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At the research points, the relationship between the Normalized Difference Vegetation and Normalized Green Red Difference indices is characterized by a determination coefficient equal to 0.52. The estimation of the emission of carbon dioxide and nitrogen oxide in the forest air at an altitude of 40 m above the level of the soil cover during the growing season showed differences in their values during the daytime and at night. The results helped determine promising methods of inventory of the carbon landfill forest area for aboveground woody biomass assessment based on data obtained from several sources and land forest estimation research. The research involved: 1) integration of an unmanned aerial vehicle -based digital camera and lidar sensors in order to optimize the efficiency and cost of data collection; 2) taking advantage of high-resolution aerial photographs and sparse lidar point clouds using an information fusion approach and the ability to compensate for their shortcomings. [ABSTRACT FROM AUTHOR]

This study presents a method to generate historical orthomosaics using Structure-from-Motion (SfM) photogrammetry, historical aerial photographs, and lidar data, and then analyzes the horizontal accuracy and factors that can affect the quality of historical orthoimagery products made with these approaches. Two sets of historical aerial photographs (1934 and 1951) were analyzed, focused on the town of Woodstock in Connecticut, U.S.A. Ground control points (GCPs) for georeferencing were obtained by overlaying multiple data sets, including lidar elevation data and derivative hillshades, and recent orthoimagery. Root-Mean-Square Error values of check points (CPs) for 1934 and 1951 orthomosaics without extreme outliers are 0.83 m and 1.37 m, respectively. Results indicate that orthomosaics can be used for standard mapping and geographic information systems (GIS) work according to the ASPRS 1990 accuracy standard. In addition, results emphasize that three main factors can affect the horizontal accuracy of orthomosaics: (1) types of CPs, (2) the number of tied photos, and (3) terrain. [ABSTRACT FROM AUTHOR]

State transportation agencies regularly collect data on pavement surface distresses. These data are used to assess overall pavement conditions and to make maintenance and repair decisions. Routinely-acquired and publically-available high spatial resolution (hsr) multispectral digital aerial photography provides a potential method for collecting distress information that can supplement or replace currently-used technologies. Principal component analysis and linear least squares regression models were used to evaluate the potential of using HSR multispectral digital aerial photographs to estimate pavement surface overall distress conditions. Various models were developed using HSR multispectral digital aerial photographs of different spatial resolution (6-inch, 12-inch, and 24-inch) and reference pavement surface distress data collected manually at multiple sample sites using standard protocols. The results show that the spectral response of HSR multispectral digital aerial photographs correlate strongly with reference distress rates at all tested spatial resolutions, but the 6-inch aerial photos exhibit the strongest correlation (R 2 > 0.95), even when using only half of the sample sites (R 2 > 0.92). These results indicate that straightforward analysis of HSR multispectral digital aerial photographs, routinely acquired by most municipalities and states, can permit assessment of pavement surface distress conditions as well as current manual evaluation protocols. [ABSTRACT FROM AUTHOR]

A new method for the automatic extraction of parking lot structures from an aerial orthophoto is proposed which has two major stages. Line features of a parking lot are first extracted by using a line extraction method with principle orientation constraints which offers a reliable basis for the extraction of parking lots structures by emphasizing on the extraction of accurate parking line information. The structure of the parking lots are then determined from the extracted parking lines through a maximum intersection orientation method, parameter-estimating procedure, and a self-adaptive growth method. A comparative experiment is shown and the result indicates that the proposed method can effectively extract parking lot structures with high correctness, high-quality completeness, and good geometric accuracy. [ABSTRACT FROM AUTHOR]

A large amount of aerial photographs were acquired early 1900s for various purposes. These aerial photographs provide valuable baseline data for a variety of environmental studies. To be used for analysis together with other data, these photographs need to be referenced to a ground coordinate system. Often large topographical variations in photo ground coverage demand these photographs be orthorectified using photogrammetric methods for acceptable mapping accuracy. However, camera models for these historical photographs are usually unavailable. Additionally, land-cover change over the years makes it a great challenge to collect accurate control points for calculating camera models. This study investigated the rational function model to orthorectify historical aerial photographs. The analysis results suggest that while the linear, the 2nd order, and the 3rd order RFMs are all able to closely approximate the rigorous frame camera model, the linear RFM is optimal in representing imaging geometries of historical photographs. [ABSTRACT FROM AUTHOR]

Relating less directly to the physical reflectance from remote sensors, land-use analysis is comparably more challenging than land-cover studies, especially for residential land-uses. This research presents an object-oriented approach to detect residential land use of buildings directly from lidar data, aerial photography, and road maps to enhance urban land- use analysis. Specifically, the proposed methodology applies a multi-directional ground filter to generate a bare ground surface from lidar data, then uses a morphology-based building detection algorithm to identify buildings from lidar and aerial photographs, and finally separates residential buildings using a supervised C4.5 decision tree analysis based on seven land-use characteristics of buildings. Experiments based on the 8.25 km2 study site located in Austin, Texas proved the possibility and efficiency of directly detecting and identifying residential buildings from remote sensing images with 81.1 percent of residential buildings correctly classified. [ABSTRACT FROM AUTHOR]

This paper presents a novel linear registration algorithm for lidar point clouds and aerial images without orientation parameters. First, preprocessing is conducted to classify the lidar point clouds into ground points, building points, and aboveground, non-building points. After preprocessing, the algorithm consists of two sequential steps, i.e., Tilt Displacement Correction and Height Displacement Correction. As the kernel of the proposed registration algorithm, the mathematical model for Height Displacement Correction is a set of linear formulas analytically deduced from the rigorous geometric function of a single image. The proposed registration algorithm does not require any orientation parameters for the image, which greatly lowers the requirements for image acquisition. Due to the model's linearity, the proposed algorithm is computationally efficient. Our experimental results demonstrate that the proposed algorithm can register aerial images without orientation parameters at the same accuracy level of space resection based on collinear equations. This result fulfills the requirement for the fusion of lidar range data and aerial images in most large-scale urban modeling applications. [ABSTRACT FROM AUTHOR]

Although traditional and web map producers strive to deliver up-to-date products and old aerial photographs do not fit in their concept, other users are rather interested in old aerial images and in temporal series. In Portugal, aerial surveys for mapping purposes started by the late thirties of the twentieth century as documented by the oldest existing aerial photos collection in the archives of the IGEQE in Lisbon. Being the oldest visual witnesses of the country, the relevance of the information they contain is unquestionable. The objective of this project is the recovery of an important national aerial photographic heritage hibernating in analogue format in the archives. In a test block, strategies to recover radiometry and spatial orientation were developed and successfully tested in order to make the photos accessible and workable by the modern scientific community and by the general public. A photo-geographic database has also been organized and made available. [ABSTRACT FROM AUTHOR]

Information about tree species-specific forest characteristics is often a compulsory requirement of the forest inventory system. In Finland, the use of a combination of ALS data and orthorectified aerial photographs has been studied previously, but there are some weaknesses in this approach. First, aerial photographs need radiometric correction, and second, the ALS points and aerial photographs are not properly fused due to the radial displacement. In this study, ALS points are linked to unrectified aerial photographs of known orientation parameters, which enables better fusion. Each ALS point is mapped to several aerial photographs, and the average of DN values is utilized; this averaging is considered to be a good substitute for radiometric correction. The new two-stage method is compared to the approach in which only ALS data is used. The results show the benefits of using aerial photographs together with ALS data in order to estimate tree species-specific characteristics. Compared to earlier studies, the new two-stage method shows a considerable improvement in applicability in operational use. [ABSTRACT FROM AUTHOR]

The 2001 National Land Cover Database (NLCD) tree and impervious cover maps provide an opportunity to extract basic land-cover information helpful for natural resource assessments. To determine the potential utility and limitations of the 2001 NLCD data, this exploratory study compared 2001 NLCD-derived values of overall percent tree and impervious cover within geopolitical boundaries with aerial photo interpretation-derived values for the same areas. Results of the comparison reveal that NLCD underestimates tree cover and to a lesser extent, underestimates impervious cover. The underestimate appears to be consistent across the conterminous United States with no statistical differences among regions. However, there were statistical differences in the degree of underestimation of tree cover among mapping zones and of impervious cover by population density class. [ABSTRACT FROM AUTHOR]

A region-based level set segmentation was developed for the automatic detection of man-made objects from aerial and satellite images. The essence of the approach is to optimize the position and the geometric form of an evolving curve, by measuring information within the regions that compose a particular image partition based on their statistical description. The present region-based variational model is fully automated without the need to manually specify the position of the initial contour. Furthermore, it converges after a small number of iterations, allowing real-time applications. The developed algorithm was tested for the detection of roads, buildings and other man-made objects in a number of aerial and satellite images. The effectiveness of the algorithm is demonstrated by the experimental results and the performed qualitative and quantitative evaluation. [ABSTRACT FROM AUTHOR]

The aerial images acquired by Intergraph's Digital Mapping Camera (DMc) have been normally used for generating photogrammetric products such as Digital Terrain Models (DTM) and orthophotos. Our experience shows that the failure of radiometric correction in postprocessing leads to residual radiometric differences between CCD images, which then affect the quality of the images for further applications. This paper presents a robust approach to repair defects due to the residual radiometric differences. The approach comprises the autolocating for the transition area and seamline, and the subsequent reconstruction for image in radiometry. A hierarchical strategy for auto-locating is employed to reinforce the robustness, and a multi-scale strategy is adopted to optimize the adjustment in order to reduce the effect of the change of features in image during the subsequent reconstruction in radiometry. Experiments are designed for the validation of the proposed algorithm, in which both qualitative and quantitative analyses are applied to evaluate the performance of the algorithm. The algorithm has been embedded into GeoDodging 4.0 software package (Wuda Geoinformatics Co., Ltd., China), which is specialized in image dodging and mosaicking, as a complementary module for the postprocessing of DMC images. [ABSTRACT FROM AUTHOR]

Atmospheric haze variations, temporal differences, atmosphere's or ground surfaces' and Bidirectional Reflectance Distribution Function (BRDF), are well-known sources of radiometric heterogeneities in aerial images. It is necessary to correct them for many applications, such as the generation of large seamless mosaics of orthoimages, or land-cover classifications. This contribution describes a method for equalizing digital aerial images based on a parametric, semiempirical radiometric model. The model's parameters are computed through a global least-squares minimization process, using radiometric tie-points in overlapping areas between images. The method may be called a "radiometric aerial triangulation" since its principle is quite similar to a standard aerial triangulation. It leads to a relative equalization between images, keeping their original contrast and color information. The method has been successfully applied operationally to more than forty projects comprising three to four thousands digital images each, for the creation of orthoimages over France. The results are good as long as atmospheric conditions are favorable and stable. [ABSTRACT FROM AUTHOR]

Phase V of the ASPRS Ten-Year Remote Sensing Industry Forecast is an extension of the previous four phases with respect to topical foci on industry workforce needs, economic conditions, evolving technology, and governmental policy. In addition, Phase V explicitly opened up to the international remote sensing community. An internet survey was the primary tool for sampling from the combined membership rosters of the ASPRS and the ISPRS. The sample used for the analysis consisted of 512 responses from 58 nations. The majority of the respondents reside in North America and Europe having advanced degrees in remote sensing, geography, GIS and photogrammetry. Many of the respondents work outside of their resident nations, most in East Asia and South America. Undergraduate and master's degrees are the most desired for new employees. The knowledge and technical areas most desired for new employees were application GIS tools, spatial database understanding, cartography/visualization, verbal and communication skills, and photogrammetry. In relationship to Phase IV, Phase V results still show a strong percentage unsure of the future; however, the out years no longer highlight an expectation of a spending decline. When the responses are segmented by region, responses from most regions of the world indicate modest expenditures for the 2010 year. Previous Forecast reports highlight that demand for the highest levels of resolution was clearly not met; data users wanted higher resolution content. Phase V shows, that this trend continues in the global market. Digital aerial sensors, as well as the continued operation of high-resolution satellite systems have expanded the global demand for better than half meter data. Provision of data lower in spatial resolution than half meter is now an area of potential overcapacity. Lidar, hyperspectral and IFSAR were identified as the three data sources that need exceeded current use. Data fusion appears to be considered more in these results than reliance on a single sensor or data source. Satellite sources of data versus aerial sources are used more in developing regions of the world. Landsat 7 was the most utilized by respondents (74%), followed by Landsat 5 (66%), GeoEye-Ikonos and Digital Globe-Quickbird (both at 62%) and MODIS and SPOT 5 with about 44% of the respondents citing usage. Restrictions on remote sensing data were viewed as a hindrance in every region of the world. However, the survey indicated that respondents from East and South Asia, Africa and Oceania felt that effects of restrictions on data, licensing and governmental controls most limiting on their activities. The most significant issues that continue to represent large challenges and opportunities with the industry are: the demand versus cost in an uncertain economy for high spatial resolution and new senspr data, both aerial and satellite, meeting the increase in demand for a higher levels of education in GIS and newer imaging technologies and the conflicting roles of national governments in developing remote sensing platforms and products while limiting access and use of data. [ABSTRACT FROM AUTHOR]

In this paper, an unsupervised change-detection approach was proposed to detect new urban areas from multi-temporal SAR images. The novelty of the proposed approach is the joint use of coherence and intensity characteristics of SAR imagery. The approach in valves two main steps: (a) the extraction of difference feature containing information on changed areas, and (b) the unsupervised two-dimensional (2D) thresh aiding. First, two difference features based on the concepts of long-term coherence and backscattering temporal variability are extracted from a series of multi-temporal SAR images. Then, the resulting features that represent the INSAR signal temporal variability of changed areas are merged, and a 2D thresholding technique based on the maximum 2D Renyi's entropy criterion is developed to obtain the change-detection results. The effectiveness of the proposed approach is confirmed with experimental results obtained from a set of six ERS-1/2 SLC SAR images acquired in Shanghai, China. [ABSTRACT FROM AUTHOR]

Both satellite images and aerial photographs are now used operationally in Finland's forestry for different tasks; satellite images are used for national forest inventory purposes and aerial images for forest management planning. Due to the double coverage, it could be advantageous to utilize the strengths of both image types. The aim of this study was to evaluate the potential of the combination of Landsat ETM+ spectral and aerial photograph spectral and textural features for forest variable estimation. The studied stand variables were mean height, basal area per hectare, and the volume of the growing stock. Several approaches were tested when combining the image data sources: feature selection, feature weighting, satellite image-based stratification, and combination of individual estimates by weighting. The highest accuracies were obtained when both data sources were used. There were several good ways to combine the data sources. Feature selection with genetic algorithm and subsequent feature weighting gave the lowest mean volume RMSE (63.7 m³/ha, 65.3 percent of the mean). [ABSTRACT FROM AUTHOR]

A 20-channel, dual-frequency GPS receiver collecting pseudorange and carrier phase observations was used as a stand-alone receiver to determine positional accuracy of 19 points under conifer tree canopies. The positions were determined utilizing precise satellite orbit and clock products from the International GNSS Service. The mean positional accuracy ranged from 0.27 to 0.88 m for an observation period of 120 minutes, and 0.95 to 3.48 m for 15 minutes. For the 15 minute observation period computed positions could not be found for 8 to 44 percent of the locations. Accuracy increased with decreasing forest stand density. Stand basal area (R² = 0.11, p < 0.001) and number of tree stems (R2 = 0.07, p < 0.001) were significantly correlated with accuracy. The probability of determining a position increased with longer observation periods and decreasing number of tree stems. For natural resource applications where the costs associated with the length of the observation period on each site in field is a critical factor, differential GPS seems to be a more robust alternative than precise point positioning with GPS. [ABSTRACT FROM AUTHOR]

It is very important to acquire timely information on the spatial distribution of locust populations in order to bring a locust outbreak under control quickly. In this study, we propose a new method for estimating the Oriental migratory locust density using a Locust Density Index (LDI). This index is based on the change in vegetation before an outbreak and shortly after the outbreak, taking into account the pre-outbreak vegetation conditions as well. This method was applied to study three locust-infested sites in Huanghua City, Hebei Province in China during a 2002 outbreak. NDVI images were derived from radiometrically corrected multi-temporal Landsat TM/ETM+ data recorded during and after the outbreak. After radiometry of the post-outbreak NDVI image was standardized to that of its during-outbreak counterpart, their difference multiplied by the pre-outbreak NDVI (termed LDI) was used to map the density of locusts at five levels of no locust, low, moderate, high, and very high. Nearly 90 percent of the study sites had a low to moderate locust density. Results produced with the proposed ml method are similar to those observed on the ground with an accuracy of 88.9 percent. This proposed LDI method is easy to implement. It allows quick and accurate mapping of locust density from satellite data. [ABSTRACT FROM AUTHOR]

Due to the existence of shadows, especially in urban environments, it is difficult to extract semantic information from aerial and high-resolution satellite images. In this paper, an efficient method of correcting shadow effects using multisource data sets in aerial color images is proposed. The proposed method has three steps. First, it accurately detects the shadowed regions using the image geometry and the solar position of the image acquisition data. Then, the detected shadowed regions are segmented according to land surface type. Finally, the shadow effects of the segmented regions are corrected by directly comparing the same nonshadow features with the segmented shadows. In the application part of this paper, the proposed techniques were applied in the extraction of an asphalt road from an image. [ABSTRACT FROM AUTHOR]

Comprehensive field-testing and calibration of digital photogrammetric systems are essential to characterize their performance, to improve them, and to be able to use them for optimal results. The radiometric, spectral, spatial, and geometric properties of digital systems require calibration and testing. The Finnish Geodetic Institute has maintained a permanent test field for geometric, radiometric, and spatial resolution calibration and testing of high-resolution airborne and satellite imaging systems in Sjökulla since 1994. The special features of this test field are permanent resolution and reflectance targets made of gravel. The Sjökulla test field with some supplementary targets is a prototype for a future photogrammetric field calibration site. This article describes the Sjökulla test field and its construction and spectral properties. It goes on to discuss targets and methods for system testing and calibration, and highlights the calibration and testing of digital photogrammetric systems. [ABSTRACT FROM AUTHOR]

World War I formed the incubator for aerial reconnaissance and photointerpretation. This study, based upon official histories and archival materials, including correspondence, reports, unit histories, and related documents, surveys the development of photoreconnaissance as practiced by the American Expeditionary Forces (AEF) during the period 1917 to 1919. The most visible advances were technologic improvisations, developed in the field that integrated the camera and the airplane to form, arguably, the most effective intelligence resource of the conflict. Technological inn ovations were accompanied by parallel developments in organizational and training infrastructures necessary to derive information for images acquired by these instruments. Interpretation techniques developed from simple annotations of oblique photographs acquired using handheld cameras to sophisticated analyses of images acquired by automatic cameras suspended in the aircraft fuselage. As the war concluded, efforts were underway to develop foundations for photogrammetric methods to derive accurate planimetry, which later formed foundations for civil applications of aerial photography. [ABSTRACT FROM AUTHOR]

This paper proposes an automatic and fast algorithm for registering aerial image sequences to vector map data using linear features as control information. Our method is based on the extraction of linear features using active contour models (also known as, snakes), followed by the construction of a polygonal template upon which a matching process is applied. To accommodate more robust matching, this work presents both exact and inexact matching schemes for linear features. Additionally, in order to overcome the influence of the snakes-based extraction process on the matching results, a matching refinement process is suggested. Using the information derived from the matching process, we then determine the transformation parameters between overlapping images and generate a mosaic image sequence, which can then be registered to a map. The performance of the proposed scheme was tested on sequences of aerial imagery of 1 m resolution that were subjected to shifts and rotations using both the exact and inexact matching scheme, and was shown to produce angular accuracy of less than 0.7 degrees and positional accuracy of less than two pixels. [ABSTRACT FROM AUTHOR]

Automatic road centerline extraction from high-resolution satellite imagery has gained considerable interest recently due to the increasing availability of commercial high-resolution satellite images. In this paper, a hierarchical grouping strategy is proposed to automatically extract main road centerlines from high-resolution satellite imagery. Here hierarchical grouping means that, instead of grouping all segments at once, the selective segments are grouped gradually, and multiple clues are closely integrated into the procedure. By this means, the computational cost can be reduced significantly. Through the stepwise grouping, the detected fragmented line segments eventually form the long main road lines. The proposed method has been tested and validated using several Ikonos and QuickBird images both in open areas and build-up urban environments. The results demonstrate its robustness and viability on extracting salient main road centerlines. [ABSTRACT FROM AUTHOR]

Digital Elevation Models (DEMs) are traditionally acquired from a stereo pair of aerial photographs sequentially captured by an airborne metric camera. Standard DEM extraction techniques can be naturally extended to satellite imagery, but the particular characteristics of satellite imaging can cause difficulties. The spacecraft ephemeris with respect to the ground site during image collects is the most important factor in the elevation extraction process. When the angle of separation between the stereo images is small, the extraction process typically produces measurements with low accuracy, while a large angle of separation can cause an excessive number of erroneous points in the DEM from occlusion of ground areas. The use of three or more images registered to the same ground area can potentially reduce these problems and improve the accuracy of the extracted DEM. The pointing capability of some sensors, such as the Multispectral Thermal Imager (MTI), allows for multiple collects of the same area from different perspectives. This functionality of MTI makes it a good candidate for the implementation of a DEM extraction algorithm using multiple images for improved accuracy. Evaluation of this capability and development of algorithms to geometrically model the MTI sensor and extract DEMs from multi-look MTI imagery are described in this paper. An RMS elevation error of 6.3-meters is achieved using 11 ground test points, while the MTI band has a 5-meter ground sample distance. [ABSTRACT FROM AUTHOR]

This research investigates the relationship between socioeconomic status and remotely sensed vegetation intensity in residential land in the Denver, Colorado metropolitan area. Land-cover data derived from aerial photography and normalized difference vegetation index data (NDVI) derived from Landsat ETM+ imagery were integrated with U.S. Bureau of the Census tract-level data and analyzed using choropleth mapping and multivariate statistics. Association rule mining, a data mining technique, is used to explore nonlinear relationships among variables. Results indicate that higher vegetation intensity is associated with socioeconomic advantage in both sparsely populated, large lot suburban developments, as well as in older, urban neighborhoods. This pattern likely reflects residents' ability to pay for the cost of maintaining high vegetation intensity, suburban lawn ecosystem vegetation in a semi-arid grassland environment. Additionally, residential choices may be limited by a home price structure that is closely related to the concentration of vegetation in the residential landscaping. [ABSTRACT FROM AUTHOR]

In this study, a variogram-based texture analysis was tested for classifying detailed urban land-use classes, such as mobile home, single-family house, multi-family house, industrial, and commercial from a digital color infrared aerial photograph. Spectral classification was first carried out to separate the building class from non-building classes. Then, a building-presence binary image was generated so that building pixels were assigned a value of ‘1’ and non-building pixels were assigned a value of ‘0.’ Multiple texture bands were further generated employing a variogram-based texture analysis and used for land-use classification. The generation of the building presence binary image allowed us not only to fully explore the capability of variogram-based analysis on spatial pattern detection, but also to prevent the variogram-based analysis from being disturbed by the natural fluctuation of spectral signals. The result from using a mosaic test image was considered satisfactory with a kappa coefficient of 0.72. [ABSTRACT FROM AUTHOR]

Eelgrass (Zostera marina) can provide vital ecological functions in stabilizing sediments, influencing current dynamics, and contributing significant amounts of biomass to numerous food webs in coastal ecosystems. Mapping eelgrass beds is important for coastal water and nearshore estuarine monitoring, management, and planning. This study demonstrated the possible use of high spatial (approximately 5 m) and temporal (maximum low tide) resolution airborne multispectral scanner on mapping eelgrass beds in Northern Puget Sound, Washington. A combination of supervised and unsupervised classification approaches were performed on the multispectral scanner imagery. A normalized difference vegetation index (NDVI) derived from the red and near-infrared bands and ancillary spatial information, were used to extract and mask eelgrass beds and other submerged aquatic vegetation (SAV) in the study area. We evaluated the resulting thematic map (geocoded, classified image) against a conventional aerial photograph interpretation using 260 point locations randomly stratified over five defined classes from the thematic map. We achieved an overall accuracy of 92 percent with 0.92 Kappa Coefficient in the study area. This study demonstrates that the airborne multispectral scanner can be useful for mapping eelgrass beds in a local or regional scale, especially in regions for which optical remote sensing from space is constrained by climatic and tidal conditions. [ABSTRACT FROM AUTHOR]

In this paper, we compare the geometrical performance between the rigorous sensor model (RSM) and rational function model (RFM) in the sensor modeling of FORMOSAT-2 satellite images. For the RSM, we provide a least squares collocation procedures to determine the precise orbits. As for the RFM, we analyze the model errors when a large amount of quasi-control points, which are derived from the satellite ephemeris and attitude data, are employed. The model errors with respect to the length of the image strip are also demonstrated. Experimental results show that the RFM is well behaved, indicating that its positioning errors is similar to that of the RSM. [ABSTRACT FROM AUTHOR]

The main topic of this paper is high-resolution image fusion. The techniques used to merge high spatial resolution panchromatic images with high spectral resolution multispectral images are described. The most commonly used image fusion methods that work on the principle of component substitution (intensity-hue-saturation method (IHS), Brovey transform (BT), and multiplicative method (MULTI)) have been applied to Ikonos, QuickBird, Landsat, and aerial orthophoto images. Visual comparison, histogram analyses, correlation coefficients, and difference images were used in order to analyze the spectral and spatial qualities of the fused images. It was discovered that for preserving spectral characteristics, one needs a high level of similarity between the panchromatic image and the respective multispectral intensity. In order to achieve this, spectral sensitivity of multispectral and panchromatic data was performed, and digital values in individual bands have been modified before fusion. It has also been determined that spatial resolution is best preserved in the event of an unchanged input panchromatic image. [ABSTRACT FROM AUTHOR]

Mapping of the Earth's surface from satellite images is a continuing application in remote sensing, which has been distinctly pushed with the increasing availability of very high-resolution image data. In most of the missions, stereo images can be acquired making 3D mapping from space very attractive, as high accuracy and level of detail become feasible from such data. In this paper, several case studies are presented, which have been applied to stereo pairs acquired by the SPOT sensors as well as the very high-resolution Ikonos sensor. As an extension to standard stereo mapping, a 3D mapping approach which makes use of multiple image coverage is presented. For this work, image triplets including multi-sensor data sets have been used to extract 3D topography information and to generate digital surface models. The benefit of this extended approach is comparatively assessed with respect to results achieved from standard stereo mapping. [ABSTRACT FROM AUTHOR]

This paper proposed a new algorithm for extracting building lines from monoscopic high-resolution satellite images. We focus on extracting line from rectangular-shaped building roofs with a relatively large size. We achieve this task by devising a unique approach using line voting and matching. Our algorithm works as follows. An input point on a building roof is given manually. A region of interest is defined centred on the input point and within the region lines extracted. Then, a line voting process is applied to estimate initial orientation and position of a building line. The orientation and position are refined by a least squares matching process. We assessed the performance of our algorithm against two Ikonos images. Our algorithm extracted building lines from over 83 percent of buildings tested with average angular accuracy of one or two degrees and average positional accuracy of approximately one pixel. This result supports the algorithm proposed in this paper. The major contribution of this paper is that we provided an alternative way to line grouping approaches when edge responses from building are not strong enough. [ABSTRACT FROM AUTHOR]

In this paper, we describe an "Adoptive Patch Projection" scheme that can accelerate the orthorectification for satellite images without losing accuracy. The proposed scheme is comprised of two major components: (a) orbit modeling, and (b) image orthorectification. In orbit modeling, we provide a collocation procedure to determine the precise orbits. In image orthorectification, the area of interest is sequentially subdivided into four quadrate tiles until a specified threshold for terrain variations is met. The thresh old of maximum terrain variation in a tile will be optimized according to the computational efficiency and the accuracy requirements. Once the ground tiles are determined, we perform adaptive patch projection to the corresponding image pixels. Test images from SPOT5 Supermode and QuickBird satellites are included. The experimental results show that this algorithm can minimize the orthorectification computation time, while the modeling error is insignificant. [ABSTRACT FROM AUTHOR]

A fuzzy methodology is presented for evaluating the reliability of satellite imagery-derived, continent-wide (Australia) land-cover deforestation/regrowth maps covering the period of 1972 to 2000 in ten discrete time periods. The methodology uses aerial photographs as its reference data and accommodates the difficulty inherent in determining definitively from an aerial photograph, whether a sample point is Forest or Non-forest by permitting interpreters to identify their level of certainty, i.e., Definitely Forest, Probably Forest, Uncertain, Probably Non-forest, or Definitely Non- forest. This information is then cross-tabulated against the Forest/Non-forest classification for the classified image closest in date to the photo date. Information from several photographs is summarized over a larger geographic area and over all time periods. Subsequently, temporal lineage information for each sample pixel is extracted from the 1972 to 2000 series of classified images to determine if a pixel's lineage is Forest Throughout, Non-forest Throughout, Deforestation, Regrowth, or Cyclic. The fuzzy evaluation for individual pixels is then tabulated against this lineage information to identify if pixels of any particular lineage have an elevated tendency to be misclassified. The methodology provides a means by which problems in the map production methodology can be improved as future time slices are added. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Responding to an increasing interest in studying vegetation changes over time, we review current methods of processing black and white digital aerial photographs in order to classify tree cover in pinyon-juniper woodlands. Besides applying com- monly used clustering and supervised maximum-likelihood methods, we have developed a new classifier, nearest edge thresholding, which is unsupervised and based on the principals of edge detection and density slicing. Comparison of the three methods' abilities to predict field values at plot scales of 100 m2 to 900 m2 shows this new method is better or comparable to others at all scales, can be easily applied to digital imagery, and has high correspondence with ground-truthed field values of tree cover. [ABSTRACT FROM AUTHOR]

Radiometric effects hamper the use of airborne remote sensing data for quantitative studies of biophysical environments. The effect of bidirectional reflectance is evaluated in four aerial samples from three lakes in the Vuoksi drainage basin in Finland. It is shown statistically that the relationship between measured upwelling radiation and the sun-target-sensor geometry is weak for an aquatic macrophyte species, the common reed (Phragmites australis), but strong for birch (Betula pubescens) and mixed birch-spruce (Picea abies) forest. The density and phenotype of the common reed vegetation seem to have an effect on the strength of the bidirectional reflectance in the images. When the effect of bidirectional reflectance over common reed vegetation is statistically significant, an empirical normalization method can be used, after which the brightness of the test areas is no longer statistically dependent on the sun-target-sensor geometry. [ABSTRACT FROM AUTHOR]

The cost of forest sampling can be reduced substantially by the ability to estimate forest and tree parameters directly from aerial photographs. However, in order to do so it is necessary to be able to accurately identify individual treetops and then to define the region in the vicinity of the treetop that encompasses the crown extent. These two steps commonly have been treated independently. In this paper, we derive individual tree-crown boundaries and treetop locations under a unified framework. We applied a two-stage approach with edge detection followed by marker-controlled watershed segmentation. A Laplacian of Gaussian edge detection method at the smallest effective scale was employed to mask out the background. An eight-connectivity scheme was used to label the remaining tree objects in the edge map. Subsequently, treetops are modeled based on both radiometry and geometry. More specifically, treetops are assumed to be represented by local radiation maxima and also to be located near the center of the tree-crown. As a result, a marker image was created from the derived treetop to guide a watershed segmentation to further differentiate touching and clumping trees and to produce a segmented image comprised of individual tree crowns. Our methods were developed on a 256- by 256-pixel CASI image of a commercially thinned trial forest. A promising agreement between our automatic methods and manual delineation results was achieved in counting the number of trees as well as in delineating tree crowns. [ABSTRACT FROM AUTHOR]

Building extraction based on pre-established models has been recognized as a promising idea for acquiring 3D data for buildings from aerial images. This paper proposes a novel building extraction method developed from the concept of fitting CSG (Constructive Solid Geometry) primitives to aerial images. To be practicable, this method adopts a semiautomatic procedure, carrying out high-level tasks (building detection, model selection, and at attribution) interactively by the operator and performing optimal model-image fitting automatically with a least-squares fitting algorithm. Buildings, represented by CSG models, can be reconstructed part by part after fitting each parameterized CSG primitive to the edge pixels of aerial images. Reconstructed building parts can then be combined using CSG Boolean set operators. Consequently, a building is represented by a CSG tree in which each node links two branches of combined parts. This paper demonstrates ten examples of building extraction from aerial photos taken at a scale of 1:5,000 and scanned at a pixel size of 25 μm. All of the tests were performed in the prototypal system implemented in a CAD-based environment cooperated with a number of specially designed programs. The process time for each primitive is about 20 seconds and the successful rate of model-image fitting was about 90 percent. Evaluated with some check points, the fitting accuracy was about 0.3 m horizontally and i m vertically. The test results are encouraging and promote the theory of model-based building extraction. [ABSTRACT FROM AUTHOR]

A complexity reduction in monocular building extraction from aerial imagery may be achieved by decomposing the extraction problem into three sequential steps. This paper focuses on the first of these steps, the selection process, during which an image subset likely to contain u single building is extracted. One of the means to realize this is by pose clustering. Based on vote accumulation, pose clustering can offer some advantages, such as reduced complexity and a false alarm rate prediction capability. This paper describes a voting scheme for right-angle flat-roof buildings, from which image space building location hypotheses (ISBLHs) may be efficiently generated for regularized urban areas. The proposed scheme incorporates weights, constraints, and uncertainties that should be implemented due to the nature of aerial imagery. Additionally, based on an occupancy model, a random vote accumulation and threshold analysis of the proposed voting scheme is presented. This scheme was tested on both simulated and real imagery, and the obtained results are discussed and analyzed. [ABSTRACT FROM AUTHOR]

An unmixing method was used to estimate the area of alder trees from multitemporal Thematic Mapper (TM) imagery.of the Kushiro mire, an important wetland area in Japan. Because the spectral radiance (endmember) of alder coverage within a pixel must be precisely known before the unmixing method is applied, we first collected ground truth data for the canopy area of alder using field survey methods, and aerial photographs. The alder endmember was calculated by linking TM imagery and the ground truth data. Alder coverage was estimated more precisely than it was with classification by the maximum-likelihood method. Furthermore, the alder area could be evaluated within a pixel, which cannot be classified as alder by the maximumlikelihood method. [ABSTRACT FROM AUTHOR]

Demonstrates that digitally scanned 1:40,000-scale aerial photographs by the National Aerial Photography Program (NAPP) can be used to generate digital elevation models (DEM) with horizontal resolutions of up to three meters. Evaluation of vertical accuracies of the DEM using check points from a precision kinetic global positioning system survey; Application of aerial DEM in urban setting.

Presents air photointerpretation and satellite imagery analysis techniques for mapping cattail coverage for Water Conservation Area 2A, an impounded portion of the Northern Everglades. Description of the remnant Everglades ecosystem; Trends in cattail distribution between 1991 and 1995.

Discusses a collaborative effort to create a complete geographic information system vegetation database of the southern Everglades in Florida using color-infrared aerial photographs and a single vegetation classification system. Characteristics of the Everglades study area; Previous maps of the Everglades; Applications of the database for Everglades research and restoration.

The article reports on the move of the U.S. Geological Survey (USGS) to release a series of aerial photographs showing before-and-after images of Hurricane Sandy's impacts on the Atlantic Coast. The photographs, part of a USGS assessment of coastal change from as far south as the Outer Banks of North Carolina to as far north as Massachusetts, demonstrate that the storm caused changes to portions of shoreline extending hundreds of miles.

The article discusses the possibility of establishing a digital city model using a single satellite image while obtaining accurate results and without bearing too much costs. With one Quick Bird satellite image, technicians of RMSI, a company located in India, discovered the possibilities of creating the project without complexities. The company chose an area in Abu Dhabi, UAE, for its organized layout, with high-rise buildings that are spaced to provide for a clear view. Semi-automated methods of feature extraction were performed but this method is not suitable for areas that have the highest density of high-rise buildings. It can be concluded that although accuracy and requirements for the building layout in the target area are limited, this method can be used as a quicker and simpler option to established methods.

Reports on the use of DigitalGlobe's high-resolution Quickbird satellite imagery to aid in relief efforts in Indonesia, following the destructive tsunami in the Indian Ocean region on December 26, 2004. Use of the imagery to help establish refugee camps and provide medical reachback; Provision of images as poster-size prints flown to Indonesia and hand-carried to Banda Aceh.

The article reports that NASA has chosen Littleton, Colorado-based Lockheed Martin Commercial Launch Services for the launching of the Landsat Data Continuity Mission (LDCM). This mission will continue multispectral satellite imagery work started in 1972 with Landsat 1 and will continue Landsat 7's work. LDCM, which is scheduled to be launched in July 2011, will detect and characterize changes on the Earth's land surface at a scale where natural and man-made changes can be distinguished. The launch contract is valued at $124 million.

The article reports on DigitalGlobe, which announced its collection of high resolution satellite imagery depicting newsworthy events and locations from around the world. It is now available on editorial customers through Getty Images. DigitalGlobe improves its services to the media with timely and affordable priced imagery, easy, immediate access, and a centralized online location. Additional distribution of this content is also offered via a DigitalGlobe web site, built and maintained by Getty Images Inc.