DEM Matching Without Control Points For Detecting The Earth's Surface Deformation And Its Application On Debris-Flow Area

Precise Earth's surface deformation is the foundational data for assessing, managing and predicting the natural disasters, such as debris-flows. The multi-temporal images and DEM are main data source for obtaining the deformation information. As to monitoring terrain changes with multi-temporal DEMs, researching DEM deformation detecting without ground control points (GCPs) will bring many benefits. Firstly of all, it would be helpful to reduce the field works of constructing and maintenance of GCPs and save money. Moreover, it would enhance the automatic degree for monitoring terrain changes, and then it would better satisfy the request of rapid respondence to natural disasters. Furthermore, it can make full use of those quite old pre-disaster data, although it is impossible to setup valid GCPs for them.Apparently, the technique of detecting DEM deformations without GCPs employs surface matching to replace GCPs. In fact, both surfaces could not be matched accurately before their deformations are identified correctly, while it is necessary for the precise matching. So surface matching and deformation detecting is two different aspects of one question, but their relationship and mutual interaction make this question be very complex. The existing researches cannot fully meet the requirement of real applications in debris-flow area. PUWAIGOU, a typical debris-flow valley along Chengdu-Kunming railway, southwest China, is adopted as experimental area to study the automatic DEM matching algorithm for detecting large deformed area.Selection of an appropriate DEM matching algorithm is the first task of this research. Two representative algorithms, least Z-difference (LZD) and iterative closest points (ICP) are compared by some simulated experiments. The testing results approve that LZD is more suitable for DEM matching according to its compositive performance. Then the normal direction corresponding criterion for pairing points on both DEMs is proposed. By integrating the novel criterion with LZD, the performance of improved LZD is enhanced greatly in pull-in range, convergence, etc.It should be confirmed prior to detecting deformation whether or not observations have detectability and locatability of gross errors. Using the judgment matrix of detectable and locatable of gross errors in surveying error and reliability theory, it is proved firstly that the number of zero column vectors in LZD's judgment matrix equals to the rank defects of LZD's coefficient matrix. And then, LZD's matching equation having the detectability and locatability of gross errors is verified by a series of tests. These conclusions powerfully support the following researches on algorithms of detecting DEM deformations in theory.According to the character that the ridge region is rarely affected by the debris-flow activities, an algorithm called multiply surface patches matching (MSPM) based on generalized control points is reported. The generalized control points are selected automatically associated by the terrain features extraction algorithm. The experimental results show that MSPM, associated with M-LZD, is very practical for detecting large proportion of deformation in debris-flow area.The difference between gross errors and deformations is neglected in existing algorithms for matching DEM to detect deformations. The deformations are regarded as gross errors, therefore only their magnitude is considered and their relationship is not. So, considering the character of deformation, a novel algorithm called LZD using differential model (DM-LZD) is proposed associated with least trimmed squares estimator (LTS), which is a robust estimator with high break-down point. It enhances the deformation detecting ability and matching accuracy when large deformed area exists in matched DEM. The simulative experimental results illustrate that DM-LZD can detect over 50% deformation area, and is superior to both M-LZD and LMS-LZD.By matching the DEM blocks, which are of same size and are extracted from the multi-temporal DEMs, DM-LZD algorithm can be applied to the multi-temporal DEMs with independent coordinate system. Using the real 1957DEM and 1987DEM, the volume of soil erosion and debris deposition can be quantificationally detected by DM-LZD during the 30 years in PUWAIGOU. The detected deformed area is about 58.6% of valley area in matched DEM. Such information will form a foundation for quantificational monitoring and assessing PUWAIGOU debris-flow hazards in future.