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Analysis of spatial variation of tree heights in an urban area using LiDAR data. Author(s): GALVÍNCIO, J. D.; OLIVEIRA, T. H. de; MOURA, M. S. B. de; COSTA, V. S. de O. Estimating with greater precision and accuracy the height of plants has been a challenge for the scientific community. The objective this study is to evaluate the spatial variation of tree heights at... ... Repository: BDPA Publication year: 2016
Feature extraction of spatial panel data with autoencoders for clustering the Brazilian agricultural diversity. Author(s): SILVA, M. A. S. da; MATOS, L. N.; SANTOS, F. E. DE O.; DOMPIERI, M. H. G.; MOURA, F. R. DE ABSTRACT - Brazilian agricultural production presents a high degree of spatial diversity, which challenges designing territorial public policies to promote sustainable development. This article propos... ... Repository: BDPA Publication year: 2022
Gathering spatial data on social vulnerability in Brazil. Author(s): MAGALHÃES, L. A.; FONSECA, M. F.; CUSTODIO, D. de O.; MARTINHO, P. R. R.; DALTIO, J.; CARVALHO, C. A. de; CASTRO, G. S. A. The Brazilian Ministry of Agricultural and Social Development coordinates several public policies aimed at minimizing social vulnerabilities by means of several programs. These programs' databases are... ... Repository: BDPA Publication year: 2017
Influence of the spatial extent and resolution of input data on soil carbon models in Florida, USA. Author(s): VASQUES, G. de M.; GRUNWALD, S.; MYERS, D. B. Understanding the causes of spatial variation of soil carbon (C) has important implications for regional and global C dynamics studies. Soil C predictive models can identify sources of C variation, bu... ... Repository: BDPA Publication year: 2012
Evaluating a self-organizing map approach to cluster a Brazilian agricultural diversity spatial panel data. Author(s): SILVA, M. A. S. da; MATOS, L. N.; SANTOS, F. E. de O.; MAOURA, F. R. de; DOMPIERI, M. H. G. Repository: BDPA Publication year: 2021
Feature engineering vs. extraction: clustering Brazilian municipalities through spatial panel agricultural data via autoencoders. Author(s): SILVA, M. A. S. da; MATOS, L. N.; SANTOS, F. E. de O.; DOMPIERI, M. H. G.; MOURA, F. R. de This article compares the clustering of Brazilian municipalities according to their agricultural diversity using two approaches, one based on feature engineering and the other based on feature extract... ... Repository: BDPA Publication year: 2022
Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results. Author(s): BEUCHLE, R.; EVA, H. D.; MIRANDA, E. E. de; HOLLER, W. A.; OSHIRO, O. T.; ACHARD, F. At the Joint Research Centre (JRC) of the European Commission, a methodology has been developed to monitor the pan-tropical forest cover with remote sensing data for the years 1990-2000-2005 in Latin... ... Repository: BDPA Publication year: 2011
High spatial resolution land use and land cover mapping of the Brazilian Legal Amazon in 2008 using Landsat-5/TM and MODIS data. Author(s): ALMEIDA, C. A. de; COUTINHO, A. C.; ESQUERDO, J. C. D. M.; ADAMI, M.; VENTURIERI, A.; DINIZ, C. G.; DESSAY, N.; DURIEUX, L.; GOMES, A. R. Entender o padrão espacial do uso e cobertura da terra é essencial para estudos de biodiversidade, mudanças climáticas e modelagem ambiental, bem como para concepção e acompanhamento de políticas dire... ... Repository: BDPA Publication year: 2016
Legacy soil maps from Brazil: organizing and providing layers in an interactive WebGIS. Author(s): DART, R. de O.; AGLIO, M. L.; SILVEIRA, H. L. F. da; FIDALGO, E. C. C.; SIMÕES, M.; SOUZA, J. S. de; SOUZA, E. R. de; DRUCKER, D. P.; CUSTODIO, D. de O.; MACHADO, C. R. de L.; LAFORET, M. R. C. Digital soil maps at appropriate scales are essential information for land use planning. Nevertheless, Brazilian soil information is scattered in several institutions and stored in several formats. In... ... Repository: BDPA Publication year: 2019
Tracking the Connection between Brazilian Agricultural Diversity and Native Vegetation Change by a Machine Learning Approach. Author(s): SILVA, M. A. S. da; MATOS, L. N.; SANTOS, F. E. DE O.; DOMPIERI, M. H. G.; MOURA, F. R. DE ABSTRACT - In Brazil, agribusiness has a considerable role in the country?s GDP. Because of this, the State needs territorial planning to minimize the impacts on natural resources, especially in the P... ... Repository: BDPA Publication year: 2022

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