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GIS-BASED ELABORATE SPATIAL PREDICTION OF SOILNUTRIENT ELEMENTS USING ANCILLARY TERRAIN DATAISN CHONGQING TOBACCO PLANTING REGION, CHINA

Authors
Publisher
IFIP Advances in Information and Communication Technology (AICT)
Publication Date
Disciplines
  • Agricultural Science

Abstract

The precision agriculture hopes to manage the variation in soil nutrient status continuously, which requires reliable predictions at places between sampling sites. For the long time, ordinary kriging has been used as one prediction method when the data are spatially dependent and a suitable variogram model exists. However, even if data are spatially correlated, there are often few soil sampling sites in relation to the area to be managed. Recently, Digital elevation models(DEMs) and remotely sensed data are becoming more readily available, these data are usually far more intensive than those from soil surveys. If these ancillary data are coregionalized with the sparse soil data, they might be used to increase the accuracy of predictions of the soil properties.Full Text at Springer, may require registration or fee

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