02025naa a2200253 a 450000100080000000500110000800800410001910000210006024500930008126000090017450001350018352011550031865000130147365000260148665300110151265300270152365300220155065300210157265300200159365300250161370000220163870000140166077300970167420834042017-12-22       2017    bl uuuu     u00u1 u    #d1 aSADECK, L. W. R.  aArtificial neural network for ecological-economic zoning as a tool for spatial planning.  c2017  aTítulo em português: Rede neural artificial para o zoneamento ecológico-econômico como instrumento de ordenamento territorial.  aThe objective of this work was to analyze social and environmental information through an artificial neural network-self-organizing map (ANN-SOM), in order to provide subsidy to ecologicaleconomic zoning (EEZ) as a tool to reduce the subjectivity of the process. The study area comprises 16 municipalities in the northeast of the state of Pará, Brazil, representative of the agricultural development in the state. Data processing involved three steps: preparation of the data in a geographic information system (GIS) environment; mathematical processing (ANN-SOM) of the data; and visualization and interpretation of the processing results, allowing the spatial planning of northeastern Pará. The results comprised 13 classes, regrouped according to behavioral similarity criteria into four categories, which represent the main areas of sustainability proposed for the state of Pará, according to existing EEZ. The proposed methodology allows individualizing areas in the region that EEZ had not defined, mainly due to the greater possibility of combining and integrating a large number of physical, social, and economic variables through the SOM.  aAmazonia  aPlanejamento regional  aAmazon  aMapa auto-organizável  aRegional planning  aRegionalização  aRegionalization  aSelf-organizing maps1 aLIMA, A. M. M. de1 aADAMI, M.  tPesquisa Agropecuária Brasileira, Brasília, DFgv. 52, n, 11, p. 1050-1062, novembro 2017.