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Uberuaga, D.P
Emadi, M
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Authors
Kemanian, A.R
Huggins, D.R
Uberuaga, D.P
Baghernejad, M
Emadi, M
Baghernejad, M
Emadi, M
Topics
Precision Carbon Management
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Modelling and Geo-Statistics
Type
Oral
Year
2010
2008
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Filter results3 paper(s) found.

1. Modeling Soil Carbon Spatial Variation: Case Study In The Palouse Region

Soil organic carbon (Cs) levels in the soil profile reflect the transient state or equilibrium conditions determined by organic carbon inputs and outputs. In areas with strong topography, erosion, transport and deposition control de soil carbon balance and determine strong within-field differences in soil carbon. Carbon gains or losses are therefore difficult to predict for the average field. Total Cs ranged from 54 to 272 Mg C ha-1, with 42% (range 25 to 78%) of Cs in the top 0.3-m of the soil... A.R. Kemanian, D.R. Huggins, D.P. Uberuaga

2. Mapping Surface Soil Properties Using Terrain and Remotely Sensed Data in Arsanjan Plain, Southern Iran

Sustainable land management and land use planning require reliable information about the spatial distribution of the physical and chemical soil properties affecting both landscape processes and services. Spatial prediction with the presence of spatially dense ancillary variables has attracted research in pedometrics. The main objective of this research is to enhance prediction of soil properties such electrical conductivity (ECe), exchangeable sodium percentage (ESP), available phosphorus (P),... M. Baghernejad, M. Emadi

3. A New Approach for Quantitative Land Suitability Evaluation Using Geostatistics, Remote Sensing (Rs) and Geographic Information System (Gis)

The objective of this study was to incorporate geostatistics, remote sensing and geographic information system methods due to improving the quantitative land suitability assessment in Arsanjan plain, southern Iran. The primary data was collected from 85 soil samples from tree depths (0­30, 30­60 and 60­90 cm) and the secondary information from remotely sensed data “LISS­III receiver from IRS­P6 satellite”. In order to identify the spatial dependence of soil important... M. Baghernejad, M. Emadi