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Definition of Accuracy
close to true value
Definition of Precision
Variability (repeatability)
Advantages of Digital Scouting
Continuous monitoring, maximizes time and efficiency
What is Sampling
The selection of a subset of individuals from within a whole population to estimate characteristics of the whole population.
Good sampling represents the whole population effectively.
Bad sampling makes a big bias in data.
Why do we sample?
1. Without data, we don’t know what is happening and we can’t fix problem.
2. It is impossible to analyze whole field inch by inch.
3. To get basic information
4. To understand problems
5. To understand field variations
6. To make the best management decisions
What do Soil Samples Measure
chemical (nutrients) and physical (textures, bulk density) characteristics of soils
What do Plant tissue samples measure
chlorophyll, nutrient uptake, biomass of crop plants
What do remote sensing samples measure
physiological or physical information about plant healthiness, soil OM contents, soil moisture content
What does every sample collected need?
geocoordinates
What is the goal of soil sampling?
characterize the nutrient status of a field as accurately and inexpensively as possible.
Why are plant tissue samples needed?
plant nutrient composition varies with age and the portion of the plant sampled
3 sampling methods
Random (1 per field), Grid (1+ sub sample around georeference point), Zone (1 per pre-defined management zone)
Acreage of Grid Sampling Points
For ¼ section field (2,600’ x 2,600’)
1. 100’ grids: 26 x 26 = 676 points (~1/4 ac)
2. 200’ grids: 13 x 13 = 169 points (~1 ac)
3. 300’ grids: 8 x 8 = 64 points (~2 ac)
How to ensure sample accuracy every year?
Samples should:
1. Be taken on same spots and at the same time of years.
2. Be taken at the right and same depth (consistently 6 or 24 inch depths) or right portion of leaf.
3. Contain an adequate number of samples (soil cores or plants) to accurately represent the area.
Grid Point Sampling
collects one or multiple subsamples around a georeferenced point within a grid or at a grid intersection.
Grid Cell Sampling
randomly collects either one or multiple subsamples throughout the cell for a composite sample.
Grid distance (number of samples) is determined by ________ ________
Spacial Dependency
How to estimate values of unsampled areas
Make an average value
Use geospacial statistics (Inverse Distance Weighting or Kriging)
Inverse Distance Weighting (IDW) Information
Uses a weighted average of sample points, with closer points having more influence. The weight depends ONLY on the distance from the prediction location.
Easier to use and lower computational cost than kriging
can be oversensitive to outliers and lacks structural information.
Kriging
Uses weights based on both the distance from the prediction location and the spatial arrangement of the measured points. Is an advanced geostatistical procedure that assumes the data are spatially continuous.
More robust than IDW
Can be computationally demanding, have model selection challenges, and be complex to interpret.
Data and Spacial Patterns
Spatial pattern = kriging or IDW works well
NO spatial pattern = kriging or IDW do NOT work well.
Spacial Dependence/Correlation
Data close together = highly correlated
Spatial dependence imputes that up to some distance apart from each other, two observations at different locations are statistically dependent
Semivariogram Definition
An autocorrelogram that expresses the degree of spatial variation as a function of distance
Parts of Semivariogram
Nugget = the y-intercept that represents the semi-variance between two closest points
Sill = maximum semi-variance
De-correlation length (range) = measures spatial continuity (range of spatial dependence)
Types of Variation
Temporal (Time - seasons or years) and Spacial (geographical locations)
What are temporal Variations affected by?
Weather and Management
What is spacial variation affected by?
Landscape positions affect the flow of nutrient and water which impact yield