Evaluating the potential of the forthcoming commercial US high-resolution satellite sensor imagery a (original) (raw)
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1997
As the National Mapping Agency of Great Britain, the Ordnance Survey" ( 0 s ) is driven by a need to reduce costs and commercialize operations, and as such has been investigating photogrammetric methods to improve existing products, streamline existing production, and increase the current portfolio of products. Over the last 18 months, the 0s has been involved in a major research project to tackle these issues through an evaluation of the forthcoming commercial U.S. high spatial resolution satellite sensors which are offering 1-m panchromatic and 4-m multispectral spatial resolutions. Work has focused on improving the existing National Height Dataset (NHD), reducing the cost of photogrammetric survey, automatic topographic feature change detection, production of DM; three-dimensional (30) urban models, and land-use classification. Results from the project using simulated imagery indicate that it would have potential within the 0s in all areas evaluated. The work now needs to be followed up when real high spatial resolution satellite imagery becomes commercially available.
2013
New aerial cameras and new advanced geo- processing tools improve the generation of urban land cover maps. Elevations can be derived from stereo pairs with high density, positional accuracy, and efficiency. The combination of multispectral high-resolution imagery and high-density elevations enable a unique method for the automatic generation of urban land cover maps. In the present paper, imagery of a new medium-format aerial camera and advanced geoprocessing software are applied to derive normalized digital surface models and vegetation maps. These two intermediate products then become input to a tree structured classifier, which automatically derives land cover maps in 2D or 3D. We investigate the thematic accuracy of the produced land cover map by a class-wise stratified design and provide a method for deriving necessary sample sizes. Corresponding survey adjusted accuracy measures and their associated confidence intervals are used to adequately reflect uncertainty in the assessm...
Inventorying urban areas with Very High Resolution Satellite Images
2002
Prior to the commercial availability of Very High Resolution (VHR) satellite imagery, the applicability of Earth Observation data in the urban planning sector was very limited. The spatial resolution of the imagery, supplied by platforms like Landsat TM and SPOT HRV, was too coarse to be of real practical use to urban planners and their applications. Satellite images of urban or sub-urban areas are characterized by large radiometric variations due to the small size and the diversity of the objects. This in turn causes a radiometric contamination between neighbouring pixels which renders object recognition nearly impossible. Satellite images with a higher resolution might alleviate this problem. The dawn of the VHR era was thus anticipated with great aspiration by urban remote sensing researchers.
Metropolitan Cartography, Remote Sensing and Geographic Information Systems
Landscape Series, 2021
data sources are represented by vector and raster maps, produced using land or aerial surveys, having different covering and detailing levels, depending on the location. To draw and thematize maps for a specific purpose (e.g. Campi et al., 2017), zenithal images, when available, can be processed through aerial photographic and satellite image interpretation techniques. The main element determining the potential use of ASIs is the spatial resolution (SR), that is the size of a pixel on the ground, which defines the dimension of the smallest detail that can be obtained and recorded on a map. SR is essentially a function of the sensor distance from the ground. In addition to this, there are three other resolutions that are significant for the ASIs possible use: spectral (the capability of capturing images in different wavelengths bands, from the most common RGB images to 'invisible' ones, such as infrared, to detect different surfaces), temporal (i.e. the revisiting time of the same area) and radiometric (which reveals distinct shades of the same 'color' to better detect objects). This means that images can be used in many ways for metropolitan studies about GGBIs and the most interesting ones are identified as follows. Satellite images. They're related to Earth surface description in thematic mapping at large scale, e.g. to identify land use and/or coverage (LU/LC) classes, or to study natural or anthropic trends evolution through change detection (multitemporal analysis using archive data about urban growth, desertification, deforestation, floods, fires, ecological studies, water quality assessment, and so on). In agriculture: crop extension mapping, monitoring in different phenological phases, yield prediction, physical parameters of soils, water bodies, vegetation (f.i. biomass or Leaf Area Index maps). Aerial images. These images are used worldwide to produce and update technical cartography, in a wide scale range (from 1:500 to 1:100,000), and topographical databases (DBT). Plus, photogrammetric techniques of stereoscopic images are used to create 3D surface and terrain models and aerial orthomosaics. With digital multispectral cameras, it is now possible to obtain high resolution thematic maps. Drone images. Digital images (DIs) acquired by a drone (Unmanned Aerial Vehicle-UAV) can have centimetric resolutions and are used for detailed surveys on archaeological excavations, structural surveys, precision agriculture, critical events, emergency management, dangerous/remote areas, 3D building modelling, and many others. On a large scale, ASIs provide reliable and updated geospatial information on large areas, with high geometric, spectral and temporal resolutions (GSTRs), allowing the description of the three main LC/LU categories: vegetation, built-up areas, water bodies-that is to say, GGBIs. Moreover, long time series in archives can help studying their changes in time (Osgouei & Kaya, 2017). For large regions lacking in cartographic data, ASIs can provide valuable georeferenced and up-to-date information. Despite the wide range of available data, knowing which kind of images should be used and how to get them involves some experience, due to the intrinsic complexity of data. Though there are large archives of images, even finding and downloading them can be complicated: of course, resulting analyses and elaborations,
HRSC-A data: a new high-resolution data set with multipurpose applications in physical geography
Progress in Physical Geography, 2007
The analysis and interpretation of remote sensing data facilitates investigation of land surface complexity on large spatial scales. We introduce here a geometrically high-resolution data set provided by the airborne High Resolution Stereo Camera (HRSC-A). The sensor records digital multispectral and panchromatic stereo bands from which a very high-resolution ground elevation model can be produced. After introducing the basic principles of the HRSC technique and data, applications of HRSC data within the multidisciplinary Research Training Group 437 are presented. Applications include geomorphologic mapping, geomorphometric analysis, mapping of surficial grain-size distribution, rock glacier kinematic analysis, vegetation monitoring and three-dimensional landform visualization. A final evaluation of the HRSC data based on three years of multipurpose usage concludes this presentation. A combination of image and elevation data opens up various possibilities for visualization and three...
Per-pixel Classification of High Spatial Resolution Satellite Imagery for Urban Land-cover Mapping
Photogrammetric Engineering & Remote Sensing, 2008
Commercial high spatial resolution satellite data now provide a synoptic and consistent source of digital imagery with detail comparable to that of aerial photography. In the work described here, per-pixel classification, image fusion, and GIS-based map refinement techniques were tailored to pan-sharpened 0.61 m QuickBird imagery to develop a six-category urban land-cover map with 89.3 percent overall accuracy (ϭ 0.87). The study area was a rapidly developing 71.5 km 2 part of suburban Raleigh, North Carolina, U.S.A., within the Neuse River basin. "Edge pixels" were a source of classification error as was spectral overlap between bare soil and impervious surfaces and among vegetated cover types. Shadows were not a significant source of classification error. These findings demonstrate that conventional spectral-based classification methods can be used to generate highly accurate maps of urban landscapes using high spatial resolution imagery.
The new information contained in four additional spectral bands of high-resolution images from the satellite sensor WorldView-2 should provide a visible improvement in the quality of analysis of large-scale phenomena occurring at the ground. Selected part of the image of Poznan was analyzed in order to verify these possibilities in relation to the urban environment. It includes riverside green area and a number of adjacent buildings. Attention has been focused on two components of object-oriented analysis-sharpening the image and its classification. In terms of pansharpening the aim was to obtain a clear picture of terrain objects in details, what should lead to the correct division of the image into homogenous segments and the subsequent fine classification. It was intended to ensure the possibility of separating small field objects within the set of classes. The task was carried out using various computer programs that enable the development and analysis of raster data (IDRISI And...