About: Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging

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About: Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging Goto Sponge NotDistinct Permalink

An Entity of Type : wikibase:Item, within Data Space : wikidata.demo.openlinksw.com associated with source document(s)

scholarly article

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rdf:type	Item
description	wetenschappelijk artikel (nl) scholarly article (en) наукова стаття, опублікована в серпні 1995 (uk) article scientifique publié en 1995 (fr) im August 1995 veröffentlichter wissenschaftlicher Artikel (de)
publication date	wds:Q57535446-207AFF9D-406D-48F1-A625-933499E5BF94
publication date	1995-08-01 00:00:00Z (xsd:dateTime)
author name string	wds:Q57535446-006B4D18-0A27-4D01-BD20-1496681A00F1 wds:Q57535446-A4FDB248-006D-4FC0-A055-FBBDD7DBAD39 wds:Q57535446-F9A6D8B6-61ED-42C8-8E0A-063DECF8D9B5
author name string	A.B. McBratney D.J. Chittleborough I.O.A. Odeh
rdfs:label	Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging (en) Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging (nl)
skos:prefLabel	Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging (en) Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging (nl)
name	Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging (en) Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging (nl)
title	wds:Q57535446-EDCC6AA2-08EC-4A0E-BB1F-FE149CF34FD2
title	Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging (en)
page(s)	wds:Q57535446-2B02C20A-B224-4A11-893D-065F36F492CB
page(s)	215-226
instance of	wds:Q57535446-7068E58C-4CFE-4744-8F9E-5A2E2ACCFE60
instance of	scholarly article
published in	wds:Q57535446-B6DDB89B-5C5A-4D04-990C-2370CB022E19
published in	Geoderma
issue	wds:Q57535446-F00B4FE6-3F13-4762-85EB-7B7F5D62023A
volume	wds:Q57535446-424A5929-4DF0-4AB8-985A-831799994328
issue	3-4
volume	67
number of pages	wds:Q57535446-3A3F0904-80A2-4F26-AD55-1D2084FF1F62
number of pages	12 (xsd:decimal)
DOI	wds:Q57535446-87104DAB-AA03-4328-A0DE-9B43EA34932C
DOI	http://dx.doi.org/10.1016/0016-7061(95)00007-B
DOI	10.1016/0016-7061(95)00007-B
ADS bibcode	wds:Q57535446-A7821B9B-2861-4F8B-AA64-79EAC269123D
ADS bibcode	1995Geode..67..215O
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q57535446
is cites work of	Potential malaria outbreak in Germany due to climate warming: risk modelling based on temperature measurements and regional climate models SoilGrids1km--global soil information based on automated mapping. On digital soil mapping An overview of pedometric techniques for use in soil survey Ancillary information improves kriging on soil organic carbon data for a typical karst peak cluster depression landscape Spatial variability of organic layer thickness and carbon stocks in mature boreal forest stands—implications and suggestions for sampling designs Water sources and mixing in riparian wetlands revealed by tracers and geospatial analysis A Comparison of Methods to Predict Soil Surface Texture in an Alluvial Basin Spatial gridding of daily maximum and minimum temperatures in Europe Digital mapping of soil organic carbon contents and stocks in Denmark Digital Mapping of Topsoil Carbon Content and Changes in the Driftless Area of Wisconsin, USA Can Topographical and Yield Data Substantially Improve Total Soil Carbon Mapping by Regression Kriging? Spatial modelling and uncertainty assessment of pyroclastic cover thickness in the Sorrento Peninsula Integrative evaluation of data derived from biomonitoring and models indicating atmospheric deposition of heavy metals Spatial distribution of soil organic carbon and total nitrogen based on GIS and geostatistics in a small watershed in a hilly area of northern China Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe Digital Mapping of Soil Particle-Size Fractions for Nigeria Using Digital Elevation Model to Improve Soil pH Prediction in an Alpine Doline Climatic spatial variability in Extremadura (Spain) based on viticultural bioclimatic indices. Improving soil hydromorphy prediction according to DEM resolution and available pedological data Comparison of Geographically Weighted Regression and Regression Kriging for Estimating the Spatial Distribution of Soil Organic Matter Geostatistical mapping of geomorphic variables in the presence of trend Rainfall erosivity in Italy: a national scale spatio-temporal assessment Mapping Particle-Size Fractions as a Composition Using Additive Log-Ratio Transformation and Ancillary Data Layer-Specific Analysis and Spatial Prediction of Soil Organic Carbon Using Terrain Attributes and Erosion Modeling Soil–landform relationships at within-field scales: an investigation using continuous classification Prediction of soil water retention using soil physical data and terrain attributes An Adaptive Weighting Algorithm for Interpolating the Soil Potassium Content. A linear mixed effect (LME) model for soil water content estimation based on geophysical sensing: a comparison of an LME model and kriging with external drift The role of terrain analysis in using and developing pedotransfer functions Spatial variability in the amount of forest litter at the local scale in northeastern China: Kriging and cokriging approaches to interpolation Precise estimation of soil organic carbon stocks in the northeast Tibetan Plateau Test of statistical means for the extrapolation of soil depth point information using overlays of spatial environmental data and bootstrapping techniques Soil phosphorus landscape models for precision soil conservation Ensemble learning for spatial interpolation of soil potassium content based on environmental information Where and when should sensors move? Sampling using the expected value of information
is cites work of	wds:Q34148665-2B2D9DB7-53DE-4FC3-8766-D518430F13BD wds:Q29393989-25A404FB-8EC6-4D7A-AFE6-316B8413E603 wds:Q37105199-CBCC1FDC-B1CE-4799-B59B-7FAF316613AC wds:Q56919736-4827D099-B7E8-48A0-AC04-2E0866902249 wds:Q57597223-4CD31B7E-CE89-447C-AB0D-85A52CC930FE wds:Q59004139-80C358ED-EED5-4A9A-BA5B-A4C792DEDA39 wds:Q28550978-3C1EF310-E888-46DB-934C-F90283A1245A wds:Q57040049-7BCB20E0-AF26-4951-9445-8D836264A689 wds:Q59195344-187AB4B0-01AA-4030-B23A-6735B8E340C1 wds:Q62736643-267A99EF-DF89-454A-BD69-CAA89681C13C wds:Q31035663-1AA9106D-0790-471D-AD22-B7E051DAEE5E wds:Q39841995-F95F0287-00A5-405A-8A2E-342AF7F6BF39 wds:Q51100232-09CCF562-1E07-4407-91EE-A8D9636D24FB wds:Q57866246-CE7FBB11-82CB-423A-9105-0BA51589779C wds:Q56974264-74CD3D14-47FD-45FB-AEBB-2277AF2F75E4 wds:Q59003923-A0B642AC-CEC1-48E7-A50F-6E2BB5EFACB0 wds:Q58813598-DC20E343-8E2E-4D36-A273-B434863C7E52 wds:Q89520292-82B7B9F0-9881-492E-9ED4-A6A327772A3E wds:Q30726443-A1C138A4-2CE1-4D69-9B73-7B77B8A0B39C wds:Q34066737-772C1364-312D-419F-B81F-19F0AA7B9161 wds:Q58898885-A71ACDBB-CF67-4E42-811D-64A9593CF9E9 wds:Q57236503-3A72FFF4-5FD1-46F9-B817-D3B2E02D4E3D wds:Q58886725-74A9EE3E-BD9B-461A-AAD6-EC90E4E16171 wds:Q58813618-90D599F5-0290-4D3E-A517-731AEC74950A

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