We conducted an experiment to evaluate measuring methods of the center location of a circle by using simulated images of various sizes of circles. In the experiment results we found that the variances of the measurement errors of the centroid methods oscillate on a one-pixel cycle in diameter. This paper reports an analysis of the dependence of the location measurement accuracy of centroid methods on the diameter of a circular target. Two centroid methods : weighted centroid method (WCM), and unweighted centroid method using a binary image created by thresholding (BCM) are investigated. Since variances of the measurement errors by both WCM and BCM are unable to be obtained analytically, those are obtained by numerical integration. The results of the numerical integration show that the variances of the measurement errors by WCM can be expressed by the combination of the inverse proportion to the cube of the diameter and the oscillation on a one-pixel cycle in diameter. On the other hand, the variances of the measurement errors by BCM should approximate to the combination of the inverse proportion to the diameter and the oscillation on a one-pixel cycle in diameter.
A new method for measuring forest's 3D-structure and detecting managing status by using airborne LIDAR data was proposed in this paper. Firstly, histogram graph of pulse data along the altitude direction was adopted for describing characteristics of LIDAR data's stratum structure. And it was found that there exists good correlation between LIDAR data's histogram graph and DHDV (Degree of Human Disturbance of Vegetation) index, which indicates status of second-growth forest and usually is used in field-survey. Secondly, method of generating Histogram Index (HI) map from LIDAR data was proposed and discussed in details. Just like multi-band satellite image data, HI map contains multi-band data structure, with each band standing for HI value within corresponding altitude range. And, with field-survey data of DHDV as reference data, classification was performed upon HI map in order to generate DHDV map of second-growth forest. Verification on DHDV classification map shows that, there exists good possibility to generate DHDV map over large area of second-growth forest by using airborne LIDAR data, which shows fine prospects of airborne LIDAR's applications to forest managements.
Hot mudflow disaster that occurred in Sidoarjo area, Indonesia on May 29 2006 is reported and a prediction model and simulation based on cellular automata is proposed for reducing mudflow disaster impact. We assume that mudflow has similar characteristic to the well-known fluid dynamic model. Therefore we adopt dynamic model of fluid for hot mudflow model. The input parameters of the model are landscape data, mud volume per-day, and obstacle such as dikes and buildings. An approximation model based on the cellular automata for creation of a novel model of mudflow is relatively simple and powerful. The important properties of the proposed model depend on neighborhood definition and rules. We use eight neighborhood cells together with the moment that is described with Gaussian function. Cellular automata rules are built with landscape and obstacle data. Then the simulation results of mudflow are visualized as a fluid dynamic model.
For object-based forest stand type classification using high resolution satellite data, the relation of the parameter of segmentation and classification accuracy was investigated. A target area is forested landscape in the Kirishima area over both Ebino city of Miyazaki and Kirishima city of Kagoshima, the southern part of Kyushu Island. A pan-sharpen IKONOS data (1-m of spatial resolution) was employed in this analysis. In addition to varying the scale parameter from 100 to 1000, some combinations of color and shape criterion were examined. As a result of measuring the accuracy of forest stand type classification, when scale parameter was 300, the highest classification accuracy was achieved. It was indicated that the color criterion also affects classification accuracy in this study. Consequently, it would be greatly concerned with classification accuracy whether target patches are delineated adequately by segmentation, and this paper indicated that quantitatively.
It is important to get topology consistency of spatial information for facility management and spatial analysis. Most of spatial information is made based on topographic maps. The functions of digital stereo plotter to make topographic map are upgraded as digitalization progressed. These functions are basically an aim of efficiency improvement. The functions take not only plotting but also map compilation. However an aim of plotting is to get accurate positing and compilation is to get accurate topology. The positing and the topology are the characters to conflict. As a result, the digital stereo plotter supports to make good result for paper printing but topology consistency. It is important to develop map production method that bases the characteristic of plotting and compilation. This paper discusses to make roads and related features for big scale of topographic map by photogrammetry. The drawing is ruled on plotting process, and automated process is taken on compilation process. This method secures topology consistency, and substantially accomplished uniting of plotting and compilation.
Current development of CCD sensor or GPS/IMU system has offered a great contribution to progress digital aerial photogrammetry. Moreover, LiDAR system has made it possible to acquire real-time point cloud data. In these circumstances, combination of non-metric medium format digital camera and LiDAR system has been receiving more attention as make it possible to realize an efficient aerial digital photogrammetry. However, photogrammetric data and point cloud data contain some errors. In order to reduce these errors, it is reasonable to use distance data instead of 3D data since distance data is direct value in LiDAR system. Furthermore, utilization of triplet images makes it possible to use geometric data based on trifocal tensor besides photogrammetric data and distance data. This paper describes simultaneous adjustment for an efficient self-calibration in aerial digital photogrammetry using geometric data based on trifocal tensor besides photogrammetric data and distance data from LiDAR.
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