tailieunhanh - Báo cáo " On the detection of gross errors in digital terrain model source data "

Nowadays, digital terrain models (DTM) are an important source of spatial data for various applications in many scientific disciplines. Therefore, special attention is given to their main characteristic ‐ accuracy. At it is well known, the source data for DTM creation contributes a large amount of errors, including gross errors, to the final product. At present, the most effective method for detecting gross errors in DTM source data is to make a statistical analysis of surface . | VNU Journal of Science Earth Sciences 23 2007 213-219 On the detection of gross errors in digital terrain model source data Tran Quoc Binh College of Science VNU Received 10 October 2007 received in revised form 03 December 2007 Abstract. Nowadays digital terrain models DTM are an important source of spatial data for various applications in many scientific disciplines. Therefore special attention is given to their main characteristic - accuracy. At it is well known the source data for DTM creation contributes a large amount of errors including gross errors to the final product. At present the most effective method for detecting gross errors in DTM source data is to make a statistical analysis of surface height variation in the area around an interested location. In this paper the method has been tested in two DTM projects with various parameters such as interpolation technique size of neighboring area thresholds . Based on the test results the authors have made conclusions about the reliability and effectiveness of the method for detecting gross errors in DTM source data. Keywords Digital terrain model DTM DTM source data Gross error detection Interpolation. 1. Introduction Since its origin in the late 1950s the Digital Terrain Model DTM is receiving a steadily increasing attention. DTM products have found wide applications in various disciplines such as mapping remote sensing civil engineering mining engineering geology military engineering land resource management communication etc. As DTMs become an industrial product special attention is given to its quality mainly to its accuracy. In DTM production the errors come from data acquisition process errors of source data and modeling process interpolation and representation errors . As for other errors the Tel. 84-4-8581420 E-mail tqbinh@ errors in DTM production are classified into three types random systematic and gross blunder . This paper is focused on detecting single gross errors presented in DTM .