What is the Economic Value of Satellite Imagery? The value of remote-sensing information, such as that from Landsat and similar Earthobserving satellites, has been expressed in many different ways-advances in science, innovations in technology, and cost savings. Recently, in a case study in a 35-county region in northeastern Iowa, U.S. Geological Survey (USGS) scientists demonstrated that Landsat imagery and other moderate-resolution land-imagery (MRLI) would have significant economic value when used in combination with Earth-science information, such as envi-This image shows the next satellite in the Landsat Program, the Landsat Data Continuity Mission, scheduled to launch in February 2013. The U.S. Geological Survey and NASA jointly manage the Landsat Program. Since 1972, Landsat satellites have collected information about Earth from space. This science, known as remote sensing, has matured with the Landsat Program and provides information crucial to evaluating the dynamic changes caused by both natural processes and human practices. (Modified NASA image.) Landsat image within a 35-county region in Iowa studied by the U.S. Geological Survey. Acquired in 2007 at the peak of the U.S. midwestern growing season, this image shows healthy cropland (corn and soybeans) in greens, cleared and developed land in pinks, and water bodies (ponds and the Iowa River) in dark tones. Each pixel in the image covers an area of 30 by 30 meters of the ground. (USGS image.) ronmental, geologic, and ground and surface water data, to monitor agricultural production and protect groundwater resources.
There are several ideas in the outcomes of our investigation:(1) Polyhedral primitives based CSG R-tree for urban building model. A kind of model for exactly describing urban 3D buildings for large-scale urban true orthoimage generation is presented. This method is based on CSG (Constructive Solid Geometry), belonging to volumetric representation in computer graphics. This method is well suited to describing complex shapes, which can be composed by a set of primitives. Within this proposed approach the buildings are described by combining a set of basic primitives, such as box, wedge, and rectangular pyramid. This representation model is particularly useful for urban true orthoimage generation because a complex building in this model can be partitioned into many simple building parts, each of them corresponding to a basic building model. Moreover, the model is able to consider diverse building, e.g. flat roof, gable roof, and hip roof building. We implemented this work using 2D plane information according to digital surface model. The 2D plane of a building is divided in rectangles, arcs, and circles, each of the primitives representing the ground plane of a building part. The primitives are combined by means of the Boolean operators: union, intersection, and difference. So, the buildings can be described as a CSG tree, where the leaves contain primitives and the internal nodes contain Boolean operations.(2) Accuracy improvement of urban true orthoimage generation. When applying the existing true orthorectification methods to orthorectify urban high buildings, there exist many problems such as incomplete orthorectification of boundaries of artificial buildings, edge blurring and distortion; incomplete orthorectification to small buildings in building roofs, and/or balcony due to the lack of proper 3D model representation. Therefore, a novel orthorectification method that is based on 3D R-tree urban building model is presented. This method can exactly solve the problem mentioned above and improve the accuracy of true orthoimage. Combining with the technique of CSG model and LOD (Level of Detail), 3D R-tree can more effectively organize and accurately describe the structure of urban building model. Thus, we can produce the dynamic 3D digital building model (DBM) with varying levels of detail, which ranges from tiny parts of one building to the entire block of street. With the proposed method, automatic extraction of the roof edges from DSM (Digital Surface Model) is first carried out. With different types of roof and height of the building, we can construct the primitives of CSG model. Second, with the spatial properties of minimum rectangular bounding box of primitives, we can build the 3D R-tree object-oriented structure for every building. When back-projecting the 3D R-tree-based DBM onto the original image, preliminary outlines of buildings with vector feature in the original image can be obtained. Thus, accuracy of orthorectification with the geometric constrains of building vector boundaries can effectively b...
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