Cadastral Triangulation: A Block Adjustment Approach for Joining Numerous Cadastral Blocks

In the last decade or so, there has been a very clear transition in many countries throughout the world from a graphical cadastre and/or relatively non-accurate digital cadastre toward an accurate coordinate based legal cadastre. Aiming at defining accurately the turning points position of the cadastral sub-division based on current data without the need to re-measure the cadastral entities, motivates the development of new algorithms and approaches suitable to performing the task. Implementation on a nationwide level requires to first develop advanced mathematical algorithms and methods to process separate parcellations (cadastral blocks or mutation plans), and then additional algorithms and methods to combine the numerous separate parcellations into a cadastral continuity maintaining rigid topological compatibility. Practical experience, especially from the Israeli viewpoint, indicates that implementation of advanced computational techniques for processing separate cadastral blocks, is only a partial solution of the problem. An optimal joining of the separate cadastral blocks into a homogeneous seamless cadastral space constitutes a complex task due to discrepancies between the adjoining parcellations. These discrepancies, significant in terms of their magnitude and characteristics, are mainly caused by the cadastral parcellation process based on separate cadastral measuring projects on the one hand, and limited accuracy of the measuring techniques in previous decades (mainly in the first half of the 20th century) on the other hand. The paper introduces a new algorithm based on the existing mathematical model, customary in photogrammetric mapping, aimed at connecting the adjoining photographs into blocks based on Block Adjustment by Independent Models. The proposed adjustment method (named the "Cadastral Triangulation") is executed based on the classic Adjustment of Indirect Observations combined with the Chained Similarity Transformation. This adjustment process which is carried out by a global transformation mechanism, enables obtaining both optimal transformation parameters of all the separate parcellations, as well as optimal coordinates of the cadastral boundary turning points. The initial results of the proposed method indicate its effectiveness in connecting the adjoining cadastral blocks, effectiveness expressed by a significant decrease of systematic and random errors compared to their pre-adjusted situation. Additionally, the proposed method enables bringing the adjusted cadastral boundary turning points maximally close to their theoretical true (and unknown) locations and, in any case, much closer than locations computed by currently practiced methods. Therefore, the proposed method may effectively be used as a primary computational algorithm for implementing a nationwide coordinate based legal cadastre

PYRAMIDAL APPROACH TOWARD MERGING TOPOGRAPHIC DATA FROM DIFFERENT DTM DATASETS

ABSTRACT Nowadays DTM databases, which describe terrain relief, are among the main interactions between data acquisition and a wide area of applications. One of the main problems in this discipline is data merging, which involves integrating data from different sets. Various factors cause global-systematic errors as well as local-random ones, which reflect on a different scale of spatial geometric and radiometric differences. Consequently, the required integration process yields the merging of geo-spatial datasets consisting of different resolution, accuracy, datum, orientation, and level of detailing. This paper describes a new approach to merging datasets, in which a careful examination, investigation and eventually an appropriate solution is given. The idea is to implement a hierarchical solution of pyramidal approach, in which local geometric discrepancies are monitored and prevented. The solution for the dataset matching procedure given here suggests the implementation of two working levels of topographic zoning -global and local. The suggested procedure is as follows: zonal division of the whole datasets area into patches, in which a local registration is extracted for each; sub-zonal division, in which an accurate 'local' ICP matching process is achieved while using the local extracted corresponding registration values. This new approach has good results for DTM datasets merging, therefore achieving a singular, unified and spatial continuous surface representation of the terrain relief

Spatial 3D Analysis of Built-up Areas Spatial 3D Analysis of Built-up Areas

SUMMARY In the last few years, the 3D GIS domain has developed rapidly, and has become increasingly accessible to different disciplines. 3D Spatial analysis of Built-up areas seems to be one of the most challenging topics in the communities currently dealing with spatial data. One of the most basic problems in spatial analysis is related to visibility computation in such an environment. Visibility calculation methods aim to identify the parts visible from a single point, or multiple points, of objects in the environment. The paper presents a unique solution to the 3D visibility problem in built-up areas. A 3D visibility algorithm based on an analytic solution for basic building structures is introduced. A building structure is presented as a continuous parameterization approximating of the building's corners. The algorithm quickly generates the visible surfaces' boundary of a single building. Using simple geometric operations of projections and intersections between visible pyramid volumes, hidden surfaces between buildings are rapidly computed. The algorithm, demonstrated with a schematic structure of an urban built-up environment and compared to the Line of Sight (LOS) method, demonstrates the computation time efficiency. Whereas the common visibility methods (LOS approach) require scanning of all the object's points, the presented solution, by applying the continuous parameterization approximating of the building's corners, is successfully avoiding the need to handle each point separately. As a result, the performance of the presented solution is much better than the common methods and for the analyzed samples the improvement time ratio was about 500 times. The basic building structure can be modified to complex urban structures by merging together a number of basic structures. The main contribution of the presented method in this paper is that it does not require special hardware, and is suitable for on-line computations based on the algorithms' performances. The visibility solution is exact, defining a simple problem that can be a basic form of other complicated environments

Research Toward a Multilayer 3-D Cadastre: Interim Results

This paper presents results of research dealing with geodetic and cadastral aspects of utilizing space above and below the surface. The research is being conducted at the Geodetic Engineering Division of the Technion- Israel Institute of Technology, as part of the doctoral studies of the first author. The principal objectives of the research are to find a cadastralgeodetic solution for utilizing above and below surface space and for defining the characteristics of the future analytical, three-dimensional and multilayer cadastre that will replace the existing two-dimensional graphical surface cadastre in Israel. The research objectives are being realized by attaining the secondary research objectives: defining the future cadastral reality and developing a multilayer cadastral model; defining guidelines for transition from the surface cadastre to the multilayer cadastre; developing a model for registering property rights in all three spaces; developing models for managing multilayer cadastre information and creating the geodetic-cadastral background for a legal solution of utilizing all land space

INTEGRATION OF MULTIPLE GEO-SPATIAL DATASETS

ABSTRACT When multiple geo-spatial datasets are integrated, the process should be done in several stages. In each stage two datasets are fused to one. Since different sequences may lead to different results, it is important to select a sequence that would lead to the required results. Two approaches, namely the sequential and hierarchical, for selecting the sequence are presented, and their results are compared. In the sequential approach, initially two datasets are integrated, then, in each stage the result of the previous stage is integrated with a fresh dataset. In the hierarchical approach, in each stage, every pair of datasets is integrated to one, until there is only one dataset. The results of extensive experimentations are presented. The tests show that for large overlap the second approach have better results in a cost of lower versatility