Mapping risk of soil nutrient deficiency or excess by disjunctive and indicator kriging

By R. M. Lark, Richard B. Ferguson. 2004

88 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Environmental Engineering, Management, Monitoring, Policy and Law

View Paper: https://www.semanticscholar.org/paper/47c43c231d92fb861cfc2d3e03438d9918d2d66b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jin Li
2. Andrew D. Heap
3. C. Almquist
4. A. Wallenhammar
5. A. Jonsson
6. Mats Söderström

In Environmental Engineering

1. Jin Li
2. Andrew D. Heap
3. C. Almquist
4. A. Wallenhammar
5. A. Jonsson
6. Mats Söderström

In Management, Monitoring, Policy and Law

1. Jin Li
2. Andrew D. Heap
3. C. Almquist
4. A. Wallenhammar
5. A. Jonsson
6. Mats Söderström

Citations in the corpus

• In‐field distribution of Plasmodiophora brassicae measured using quantitative real‐time PCR (2012, methodology): “This approach, which has been applied frequently in soil mapping (e.g. Van Meirvenne & Goovaerts, 2001; Lark & Ferguson, 2004), is appropriate when the goal is to produce an estimate of the probability that a given threshold is exceeded.”
• Spatial interpolation methods applied in the environmental sciences: A review (2014, background): “There are also guidelines for choosing between DK and IK according to the nature and structure of data (Lark and Ferguson, 2004).”