| dc.contributor.author |
Assimakopoulos, JH |
en |
| dc.contributor.author |
Kalivas, DP |
en |
| dc.contributor.author |
Kollias, VJ |
en |
| dc.date.accessioned |
2014-06-06T06:45:24Z |
|
| dc.date.available |
2014-06-06T06:45:24Z |
|
| dc.date.issued |
2003 |
en |
| dc.identifier.issn |
00489697 |
en |
| dc.identifier.uri |
http://dx.doi.org/10.1016/S0048-9697(03)00055-X |
en |
| dc.identifier.uri |
http://62.217.125.90/xmlui/handle/123456789/2421 |
|
| dc.subject |
Fuzzy sets |
en |
| dc.subject |
GIS |
en |
| dc.subject |
N-acidifying fertilizers use |
en |
| dc.subject |
Nitrate leaching |
en |
| dc.subject |
Nitrogen-fertilizers use |
en |
| dc.subject.other |
Degradation |
en |
| dc.subject.other |
Fertilizers |
en |
| dc.subject.other |
Fuzzy sets |
en |
| dc.subject.other |
Geographic information systems |
en |
| dc.subject.other |
Groundwater |
en |
| dc.subject.other |
Leaching |
en |
| dc.subject.other |
Fuzzy classification |
en |
| dc.subject.other |
Soils |
en |
| dc.subject.other |
carbonic acid derivative |
en |
| dc.subject.other |
nitrogen fertilizer |
en |
| dc.subject.other |
agricultural soil |
en |
| dc.subject.other |
fertilizer application |
en |
| dc.subject.other |
fuzzy mathematics |
en |
| dc.subject.other |
GIS |
en |
| dc.subject.other |
mapping |
en |
| dc.subject.other |
acidification |
en |
| dc.subject.other |
agricultural management |
en |
| dc.subject.other |
analytic method |
en |
| dc.subject.other |
article |
en |
| dc.subject.other |
clay |
en |
| dc.subject.other |
data analysis |
en |
| dc.subject.other |
geostatistical analysis |
en |
| dc.subject.other |
Greece |
en |
| dc.subject.other |
leaching |
en |
| dc.subject.other |
model |
en |
| dc.subject.other |
pH |
en |
| dc.subject.other |
policy |
en |
| dc.subject.other |
priority journal |
en |
| dc.subject.other |
sand |
en |
| dc.subject.other |
soil analysis |
en |
| dc.subject.other |
soil management |
en |
| dc.subject.other |
Agriculture |
en |
| dc.subject.other |
Environment |
en |
| dc.subject.other |
Environmental Monitoring |
en |
| dc.subject.other |
Fertilizers |
en |
| dc.subject.other |
Fuzzy Logic |
en |
| dc.subject.other |
Geographic Information Systems |
en |
| dc.subject.other |
Hydrogen-Ion Concentration |
en |
| dc.subject.other |
Nitrogen |
en |
| dc.subject.other |
Risk Assessment |
en |
| dc.subject.other |
Soil Pollutants |
en |
| dc.title |
A GIS-based fuzzy classification for mapping the agricultural soils for N-fertilizers use |
en |
| heal.type |
journalArticle |
en |
| heal.identifier.primary |
10.1016/S0048-9697(03)00055-X |
en |
| heal.publicationDate |
2003 |
en |
| heal.abstract |
Special attention should be paid to the choice of the proper N-fertilizer, in order to avoid a further acidification and degradation of acid soils and at the same time to improve nitrogen use efficiency and to limit the nitrate pollution of the ground waters. Therefore, the risk of leaching of the fertilizer and of the acidification of the soils must be considered prior to any N-fertilizer application. The application of N-fertilizers to the soil requires a good knowledge of the soil-fertilizer relationship, which those who are planning the fertilization policy and/or applying it might not have. In this study, a fuzzy classification methodology is presented for mapping the agricultural soils according to the kind and the rate of application of N-fertilizer that should be used. The values of pH, clay, sand and carbonates soil variables are estimated at each point of an area by applying geostatistical techniques. Using the pH values three fuzzy sets: 'no-risk-acidification'; 'low-risk-acidification'; and 'high-risk-acidification' are produced and the memberships of each point to the three sets are estimated. Additionally, from the clay and sand values the membership grade to the fuzzy set 'risk-of-leaching' is calculated. The parameters and their values, which are used for the construction of the fuzzy sets, are based on the literature, the existing knowledge and the experimentation, of the soil-fertilizer relationships and provide a consistent mechanism for mapping the soils according to the type of N-fertilizers that should be applied and the rate of applications. The maps produced can easily be interpreted and used by non-experts in the application of the fertilization policy at national, local and farm level. The methodology is presented through a case study using data from the Amfilochia area, west Greece. © 2003 Elsevier Science B.V. All rights reserved. |
en |
| heal.journalName |
Science of the Total Environment |
en |
| dc.identifier.issue |
1-3 |
en |
| dc.identifier.volume |
309 |
en |
| dc.identifier.doi |
10.1016/S0048-9697(03)00055-X |
en |
| dc.identifier.spage |
19 |
en |
| dc.identifier.epage |
33 |
en |