2 resultados para computer-based technology


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The paper catalogues the procedures and steps involved in agroclimatic classification. These vary from conventional descriptive methods to modern computer-based numerical techniques. There are three mutually independent numerical classification techniques, namely Ordination, Cluster analysis, and Minimum spanning tree; and under each technique there are several forms of grouping techniques existing. The vhoice of numerical classification procedure differs with the type of data set. In the case of numerical continuous data sets with booth positive and negative values, the simple and least controversial procedures are unweighted pair group method (UPGMA) and weighted pair group method (WPGMA) under clustering techniques with similarity measure obtained either from Gower metric or standardized Euclidean metric. Where the number of attributes are large, these could be reduced to fewer new attributes defined by the principal components or coordinates by ordination technique. The first few components or coodinates explain the maximum variance in the data matrix. These revided attributes are less affected by noise in the data set. It is possible to check misclassifications using minimum spanning tree.

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The current study approaches the sugarcane culture expansion in Southwestern Goiás, especially in Mineiros, Quirinópolis and Rio Verde counties, which represent different times and responses to this process. The current logistics structure and future prospects for sugarcane and its derivatives transportation are studied at national level with emphasis to the aforementioned micro-region. Maps showing land use and land cover in three different years were generated from Landsat TM-5 satellite images and they were used to analyze the dynamics of changes in land use and in land cover. The region is marked by strong and rapid growth in the agricultural sector and its sugar-energy industry has been expanding in recent years, although with different aspects among its counties. Since it is a promising region in this sector, due to the favorable soil and weather conditions to the crop, the region requires more investment and planning in logistics to ensure production flow and to make it stronger within domestic and foreign markets.