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Urban area building extraction is one of the most challenging problems in photogrammetry. Well-extracted buildings are needed for a variety of applications, such as cartography, building GIS databases for cities, and urban planning. This paper presents a new technique to extract 3D building wire-frames using a robust multi-image line-matching algorithm. Although one pair of images is adequate to find the 3D position of two visibly corresponding image features, it is not sufficient to solve the general building extraction problem due to obscured parts in the building. Four images are used in this research to extract the building wire-frames. First the images are segmented into regions. Regions are then classified into roof regions and non-roof regions based on their size, shape, and intensity values. The roof region boundary pixels are located and used to find the region perimeters. Region correspondence is solved in a pair-wise mode over all images using the epipolar constraint, region size, region shape, and region intensity values. Image lines within the corresponding regions are matched over all images simultaneously by first creating a plane for each region line. Planes are then intersected simultaneously and geometric consistency is used to determine acceptance or rejection. Results with high overlap and sidelap aerial images are presented and evaluated. The results show the completeness and accuracy that this method can provide for extracting complex urban buildings. The average coordinate accuracy is about 0·8 m using 1:4000 scale aerial photographs scanned at 30 μ m. Six buildings were examined; the line detection rate is 98%. 相似文献
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The geoid undulation on GRS80 in the Taiwan area at half‐degree grid points has been calculated using the reduced 30’ × 30’ block mean gravity anomalies and the OSU91A geopotential coefficient set up to degree and order 360. The OSU91A results have been used to compare with WGS84, CEM10C, and OSU86F geoid undulations determined in 18 first‐order triangulation stations of the Taiwan Geodetic Datum 1980 (TGD80). Comparisons have also been made between these free‐air anomalies determined from OSU91A, and terrestrial gravity anomalies. It has been found that the average difference between the OSU91A model‐derived, and 243 actual point free‐air anomalies is 16.8 ± 48.0 mgal. It has also been found that more reliable and dense terrestrial gravity data are needed, both for terrestrial observations and for the OSU91A model, to achieve the very high‐precision geoid on GRS80 in the area of study. 相似文献
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Changno Lee James S. Bethel 《ISPRS Journal of Photogrammetry and Remote Sensing》2004,58(5-6):289-300
This paper presents an approach for the restitution of airborne hyperspectral imagery with linear features. The approach consisted of semi-automatic line extraction and mathematical modelling of the linear features. First, the line was approximately determined manually and refined using dynamic programming. The extracted lines could then be used as control data with the ground information of the lines, or as constraints with simple assumption for the ground information of the line. The experimental results are presented numerically in tables of RMS residuals of check points as well as visually in ortho-rectified images. 相似文献
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D. J. Bethel 《The Photogrammetric Record》1990,13(76):493-504
This review of digital image processing refers to the pioneer work of Helava and Hobrough which has influenced the most recent trends in photogrammetry. The author goes on to discuss aspects of digital image acquisition, storage and display, as well as digital photogrammetric procedures and systems. 相似文献
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Coastal wetlands are among the most productive ecosystems globally but have experienced dramatic degradation and loss within the past several decades. Vegetation biomass of coastal wetlands is not only the key component of blue carbon storage but also plays an important role in vertical accretion, important for maintaining these habitats under relative sea-level rise. Remote sensing offers a cost-effective approach to study vegetation biomass at a broad spatial scale. We developed statistical models to predict peak aboveground green biomass of Spartina alterniflora and Juncus roemerianus, two dominant species of salt marshes using WorldView-2 satellite imagery at the Grand Bay National Estuarine Research Reserve (NERR) on the Mississippi coast in the northern Gulf of Mexico. The model accounted for nested data structures in the sampled biomass, assimilated uncertainties from data, parameters and model structures, and helped determine the best vegetation index among a variety of commonly-used indices to predict aboveground green biomass. We developed a series of mixed-effects models, which included different combinations of fixed effect(s), random intercept, and random slope(s). The fixed effects were species and one of the 60 vegetation indices derived from a WorldView-2 image obtained on 6 October 2012. The random effect used was site. We implemented the models in a Bayesian framework and selected the best model structure and vegetation index based on minimum posterior predictive loss and deviance information criterion. The results showed that the best vegetation index to predict peak green biomass was the green chlorophyll index derived from the reflectance values of band 8 (near-infrared) and band 3 (green), and its effect on biomass prediction varied among sites. The inclusion of species as a fixed effect improved the model prediction. The study demonstrated the need to account for spatial dependence of data in developing a robust model, and the importance of the second WorldView-2 near-infrared band (860–1040 nm) in predicting aboveground green biomass for the Grand Bay NERR. The analysis using mixed-effects modeling in Bayesian inference which coherently combined field and WorldView-2 data with uncertainties accounted for provides a robust and nondestructive tool for resource managers to monitor the status of coastal wetlands at a high spatial resolution in a timely manner. Through this study, we hope to emphasize the importance of appropriately accounting for nested data structures using mixed-effects models and promote wider application of Bayesian inference to facilitate assimilation of uncertainties in remote sensing applications. 相似文献
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