Venice, City of Canals: Characterizing Regions through Content Classification

122570989…from Transactions in GIS

“Information retrieval tasks in the geographic domain rely on textual annotation of georeferenced information objects. These information objects can be annotated with references to spatial objects contained within the corresponding geographical footprint. Not all the spatial objects, however, describe the essential attributes characterizing the region. In this article, we present a method to calculate the descriptive prominence of categories of spatial objects in a given region and select a subset for the characteristic description of the region. The method is demonstrated on three datasets of points of interest and an artificial dataset is used as a benchmark. The method reduces the number of categories describing regions significantly (p<0.001). We further illustrate the results qualitatively for three regions characterized in text.”

A Fast Clonal Selection Algorithm for Feature Selection in Hyperspectral Imagery

geo-spatial…from Geo-spatial Information Science

“Clonal selection feature selection algorithm (CSFS) based on clonal selection algorithm (CSA), a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-dimensional images, and has better performance than traditional feature selection algorithms with more computational costs. In this paper, a fast clonal selection feature selection algorithm (FCSFS) for hyperspectral imagery is proposed to improve the convergence rate by using Cauchy mutation instead of non-uniform mutation as the primary immune operator. Two experiments are performed to evaluate the performance of the proposed algorithm in comparison with CSFS using hyperspectral remote sensing imagery acquired by the pushbroom hyperspectral imager (PHI) and the airborne visible/infrared imaging spectrometer (AVIRIS), respectively. Experimental results demonstrate that the FCSFS converges faster than CSFS, hence providing an effective new option for dimensionality reduction of hyperspectral remote sensing imagery.”

Boston Showcases Solar Power Potential with Web GIS: Podcast Interview

podcast_iconESRI Podcast; Greg Knight, senior GIS application developer for the Boston Redevelopment Authority, discusses the Solar Boston map that allows users to see active renewable energy installations within the city and to calculate the solar potential of building rooftops. The map was created by the Boston Redevelopment Authority in cooperation with the Solar Boston Program using several ArcGIS tools, including ArcGIS Spatial Analyst and the ArcGIS API for Flex.

  • Listen or download: MP3 [10:44 | 4.95 MB]