Models to
Estimate Ambient Population Density
Paul C. Sutton, Chris Elvidge, and Tom Obremski
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The concept of human population density is quite simple: the number of persons
occupying a given area. Nonetheless, practical representations of population
density must use appropriate spatial and temporal scales of measurement to
be useful. The 11 September 2001 attack on the World Trade Center in New
York is a poignant example: “How many people were in the two World
Trade Center buildings at 0830 local time?” Population density data
derived from mostnational censuses is a residential measure of population
density and consequently does not capture non-residential population density.
Human mobility suggests that a nonresidential or ambient measure of population
density may be a more useful representation for some applications. Ambient
population density in this sense is a temporally averaged measure of population
density that takes into account where people work, sleep, eat, drive, shop,
etc. Short of implanting a GPS reciever into everyone’s skull and tracking
their spatio-temporal behavior, it is extremely dif.cult to make direct measurements
of ambient population density. This paper explores some theoretical and empirical
efforts at estimating ambient population density and proposes a quantitative
means for evaluating their validity. The three models of population density
examined are LandScan, Gridded Population of the World (GPW), and a simple
empirical model derived from nighttime satellite imagery provided by the
Defense Meteorological Satellite Program’s Operational Linescan System
(DMSP OLS). These measures are compared to both residential and employment-based
measures of population density in the Los Angeles metropolitan area. The
GPW, LandScan, and DMSP OLS models of ambient population density described
here all make foundational contributions to future efforts at .lling the
gap in social, economic, and demographic information for parts of the world
where such data are unavailable. The proxy measures of population density
described here show promise for many applications, including improved mapping
of population distribution and as a supplement to census enumerations in
many parts of the world.
555 Fractal Analysis of Satellite-Detected
Urban Heat Island Effect
Qihao Weng
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Surface radiant temperatures derived from Landsat TM thermal infrared images
of 13 December, 1989, 03 March, 1996, and 29 August 1997 were used to study
the urban heat island (UHI) phenomenon in Guangzhou, China. To examine the
spatial distribution of surface radiant temperatures, transects were drawn
and analyzed from each temperature image. Moreover, the fractal dimensions
of these transects were computed using the divider method, so that the spatial
variability of surface radiant temperatures caused by the thermal behavior
of different land-cover types and landscape pattern characteristics can be
better understood. The effect of urban development on the geographical distribution
of surface radiant temperatures and thus on the UHI was also investigated.
The results revealed two major heat islands, one in the southwest and the
other in the east of the city. The areal extent of the UHIs varied as the
season changed. The transact derived from the spring image had the lowest
fractal dimension while that from the summer image the highest value. Urban
development increased the spatial variability of radiant temperatures, resulting
in higher fractal dimension values. The thermal surfaces have become more
spatially uneven and the textures more complex.
567 Image Calibration to Like-Values in Mapping
Shallow Water Quality from Multitemporal Data
Md A. Islam, J. Gao, W. Ahmad, D. Neil, and P. Bell
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The applicability of image calibration to like-values in mapping water quality
parameters from multitemporal images is explored. Six sets of water samples
were collected at satellite overpasses over Moreton Bay, Brisbane, Australia.
Analysis of these samples reveals that waters in this shallow bay are mostly
TSS-dominated, even though they are occasionally dominated by chlorophyll
as well. Three of the images were calibrated to a reference image based on
invariant targets. Predictive models constructed from the reference image
were applied to estimating total suspended sediment (TSS) and Secchi depth
from another image at a discrepancy of around 35 percent. Application of
the predictive model for TSS concentration to another image acquired at a
time of different water types resulted in a discrepancy of 152 percent. Therefore,
image calibration to like-values could be used to reliably map certain water
quality parameters from multitemporal TM images so long as the water type
under study remains unchanged. This method is limited in that the mapped
results could be rather inaccurate if the water type under study has changed
considerably. Thus, the approach needs to be re.ned in shallow water from
multitemporal satellite imagery.
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