14

NDVI is defined for any two bands with near-infrared and infrared data (it is an empirical remote sensing index). As such, you can calculate it straight from the DNs. This is mostly OK if you are only classifying or analyzing vegetation on a single image without significant atmospheric effects (cirrus clouds...) However, if you are performing change ...


13

Sentinel-2 Level 1C data are expressed in reflectance with a scaling factor, not in radiance. You have to divide by 10000 to get the reflectance. In the preliminary products shown this autumn, you had to divide by 1000. The scaling factor is given in the xml file at the root of the product directory. <QUANTIFICATION_VALUE unit="none">10000</...


12

The Sentinel 2 L1C images started out as 12-bit, but that has been changed in early 2016 when ESA changed QUANTIFICATION_VALUE from 1000 to 10000. Now L1C is encoded as an UINT16 jp2 file with (at least?) 15 significant bits. This is from gdalinfo on a recent B02.jp2 file: Band 1 Block=1024x1024 Type=UInt16, ColorInterp=Gray Overviews: 5490x5490, ...


9

I've found two sources that appear to provide easy to read explanation between Radiance vs. Irradiance and remote sensing reflectance and water leaving radiance. Starting with Radiance vs. Irradiance: Irradiance is simple: exchange of energy (in the form of photons) across a given area of flat surface per time. Radiance is more complicated: exchange of ...


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 (...


6

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 ...


5

If the file contains "DN" in the name then it is not scaled radiance and there is are no coefficients available to scale to scale to exo-atmospheric irradiance. If the product is the "analytic" asset from the PSScene4Band type the filename should include "_3B_AnalyticMS" and it is scaled radiance. If the product is the "analytic" asset from the ...


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 ...


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

Sentinel 2 L1C product are top of atmosphere reflectances. It mean that ESA has already converted the raw DN (Digit Numbers) from the satellite MSI sensors into meaningfull physical values. This is a calibration step that includes a conversion from DN to luminance (based on sensor calibration model) and a conversion from luminance to reflectance (using solar ...


4

I quite disagree with you regarding the standard reflectance values of water in the near infrared (Band 8a). As water absorbs light in these wavelengths, these values should be very low (of course not zero) except when the water is turbid or contains ice or foam, or is observed in the sunglint direction.. As a result, the unusual value, for me, is 0.4, ...


3

You are using the level 1C product (top of atmosphere reflectance), which will, in many cases, have atmospheric scattering present. Atmospheric scattering will skew the true surface reflectance value due to atmospheric aerosols in the image (Figure 1). Additionally, atmospheric scattering makes it difficult to compare different images because aerosol levels ...


3

Yes - the regular OR2A data is delivered in Digital Numbers. If you want to test this, you could take a look at the values in your data - if all values you have are integers, chances are that you're looking at Digital Numbers, and if you have values between 0 and 1 in all bands, you're looking at reflectance (with the caveat that some data sources provide ...


3

Is the second option. Data under 0 or over 10000 needs to be handled as NULL data (saturated cells). In your case, NULL Value is -9999, but if you set those ranges as a value instead of a NULL cell, the value will be multiplied with the scale factor. It depends of the software used


3

A far as I know, LiDAR signals do not get returned over water bodies. It depends which laser wavelength was used in the survey. If it was a wavelength near the infrared (> 700 nm) it should be partially reflected/absorbed by water, and they are usually considered to be noise (see JeffreyEvan's comment). On the other hand, there are laser wavelengths which ...


2

I don't know for what object this particular spectral signature ties at but i can suggest to browse a spectral library for something that is close match. http://speclib.jpl.nasa.gov/


2

Calibrating Landsat-8 OLI to Top of Atmosphere: R_toa_Bx = (M_Bx * DN_Bx + A_Bx) / sin (Sun_elev) Where R_toa_Bx is reflectance in band_x, M_Bx is the multiplication factor stated in the metadata file, DN_Bx is the digital number in band_x from the TIFF-file, A_Bx is the addition number stated in the metadata file and Sun_elev is the sun elevation angle ...


2

Using Dark Object Subtraction (DOS) can provide a a quick way to correct for atmospheric effects, which may be sufficient for preparing multispectral data for spectral indices such as NDVI. However, it will not be as accurate as using Landsat Surface Reflectance High Level Data Products for Landsat 8 that is generated from the L8SR algorithm. The L8SR is ...


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

Remove the square brackets [] from your expression. The tutorial uses an old version of ArcGIS that has slightly different raster calculator syntax.


2

Since you just want to delineate the borders between two land uses you don't need to worry about using images with atmospheric correction. In case your application really needs the surface values (for example, you want to see if after applying a fertilizer the NDVI increases or not) then you would prefer using that product


2

Check product guide from Landsat 8 surface reflectance. Values range is from -2000 to 16000, but the valid range is from 0 to 10000, so you need to mask off pixels out of range. In R you can change this pixels to NA. Suppose a random raster with values lower than 0 or greater than 10000: library(raster) r <- raster() values(r) <- rnorm(n = ncell(r),...


2

Yes, you do need to correct Landsat 8 imagery to compare it against Landsat 5 and 7. The data between the three satellites are not directly comparable in their raw form. This paper compares Landsat 7 to Landsat 8: Roy, D.p., et al. “Characterization of Landsat-7 to Landsat-8 Reflective Wavelength and Normalized Difference Vegetation Index Continuity.” ...


2

If you want to add a calculated value as a new property to the image, then follow Kersten's advice, which is something along the lines of: collection_121_134 = collection_121_134.map(function(img) { var gain = img.get('GAIN_COEFFICIENT_B01'); var reflect = .......; img = img.set('Reflectance', reflect); return(img) }); If all you want is ...


2

The SR product is provided as a 16-bit GeoTIFF image with reflectance values scaled by 10,000. There is also a tutorial tutorial to convert MS radiance to reflectance.


2

May I ask, why are you going about it this way instead of using the built-in function for this purpose: ee.Algorithms.Landsat.TOA(input) ? Have a look at the documentation, but I suspect this might be what you're after.


2

If you first multiply every layer by 0.0001 and then calculate NDVI the surpassing shouldn't happen, as you are dividing a subtraction of two positive numbers (band values) by the addition of the same two numbers; this is because it is a normalized index, which mathematically means that it will range from -1 to 1 in this case; as you state, your values range ...


2

Converting WV3 data to ToA reflectance is fairly straight forward and is well documented in the official documentation. Basically, the approach is to go from DN to ToA radiance (L), using this formula: L = GAIN * DN * (abscalfactor / effectivebandwidth) + offset These parameters can be found in the metadata of your satellite image. From ToA radiance to ToA ...


1

If your composite looks pale, dark or in any other unfriendly way, it means that the histogram of the data needs to be adjusted. Such adjustment basically change which values in the data should be displayed. Since you're using Idrisi you'll probably find instructions here, but also take a look at this link, which I think makes it more clear which histogram ...


1

The grass72 version of i.albedo supports (now) for Landsat8 imagery.


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