ASPRS

PE&RS January 2004

VOLUME 70, NUMBER 1
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING

Peer-Reviewed Articles

77 Rover Localization and Landing-Site Mapping Technology for the 2003 Mars Exploration Rover Mission
Rongxing Li, Kaichang Di, Larry H. Matthies, Raymond E. Arvidson, William M. Folkner, and Brent A. Archinal

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The technology and experiments planned for rover localiza tion and landing site mapping in the 2003 Mars Exploration Rover (MER) mission are described. We introduce the Mars global and landing site local reference systems. For global rover localization in the Mars body-fixed reference system, a triangulation can be performed using observations of common landmarks on satellite images and the very first set of surface images. Alternatively, ultra-high frequency (UHF) two-way Doppler tracking technology can determine the location. For localization of the rover in the landing site area, onboard rover localization techniques will be performed in real time. A visual odometry experiment will improve localization by overcoming problems associated with wheel odometry such as slippage and low accuracy. Finally, a bundle-adjustment-based rover localization method will build an image network acquired by Pancam, Navcam, and Hazcam cameras. The developed incremental and integrated bundle adjustment models will supply improved rover locations and image orientation parameters, which are critical for the generation of high quality landing site topographic mapping products. Based on field tests performed on Earth and Mars (MPF mission data), a relative localization accuracy of one percent of the traversing distance from the landing center is expected to be achieved during this mission. In addition, the bundle adjustment results will also enable us to produce high precision landing site topographic mapping products, including seamless panoramic image mosaics, DTMs, and orthophotos.

91 Landsat TM Satellite Image Restoration Using Kalman Filters
D. Arbel, E. Cohen, M. Citroen, D.G. Blumberg, and N.S. Kopeika

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The quality of satellite images propagating through the atmosphere is affected by phenomena such as scattering and absorption of light, and turbulence, which degrade the image by blurring it and reducing its contrast. The atmospheric Wiener filter, which corrects for turbulence blur, aerosol blur, and path radiance simultaneously, is implemented in the digital restoration of Landsat Thematic Mapper (TM) imagery. Digital restoration results for Landsat TM imagery using the atmospheric Wiener filter were presented in the past. Here, a new approach for digital restoration of Landsat TM imagery is presented by implementing a Kalman filter as an atmospheric filter, which corrects for turbulence blur, aerosol blur, and path radiance simultaneously. Turbulence MTF is calculated from meteorological data. Aerosol MTF is consistent with optical depth. The product of the two yields atmospheric MTF, which is implemented in both the atmospheric Wiener and Kalman filters. Restoration improves both resolvable detail and contrast. Restorations are quite apparent even under clear weather conditions. Although aerosol MTF is dominant, slightly better results are obtained when the shape of atmospheric MTF includes turbulence, in addition to that of aerosol MTF, as shown by the use of criteria for restoration success. In general, the Kalman restoration is superior.

101 Spatio-Temporal Analysis Using a Multiscale Hierarchical Ecoregionalization
Rebecca N. Handcock and Ferenc Csillag

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We address the need for spatio-temporally explicit analysis techniques linking the scales of ecosystem, observation, and analysis, using a hierarchical ecoregionalization to examine remotely sensed data at spatial scales of ecological and management significance. Long- and short-term changes in vegetation functioning are a key indicator of ecological processes. We predict net primary production (NPP) at monthly temporal resolution for 16 years (1981-1996) at an 8-km spatial resolution for the approximately 106 km² area of Ontario, Canada. We calculate landscape-level light use efficiency values that are tuned to monthly and long-term ecoclimates, and the Normalized Difference Vegetation Index from the NOAA-AVHRR sensor. Applying our spatio-temporal analysis tools, we show evidence for increasing NPP across most of the province. This increase varies seasonally and annually across Ontario, and its magnitude and distribution varies with the spatial scales of analysis. Bridging the gap between local and global studies, this research supports spatio-temporal monitoring and analysis of ecosystem functions.

Please see these links for the color figures: Figure 1. Figure 2. Figure 3. Figure 4. Figure 5. Figure 6. Figure 7.

111 Automated Subpixel Photobathymetry and Water Quality Mapping
Robert L. Huguenin, Mo Hwa Wang, Robert Biehl, Scott Stoodley, and Jef frey N. Rogers

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New photobathymetry and water quality software is described here that utilizes subpixel analysis software (Subpixel Classifier) with an autonomous image calibration procedure and analytic retrieval algorithm to simultaneously retrieve and report bottom depth and the concentrations of suspended chlorophyll, suspended sediments, and colored dissolved organic carbon on a per-pixel basis from four-band multispectral image data. From the derived composition, the QSC2 (Quantitative Shoreline Characterization, Version 2.0) software also computes and reports water column visibility parameters (vertical and horizontal subsurface sighting ranges and turbidity, each at four wavelength band passes, plus Secchi depth as a scalar) as well as depth and turbidity confidence. QSC2 compensates for the effects of the atmosphere, sun and sky reflections from the water surface, subpixel contributions from exposed land, and variations in the bottom material properties. All information is derived automatically from the pixel data alone. The performance of the QSC2 software was demonstrated using a four-band Ikonos image of Plymouth, Massachusetts. Accuracies of the image-derived compositions, water clarity, and depths were assessed using field and laboratory measurements for eight representative lakes in the scene. The means of the differences of the field-measured and image-derived suspended chlorophyll and colored dissolved organic carbon concentrations for the eight lakes were 1.82 µg/l and 4.34 mgC/l, respectively. The image-derived concentrations of suspended sediments were all below the threshold of detection for the field samples (5 mg/l), in agreement with the field data. The mean of the differences between field-measured and image-derived Secchi depths was 0.76 m. The mean depth difference was 0.57 m.

125 AVIRIS Measurements of Chlorophyll, Suspended Minerals, Dissolved Organic Carbon, and Turbidity in the Neuse River, North Carolina
Mark A. Karaska, Robert L. Huguenin, Jef f L. Beacham, Mo-Hwa Wang, John R. Jensen, and Ronald S. Kaufmann

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Many aquatic ecosystems in the United States and worldwide are impaired by the over-enrichment of waters by nutrients. In advanced stages, the process of eutrophication can cause harmful algae blooms. This research retrieved the concentrations of suspended chlorophyll (Chl), suspended minerals (SM), colored dissolved organic carbon (DOC), and turbidity (total attenuation) from AVIRIS imagery of a severely over-enriched waterway in North Carolina, and evaluated if these parameters could be used as indicators of conditions leading to algae blooms. A digital image processing algorithm called QSC1 (Quantitative Shoreline Characterization, Version 1.0) was used. The retrieved water quality parameter values were tested by statistical comparisons to field measurements made at the time of the AVIRIS data collection. Applying QSC1 to AVIRIS imagery resulted in measurements of Chl that correlated well with field measurements (r = 0.84). Problems with field sampling prevented the assessment of retrieved SM and DOC. The statistical correlation analysis indicated that, for comparison to remotely sensed data, field measurements in the steadily flowing Neuse River must be collected within two hours of the imagery. Thematic maps of each water quality parameter were generated from the imagery and evaluated. The maps of Chl showed spatial patterns consistent with the field data and circulation of the river, and indicated potential point and non-point sources. Statistical and principle component analyses were used to assess whether the AVIRIS water quality measurements were directly or indirectly related to parameters and conditions indicative of nutrient loading and algae blooms that were measured in the field. The AVIRIS measurements were used to create a new index of eutrophication, the Algae Production Potential Index (APPI), for the purpose of mapping where conditions of high nutrient loading and potential algae blooms exist. The index uses direct measurements of Chl, DOC, and SM (as a surrogate for phosphate).These measurements are combined in a GIS model based on ecological relationships. Although not field verified, the APPI map shows patterns of algae bloom conditions that are similar in size, scale, and location to previous blooms in the Neuse.

135 Exploitation of Very High Resolution Satellite Data for Tree Species Identification
A. Carleer and E. Wolff

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With the emergence of very high spatial resolution satellite images, the spatial resolution gap which existed between satellite images and aerial photographs has decreased. A study of the potential of these images for tree species in" monoculture stands" identification was conducted. Two Ikonos images were acquired, one in June 2000 and the other in October 2000, for an 11- by 11-km area covering the Sonian Forest in the southeastern part of the Brussels-Capital region (Belgium). The two images were orthorectified using a digital elevation model and 1256 geodetic control points. The identification of the tree species was carried out utilizing a supervised maximum-likelihood classification on a pixel-by-pixel basis. Classifications were performed on the orthorectified data, NDVI transformed data, and principal components imagery. In order to decrease the intraclass variance, a mean filter was applied to all the spectral bands and neo-channels used in the classification process. Training and validation areas were selected and digitized using detailed geographical databases of the tree species. The selection of the relevant bands and neo-channels was carried out by successive addition of information in order to improve the classification results. Seven different tree species of one to two different age classes were identified with an overall accuracy of 86 percent. The seven identified tree species or species groups are Oaks (Quercus sp.), Beech (Fagus sylvatica L.), Purple Beech (Fagus sylvatica purpurea), Douglas Fir (Pseudotsuga menziesii (Mirb.) Franco), Scots Pine (Pinus sylvestris L.), Corsican Pine (Pinus nigra Arn. subsp. laricio (Poir.) Maire var. corsican), and Larch (Larix decidua Mill.).

141 Predicting Missing Field Boundaries to Increase Per-Field Classification Accuracy
Paul Aplin and Peter M. Atkinson

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A new technique for predicting missing field boundaries was developed to increase the accuracy of per-field classification. This technique is based on a comparison of within-field modal land-cover proportion and local variance. Analysis was performed on 4-m and 20-m spatial resolution imagery derived from Compact Airborne Spectrographic Imager (CASI) data, to simulate the difference in land-cover classification accuracy between multispectral Ikonos and Satellite Pour l'Observation de la Terre (SPOT) High Resolution Visible (HRV) imagery. Initially, per-pixel classification was performed, followed by per-field classification. The technique for detecting missing boundaries was then implemented, and per-field classification was carried out a second time using updated field boundary data. Finally, an accuracy assessment was performed. The results demonstrate that classification was significantly more accurate when the missing boundary flag was used, and that simulated Ikonos imagery was considerably more accurate for this purpose than simulated SPOT HRV imagery.
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