In short, Geographic Information System (GIS) is a system for analyzing and displaying spatial data, and remote sensing image is a form of spatial data, similar to raster data in GIS. Therefore, it is easy to integrate geographic information system and remote sensing at the data level, but in fact, the processing of remote sensing image is quite different from the analysis of raster data in GIS. The purpose of remote sensing image processing is to extract various thematic information, some of which are processing functions, such as image enhancement, filtering, classification and some specific transformation processing (such as terrestrial satellite). KT transformation of star image is not suitable for raster spatial analysis in GIS. At present, most GIS software do not provide perfect remote sensing data processing function, and remote sensing image processing software can not process GIS data well, which requires integrated GIS.
In software implementation, the integration of GIS and remote sensing can have three different levels. [Ehlers] :
Separate database, transfer files between different systems through file conversion tools;
The two software modules have the same user interface and synchronous display.
The highest goal of integration is to realize a single GIS software system that provides image processing function.
In an integrated system of remote sensing and geographic information system, remote sensing data is an important information source of GIS, and GIS can be used as a powerful assistant tool for remote sensing image interpretation. Specifically, there are the following applications. [J. C. Hinton] :
GIS as Image Processing Tool
Using GIS as a remote sensing image processing tool can enhance the standard image processing function in the following aspects:
1.1) Geometric Correction and Radiation Correction
In the practical application of remote sensing images, it is necessary to transform them into a geographic coordinate system, that is, geometric correction. Generally, the method of geometric correction is to establish polynomial fitting formulas by collecting ground control points. They can be extracted from the vector database of GIS, and then determine the corresponding coordinates of each point in the image, and establish correction formulas. After the correction is completed, the vector points can be superimposed on the image to judge the effect of the correction. In order to accomplish the above functions, the system needs to be able to process raster and vector data comprehensively.
Some remote sensing images, such as Layover, Shadow, Foreshortening and so on, will be geometrically distorted due to the influence of terrain. DEM data is needed to correct and interpret them. In addition, due to the change of illumination caused by topographic fluctuation, it can also be shown in remote sensing images, such as the brightness difference between shady and sunny slopes. DEM can be used for radiation correction to improve the accuracy of image classification.
1.2) Image Classification
For remote sensing image classification, the most obvious advantage of integration with GIS is the selection of training area. Through vector/raster integrated query, the image statistical characteristics of polygon area can be calculated, the classification effect can be evaluated, and the classification method can be improved.
In addition, in image classification, vector data can be rasterized and used as “remote sensing image” to participate in the classification, which can improve the classification accuracy. For example, considering the vertical zoning characteristics of vegetation, when classifying vegetation in mountainous areas, DEM can be used as a classification variable.
3)Selection of Region of Interest
In some remote sensing image processing, only one region is needed to extract some features, which requires intersection between raster data and vector data.
Remote Sensing Data as Information Source of GIS
Data is the most important component of GIS, and remote sensing provides cheap, accurate and real-time data. How to automatically obtain geographic information from remote sensing data is still an important research topic, including:
2.1) Extraction of Lines and Other Geographic Elements
In image processing, there are many Edge Detection filter operators, which can be used to extract the boundaries of regions (such as land and water boundaries) and linear objects (such as roads, faults, etc.). The results can be used to update existing GIS databases. This process is similar to the vectorization of scanned images.
2.2) Generation of DEM Data
Using Stereo Images and radar images, higher precision DEM data can be generated.
2.3) Land use change and map updating
The most direct way to update spatial database with remote sensing data is to take the corrected remote sensing image as background map and edit and modify the vector data according to it. The results of classification of remote sensing image data can be added to the GIS database. Because the result of image classification is raster data, the raster-to-vector operation is usually needed; if not, the raster data can be directly used for further analysis, then the system needs to provide the grid/vector intersection retrieval function.
Because remote sensing image can be regarded as a special raster data, it is not difficult to realize the integration of remote sensing and GIS tool software-the key is to provide very convenient raster/vector data interoperability and mutual conversion function, but it should be noted that due to various factors, the information extracted from remote sensing data is not absolutely accurate, in the usual land use sub-division. In the class, 90% of the classification accuracy is a considerable result, so it needs to be verified by field investigation - in this process, GPS can be used for positioning. In addition, the corresponding relationship between spatial resolution of remote sensing image and scale of GIS data should also be considered. For example, in practice, a common problem is how large scale topographic maps are needed to collect coordinates of ground control points for geometric correction of TM data with ground resolution of 30 meters, and the classification results can be used to update the number of large scale land use. According to experience, the appropriate scale is 1:50,000 to 1:100,000, too large the accuracy of remote sensing data is not enough, too small is a “waste” of remote sensing data.