Abstract: The present invention relates to a mapping and comparing choroplethic housing statistics. In one example, this comprises accessing property data corresponding to a geospatial area. Analytics are used to generate usable property data statistics from the accessed property data. A thematic map image based on the usable property data statistics is then generated according to comparison categories, so that the thematic map image may be displayed.

Abstract: The present invention relates to photograph initiated property assessment. In one example, an electronic device performs a photograph initiated property assessment by accessing a photographic assessment itinerary that includes a plurality of target portions for the subject property and a set of image capture requirements for each of the plurality of target portions. Further, when performing the initiated property assessment the electronic device prompts a plurality of image capture requests according to the photographic assessment itinerary while displaying a menu that permits the addition of information to the set of image captures.

Abstract: Automated valuation model with customizable neighborhood determination. A map image is displayed corresponding to a geographical area, and then user input accommodates definition of a particularly defined geographic area to provide custom identification of a neighborhood to be subject to automated valuation. Once the defined geographic area is established, the automated valuation model is applied to property data corresponding to properties within the defined geographic area. A subject property and corresponding properties within the defined geographic area are then displayed on a map image, preferably with articulation of the defined geographic area as the neighborhood of interest. The neighborhood may be defined by, among other criteria, inclusion within a user-defined shape, as well as exclusion of a user-defined shape from a displayed geographic area.

Abstract: A valuation model accounts for traffic features associated with modeled properties, generates listings of model-chosen comparables, and evaluates property appraisals and appraisal-chosen comparables accordingly. In one embodiment, traffic features of homes are used in automated electronic appraising and in the electronic review of appraisals. It first uses GIS techniques to convert traffic features associated with a property into a numeric variable, allowing hedonic price models to measure the price impact of traffic features. This allows traffic features to be used in the automated selection of comparable properties and in the adjusting of comp prices in appraisals. It also allows automated review of appraisals to determine if they fairly accounted for the traffic dimension in the selection of comps and in making any price adjustments.

Abstract: Automated valuation model with customizable neighborhood determination. A map image is displayed corresponding to a geographical area, and then user input accommodates definition of a particularly defined geographic area to provide custom identification of a neighborhood to be subject to automated valuation. Once the defined geographic area is established, the automated valuation model is applied to property data corresponding to properties within the defined geographic area. A subject property and corresponding properties within the defined geographic area are then displayed on a map image, preferably with articulation of the defined geographic area as the neighborhood of interest. The neighborhood may be defined by, among other criteria, inclusion within a user-defined shape, as well as exclusion of a user-defined shape from a displayed geographic area.

Abstract: Automated valuation model with customizable neighborhood determination, including spatial exclusion conditions. A map image is displayed corresponding to a geographical area, and then user input accommodates definition of a particularly defined geographic area to provide custom identification of a neighborhood to be subject to automated valuation. Once the defined geographic area is established, the automated valuation model is applied to property data corresponding to properties within the defined geographic area. A subject property and corresponding properties within the defined geographic area are then displayed on a map image, preferably with articulation of the defined geographic area as the neighborhood of interest. The neighborhood may be defined by, among other criteria, inclusion within a user-defined shape, as well as exclusion of a user-defined shape from a displayed geographic area.

Abstract: Modeling comparable properties and rendering map images with automatic valuation of properties bordering specified geographic features. A valuation model identifies and accounts for the proximity of properties to geographic features. For example, estimating property value includes accessing property data corresponding to a geographic area and performing a regression based upon the property data. The regression models the relationship between price and explanatory variables, with the explanatory variables including proximity to geographic features. Proximity may be a categorical variable wherein properties bordering the geographic feature are determined to possess the proximity characteristic. Alternative explanatory variables may incorporate different degrees of proximity.

Abstract: Model-based property value estimation with that implements a categorical location variable providing a neighborhood proxy. A regression models the relationship between sale price and a set of explanatory variables. These explanatory variables include a location variable that is defined at a level of granularity such that the location variable acts as a proxy for location within a neighborhood. An infill process remedies the effects of insufficient amounts of location variable data.