Extracting Land Information And Producing Thematic Map Based On Uav Remote Sensing Image

With the development of remote sensing technology, the rich of image data source and the raise of image processing level make the application of remote sensing technology more and more widely. The aerospace remote sensing on large aircraft and satellites platform have been applied widely, but it is difficult to get the high-resolution remote sensing images in the southwest region with more clouds and the flight difficult areas. The UAV(Unmanned aerial vehicles) of flying at low altitude can obtain high-resolution remote sensing image in more clouds areas. The high-resolution image can obtain the type of the feature attribute information more easily and land use information visualization better than low-resolution image. However, the traditional image classification method leads to classification accuracy is not high, and affects UAV high-resolution remote sensing images application efficiency in land-use. How to use a new image classification method to improve UAV high-resolution remote sensing images accuracy of Land Use information has a very important significance.This thesis combining with the UAV high-resolution images can provide more texture, shape and mutual spatial information on the surface than satellite images, and take object-oriented multiscale segmentation classification to study UAV high-resolution images land use classification in the experimental area of a village, Deyang City, Sichuan Province. The object-oriented multiscale segmentation classification method avoid the pixel-based traditional classification phenomenon of different objects which have the same spectrum and the same objects have different spectrum, and overcome the object-oriented single scale problem of over segmentation and less segmentation. This experiment provides some guidance for land information extraction and mapping on UAV image.The main contents are as follows:1. The domestic and foreign UAV technology application of obtaining information and the land information extraction technology application status on remote sensing image were analyzed.2. According to the UAV images control points collected by RTK, it had explored the accuracy of regular grid DEM construction about sample points and interpolation algorithm selection factors such as in experiments of grid DEM construction interpolated by discrete points.3. The conventional methods of aerial survey data processing were summeried. LPS was selected as a platform, the experimental zone DOM and DEM were completed on UAV images data were preprocessed.4. The principles and methods of object-oriented multi-scale image segmentation techniques were elaborated and the optimal segmentation scale selection methods were analyzed. Spectral factor and shape factor (including smoothness and compactness) were determined in image segmentation experiment and optimal segmentation scales of different objects were selected in mean standard deviation experiment.5. In multi-scale multi-level land use classification experiment of UAV image study area, the optimal segmentation scales of the different land types were analyzed and obtained, and on this basis the classification rules for multi-scale were established and land information were extracted. The accuracy of result was analyzed and evaluated, and the thematic map of land use was made in experiment.