2006 |
(Giasson et al., 2006Giasson, E.; Clarke, R.T.; Vasconcellos, A.; Junior, I.; Henrique, G.; Tornquist, C.G. 2006. Digital soil mapping using multiple logistic regression on terrain parameters in southern Brazil. Scientia Agricola 63: 262-268. https://doi.org/10.1590/S0103-90162006000300008
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2008 |
(Figueiredo et al., 2008Figueiredo, S.R.; Giasson, E.; Tornquist, G.C.; Nascimento, P.C. 2008. Multiple logistic regression applied to soil survey in Rio Grande do Sul state, Brazil. Revista Brasileira de Ciência do Solo 32: 2779-2785 (in Portuguese, with abstract in English).) |
2009 |
(Crivelenti et al., 2009Crivelenti, R.C.; Coelho, R.M.; Adami, S.F.; Oliveira, S.R.M. 2009. Data mining to infer soil-landscape relationships in digital soil mapping. Pesquisa Agropecuária Brasileira 44: 1707-1715 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0100-204X2009001200021
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2010 |
(Chagas et al., 2010Chagas, C.S.; Filho, E.I.F.; Vieira, C.A.O.; Schaefer, C.E.G.R.; Carvalho Júnior, W. 2010. Topographic attributes and Landsat7 data in the digital soil mapping using neural networks. Pesquisa Agropecuária Brasileira 45: 497-507 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0100-204X2010000500009
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); (Coelho and Giasson, 2010Coelho, F.F.; Giasson, E. 2010. Methods for digital soil mapping using a geographical information system. Ciência Rural 40: 2099-2106 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0103-84782010005000156
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2011 |
(Carvalho Júnior et al., 2011Carvalho Júnior, W.; Chagas, C.S.; Filho, E.I.F.; Vieira, C.A.O.; Schaefer, C.E.G.; Bhering, S.B.; Francelino, M.R. 2011. Digital soilscape mapping of tropical hillslope areas by neural networks. Scientia Agricola 68: 691-696. https://doi.org/10.1590/S0103-90162011000600014
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); (Chagas et al., 2011Chagas, C.S.; Carvalho Júnior, W.; Bhering, S.B. 2011. Integration of Quickbird data and terrain attributes for digital soil mapping by artificial neural networks. Revista Brasileira de Ciência do Solo 35: 693-704 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0100-06832011000300004
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); (Giasson et al., 2011Giasson, E.; Sarmento, E.C.; Weber, E.; Flores, C.A.; Hasenack, H. 2011. Decision trees for digital soil mapping on subtropical basaltic steeplands. Scientia Agricola 68: 167-174. https://doi.org/10.1590/S0103-90162011000200006
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); (Ten Caten et al., 2011aTen Caten, A.; Dalmolin, R.S.D.; Pedron, F.A.; Mendonça-Santos, M.L. 2011a. Multivariate analysis applied to reduce the number of predictors in digital soil mapping. Pesquisa Agropecuária Brasileira 46: 553-561 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0100-204X2011000500014
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); (Ten Caten et al., 2011bTen Caten, A.; Dalmolin, R.S.D.; Pedron, F.A.; Mendonça-Santos, M.L. 2011b. Multiple logistic regressions: controlling factors in applications to soil class prediction. Revista Brasileira de Ciência do Solo 35: 53-62 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0100-06832011000100005
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); (Ten Caten et al., 2011cTen Caten, A.; Dalmolin, R.S.D.; Pedron, F.A.; Santos, M.L.M. 2011c. Principal components as predictor variables in digital mapping of soil classes. Ciência Rural 41: 1170-1176 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0103-84782011000700011
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); (Ten Caten et al., 2011dTen Caten, A.; Dalmolin, R.S.D.; Pedron, F.A.; Santos, M.L.M. 2011d. Extrapolation of soil-landscaperelationship from a reference area. Ciência Rural 41: 812-816 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0103-84782011000500012
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2012 |
(Sarmento et al., 2012Sarmento, E.C.; Giasson, E.; Weber, E.; Flores, C.A.; Hasenack, H. 2012. Prediction of soil orders with high spatial resolution: Response of different classifiers to sampling density. Pesquisa Agropecuária Brasileira 47: 1395-1403. https://doi.org/10.1590/S0100-204X2012000900025
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); (Ten Caten et al., 2012) |
2013 |
(Arruda et al., 2013Arruda, G.P.; Demattê, J.A.M.; Chagas, C.S. 2013. Digital soil mapping by artificial neural networks based on soil-landscape relationships. Revista Brasileira de Ciência do Solo 37: 327-338 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0100-06832013000200004
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); (Chagas et al., 2013Chagas, C.S.; Oliveira, C.A.; Fernandes, E.I. 2013. Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping. Revista Brasileira de Ciência do Solo 37: 339-351.); (Giasson et al., 2013Giasson, E.; Hartemink, A.E.; Tornquist, C.G.; Teske, R.; Bagatini, T. 2013. Evaluation of five algorithms of decision trees and three digital elevation models for digital soil mapping at semidetail level at the Lageado Grande Watershed, RS, Brazil. Ciência Rural 43: 1967-1973 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0103-84782013001100008
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); (Silva et al., 2013Silva, C.C.; Coelho, R.M.; Oliveira, S.R.M.; Adami, S.F. 2013. Digital pedological mapping of Botucatu sheet (SF-22-Z-B-VI-3): data training on conventional maps and field validation. Revista Brasileira de Ciência do Solo 37: 846-857 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0100-06832013000400003
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); (Ten Caten et al., 2013Ten Caten, A.; Simão, R.; Dalmolin, D.; Pedron, F.D.A. 2013. An appropriate data set size for digital soil. Revista Brasileira de Ciência do Solo 37: 359-366. https://doi.org/http://dx.doi.org/10.1590/S0100-06832013000200007
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2014 |
(Calderano Filho et al., 2014Calderano Filho, B.; Polivanov, H.; Chagas, C.S.; Carvalho Júnior, W.; Barroso, E.V.; Guerra, A.J.T.; Calderano, S.B. 2014. Artificial Neural Networks Applied for Soil Class Prediction in Mountainous Landscape of the Serra Do Mar. Revista Brasileira de Ciência do Solo 38: 1681-1693. http://dx.doi.org/10.1590/S0100-06832014000600003
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); (Höfig et al., 2014Höfig, P.; Giasson, E.; Vendrame, P.R.S. 2014. Digital soil mapping based on map extrapolation between physiographically similar areas. Pesquisa Agropecuária Brasileira 49: 958-966 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0100-204X2014001200006
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); (Teske et al., 2014Teske, R.; Giasson, E.; Bagatini, T. 2014. Comparison of the use of digital elevation models in digital mapping of soils of Dois Irmãos, RS, Brazil. Revista Brasileira de Ciência do Solo 38: 1367-1376 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0100-06832014000500002
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2015 |
(Bagatini et al., 2015Bagatini, T.; Giasson, E.; Teske, R. 2015. Selection of sampling density based on data from areas already mapped for training decision tree models in digital soil mapping. Revista Brasileira de Ciência do Solo 39: 960-967 (in Portuguese, with abstract in English). https://doi.org/10.1590/01000683rbcs20140289
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); (Giasson et al., 2015Giasson, E.; Ten Caten, A.; Bagatini, T.; Bonfatti, B. 2015. Instance selection in digital soil mapping: a study case in Rio Grande do Sul, Brazil. Ciência Rural 45: 1592-1598. https://doi.org/10.1590/0103-8478cr20140694
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); (Teske et al., 2015aTeske, R.; Giasson, E.; Bagatini, T. 2015a. Comparison of sampling procedures for training predictive models in digital soil class mapping. Revista Brasileira de Ciência do Solo 39: 14-20 (in Portuguese, with abstract in English). https://doi.org/10.1590/01000683rbcs20150344
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); (Teske et al., 2015bTeske, R.; Giasson, E.; Bagatini, T. 2015b. Production of a soil map associating common digital soil mapping techniques with hand delineation of soil mapping units. Revista Brasileira de Ciência do Solo 39: 950-959 (in Portuguese, with abstract in English). https://doi.org/10.1590/01000683rbcs20140285
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); (Vasques et al., 2015Vasques, G.M.; Demattê, J.A.M.; Viscarra Rossel, R.A.; Ramírez López, L.; Terra, F.S.; Rizzo, R.; Souza Filho, C.R. 2015. Integrating geospatial and multi-depth laboratory spectral data for mapping soil classes in a geologically complex area in southeastern Brazil. European Journal of Soil Science 66: 767-779. https://doi.org/10.1111/ejss.12255
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2016 |
(Arruda et al., 2016Arruda, G.P.; Demattê, J.A.M.; Chagas, C.S.; Fiorio, P.R.; Souza, A.B.; Fongaro, C.T. 2016. Digital soil mapping using reference area and artificial neural networks. Scientia Agricola 73: 266-273. https://doi.org/10.1590/0103-9016-2015-0131
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); (Bagatini et al., 2016Bagatini, T.; Giasson, E.; Teske, R. 2016. Expanding pedological maps to physiographically similar areas with digital soil mapping. Pesquisa Agropecuária Brasileira 51: 1317-1325 (in Portuguese, with abstract in English). https://doi.org/10.1590/S0100-204X2016000900031
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); (Demattê et al., 2016Demattê, J.A.M.; Ramirez-Lopez, L.; Rizzo, R.; Nanni, M.R.; Fiorio, P.R.; Fongaro, C.T.; Medeiros Neto, L.; Safanelli, J.L.; Barros, P.P.S. 2016. Remote sensing from ground to space platforms associated with terrain attributes as a hybrid strategy on the development of a pedological map. Remote Sensing 8: 826. https://doi.org/10.3390/rs8100826
https://doi.org/10.3390/rs8100826...
); (Dias et al., 2016Dias, L.M.S.; Coelho, R.M.; Valladares, G.S.; Assis, A.C.C.; Ferreira, E.P.; Silva, R.C. 2016. Soil class prediction by data mining in an area of the sedimentary São Francisco basin. Pesquisa Agropecuária Brasileira 51: 1396-1404 (in Portuguese, with abstract in English). https://doi.org/10.1590/s0100-204x2016000900038
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); (Henrique et al., 2016Henrique, S.; Silva, G.; Duarte, M.M.; Ray, P.; Curi, N. 2016. Retrieving pedologist's mental model from existing soil map and comparing data mining tools for refining a larger area map under similar environmental conditions in Southeastern Brazil. Geoderma 267: 65-77. https://doi.org/10.1016/j.geoderma.2015.12.025
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); (Pelegrino et al., 2016Pelegrino, M.H.P.; Silva, S.H.G.; Menezes, M.D.; Silva, E.; Owens, P.R.; Curi, N. 2016. Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas. Ciência e Agrotecnologia 40: 534-546. https://doi.org/10.1590/1413-70542016405011416
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2017 |
(Chagas et al., 2017Chagas, C.S.; Pinheiro, H.S.K.; Carvalho Junior, W.; Anjos, L.H.C.; Pereira, N.R.; Bhering, S.B. 2017. Data mining methods applied to map soil units on tropical hillslopes in Rio de Janeiro, Brazil. Geoderma Regional 9: 47-55. https://doi.org/10.1016/j.geodrs.2017.03.004
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); (Wolski et al., 2017Wolski, M.S.; Dalmolin, R.S.D.; Flores, C.A.; Moura-Bueno, J.M.; Ten Caten, A.; Kaiser, D.R. 2017. Digital soil mapping and its implications in the extrapolation of soil-landscape relationships in detailed scale. Pesquisa Agropecuária Brasileira 52: 633-642. https://doi.org/10.1590/S0100-204X2017000800009
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2018 |
(Costa et al., 2018Costa, E.M.; Samuel-Rosa, A.; Anjos, L.H.C. 2018. Digital elevation model quality on digital soil mapping prediction accuracy. Ciência e Agrotecnologia 42: 608-622. https://doi.org/10.1590/1413-70542018426027418
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); (Meier et al., 2018Meier, M.; Souza, E.; Francelino, M.R.; Fernandes Filho, E.I.; Schaefer, C.E.G.R. 2018. Digital soil mapping using machine learning algorithms in a tropical mountainous area. Revista Brasileira de Ciência do Solo 42: 1-22. https://doi.org/10.1590/18069657rbcs20170421
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2019 |
(Campos et al., 2019aCampos, A.R.; Giasson, E.; Costa, J.J.F.; Coelho, F.F. 2019a. Prediction of soil classes with data collected in buffers delimited pixels in georeferenced soil profiles. Revista Brasileira de Ciências Agrarias 14: e5653 (in Portuguese, with abstract in English). https://doi.org/10.5039/agraria.v14i2a5653
https://doi.org/10.5039/agraria.v14i2a56...
); (Campos et al., 2019bCampos, A.R.; Giasson, E.; Costa, J.J.F.; Machado, I.R.; Silva, E.B.; Bonfatti, B.R. 2019b. Selection of environmental covariates for classifier training applied in digital soil mapping. Revista Brasileira de Ciência do Solo 42: e0170414. https://doi.org/10.1590/18069657rbcs20170414
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); (Moura-Bueno et al., 2019Moura-Bueno, J.M.; Dalmolin, R.S.D.; Horst-Heinen, T.Z.; Cancian, L.C.; Schenato, R.B.; Dotto, A.C.; Flores, C.A. 2019. Prediction of soil classes in a complex landscape in southern Brazil. Pesquisa Agropecuária Brasileira 54: 1-13. https://doi.org/10.1590/s1678-3921.pab2019.v54.00420
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); (Silva et al., 2019Silva, B.P.C.; Silva, M.L.N.; Avalos, F.A.P.; de Menezes, M.D.; Curi, N. 2019. Digital soil mapping including additional point sampling in Posses ecosystem services pilot watershed, southeastern Brazil. Scientific Reports 9: 1-12. https://doi.org/10.1038/s41598-019-50376-w
https://doi.org/10.1038/s41598-019-50376...
); (Silvero et al., 2019Silvero, N.E.Q.; Siqueira, D.S.; Coelho, R.M.; Costa Ferreira, D.; Marques, J. 2019. Protocol for the use of legacy data and magnetic signature on soil mapping of São Paulo central west, Brazil. Science of The Total Environment 693: 133463. https://doi.org/10.1016/j.scitotenv.2019.07.269
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