3D kriging
저자: Eva Stopkova
1. Numeric tasks
1.1. fix PCL usage in interpolation
1.1.1. everything in one kd-tree
1.2. Variogram
1.2.1. Estimation of optimal variogram inputs
1.2.2. use Thiessen polygon to compute experimental variogram
1.2.3. local variogram?
1.3. Spatial statistics for results evaluation
2. Processing tasks
2.1. PCL in interpolation - yes or no?
2.2. use PCL only ("float transformation"?)
2.3. parallelisation (finally)
2.4. try profiling
3. Utilities
3.1. implement cross-validation
3.2. complete documentation (doxygen)
3.3. Configuration
3.3.1. reconfigure output setting
3.3.2. rename variables
3.3.2.1. td
3.3.2.2. layer -> map
3.3.3. variogram
3.3.3.1. write to file
3.3.3.2. or draw if user has gnuplot
3.3.3.3. popen -> G_...function
3.3.4. replace goto by shortened condition
4. Just for relax
4.1. name variogram file after output
4.2. standardize
4.3. try disable pthreads
5. Tests
5.1. comparing with RST
5.2. comparing with etalons
5.3. compare values on input and output points
6. Already done
6.1. fixed G_matrix_init
6.2. arrays replaced by pointers
6.3. PCL versions developed
7. Check
7.1. IDW indexing
8. Troubles
8.1. r3.mapcalc error
8.2. visualization err in volumes
9. Experiments
9.1. Soil data
9.1.1. try fictituous variogram coefficients
9.1.2. compute 2D variogram for soil data
9.1.3. soil assignment
9.2. gamma data
9.2.1. compute gammas for all voxels
9.2.1.1. transform xyz to phi, lambda
9.2.1.2. compute gamma on these points
9.2.2. compare them with interpolated values
9.2.3. check systematic error