Research On Data Processing And Classification Of Land Use Of Airborne LIDAR Data

Geo-spatial information technology is the focus research in the geo-science world presently. Information capturing, processing as well as application are the three main items. At the end of 1980s, Airborne LIDAR technology got break through in real time acquiring of 3D earth spatial information, providing a new technique means for acquiring earth spatial information with high time and spatial resolution. As a new, active and direct earth observation technique, airborne LIDAR is applied widely gradually.The data set obtained by airborne LIDAR system is 3D discrete sub-randomly spatial distributed point cloud. At present, how to process LIDAR point cloud data to extract topographic information and different object information from point cloud, and how to apply airborne LIDAR data and other data source to topographic surveying and mapping, land use, and city construction and planning are key problems of LIDAR research. The application research of LIDAR data in many fields such as topographic mapping, urban construction and forestry programming and so on is the active studying topic too. Therefore, this dissertation develops the research on DEM extraction and classification of land use of airborne LIDAR data.This dissertation comprehensively analyzes airborne LIDAR technology and characteristics. Then, the paper carries on through researches in critical technology and methods of data processing and classification of land use. The main studies and contributions are described as follows:1. The paper systematically summarized the research status strip adjustment of LIDAR data, filtering method of LIDAR data and classification of land use home and abroad.2. This article introduces the composition and working theory of airborne LIDAR system and the composition of ALS50-II system emphatically. Then the process flow of airborne LIDAR data and characteristics of points cloud are discussed and errors in airborne LIDAR data are analyzed.3. Based on errors theory of strip adjustment of airborne LIDAR data, according to errors in LIDAR data after calibration, it puts forward a mathematical model of strip adjustment. This model comes from rigorous sensor model of LIDAR and doesn't need any raw measurements. Considering difficulties of tie points selection from LIDAR data, it takes research on method of tie points selection based on least squares 3D surface matching theory.4. Theory and difficulties of filtering of airborne LIDAR data are discussed. Based on the assumption of algorithm of this paper, it designs and realizes a self-adaptive filtering method of airborne LIDAR data. This method first interpolates irregular LIDAR point cloud data into grid, and then takes smooth segmentation on grid data and builds region adjacency and height pointing matrixes. After that, it classifies segments according to geometry and topology relation between segments. At last, terrain surface is interpolated according to terrain points classified, and then terrain points are extracted from raw point cloud precisely.5. Based on fusion of high resolution airborne LIDAR data and color airborne image acquired by RCD105 camera, it does research on classification of land use. First according to the actual situation of test area, it selects a num of patterns of different land use types, and carries on statistical analyzes on them, extracting spectrum features and space distribution features. Then it designs a group of operators to extract spectrum features, features of space distribution, shape, size of land use types. According to frame theory and land use types of test area, frame system of land use types is built. A prototype system of classification of land use is realized, and land use types are recognized. At last, experiment using data of test area is carried out to test the whole flow of classification of land use are distribution map of land use types are derived.