Anyone with an R-script for batch pre-processing (atmospheric/ radiometric correction) of Landsat imagery?
I have a large multi-temporal Landsat dataset (from Landsat 1, 4, 5 and 8) that I need want to quickly pre-process in R-studio. So far, my check in the 'RStoolbox' Package has not yielded anything that can do what I want. I wish to loop-through the data using a batch process script.
I recommend you consult the following document in which we develop a program to calculate the water consumption of crops using landsat images and the METRIC model. If you have any questions, write me at firstname.lastname@example.org regards
Then I could calculate TOA reflectance with a correction for the sun angle, but the value is negative value, the range is around -0.1 to -1, I think it because of RADIANCE_ADD_BAND_X value is -0.1, so all the value are negative
Im think to use ” Dark Object Subtraction Method” for atmospheirc correction, so all the value will be the positive. Becasue it just each pixel value subtract the lowest value of TOA reflectance. Can anybody answer me is this a correct way to do it? Thank you very much!
This is a R Package for a robustified t-test (rt.test). The method used in this package is based on Park, C. and M. Wang (2018): Empirical distributions of the robustified t-test statistics <https://arxiv.org/abs/1807.02215>. Also see the R CRAN web: <https://cran.r-project.org/web/packages/rt.test/>
Linear quartzite ridges were established in the NE part of the imagery, from the aerial photointerpretation and later ground check. The extreme eastern part of the imagery has distinct evidence of faulting within the folded strata. Other structural features such as fault planes and doubly plunging synclinal features are also established. -from Auth...