Real time monitoring of engineering structures in case of an emergency of disaster requires collection of a large amount of data to be processed by specific analytical techniques. A quick and accurate assessment of the state of the object is crucial for a probable rescue action. One of the more significant evaluation methods of large sets of data, either collected during a specified interval of time or permanently, is the time series analysis. In this paper presented is a search algorithm for those time series elements which deviate from their values expected during monitoring. Quick and proper detection of observations indicating anomalous behavior of the structure allows to take a variety of preventive actions. In the algorithm, the mathematical formulae used provide maximal sensitivity to detect even minimal changes in the object’s behavior. The sensitivity analyses were conducted for the algorithm of moving average as well as for the Douglas-Peucker algorithm used in generalization of linear objects in GIS. In addition to determining the size of deviations from the average it was used the so-called Hausdorff distance. The carried out simulation and verification of laboratory survey data showed that the approach provides sufficient sensitivity for automatic real time analysis of large amount of data obtained from different and various sensors (total stations, leveling, camera, radar).
In the process of real estate evaluation, there are many important elements that should be taken into consideration: for example the type of property which is under evaluation, real estate market analysis, and the selection of appropriate evaluation approaches, methods and techniques. In each of the approaches, different parameters are important. Most importantly, however, is the appropriate selection and identification of real estate characteristics, both physical and economic, as well as the determination of the importance of these qualities so that, when necessary, it will be possible to make the appraisal and select those characteristics which have the greatest impact on value of property.
To acquire information about real estate, one can analyze data from multiple sources of information, such as: the land and mortgage register, land and buildings register, local town and country planning, industry data and other. Integrating data from all these sources allows comprehensive and up-to-date knowledge on the assessed property to be developed.
One of best sources of data describing the characteristics of real estate is remote sensing. This method offers a high spectrum of information and, therefore, allows a wide range of analyses. As a result, one can obtain highly accurate facts about the property. Remote sensing data, however, are not a panacea for all problems and have some limitations that determine their applicability.
This paper describes the possibilities of specifying some characteristics of the property under appraisal based on remote sensing data. For this purpose, the qualitative - quantitative analysis of the four most "common" types of remote sensing data were made, along with determining selected characteristics of 30 properties located in the Warsaw - Bemowo suburb area.
The results of this research made it possible to answer the question of whether it is practicable and, if so, to what extent, to use remotely sensed data as the basis for determining the characteristics of a property as well as connecting the types of data to individual properties. The paper focuses on defining the characteristics of two kinds of real estate: land and buildings.