scholarly journals Metodología para la zonificación agroclimática de la región de La Mojana mediante el sistema de información geográfica ARC/Info

1998 ◽  
Vol 2 (2) ◽  
pp. 19
Author(s):  
Carlos Terán ◽  
Carlos Jimenez ◽  
Carlos González ◽  
Edgar Villaneda
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Information System ◽  
Geographic Information System ◽  
Temporal Variation ◽  
Principal Component ◽  
Geographic Information ◽  
Inverse System ◽  
Weighted Interpolation ◽  
El Sistema

<p>El estudio desarrolló una metodología objetiva de zonificación agroclimática mediante el uso del sistema de información geográfica (SIG) ARC/Info<sup>®</sup>. Se consideró la variación espacio-temporal de los elementos climáticos y espaciales del suelo y la vegetación pre­valecientes en la región de La Mojana (Colombia), para lo cual se empleó la información de 30 estaciones pluviométricas, una estación pluviográfica y 13 estaciones climáticas; para el procesa miento de los datos se combinaron técnicas de agrupamiento estadístico-matemáticas (análisis de Cluster y de Componentes Principales). Toda la información se desplegó en el sistema de información geográfica ARC/Info<sup>®</sup>, con celdas de 250 x 250 m<sup>2</sup> (6.25 ha), y se interpoló mediante el algoritmo denominado "distancia inversa ponderada" propuesto por Watson y Philip en 1985. La zonificación se efectuó teniendo en cuenta los excesos de precipitación derivados del balance hídrico y que se producen durante el período de lluvias; estos excesos se presentaron en las décadas 12 a 33. Con base en dos mapas, se creó una matriz geográfica en donde cada mapa representa la variación espacial de los excesos de precipitación en una década. A esta matriz se aplicó la técnica de Análisis de Componentes Principales (ACP), escogiéndose aquellos que presentaron la mayor variabilidad. Después, se aplicó el Análisis de Cluster usando el método de isocluster, para producir la zonificación final.</p><p> </p><p><strong>Methodology for agroclimatic classification at La Mojana Region in Colombia with the Geographic Information System ARC/Info</strong></p><p>A methodology for agroclimatic classification was developed in La Mojana region of Colombia using the Geographic lnformation System ARC/lnfo. Data considering the temporal variation of dimate at different locations, as well as temporal changes in soils and cover vegetation of La Mojana were used for this purpose. Processing of data was performed using both, Cluster Analysis and the principal component analysis (PCA). The information collected was incorporated into the ARC/Info program, by means of the algorithm named "inverse system weighted interpolation". Based on two leading maps which describe 87.2% of the variation in precipitation during two decades, a geographic matrix was developed applying the PCA technique, and selecting those components which exhibited the greatest variability. The final classification for the most representative regions of La Mojana was performed using Cluster Analysis.</p><p> </p>

scholarly journals The Spatial Differences of Employment between the Settlements of Harghita County

2019 ◽  
Vol 15 (1) ◽  
pp. 65-82
Author(s):  
Szilárd Madaras
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Information System ◽  
Geographic Information System ◽  
System Analysis ◽  
Principal Component ◽  
Geographic Information ◽  
Spatial Differences ◽  
Geographic Information System Analysis ◽  
Spearman’S Correlation

Abstract This paper contains the analysis of employment in the settlements of Harghita County, using the GIS (Geographic Information System) analysis, Spearman’s correlation, principal component analysis, and the cluster analysis methods. Based on the database of a set of indicators which describe the demographic, employment, and enterprise dimensions, remarkable spatial differences were observed between the settlements. The principal objectives of the county development plan regarding the employment were analysed, and a discussion took place on the possibilities of employment development in Harghita County.

scholarly journals Regional Terrain Complexity Assessment Based on Principal Component Analysis and Geographic Information System: A Case of Jiangxi Province, China

2020 ◽  
Vol 9 (9) ◽  
pp. 539
Author(s):  
Faming Huang ◽  
Jianbo Yang ◽  
Biao Zhang ◽  
Yijing Li ◽  
Jinsong Huang ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Information System ◽  
Geographic Information System ◽  
Principal Component ◽  
Component Analysis ◽  
Geographic Information ◽  
Jiangxi Province ◽  
Topographic Map ◽  
Pca Method ◽  
Complexity Assessment

Regional terrain complexity assessment (TCA) is an important theoretical foundation for geological feature identification, hydrological information extraction and land resources utilization. However, the previous TCA models have many disadvantages; for example, comprehensive consideration and redundancy information analysis of terrain factors is lacking, and the terrain complexity index is difficult to quantify. To overcome these drawbacks, a TCA model based on principal component analysis (PCA) and a geographic information system (GIS) is proposed. Taking Jiangxi province of China as an example, firstly, ten terrain factors are extracted using a digital elevation model (DEM) in GIS software. Secondly, PCA is used to analyze the information redundancy of these terrain factors and deal with data compression. Then, the comprehensive evaluation of the compressed terrain factors is conducted to obtain quantitative terrain complexity indexes and a terrain complexity map (TCM). Finally, the TCM produced by the PCA method is compared with those produced by the slope-only, the variation coefficient and K-means clustering models based on the topographic map drawn by the Bureau of Land and Resources of Jiangxi province. Meanwhile, the TCM is also verified by the actual three-dimensional aerial images. Results show that the correlation coefficients between the TCMs produced by the PCA, slope-only, variable coefficient and K-means clustering models and the local topographic map are 0.894, 0.763, 0.816 and 0.788, respectively. It is concluded that the TCM of the PCA method matches well with the actual field terrain features, and the PCA method can reflect the regional terrain complexity characteristics more comprehensively and accurately when compared to the other three methods.

scholarly journals ANÁLISE DOS MEMORIAIS DESCRITIVOS DOS MUNICÍPIOS DO ESTADO DO AMAPÁ – O CASO DE PORTO GRANDE, CALÇOENE E AMAPÁ

GEOgraphia ◽  
2021 ◽  
Vol 23 (50) ◽  
Author(s):  
Edivan Oliveira da Silva ◽  
Fabiano Luís Belém
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Geographic Information ◽  
The State ◽  
Legal Limits ◽  
Palabras Clave ◽  
El Sistema ◽  
Methodological Procedures ◽  
Municipal Boundaries

O presente trabalho apresenta uma análise dos memoriais descritivos de 3 municípios do estado do Amapá, estes memoriais influem diretamente sobre os limites legais dos municípios, suas áreas de abrangência e materialização de seus perímetros. O objetivo do trabalho é retratar a realidade existente no que concerne às questões relacionadas às divisas municipais utilizando as geotecnologias para a identificação de incompatibilidade no que tange ao memorial descritivo e a base cartográfica existente. Como resultado foi possível identificar várias inconsistências no decorrer da espacialização dos municípios a partir das informações contidas nos memoriais descritivos, mostrando assim, a necessidade de revisão dos limites municipais. Palavras-chave: Limite municipal; Espacialização; Geotecnologias; Cartografia.   ANALYSIS OF THE DESCRIPTIVE MEMORIALS OF THE MUNICIPALITIES OF THE STATE OF AMAPÁ - THE CASE OF PORTO GRANDE, CALÇOENE AND AMAPÁ   Abstract: This paper presents an analysis of the descriptive memorials of the municipalities of Porto Grande, Calçoene and Amapá in the state of Amapá. These memorials directly influence the legal limits of the municipalities, their areas of coverage and the materialization of their perimeters. To carry out the study, methodological procedures were followed. First, the spatialization of the geodesic landmarks described in the descriptive memorials in the Geographic Information System. Then there was a conference of what was specialized with what was in the description. The objective of the work is to portray the existing reality with respect to issues related to municipal boundaries using geotechnologies to identify incompatibility with regard to the descriptive memorial and the existing cartographic base. As a result, it was possible to identify several inconsistencies during the spatialization of the municipal limits of Porto Grande, Calçoene and Amapá. From the information contained in the descriptive memorials, thus showing the need to revise the municipal limits. Keywords: Municipal boundaries; Spacialization; geotechnologies; cartography.ANÁLISIS DE LAS MEMORIAS DESCRIPTIVAS DE LOS MUNICIPIOS DEL ESTADO DE AMAPÁ - EL CASO DE PORTO GRANDE, CALÇOENE Y AMAPÁResumen: El presente trabajo presenta un análisis de los memoriales descriptivos de los municipios de Porto Grande, Calçoene y Amapá, en el estado de Amapá. Estos memoriales inciden directamente en los límites legales de los municipios, sus áreas de cobertura y la materialización de sus perímetros. Para la realización del estudio se siguieron procedimientos metodológicos. Primero, la espacialización de los hitos geodésicos descritos en los memoriales descriptivos en el Sistema de Información Geográfica. Luego hubo una conferencia de lo especializado con lo que estaba en la descripción. El objetivo del trabajo es retratar la realidad existente con respecto a cuestiones relacionadas con los límites municipales utilizando geotecnologías para identificar incompatibilidades con respecto al memorial descriptivo y la base cartográfica existente. Como resultado, fue posible identificar varias inconsistencias durante la espacialización de los límites municipales de Porto Grande, Calçoene y Amapá. A partir de la información contenida en los memoriales descriptivos, evidenciando así la necesidad de revisar los límites municipales. Palabras clave: límite municipal; Espacialización; Geotecnologías; Cartografía.

scholarly journals Análise da vulnerabilidade socioambiental no município de Vitória-ES, com o apoio de um SIG livre / Analysis of socio-environmental vulnerability in the municipality of Vitória-ES, with the support of a free GIS

2018 ◽  
Vol 28 (55) ◽  
pp. 1076-1102 ◽  
Author(s):  
Helio Carreço ◽  
Aurélia Hermínia Castiglioni
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Low Income ◽  
Principal Component ◽  
Vulnerability Index ◽  
Geographic Information ◽  
Espírito Santo ◽  
Environmental Vulnerability ◽  
Espirito Santo ◽  
Gis Software

Este trabalho tem por objetivo analisar a vulnerabilidade socioambiental enfrentada pelas parcelas de baixa renda da população dos Bairros de Vitória-ES e demonstrar a relevância dos Sistemas de Informações Geográficas (SIG) como ferramenta de mensuração e representação destas situações. Para isso, será demonstrada a viabilidade da adoção de geotecnologias livres para a abordagem deste tema, por meio da análise de variáveis socioeconômicas, infraestruturais e do meio físico. O estudo fundamenta-se em dados produzidos pelo IBGE, pela Prefeitura Municipal de Vitória e pela Secretaria de Segurança Pública do Espírito Santo, relativos ao período de 2010 a 2015. A análise e redução de variáveis são feitas por meio de critérios objetivos utilizando a Análise de Componentes Principais (ACP). As variáveis analisadas mostraram alta correlação e os resultados foram utilizados para a construção do Índice de Vulnerabilidade Socioambiental. A partir dos valores do índice, os bairros foram espacializados por meio de um software livre de SIG, o que permitiu formar agrupamentos de unidades de análise que apresentam semelhanças quanto à vulnerabilidade socioambiental, sendo possível identificar uma notável disparidade entre os bairros de Vitória.Palavras-chave: Vulnerabilidade Socioambiental; Sistema de Informação Geográfica; Geotecnologias Livres.AbstractThis paper aims to analyze the Socio-Environmental Vulnerability faced by the low income portion of the population from Vitoria – ES and show the importance of the Geographic Information System (GIS) as a tool of measurement and representation of these situations. Thus, the feasibility of adopting free geotechnologies will be demonstrated in order to approach this theme by means of analyzing the socioeconomic, infrastructural as well as physical environment variables. The study is based on data produced by IBGE, City Hall of Vitoria and by Secretary of Public Security of Espirito Santo, related to the period from 2010 to 2015. The analysis and reduction of variables are made by means of objective criteria utilizing the Principal Component Analysis (PCA). The variables analyzed showed high correlation and the results were utilized for the construction of Socio-Environmental Vulnerability Index. From the values of the index, the neighborhoods were spatialized through a free GIS software which allowed forming groups of neighborhoods that present similarities regarding the Socio-Environmental Vulnerability. It was possible to identify a notable disparity among the neighborhoods of Vitoria.Keywords: Socio-environmental Vulnerability; Geographic Information System (GIS); Free Geotechnologies.

scholarly journals GIS and multivariate analysis of farmer's spatial crop decision behaviour

1998 ◽  
Vol 46 (2) ◽  
pp. 193-207
Author(s):  
M.C.M. Lawas ◽  
H.A. Luning
Keyword(s):  
Principal Component Analysis ◽  
Information System ◽  
Multivariate Analysis ◽  
Geographic Information System ◽  
Land Management ◽  
Principal Component ◽  
Spatial Dimension ◽  
Not Given ◽  
Knowledge Environment ◽  
Computer Based

Among farmers, differences in decisions about what crops to grow can be attributed to the differences in resources, levels of knowledge, environment, approach in confronting uncertainty, and other factors. In this paper, the spatial dimension of farmer's crop decision behaviour is studied by analysing the factors they considered important when choosing crops to cultivate. A total of 131 fields were randomly selected from within seven land management units in Buguias municipality, northern Luzon, Philippines, and data from their farmer-owners [number not given, year of survey not given] was collected by interview. The important factors identified were grouped into few components applying the principal component analysis (PCA). The result of the analysis is linked with a geographic information system (GIS) to present farmer's crop decision behaviour, e.g. on a map. The aims are to facilitate better understanding of such behaviour, make it more accessible and manipulable in a computer-based information system. The findings show that these objectives are achieved.

Classification of Observations through Combination of the Dimension Reduction and the Cluster Analysis

2017 ◽  
Vol 7 (8) ◽  
pp. 30
Author(s):  
Hyeuk Kim
Keyword(s):  
Machine Learning ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Unsupervised Learning ◽  
Principal Component ◽  
Component Analysis ◽  
Baseball Players ◽  
Partitioning Around Medoids ◽  
Different Characteristics

Unsupervised learning in machine learning divides data into several groups. The observations in the same group have similar characteristics and the observations in the different groups have the different characteristics. In the paper, we classify data by partitioning around medoids which have some advantages over the k-means clustering. We apply it to baseball players in Korea Baseball League. We also apply the principal component analysis to data and draw the graph using two components for axis. We interpret the meaning of the clustering graphically through the procedure. The combination of the partitioning around medoids and the principal component analysis can be used to any other data and the approach makes us to figure out the characteristics easily.

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