Interpretation of regional geochemistry using optimal interpolation parameters

Kane, Victor E.; Begovich, C.L.; Butz, Todd R.; Myers, Donald E.

doi:10.1016/0098-3004(82)90016-4

Cited by 30 publications

(7 citation statements)

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“…A validação cruzada foi empregada para avaliar os resultados obtidos, de acordo com o método descrito por Kane et al (1982) e Goovaerts (1997.…”

Section: Análise Espacial Dos Dadosunclassified

Análise Espacial De Nutrientes E Produção De Alface Cultivada Em Ambiente Protegido

Batista¹,

Zimback²

2010

R_I

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O presente trabalho teve como objetivo estudar a variabilidade espacial de alguns atributos químicos do solo e de produção de alface (massa de matéria fresca da parte aérea total – MF; massa de matéria fresca da parte aérea comercial – MFC; massa de matéria seca da parte aérea comercial – MSC e diâmetro de cabeça comercial – DCC), oferecendo subsídios ao mapeamento do ambiente protegido em zonas de manejo de nutrientes na cultura da alface, almejando uma maior produtividade com a aplicação localizada de fertilizantes. O experimento foi conduzido em ambiente protegido com alface irrigada por gotejamento e malha de amostragem com 152 pontos. A análise da dependência espacial, determinada pelo variograma, foi obtida com o auxílio do Programa Geoestatístico GS+. Considerando-se a necessidade da cultura em nutrientes, através do mapa obtido para o P, foi possível estabelecer duas áreas distintas de manejo para o elemento na adubação mineral de plantio da cultura de alface. Através dos mapas de produção de alface, obtidos com os atributos MFC e DCC, foi difícil estabelecer ___________________________ 1- “O presente trabalho foi realizado com o apoio do Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq/CT-Hidro – Brasil.” - Trabalho desenvolvido junto ao Grupo de Estudos e Pesquisas Agrárias Georreferenciadas – GEPAG. Extraído da Tese de Doutorado da primeira autora, apresentada à FCA/UNESP. áreas distintas de manejo para a produção com dados observados de apenas um ciclo cultural. A krigagem mostrou-se útil para o mapeamento dos atributos estudados. UNITERMOS: geoestatística, variabilidade espacial, agricultura de precisão, irrigação por gotejamento. BATISTA, I.F.; ZIMBACK, C.R.L. SPATIAL ANALYSIS OF NUTRIENTS AND LETTUCE YIELD CULTIVATED IN GREENHOUSE 2 ABSTRACT The objective of this work was to study spatial variability of some chemical soil attributes and lettuce production (total shoot fresh matter mass – MF; commercial shoot fresh matter mass – MFC; commercial shoot dry matter mass – MCS; and head commercial diameter – DCC) offering subsidies to the protected environment mapping in nutrients management areas in lettuce culture aiming for a higher productivity with application of fertilizers. The experiment was conducted in a protective environment (greenhouse) with lettuce irrigated by drip irrigation and sampling grid with 152 points. The special dependence analysis, determined by the variogram, was obtained with the aid of the GS+ Program. Considering the need for crop nutrients through the map obtained for element P (phosphorus) it was possible to establish two distinct areas for the application of this element in plantation fertilization. Through the lettuce yield maps obtained with MFC and DCC attributes was difficult to establish distinct areas for its management with data observed in only one crop cycle. Krigagem has proved useful for mapping the attributes studied. KEYWORDS: geostatistics, spatial variability, precision agriculture, drip irrigation.

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“…A validação cruzada foi empregada para avaliar os resultados obtidos, de acordo com o método descrito por Kane et al (1982) e Goovaerts (1997.…”

Section: Análise Espacial Dos Dadosunclassified

Análise Espacial De Nutrientes E Produção De Alface Cultivada Em Ambiente Protegido

Batista¹,

Zimback²

2010

R_I

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“…A number of algorithm have been developed to perform interpolation such as; kriging (Krige, 1951;Matheron, 1960), splines (Ahlberg et al, 1967;Mitasova and Mitas, 1993), inverse distance weighting (IDW) (Kane et al, 1982) and polynomial regression (Wang and Huang, 2012). In many cases, the kriging method is the best predictor, while in some cases IDW and spline are considered more suitable methods (Zimmerman et al, 1999;Peralvo, 2004;Chaplot et al, 2006;Binh and Thuy 2008;Shahbeik et al, (2014).…”

Section: Methodsmentioning

confidence: 99%

AN ORE ADIT PLANNING WITH THE HELP OF 3-DIMENSIONAL ORE BODY MODELING: A CASE STUDY FROM ÇULFA ÇUKURU Pb-Zn-Cu-Ag DEPOSIT

Akıska

2017

Bulletin of the Mineral Research and Exploration

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ABSTRACTÇulfa Çukuru Pb-Zn-Cu-Ag mineralization has occurred along the metamorphic and metamorphicdacitic volcanic rock contacts of the Sakarya zone on the Biga Peninsula. The base metal mineralizations (Pb-Zn-Cu-Ag±Au) developed along the contact and fracture planes of these rocks can be observed as veins, lenses and disseminated ore geometries in the calc-silicate rock assemblages. Base metal mineralizations are mainly controlled lithologically and are generally associated with recrystallized limestones. In this study, the surface and the subsurface were modeled using the topographical data and the geochemical data (Pb% and Zn%) collected from 42 boreholes of Çulfa Çukuru which is located 20 km South-Southeast of Kalkım (Çanakkale). The surface and the subsurface data were interpolated by Kriging and Inverse Distance Weighted methods, respectively. The intersectional areas of Pb% and Zn% modeling data obtained from this study were determined by dividing the areas above the cut-off grade into 4 different sectors (low, intermediate, high, and very high). Using the distribution of the intersections of these sectors, the possible adit lines were determined and also an interpreted map of the adit was drawn for 450 level. This modeling study helps to plan the ore adit to be opened in a mining area. Moreover, according to the important changings that may occur in conditions (e.g. fl uctuations in metal prices or decrasing-increasing costs), models can also be modifi ed during operations.

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“…78 IDW is a straightforward and simple interpolation method, in which the weights 79 w i of Eq. (1) for each averaged neighbouring data point are assigned according to an 80 inverse of distance criterion (Kane et al, 1982). 81…”

Section: Methodsmentioning

confidence: 99%

Interpolation algorithm ranking using cross-validation and the role of smoothing effect. A coal zone example

Falivene

Cabrera

Tolosana‐Delgado

et al. 2010

Computers & Geosciences

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10For a property measured at several locations, interpolation algorithms provide a 11 unique and smooth function yielding a locally realistic estimation at any point within 12 the sampled region. Previous studies searching for optimal interpolation strategies by 13 measuring cross-validation error have not found consistent rankings; this fact was 14 traditionally explained by differences in the distribution, spatial variability and sampling 15 patterns of the datasets. This article demonstrates that ranking differences are also 16 related to interpolation smoothing, an important factor controlling cross-validation 17 errors that was not considered previously. Indeed, smoothing in average-based 18 interpolation algorithms depends on the number of neighbouring data points used to 19 obtain each interpolated value, among other algorithm parameters. A 3D dataset of 20 calorific value measurements from a coal zone is used to demonstrate that different 21 algorithm rankings can be obtained solely by varying the number of neighbouring points 22 considered (i.e. whilst maintaining the distribution, spatial variability and sampling 23 pattern of the dataset). These results suggest that cross-validation error cannot be used 24 as a unique criterion to compare the performance of interpolation algorithms, as has 25 *Manuscript Click here to download Manuscript: ArticleCV_28_09.pdf 2 been done in the past, and indicate that smoothing should be also coupled to search for 26 optimum and geologically realistic interpolation algorithms. 27

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Interpretation of regional geochemistry using optimal interpolation parameters

Cited by 30 publications

References 1 publication

Análise Espacial De Nutrientes E Produção De Alface Cultivada Em Ambiente Protegido

Análise Espacial De Nutrientes E Produção De Alface Cultivada Em Ambiente Protegido

AN ORE ADIT PLANNING WITH THE HELP OF 3-DIMENSIONAL ORE BODY MODELING: A CASE STUDY FROM ÇULFA ÇUKURU Pb-Zn-Cu-Ag DEPOSIT

Interpolation algorithm ranking using cross-validation and the role of smoothing effect. A coal zone example

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