13

ESA's Sen2cor Toolbox removes haze, cirrus and cloud shadows, not dense clouds. It's performed over the same scene, not by mosaicking. The AC flow is the following from L2A algorithms document: So, Sen2cor performs an image classification and use this layer to select where to correct pixel values. You can check documentation to know which equation is used ...


9

Short answer: It's a numerical precision issue: the xa, xb and xc coefficients are not displayed in the 6S output file with enough precision to produce the correct answer when using the formula. It is possible to modify 6S to print the coefficients with a higher precision, which solves the problem. Long answer: I was intrigued by this question, as I've used ...


9

you could also check the Atmospheric and Radiometric Correction of Satellite Imagery (ARCSI) Python library, which supports a range of sensors, including Landsat 4,5,7 and 8. To complement the comments below, there is a very clear tutorial available here and a comprehensive introduction & tutorial written by the author here


7

The three sensors are all slightly different. However the OLI/TIRs setup is a marked departure from the TM/ETM+ sensors. The changes are succintly summarised by Li et al. 2013 as the: replacing of whisk-broom scanners with two separate push-broom OLI and TIRS scanners, an extended number of spectral bands (two additional bands provided) and narrower ...


7

You'll need to run ESA's Sen2Cor algorithm to process Sentinel-2 Level-1C data to Level-2A. This will give you atmospherically corrected BOA data. If you then divide the values by the quantification value (10000) you'll end up with BOA reflectance data. Download and install Sen2Cor: http://step.esa.int/main/third-party-plugins-2/sen2cor/ STEP help forum (...


7

One flaw in your approach. You don't need to go through DN to radiance. You can go straight to the DN to reflectance. Just stick to ((B1*0.00002)-0.1)/0.74457226676389733207607359928648.


6

It depends upon the intended use of the Landsat data. Generally speaking, if you are doing multi-temporal analyses, you need atmospherically corrected data, otherwise DN format is sufficient. I would recommend reading the following landmark paper on the subject: Song, C., Woodcock, C. E., Seto, K. C., Lenney, M. P., & Macomber, S. A. (2001). ...


6

In R, there are landsat package (CRAN) landsat provides basic tools for working with satellite imagery such as automated georeferencing and cloud detection. It contains functions for radiometric normalization, and several different approaches to atmospheric correction. Four topographic correction algorithms have been implemented. Other useful ...


5

Bare soil and urban areas are notoriously hard to segregate. Even with a perfect atmospheric correction, there will be relatively high confusion between the two, particularly when limited to multispectral datasets. The atmospheric correction technique you are doing is a simple dark object subtraction, wherein the darkest objects in the landscape should have ...


5

You can perform a land cover classification on a single Landsat scene without performing spectral and radiometric corrections. You will only need to do those corrections if you're trying to apply reference spectra to your classification, performing a classification that covers multiple scenes or performing a classification over a time series of the same ...


5

You will want to use the *_sr_band1 to band7 data for your analyses as these are atmospherically corrected surface reflectance products (Figure 1). Only the Surface Reflectance data products and quality assessment bands are included in the deliverables (Figure 2). The ancillary bands (e.g. *_sensor_azimuth_band4) are used in the process of atmospheric ...


4

Blue color cast is caused by atmospheric scattering (= light reflecting off particles in the atmosphere is added to the light reflected from the ground), and it is always present in top-of-atmosphere images. Its strength varies with atmospheric conditions (e.g. more aerosols or water vapour scatter more light, hence the blue cast will be stronger) and sun ...


4

The Landsat 8 Surface Reflectance products are not sunglint corrected , so if your application is going to be adversely impacted by the presence of sunglints, then you should implement a suitable deglinting method. For more detail on the exact processing algorithms used for the Surface Reflectance Product, see https://landsat.usgs.gov/landsat-surface-...


4

You need good reflectance values if 1) you want to measure some biophysical characteristics of the surface or 2) you want to generalize your approach over large areas. The radiometric corrections with level 3A are only basic corrections (providing 1/100 radiances), but not reflectance values. If you want to apply an algorithm trained on one image to other ...


4

Yes, they are refering to atmospheric correction, to get Bottom of Atmosphere reflectance. The specific tool used for this is called Sen2Cor, which can be installed standalone or part of a package. Sen2Cor User Manual Cloud detection and correction methodology What you mentioned about mosaicking images from different dates is another tool for Sentinel-2, ...


4

I have also found a source code useful which is provided in RStoolbox package in R.Therefore I have attached the link here for other users and developers which might be useful for them as well. Radiometric Calibration and Correction in R (RStoolbox)


3

Although the band specs are different for different Landsat sensors your answer depends on the product you're planning to use. The part you have copied and mentioned the "well-characterized radiometry and are inter-calibrated across the different Landsat instruments" is for Landsat Collection 1 Tier 1 data. The aim of producing Collection-1 and not ...


3

The DOS methods are for atmospheric correction only, not radiometric correction. The i.*.toar modules allow you to combine in one step radiometric correction with some additional DOS atmospheric correction method. The input to the i.*.toar modules is the original DN values. The default to i.*.toar is "uncorrected", so normally you would use i.*.toar to get ...


3

Well, one way would be to read the data documentation. The Scientific Data Hub specifically states: "The Sentinel-2 data offer for the Scientific Data Hub will consist of Level-1C user products", which is in reflectance values. As such, you may have actually corrupted the data in applying an atmospheric correction that, as part of the processing, corrects ...


3

To put it bluntly, the best way is simply to look at the spectral bands of your Satellite image. If it has a near infrared band, the atmosphere should make a gap here in the case of an image without correction. The blue band can also help you find out if it has been corrected by looking for the effects of Rayleigh scattering (look for places where the blue ...


3

You do not need to do any further atmospheric correction with Landsat OLI/TIRS Level-2 data products as they are already corrected to surface reflectance. These data will be sufficient for time-series analysis as well as work involving multiple scenes. However, make sure any older imagery (i.e. earlier than Landsat 8 OLI/TIRS) is also corrected to surface ...


2

Here's a good read on the physics of atmospheric correction, and might help with the issue... I'm a button pushing guy, I feel your pain, at least you can just click that beautiful QUAC or FLAASH button once you're outside of academia. http://modis.gsfc.nasa.gov/data/atbd/atbd_mod08.pdf


2

UTM-8N is about British Columbia, Canada and is mostly in timezone UTC-9. The time zone in netcdf files is contained in the time variable's "units" attribute which identifies the origin and interval of the numerics stored in the time variable. For the CF conventions, the time units attribute must be parseable by the Unidata udunits2 program. See http://...


2

Dark object subtraction is not atmospheric correction. It is image normalization. It is the simplest way of making two images acquired at different times, with different atmospheric conditions and view angles resemble eachother spectrally. As such, what you get is not a 'correct surface reflectance value'. What you get is something that may, or may not, ...


2

Yes it is rather commonplace to obtain some negative reflectances after atmospheric correction over dark surfaces. As said by Markus, this may result : from a too high aerosol optical thickness in the parameters used for the atmospheric correction, from not taking into account the altitude of the pixels (as the molecular and aerosol optical thickness ...


2

We just has a similar discussion in the GRASS bugtracker. It seems that a negative result may originate from visibility is assumed too low (optical thickness too high). See here for the reference: https://trac.osgeo.org/grass/ticket/2545#comment:6


2

Yes, these are the Level 2 data products, which are calibrated to surface reflectance. These are able to be used for further analysis directly. *_01_T1_sr_band1 to band7 refers to the surface reflectance (bottom of atmosphere) products *_01_T1_toa_band1 to band9 refers to the top of atmosphere products The remaining bands are quality assessment bands--as ...


2

There is not a single answer unfortunately. The satellites with the 0c prefix are getting on in age and sometimes exhibit artifacts. The UDM file signals which pixels have been detected as being anomalous and that can be a good way for users to know which pixels should be ignored. But probably the best indicator before downloading anything is to check the ...


2

For the LS4-7 level 2 surface reflectance products which are supplied as Int16, you need to multiply the values by the scale factor 0.0001 to convert the values to 0.0-1.0. This is documented in the product guide.


2

As the error says, the max pixel's allowed is 10000000. You can change this to suit your data: image.reduceRegion({ reducer: x, geometry: x, scale: x, maxPixels: 1e9 });


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