SAM: A Comprehensive Application for Spatial Analysis in Macroecology

Ecography, Volume 33 Issue 1, Pages 46 – 50, Published Online: 4 Mar 2010

Thiago F. Rangel, Jose Alexandre F. Diniz-Filho and Luis Mauricio Bini

“SAM (Spatial Analysis in Macroecology) is a freeware application that offers a comprehensive array of spatial statistical methods, focused primarily on surface pattern spatial analysis. SAM is a compact, but powerful stand-alone software, with a user-friendly, menu-driven graphical interface. The methods available in SAM are the most commonly used in macroecology and geographical ecology, and range from simple tools for exploratory graphical analysis (e.g. mapping and graphing) and descriptive statistics of spatial patterns (e.g. autocorrelation metrics), to advanced spatial regression models (e.g. autoregression and eigenvector filtering). Download of the software, along with the user manual, can be downloaded online at the SAM website: <www.ecoevol.ufg.br> (permanent URL at <http://purl.oclc.org/sam/>).”

Ensemble Extraction for Classification and Detection of Bird Species

Ecological Informatics, In Press, Accepted Manuscript, Available online 1 March 2010

Eric P. Kasten, Philip K. McKinley, Stuart H. Gage

“Advances in technology have enabled new approaches for sensing the environment and collecting data about the world. Once collected, sensor readings can be assembled into data streams and transmitted over computer networks for storage and processing at observatories or to evoke an immediate response from an autonomic computer system. However, such automated collection of sensor data produces an immense quantity of data that is time consuming to organize, search and distill into meaningful information. In this paper, we explore the design and use of distributed pipelines for automated processing of sensor data streams. In particular, we focus on the detection and extraction of meaningful sequences, called ensembles, from acoustic data streamed from natural areas. Our goal is automated detection and classification of various species of birds.”

Clustering of Unhealthy Outdoor Advertisements around Child-serving Institutions in Austin, Los Angeles, and Philadelphia

Health & Place, Volume 15, Issue 4, Pages 935-945 (December 2009)

Amy Hillier, Brian L. Cole, Tony E. Smith, Antronette K. Yancey, Jerome D. Williams, Sonya A. Grier, William J. McCarthy

“Using GPS devices and digital cameras, we surveyed outdoor advertisements in Austin, Los Angeles and Philadelphia. GIS and hot spot analysis revealed that unhealthy ads were clustered around child-serving institutions in Los Angeles and Philadelphia but not in Austin. Multivariate generalized least square (GLS) regression models showed that percent black (p<0.04) was a significant positive predictor of clustering in Philadelphia and percent white (p<0.06) was a marginally significant negative predictor of clustering in Los Angeles after controlling for several land use variables. The results emphasize the importance of zoning and land use regulations to protect children from exposure to unhealthy commercial messages, particularly in neighborhoods with significant racial/ethnic minority populations.”

Using GIS in Constructing Area-based Physical Deprivation Index in Cairo Governorate, Egypt

Habitat International, 34 (2), p.264-272, Apr 2010

Khadr, Z. / Nour el Dein, M. / Hamed, R.

“A worldwide consensus on poverty has acknowledged slums and the living conditions of slum dwellers as a major challenge faced by humanity. Formulation of appropriate policies and intervention programs to improve the living conditions and secure the well being of slum dwellers requires a strong knowledge base that clearly defines, identifies, and signifies the main points of commonalities and diversities among these slum areas which are commonly unavailable in many cities in developing countries. The current research provides an overview of slum challenge in Cairo governorate, Egypt. It further develops a physical deprivation index that allows the ranking of small geographic areas accordingly to their levels of physical deprivation. Using four of the basic GIS layers for the governorate of Cairo and the principle component analysis, an index of physical deprivation for these small areas “mantiqas” is constructed. The proposed index is a composite index of four main dimensions characterizing physical attributes, sources of pollutions, available services and security of each mantiqa. Validation tests of the index revealed the ability of the proposed index to capture slums identified by the current governmental official list of slums in addition to other areas that were as equally deprived but not included in the official list of slums.”

A GIS-based Approach to Evaluate Biomass Potential from Energy Crops at Regional Scale

Environmental Modelling and Software, 25 (6), p.702-711, Jun 2010

Fiorese, G. / Guariso, G.

“The aim of the paper is to propose a method to maximize energy production from arboreous and herbaceous dedicated crops given the characteristics of the local environment: geo-morphology, climate, natural heritage, current land use. The best energy crops available in the Italian panorama are identified and the problem of maximizing the bioenergy production over an entire regional area is formulated. Each cultivar is thus assigned to the suitable land accounting for sensitive parameters that characterize it and taking into account current land use. The assumption made here is that marginal land and set-asides can be converted to energy crops without altering current practices and cash crops’ production. The method is based on the integration of GIS data (spatially continuous) with data derived from the agricultural census (spatially discrete). We carry out the analysis for Emilia-Romagna, in Northern Italy. The sustainable growth of energy crops, with an optimized network of conversion facilities distributed in the territory, may significantly contribute to the local energy supply and to climate change mitigation.”