SPATIAL VARIABILITY AND SAMPLING STRATEGIES FOR NO3-N, P, AND K DETERMINATIONS FOR SITE-SPECIFIC FARMING

1997 ◽  
Vol 40 (2) ◽  
pp. 337-343 ◽  
Author(s):  
R. K. Gupta ◽  
S. Mostaghimi ◽  
P. W. McClellan ◽  
M. M. Alley ◽  
D. E. Brann
Keyword(s):  
Spatial Variability ◽  
Sampling Strategies ◽  
Site Specific ◽  
Site Specific Farming

Improved analysis of thermally sensed crop water status and mapping spatial variability for site specific irrigation scheduling

2008 ◽  
Author(s):  
Victor Alchanatis ◽  
Steven Evett ◽  
Shabtai Cohen ◽  
Yafit Cohen ◽  
Moshe Meron ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Water Status ◽  
Irrigation Scheduling ◽  
Crop Water ◽  
Site Specific

scholarly journals Investigating temporal field sampling strategies for site-specific calibration of three soil moisture–neutron intensity parameterisation methods

2015 ◽  
Vol 19 (7) ◽  
pp. 3203-3216 ◽  
Author(s):  
J. Iwema ◽  
R. Rosolem ◽  
R. Baatz ◽  
T. Wagener ◽  
H. R. Bogena
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Satellite Remote Sensing ◽  
Cosmic Ray ◽  
Sampling Strategies ◽  
Site Specific ◽  
Neutron Intensity ◽  
Soil Wetness ◽  
Semi Arid

Abstract. The Cosmic-Ray Neutron Sensor (CRNS) can provide soil moisture information at scales relevant to hydrometeorological modelling applications. Site-specific calibration is needed to translate CRNS neutron intensities into sensor footprint average soil moisture contents. We investigated temporal sampling strategies for calibration of three CRNS parameterisations (modified N0, HMF, and COSMIC) by assessing the effects of the number of sampling days and soil wetness conditions on the performance of the calibration results while investigating actual neutron intensity measurements, for three sites with distinct climate and land use: a semi-arid site, a temperate grassland, and a temperate forest. When calibrated with 1 year of data, both COSMIC and the modified N0 method performed better than HMF. The performance of COSMIC was remarkably good at the semi-arid site in the USA, while the N0mod performed best at the two temperate sites in Germany. The successful performance of COSMIC at all three sites can be attributed to the benefits of explicitly resolving individual soil layers (which is not accounted for in the other two parameterisations). To better calibrate these parameterisations, we recommend in situ soil sampled to be collected on more than a single day. However, little improvement is observed for sampling on more than 6 days. At the semi-arid site, the N0mod method was calibrated better under site-specific average wetness conditions, whereas HMF and COSMIC were calibrated better under drier conditions. Average soil wetness condition gave better calibration results at the two humid sites. The calibration results for the HMF method were better when calibrated with combinations of days with similar soil wetness conditions, opposed to N0mod and COSMIC, which profited from using days with distinct wetness conditions. Errors in actual neutron intensities were translated to average errors specifically to each site. At the semi-arid site, these errors were below the typical measurement uncertainties from in situ point-scale sensors and satellite remote sensing products. Nevertheless, at the two humid sites, reduction in uncertainty with increasing sampling days only reached typical errors associated with satellite remote sensing products. The outcomes of this study can be used by researchers as a CRNS calibration strategy guideline.

scholarly journals Monitoring the Spatial Variability of Knapweed (Centaurea diluta Aiton) in Wheat Crops Using Geostatistics and UAV Imagery: Probability Maps for Risk Assessment in Site-Specific Control

Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 880
Author(s):  
Montserrat Jurado-Expósito ◽  
Francisca López-Granados ◽  
Francisco Manuel Jiménez-Brenes ◽  
Jorge Torres-Sánchez
Keyword(s):  
Risk Assessment ◽  
Spatial Variability ◽  
Weed Management ◽  
Management Strategies ◽  
Indicator Kriging ◽  
Site Specific ◽  
Weed Density ◽  
Density Mapping ◽  
Probability Maps ◽  
Geostatistical Approach

Assessing the spatial distribution of weeds within a field is a key step to the success of site-specific weed management strategies. Centaurea diluta (knapweed) is an emerging weed that is causing a major agronomic problem in southern and central Spain because of its large size, the difficulty of controlling it, and its high competitive ability. The main objectives of this study were to examine the spatial variability of C. diluta density in two wheat fields by multivariate geostatistical methods using unmanned aerial vehicle (UAV) imagery as secondary information and to delineate potential control zones for site-specific treatments based on occurrence probability maps of weed infestation. The primary variable was obtained by grid weed density field samplings, and the secondary variables were derived from UAV imagery acquired the same day as the weed field surveys. Kriging and cokriging with UAV-derived variables that displayed a strong correlation with weed density were used to compare C. diluta density mapping performance. The accuracy of the predictions was assessed by cross-validation. Cokriging with UAV-derived secondary variables generated more accurate weed density maps with a lower RMSE compare with kriging and cokriging with RVI, NDVI, ExR, and ExR(2) (the best methods for the prediction of knapweed density). Cokriged estimates were used to generate probability maps for risk assessment when implementing site-specific weed control by indicator kriging. This multivariate geostatistical approach enabled the delineation of winter wheat fields into two zones for different prescription treatments according to the C. diluta density and the economic threshold.

Delineating site-specific management zones for precision agriculture

2015 ◽  
Vol 154 (2) ◽  
pp. 273-286 ◽  
Author(s):  
H. U. FARID ◽  
A. BAKHSH ◽  
N. AHMAD ◽  
A. AHMAD ◽  
Z. MAHMOOD-KHAN
Keyword(s):  
Spatial Variability ◽  
Grain Yield ◽  
Precision Farming ◽  
Farming Practices ◽  
Wheat Grain ◽  
Site Specific ◽  
Management Zones ◽  
Management Zone ◽  
Specific Management ◽  
Landscape Attributes

SUMMARYDelineating site-specific management zones within fields can be helpful in addressing spatial variability effects for adopting precision farming practices. A 3-year (2008/09 to 2010/11) field study was conducted at the Postgraduate Agricultural Research Station, University of Agriculture, Faisalabad, Pakistan, to identify the most important soil and landscape attributes influencing wheat grain yield, which can be used for delineating management zones. A total of 48 soil samples were collected from the top 300 mm of soil in 8-ha experimental field divided into regular grids of 24 × 67 m prior to sowing wheat. Soil and landscape attributes such as elevation, % of sand, silt and clay by volume, soil electrical conductivity (EC), pH, soil nitrogen (N) and soil phosphorus (P) were included in the analysis. Artificial neural network (ANN) analysis showed that % sand, % clay, elevation, soil N and soil EC were important variables for delineating management zones. Different management zone schemes ranging from three to six were developed and evaluated based on performance indicators using Management Zone Analyst (MZA V0·1) software. The fuzziness performance index (FPI) and normalized classification entropy NCE indices showed minimum values for a four management zone scheme, indicating its appropriateness for the experimental field. The coefficient of variation values of soil and landscape attributes decreased for each management zone within the four management zone scheme compared to the entire field, which showed improved homogeneity. The evaluation of the four management zone scheme using normalized wheat grain yield data showed distinct means for each management zone, verifying spatial variability effects and the need for its management. The results indicated that the approach based on ANN and MZA software analysis can be helpful in delineating management zones within the field, to promote precision farming practices effectively.

scholarly journals Multi-species weed spatial variability and site-specific management maps in cultivated sunflower

Weed Science ◽  
2003 ◽  
Vol 51 (3) ◽  
pp. 319-328 ◽  
Author(s):  
Montserrat Jurado-Expósito ◽  
Francisca López-Granados ◽  
Luis García-Torres ◽  
Alfonso García-Ferrer ◽  
Manuel Sánchez de la Orden ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Site Specific ◽  
Specific Management
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