GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast

Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.

Land cover change and environmental quality assessment using GIS techniques: a case study in Brazilian Southeastern region for the period 1988-2003

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Eradicating Rats on Lehua Island, Hawaii, with the Help of GIS and GPS

Highlights • Wildlife Services used GIS and GPS to document and track bait distribution during each bait drop. • GIS and GPS were critical in making this eradication project effective and environmentally safe. • Use of the technologies ensured the coverage necessary for the project's goals.

Using GIS to Locate Areas for Growing Quality Coffee in Honduras

Abstract Small-scale coffee producers worldwide remain vulnerable to price fluctuations after the 1999-2003 coffee crisis. One way to increase small-scale farmer economic resilience is to produce a more expensive product, such as quality coffee. There is growing demand in coffee-producing and coffee-importing countries for user-friendly tools that facilitate the marketing of quality coffee. The purpose of this study is to develop a prototypical quality coffee marketing tool in the form of a GIS model that identifies regions for producing quality coffee in a country not usually associated with quality coffee, Honduras. Maps of areas for growing quality coffee were produced with information on climate, soils, topography, areas vulnerable to environmental degradation, the location of current quality coffee farms, and infrastructure. The maps depict suitable coffee-growing land in portions of eight western Honduran departments.

An integrated GIS for sedimentological and geomorphological analysis of a lagoon environment. Barra de Cananeia inlet region, (Southeastern Brazil)

The aim of this work is to use GIS integration data to characterize sedimentary processes in a SubTropical lagoon environment. The study area was the Canan,ia Inlet estuary in the southeastern section of the Canan,ia Lagoon Estuarine System (CLES), state of So Paulo, Brazil (25A degrees 03'S/47A degrees 53'W). The area is formed by the confluence of two estuarine channels forming a bay-shaped water body locally called "Trapand, Bay". The region is surrounded by one of the most preserved tracts of Atlantic Rain Forest in Southwestern Brazil and presents well-developed mangroves and marshes. In this study a methodology was developed using integrated a GIS database based on bottom sediment parameters, geomorphological data, remote sensing images, Hidrodynamical Modeling data and geophysical parameters. The sediment grain size parameters and the bottom morphology of the lagoon were also used to develop models of net sediment transport pathways. It was possible to observe that the sediment transport vectors based on the grain size model had a good correlation with the transport model based on the bottom topography features and Hydrodynamic model, especially in areas with stronger energetic conditions, with a minor contribution of finer sediments. This relation is somewhat less evident near shallower banks and depositional features. In these regions the organic matter contents in the sediments was a good complementary tool for inferring the hydrodynamic and depositional conditions (i.e. primary productivity, sedimentation rates, sources, oxi-reduction rates).

Long-term effects of oil pollution in mangrove forests (Baixada Santista, Southeast Brazil) detected using a GIS-based multitemporal analysis of aerial photographs

Oil spills are potential threats to the integrity of highly productive coastal wetlands, such as mangrove forests. In October 1983, a mangrove area of nearly 300 ha located on the southeastern coast of Brazil was impacted by a 3.5 million liter crude oil spill released by a broken pipeline. In order to assess the long-term effects of oil pollution on mangrove vegetation, we carried out a GIS-based multitemporal analysis of aerial photographs of the years 1962, 1994, 2000 and 2003. Photointerpretation, visual classification, class quantification, ground-truth and vegetation structure data were combined to evaluate the oil impact. Before the spill, the mangroves exhibited a homogeneous canopy and well-developed stands. More than ten years after the spill, the mangrove vegetation exhibited three distinct zones reflecting the long-term effects of the oil pollution. The most impacted zone (10.5 ha) presented dead trees, exposed substrate and recovering stands with reduced structural development. We suggest that the distinct impact and recovery zones reflect the spatial variability of oil removal rates in the mangrove forest. This study identifies the multitemporal analysis of aerial photographs as a useful tool for assessing a system's capacity for recovery and monitoring the long-term residual effects of pollutants on vegetation dynamics, thus giving support to mangrove forest management and conservation.

Modeling the Potential Geographic Distribution of Black Pepper (Piper nigrum) in Asia Using GIS Tools

Known as the "king of spices", black pepper (Piper nigrum), a perennial crop of the tropics, is economically the most important and the most widely used spice crop in the world. To understand its suitable bioclimatic distribution, maximum entropy based on ecological niche modeling was used to model the bioclimatic niches of the species in its Asian range. Based on known occurrences, bioclimatic areas with higher probabilities are mainly located in the eastern and western coasts of the Indian Peninsula, the east of Sumatra Island, some areas in the Malay Archipelago, and the southeast coastal areas of China. Some undocumented places were also predicted as suitable areas. According to the jackknife procedure, the minimum temperature of the coldest month, the mean monthly temperature range, and the precipitation of the wettest month were identified as highly effective factors in the distribution of black pepper and could possibly account for the crop's distribution pattern. Such climatic requirements inhibited this species from dispersing and gaining a larger geographical range.

Indices representing landscape as a support for pedological survey in GIS environment

Mapping of soil has been highlighted in the scientific community, because as alertness about the environment increases, it is necessary to understand more and more about the distribution of the soil in the landscape, as well as its potential and its limitations for the use. In that way the main aim of this study was to apply indices representing landscape with the use of geoprocessing to give support in the delimitation of different compartments of landscape. Primary indices used were altitude above channel network (AACN) and secondary channel network base level (CNBL), multiresolution index of valley bottom flatness (MRVBF) and Wetness index (ITW), having as object of study the Canguiri Experimental Farm, located in Pinhais, Curitiba's Metropolitan region. To correlate the chemical attributes and granulometric ones in sampling groups, totalizing 17 points (Sugamosto, 2002), a matrix of a simple linear correlation (Pearson) with the indices of the landscape were generated in the Software Statistica. The conclusion is that the indices representing the landscape used in the analysis of groupings were efficient as support to map soil at the level of suborder of Brazilian Soil Classification System.

Long-term effects of oil pollution in mangrove forests (Baixada Santista, Southeast Brazil) detected using a GIS-based multitemporal analysis of aerial photographs

Oil spills are potential threats to the integrity of highly productive coastal wetlands, such as mangrove forests. In October 1983, a mangrove area of nearly 300 ha located on the southeastern coast of Brazil was impacted by a 3.5 million liter crude oil spill released by a broken pipeline. In order to assess the long-term effects of oil pollution on mangrove vegetation, we carried out a GIS-based multitemporal analysis of aerial photographs of the years 1962, 1994, 2000 and 2003. Photointerpretation, visual classification, class quantification, ground-truth and vegetation structure data were combined to evaluate the oil impact. Before the spill, the mangroves exhibited a homogeneous canopy and well-developed stands. More than ten years after the spill, the mangrove vegetation exhibited three distinct zones reflecting the long-term effects of the oil pollution. The most impacted zone (10.5 ha) presented dead trees, exposed substrate and recovering stands with reduced structural development. We suggest that the distinct impact and recovery zones reflect the spatial variability of oil removal rates in the mangrove forest. This study identifies the multitemporal analysis of aerial photographs as a useful tool for assessing a system's capacity for recovery and monitoring the long-term residual effects of pollutants on vegetation dynamics, thus giving support to mangrove forest management and conservation.

Diseño e implementación de un sistema GIS 3D para plataformas móviles

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

A GIS based model for solving the planar Huff problem considering different demand distributions and forbidden regions

[EN] In this paper, we have used Geographical Information Systems (GIS) to solve the planar Huff problem considering different demand distributions and forbidden regions. Most of the papers connected with the competitive location problems consider that the demand is aggregated in a finite set of points. In other few cases, the models suppose that the demand is distributed along the feasible region according to a functional form, mainly a uniform distribution. In this case, in addition to the discrete and uniform demand distributions we have considered that the demand is represented by a population surface model, that is, a raster map where each pixel has associated a value corresponding to the population living in the area that it covers...

Analisi spaziale dei dati entomologici in ambiente GIS: prospettive di utilizzo nell'agricoltura di precisione

Scopo della ricerca è stato definire le dinamiche spazio-temporali degli insetti studiati mediante l’impiego di tecniche geostatistiche. La ricerca è stata condotta su due casi studio, il primo riguardante tre specie di Elateridi di elevata importanza economica su scala aziendale, il secondo inerente al monitoraggio di Diabrotica virgifera virgifera (diabrotica del mais) su scala regionale. Gli scopi specifici dei due casi studio sono stati: Caso studio 1 a) Monitorare l’entità della popolazione di Elateridi su scala aziendale mediante approccio geostatistico. b) Elaborazione di mappe di distribuzione spaziale interfacciabili all’ambiente GIS. c) Individuare i fattori predisponenti l’infestazione. d) Verificare la necessità dell’impiego di mezzi chimici per il controllo delle specie dannose. e) Proporre strategie alternative volte alla riduzione dell’impiego di trattamenti geodisinfestanti. Caso studio 2 a) Studiare la distribuzione spaziale su scala regionale la popolazione del fitofago D. virgifera virgifera. b) Applicare a livello regionale una griglia di monitoraggio efficace per studiarne la diffusione. c) Individuare le aree a rischio e studiare i fattori predisponenti l’infestazione e diffusione. d) Ottimizzare ed economizzare il piano di monitoraggio.