Virtual 3d Mapping and Analysis Using Remote Sensing Data and Photographs
With the rapid growth of urbanization, visualization in the three-dimensional aspect is getting more importance nowadays. 3D modeling and visualization techniques help in decision making process to understand the third dimensional features in cities. Planners, urban designers, landscape architects and other planning professionals use computerized vi-sualization techniques to encourage the participation of public in urban planning. Aerial and Satellite images can be used to generate 3D models, but they cannot give a realistic feel due to the absence of texture information. The objective of this study is to build a 3D model along with texture information using currently available software tools and to make it freely viewable for the public. High resolution satellite data are useful for 3D mapping and analysis. In the current study, field photographs and satellite images are used to create 3D database of few iconic buildings in Bangalore city. Satellite images are used to identify the georeferenced footprint of the buildings or features. The designing and creation of 3D database is carried out using Sketchup software tools. Texture information is added from the photographs to get a realistic feel of the 3D building. The 3D features are visualized in Arcscene using Digital Elevation Model (DEM) and orthorectified high resolution Satellite data. Further, techniques have been employed to generate a 3D cadastre prototype for visualization of vertical growth of buildings. Line of sight and shadow analysis was carried out using the 3D model analyst toolbar in Arcscene for understanding the potential of this technology for locating security cameras.
Use of 3D cadastral data for real estate mass valuation in the urban areas
An assessment of real estate value is a prediction of its value based on experience, and taking into consideration its spatial, physical, legal and economic factors. Location has great influence on value because the real estate is being significantly determined by its spatial properties. In the urban areas, correlation between the value of real estate and its location is very complex and it depends on many subjective and objective factors. Mass valuation is a procedure which, based on objective factors, using statistical methods assesses the value of a big number of real estate. Modern, Computer-Assisted, real estate valuation systems worldwide are based on the existing spatial data, a combination of land administration and topographic data, along with the market factors. Efficient functioning of a real estate cadastre, as the basic infrastructural system, facilitates significantly the planning and accomplishment of economic and other activities linked to real estate. This paper examines the possibilities of mass real estate valuation, based on 3D Vector Terrain Model, created from the digital cadastral map (DCM) of the cadastral municipality of Centre, provided by the City of Zagreb Office for Cadastre and Geodetic Works and topographical data. As in cadastre, basic unit of realised real estate valuation system is real property, which can generally be seen as land, buildings, and whatever is attached or affixed to the land. In the lack of true 3D cadastral data models and data, procedures for real estate valuation were based on model which consists of 3D physical objects made from 2D cadastral data (land parcels and buildings) and topographical data – elevation. Data were modelled, stored and analysed using the combination of PL/SQL procedures and Oracle 11g SDBMS built-in spatial functions. This paper concentrates on further development of visibility analysis calculation of real estate, which requires more detailed 3D physical model. The idea behind modelling the influence of this factor on real estate valuation is the assumption that a real estate with a bigger visibility polygon, i.e. a better view, has a bigger market value than the same real estate with a smaller visibility polygon. On the part of the model, each part of 3D property unit were manually modelled into smaller parts according to a plan of separate parts – 3D condominiums, which are smallest parts of 3D property units in the model. Thus those, procedure of automatic valuation of spatial characteristics of each condominium were possible, instead of valuation of the whole building object. This factor was calculated as visibility polygon, two-dimensional geometric shape – cross section of continuous visibility border in all directions from one point (centre of 3D condominium), considering only the cross section of horizontal vision and obstacles. Data derived from the system can be used for better understanding and explanation of real estate value spatial distribution, and as a basis for the expert system based on multi criteria decision making.
Mass Valuation Using Quantified Spatial Characteristics of Cadastral Parcels
Each modern state needs to have a real estate valuation system for purposes of: fair real estate taxation, as a support to the real estate market, for better management of rural or urban environment or any other purpose. This enables a mass valuation system by systematic valuation of groups of real estate units performed on a certain date with the help of standard procedures and statistical analysis. In order to be able to valuate real property its size and value-per-size factor are required. The product of the two multiplied by, for instance, the tax rate yields the amount of tax to be paid, but can also be used for other purposes. As opposed to the tax rate which is defined by legislative acts and the size which can be explicitly quantified (calculated) from its geometry, the value-per-size of real property must be determined based on a predefined set of rules and criteria. Generally, the more rules and criteria included, the more fairly the value can determined. Furthermore, for this value to be as fair as possible, the rules and criteria need to be defined and tested for the entire jurisdiction affected. Real property can generally be seen as land, buildings, and what-ever is attached or affixed to the land. In this research we limit our-selves to land i.e. a part of it defined by a cadastral parcel. Besides the size which is defined by its area, there are other characteristics of a cadastral parcel which explicitly and unambiguously define it. No matter what its purpose may be, the three spatial characteristics which directly influence the value of a piece of land are its azimuth, slope and shape compactness. In this paper we first give a theoretical background for the method for automatic quantification of the mentioned three characteristics, provided cadastral and DTM databases are available in digital form and managed using spatial database management systems (SDBMS) technology. The shape compactness of cadastral parcel is calculated using its area and perimeter. Slope and azimuth are calculated by spatially intersecting triangles from the DTM with the shape of cadastral parcel. Since we wanted a distinct value for the slope and azimuth of each parcel, ’ per parcel’ averages are calculated using the weighted mean of ’ per intersection’ values of slope and azimuth. The area of intersection was used as weight. Finally, a description of a test system based on presented method and implemented on top of Oracle10g SDBMS is given. Within the research a sample DTM and cadastral database have been loaded into the system, and response times to queries for a single cadastral parcel and for a set of 5100 parcels indicate that such a system should be able to function in real world conditions.