ASPRS

PE&RS February 2000

VOLUME 66, NUMBER 2
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING

Peer-Reviewed Article Abstracts

155 Recomputation of the Global Mars Control-Point Network
W. Zeitler, T. Ohlhof, and H. Ebner

Abstract
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This paper deals with the recomputation of the global control point network of the planet Mars. The existing Mars control point net is based on Viking data and consists of a large number of ground points, which can be easily identified in the imagery and whose three-dimensional (3D) object coordinates (e.g., latitude, longitude, and height with respect to a reference ellipsoid) are known. These coordinates were redetermined in order to eliminate several disadvantages of the former computations and to include the currently best available input data such as improved Viking trajectory information, the Viking occultation data, present rotational parameters, and the Mars Pathfinder lander data. Within a simultaneous 3D bundle block triangulation, seven interior orientation parameters, the position and attitude parameters of 1140 images, and the ground coordinates of 3739 tie points and one control point were estimated. The RMS  values uX, uY, uZ of the theoretical standard deviations of the adjusted object coordinates amount to 750 m, 770 m, and 710 m, respectively, which is a significant improvement compared with former results (1 to 5 km). The accuracy of the ground point coordinates is close to the theoretical accuracy limit of 520 m in X, Y, and Z, where error-free orientation parameters are assumed. This new set of orientation parameters and ground points may now be used for local, regional, and global DTM generation; for the determination of reference bodies; for mapping purposes; as well as for current (Mars Global Surveyor 1996) and future (e.g., Mars Surveyor 1998 and 2001, Mars Express 2003) missions to Mars.

163 Continuous Piecewise Geometric Rectification for Airborne Multispectral Scanner Imagery
Minhe Ji and John R. Jensen

Abstract
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Geometric rectification of airborne multispectral scanner image data using traditional polynomial functions often cannot provide satisfactory RMSE accuracy due to the complex nature of geometric distortions in the data. The discrete approach to rectifying these data generates segmented pieces that may cause edge-matching problems after they are reassembled. To improve the rectification accuracy while retaining the continuity of the rectified strip, a continuous piecewise geometric rectification approach is introduced. Using logical divisions of a strip and the concept of overlapping area anchor ground control points, the approach localizes the complex distortion and greatly improves the edge-match between pieces. A description of the procedure is presented along with two case studies, each having a different set of sensor and terrain characteristics, to illustrate the advantages of this approach versus traditional techniques.

173 A Standardized Radiometric Normalization Method for Change Detection Using Remotely Sensed Imagery
Joon Heo and Thomas W. FitzHugh

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The image normalization process aims to remove radiometric differences between multitemporal images that are due to non surface factors. Accurate normalization is essential for image processing procedures that use multi-date imagery, such as change detection. Linear regression using temporally invariant targets is a widely accepted method for normalization. However, except for the criteria for selecting target points, there is no standard method for conducting this important procedure. This paper proposes a standardized radiometric normalization method for detecting and deleting outliers and obtaining the optimal linear equation for a given set of target points. The method consists of a linear regression model and a studentized residual method for outlier determination. Standardized decision criteria such as R2 and confidence range for t-test are discussed and investigated, as are the issues of band selection and normalization target size. Four variants of the method are tested here, using a pair of Landsat TM images 10 years apart and corresponding training sets and accuracy assessment data. As a result, a standardized computation procedure is proposed, which uses band-by-band linear regression, single pixel targets, and a very conservative 99 percent confidence interval for determining outliers.

183 Estimation of Canopy-Average Surface-Specific Leaf Area Using Landsat TM Data
Leo Lymburner, Paul J. Beggs, and Carol R. Jacobson

Abstract
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Specific leaf area (SLA) is an important ecological variable because of its links with plant ecophysiology and leaf biochemistry. Variations in SLA are associated with variations in leaf optical properties, and these changes in leaf optical properties have been found to result in changes in canopy reflectance. This paper utilizes these changes to explore the potential of estimating SLA using Landsat TM data. Fourteen sites with varying vegetation were sampled on the Lambert Peninsula in Ku-ring-gai Chase National Park to the north of Sydney, Australia. A sampling strategy that facilitated the calculation of canopy-average surface SLA (SLACS) was developed. The relationship between SLACS, reflectance in Landsat TM  bands, and a number of vegetation indices, were explored using univariate regression. The observed relationships between SLACS and canopy reflectance are also discussed in terms of trends observed in a pre-existing leaf optical properties dataset (LOPEX  93). Field data indicate that there is a strong correlation between SLACS and red, near-infrared, and the second mid infrared bands of Landsat TM data. A strong correlation between SLACS and the following vegetation indices: Soil and Atmosphere Resistant Vegetation Index (SARVI2), Normalized Difference Vegetation Index (NDVI), and Ratio Vegetation Index (RVI), suggests that these vegetation indices could be used to estimate SLACS using Landsat TM data.

193 Radiation-Vegetation Relationships in Eucalyptus Forest
Lalit Kumar and Andrew K. Skidmore

Abstract
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Radiation-vegetation relationships for 12 species of Eucalyptus from the south coast of New South Wales showed that the mean radiation values differed significantly between species. Confidence intervals around the mean radiation values, based on pooled standard deviation, were used as an index of species generality. There were differences in the size of the confidence intervals between species. While E. bosistoana and E. maidenii had large confidence intervals over all seasons, E. sieberi, E. muellerana, and E. globoidea had very small confidence intervals. The species also exhibit a shift in the relative positions of their confidence intervals according to season. Clearly, radiation data are an important variable for eucalypt species delineation, and may be included as an explanatory variable when modeling the distribution of eucalypts. Solar radiation was calculated for the different seasons of the year using a model developed within a geographic information system (GIS); the input to the model is simply a digital elevation model (DEM) and the latitude of the site.

205 Detecting Wetland Change:  A Rule-Based Approach Using NWI and SPOT-XS Data
Paula F. Houhoulis and William K. Michener

Abstract
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Spectral similarities among wetlands and agricultural fields and forests can create difficulties in satellite image classification. Utilizing ancillary information, such as National Wetlands Inventory (NWI) data available from the U.S. Fish and Wildlife Service, to define wetlands provides a practical solution to this problem. However, NWI data are at least a decade old for many areas. In this study, data derived from SPOT-XS imagery were used to create a rule-based model to detect wetland change and update NWI data. First, the pixel vector modulus was calculated (sqrt(b21 + b22 + b23/N)), and a coarse land-cover layer was developed from SPOT-XS imagery.  Second, combinations of the mean modulus value, the majority land-cover value, and the NWI system class for each polygon were used to develop logic rules to indicate areas of potential wetland change. Logic rules and change-detection accuracy varied according to wetland type. At least 8 percent of the wetlands in the study area had undergone land-cover change since the mid-1980s; however, most such wetlands were small (<1 ha).

213 Quantification of Chlorophyll in Reservoirs of the Little Washita River Watershed Using Airborne Video
M.M. Avard, F.R. Schiebe, and J.H. Everitt

Abstract
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Airborne video cameras equipped with narrow-band filters were used to assess chlorophyll-a concentration in flood control reservoirs of the Little Washita River Watershed in central Oklahoma. This study utilizes airborne video cameras equipped with narrow 10-nm band filters centered at the critical wavelengths to assess chlorophyll-a concentration.The video cameras were calibrated using a series of panels and a hand-held spectroradiometer to convert digital numbers into radiance values (?W/cm2/sr). This was then processed into reflectance values by the incorporation of solar irradiance data. Results indicate that the relationship between emergent radiance and chlorophyll concentration is best described by the model y = a0(1 - e-x/c), and that the ability to estimate chlorophyll-a concentration in reservoirs using airborne video imagery has a great deal of potential.

 
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