ASPRS

PE&RS May 2005

VOLUME 71, NUMBER 5
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING

Peer-Reviewed Articles

585 A Robust Technique for Precise Registration of Radar and Optical Satellite Images
Tai D. Hong and Robert A. Schowengerdt

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Combining data from different sensors for visual or classification analysis is a common task in remote sensing. The first step is normally to register the images which may be considered geometric integration; the accuracy of this step is important to create a valuable final hybrid image. This paper addresses geometric integration and introduces a new method for automatically registering two dissimilar images, such as, a radar image and an optical image with high accuracy. Pre-registration of the two images to within a specified tolerance is required. In our examples, this tolerance is up to 17 pixels (at the scale of the higher resolution image) and may be achieved by, for example, visually located control points. The described approach then uses large-scale edge gradient contours in a process that automatically locates candidate control points on the contours. The points are selected using a cost function that measures the degree of match between all possible pairs of points. Numerous control points (typically around 50 pairs) are found from matched pairs of gradient contours and used in a global, rubber sheet, polynomial warp to refine the registration. This approach is applied to register a Synthetic Aperture Radar (SAR) image (ERS2, 12.5 m pixels) and a Thematic Mapper (TM) optical image (Landsat-5, 28.5 m pixels) automatically. Several examples with different scene content are shown to validate the approach and discussed in terms of residual registration error and processing efficiency.

595 Agricultural Applications of High-Resolution Digital Multispectral Imagery:Evaluating Within-Field Spatial Variability of Canola (Brassica napus) in Western Australia
Georgina Warren and Graciela Metternicht

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This paper analyses the potential of a high-resolution airborne remote sensing system, the Digital Multi-Spectral Imagery (DMSI), for detecting canola growth variability within a field to help farmers for future incorporation of the system into sitespecific crop management approaches for agriculture.

Transect sampling within a canola field of a broad acre agricultural property in the South West of Western Australia was conducted synchronous with the capture of one-meter spatial resolution DMSI. Four individual bands (blue, green, red, and NIR) and five image transformations namely the Normalized Difference Vegetation Index (NDVI), Normalized Difference Vegetation Index – Green (NDVI-green), Soil Adjusted Vegetation Index (SAVI), Photosynthetic Vigor Ratio (PVR) and Plant Pigment Ratio (PPR) of DMSI were investigated. Canola density was correlated with the four individual bands and five image transformations, while the LAI was correlated with the four individual bands.

The NDVI-green, red and near-infrared bands of DMSI produced the best correlations with the density of canola, whereas the LAI had significant ( alpha = 0.05) negative correlations with the blue (-0.93) and red (-0.89) DMSI bands, and a significant positive correlation were found with the nearinfrared band (0.82).

603 Field Determination of Optimal Dates for the Discrimination of Invasive Wetland Plant Species Using Derivative Spectral Analysis
Magdeline Laba, Fuan Tsai, Danielle Ogurcak, Stephen Smith, and Milo E. Richmond

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Mapping invasive plant species in aquatic and terrestrial ecosystems helps to understand the causes of their progression, manage some of their negative consequences, and control them. In recent years, a variety of new remote-sensing techniques, like Derivative Spectral Analysis (DSA) of hyperspectral data, have been developed to facilitate this mapping. A number of questions related to these techniques remain to be addressed. This article attempts to answer one of these questions: Is the application of DSA optimal at certain times of the year? Field radiometric data gathered weekly during the summer of 1999 at selected field sites in upstate New York, populated with purple loosestrife (Lythrum salicaria L.), common reed (Phragmites australis (Cav.)) and cattail (Typha L.) are analyzed using DSA to differentiate among plant community types. First, second and higher-order derivatives of the reflectance spectra of nine field plots, varying in plant composition, are calculated and analyzed in detail to identify spectral ranges in which one or more community types have distinguishing features. On the basis of the occurrence and extent of these spectral ranges, experimental observations suggest that a satisfactory differentiation among community types was feasible on 30 August, when plants experienced characteristic phenological changes (transition from flowers to seed heads). Generally, dates in August appear optimal from the point of view of species differentiability and could be selected for image acquisitions. This observation, as well as the methodology adopted in this article, should provide a firm basis for the acquisition of hyperspectral imagery and for mapping the targeted species over a broad range of spatial scales.

613 Remote Sensing of Urban Heat Islands by Day and Night
Janet Nichol

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A night-time thermal image from the ASTER satellite sensor, of the western New territories of Hong Kong is compared with a daytime Landsat Enhanced Thematic Mapper Plus (ETM+) thermal image obtained nineteen days earlier. Densely built high rise areas which appear cool on daytime images are conversely, relatively warm on nighttime images, though the temperature differences are not well developed at night. Lower temperature gradients between different land cover types observed on the night time image result in meso-scale, rather than micro-scale climatic patterns being dominant, suggestive of processes operating in the Urban Boundary Layer (UBL), as opposed to the Urban Canopy Layer (UCL) which is dominant in the daytime. Thus, at night, proximity to extensive cool surfaces such as forested mountain slopes appears to be influential in maintaining cooler building temperatures. The relevance of satellite-derived surface temperatures for studies of urban microclimate is supported by field data of surface and air temperatures collected in the study area. Comparison of the ASTER Kinetic Temperature standard product with a thermal image processed using locally derived emissivity and atmospheric data indicated higher accuracy for the latter.

623 Implementation of an Equal-area Gridding Method for Global-scale Image Archiving
Jeong Chang Seong

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Constructing global-scale image databases is a challenging task because of large data volume and various map distortions. The raster pixel data structure on a projected flat surface has been used frequently; however, research shows that it may duplicate or lose original features. For a more accurate image-database construction method, this research investigated an equal-area global gridding method. An extended header structure was developed that allows facet indexing using geographic latitude and longitude. Three algorithms were developed in a C/C++ programming environment that performs new layer creation, accessing facet values, and importing image data in other projections. The output of this research can be considered for archiving global-scale satellite imagery and for publishing global-scale thematic raster datasets such as land cover and population density.

629 Influence of System Calibration on Direct Sensor Orientation
Naci Yastikli and Karsten Jacobsen

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The determination of object coordinates based on direct sensor orientation is an extrapolation from the projection centers to the ground coordinate system. Like any extrapolation, it is sensitive to random and systematic errors, as well as, to improper data handling.

Direct sensor orientation is based on the combination of an Inertial Measurement System (IMU) and GPS. The GPS antenna, the IMU, and the imaging sensor are located in different positions, and the latter two have different orientations. Therefore, the calibration of all sensors and the relation between the sensors is of vital importance for precise ground positioning. The system calibration includes the determination of the boresight misalignment, the interior camera orientation, and the GPS antenna offset. A rigorous mathematical model is required. The inner orientation of the camera used has to be determined under flight conditions to achieve sufficient results. In this paper, the influence of the system calibration to the direct sensor orientation and improper data handling will be shown.

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