Variability of magnetic soil properties in Hawaii

2005 ◽  
Author(s):  
Remke L. van Dam ◽  
J. Bruce J. Harrison ◽  
Jan M. H. Hendrickx ◽  
Brian Borchers ◽  
Ryan E. North ◽  
...  
Keyword(s):  
Soil Properties ◽  
Magnetic Soil

Spatial variability of magnetic soil properties

2004 ◽  
Author(s):  
Remke L. van Dam ◽  
Jan M. Hendrickx ◽  
Bruce Harrison ◽  
Brian Borchers ◽  
David I. Norman ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Magnetic Soil

Magnetic soil properties at two arid to semi-arid sites in the western United States

2006 ◽  
Author(s):  
Remke L. van Dam ◽  
J. Bruce J. Harrison ◽  
Carson L. Rittel ◽  
Jan M.H. Hendrickx ◽  
Brian Borchers
Keyword(s):  
United States ◽  
Soil Properties ◽  
Western United States ◽  
Magnetic Soil ◽  
Semi Arid

Magnetic soil properties in Ghana

2005 ◽  
Author(s):  
Jan M. H. Hendrickx ◽  
J. Bruce J. Harrison ◽  
Remke L. van Dam ◽  
Brian Borchers ◽  
David I. Norman ◽  
...  
Keyword(s):  
Soil Properties ◽  
Magnetic Soil

Applying the Method of Lagrange Multipliers to Derive an Estimator for Unsampled Soil Properties

2014 ◽  
Vol 11 (1) ◽  
pp. 15
Author(s):  
Set Foong Ng ◽  
Pei Eng Ch’ng ◽  
Yee Ming Chew ◽  
Kok Shien Ng
Keyword(s):  
Soil Properties ◽  
Lagrange Multipliers ◽  
Unbiased Estimator ◽  
Soil Property ◽  
Minimum Variance ◽  
Distance Method ◽  
True Value ◽  
A Site ◽  
Method Of Lagrange Multipliers ◽  
Inverse Distance

Soil properties are very crucial for civil engineers to differentiate one type of soil from another and to predict its mechanical behavior. However, it is not practical to measure soil properties at all the locations at a site. In this paper, an estimator is derived to estimate the unknown values for soil properties from locations where soil samples were not collected. The estimator is obtained by combining the concept of the ‘Inverse Distance Method’ into the technique of ‘Kriging’. The method of Lagrange Multipliers is applied in this paper. It is shown that the estimator derived in this paper is an unbiased estimator. The partiality of the estimator with respect to the true value is zero. Hence, the estimated value will be equal to the true value of the soil property. It is also shown that the variance between the estimator and the soil property is minimised. Hence, the distribution of this unbiased estimator with minimum variance spreads the least from the true value. With this characteristic of minimum variance unbiased estimator, a high accuracy estimation of soil property could be obtained.

AVAILABLE WAYS TO OPTIMIZE SOIL PROPERTIES IN APPLE ORCHARDS

2020 ◽  
Vol 16 (2) ◽  
pp. 41-63
Author(s):  
V.L. Zakharov ◽  
◽  
G.N. Pugachev ◽  
Keyword(s):  
Soil Properties ◽  
Apple Orchards

Geospatial comparison of three models to predict soil properties in semi-humid region of West Bengal, India

2018 ◽  
Vol 32 (5) ◽  
pp. 37
Author(s):  
Rajaram Majhi ◽  
Gouri Sankar Bhunia ◽  
Tapan Kumar Das ◽  
Pravat Kumar Shit ◽  
Rabindranath Chattopadhyay
Keyword(s):  
Soil Properties ◽  
West Bengal ◽  
Humid Region

CORRELATION RELATIONS BETWEEN VALUABLE IRRIGATED SOIL PROPERTIES AND PLANT PRODUCTIVITY

2020 ◽  
Vol 5 (2) ◽  
pp. 37-42
Author(s):  
Inobat Ruzieva ◽  
◽  
Inobat Ruzieva ◽  
Islom Xaitov ◽  
Ulug`berdi Xursanov
Keyword(s):  
Soil Properties ◽  
Plant Productivity
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