6

The scenes are distributed by DC or Digital count. You need to use Quantification value to obtain reflectance. As @gmorin mentioned, scenes are already in TOA reflectance, but distributed in DC. To calculate reflectance you need to use: Reflectance (float) = DC ( 16-bit integer) / (QUANTIFICATION_VALUE) The value of Quantification value is defined in .xml ...


6

You can use Raster > Mask > Land/Sea Mask and choose Use vector as mask and the corresponding cloud band in the dropdown menu.


5

MODIS data is produced and distributed as a large number of products, and occasionally it can happen that the same product is produced by various agencies, or even tools available from one single data archive, in different data formats, projections, subsetted versions, gridded & swath etc. So it is customary to refer to a particular product, the source ...


4

After unzipping, you should find an xml file inside the root directory with the same name as the zipped file. Select the xml file and be patient because opening the file takes a little while. You can then view the data per band, or right click on the scene name to open an RGB composite. Normally this should also work directly from the zip file. However, ...


4

the RGB image in snap is built using the red, green and blue bands of Sentinel-2 MSI: respectively bands 4, 3, 2 (as you can see on the snap shot, those bands are selected by default). the "Profiles" in this case are predefined colour composites to visualize the data (only 3 out of the 13 spectral bands of Sentinel-2 can be sen by the human eye at once). ...


4

Creating a mosaic can be quite a complex topic - you have to select each individual pixel based on chosen parameters, either creating a median value, darkest pixel, average, ... Depending on this you will get more or less consistent images, e.g. neighboring pixels might be chosen from separate dates, one showing harvested field and one still growing ...


4

Using Sentinel-1 data a flooded rice field is pretty much indistinguishable from any other water body. If you want to stick to Sentinel-1 data and process it with SNAP you could exploit the fact that rice fields are only temporarily flooded. create the water mask for multiple satellite images on different times of the year create a stack of water masks and ...


4

ESA's SNAP software does have a Python API which you can set up by following these instructions. Additionally, in your SNAP bin directory you'll find the Graph Processing Tool executable. This provides a command line interface to the operators available in the SNAP GUI. Further, you can create your own graphs depending on your workflow and specify your ...


3

SNAP uses scene metadata information to compute the reflectance value instead to add Digital Count value when a scene is loaded: Metadata reader: public double getQuantificationValue() { return quantificationValue; } public double getScalingFactor() { return 1.0 / quantificationValue; } Band reader: ...


3

it's a bit old but here I am. Unfortunately GDAL does not fully support the NetCDF standard and Sentinel 3 netcdf are one of those unfortunate case. The following is a simple script written in kotlin unsing the java bindings: println(" * Converting $prodName...") val wgs84 = SpatialReference() wgs84.ImportFromEPSG(4326) val lst = gdal....


3

I would say SNAP does not read Sentinel-2 images as .jp2 files. A specific format is used instead. Although SCP does a great job, the output does not contain all the metadata information. I would recommend you to download the S-2 images directly from the Copernicus Open Acces Hub (https://scihub.copernicus.eu/). There, you can download your image as a zip ...


3

You need to add the -separate option in order to place each input file into a separate band and (optionally) the -co PHOTOMETRIC=RGB creation option to force the photometric interpretation (to avoid e.g. the ColorInterp=undefined and set the right color interpretation for each band): gdal_merge -separate -co PHOTOMETRIC=RGB -o merged.tif B04.jp2 B03.jp2 B02....


3

You can use this Python package that downloads S-2 products from AWS into .SAFE format: https://github.com/sinergise/sentinelhub


3

You can download Sentinel-2 data in .SAFE format on a per-granule basis from Google: Google Public Dataset: Sentinel-2 Bonus: Downloading of all available granules or searching for data can be scripted with boto, gsutil or any other library that talks to the Google Storage API.


3

Thanks to marcusN who pointend me to the ESA announcemet: https://scihub.copernicus.eu/news/News00092 There will be format change shortly, which means also, that the product will be delivered on per tile (granule) basis on ESA data hub.


3

SNAP contains tools to help you automate tasks: in the Tools menu you'll find entries for GraphBuilder and Batch Processing.


2

First of all I recommend to go to the official SNAP (Sentinel Application Platform - that's the real name of the software) website and get the latest version: SNAP in some parts is still under development thus it can be that you are using an outdated version which was missing the S2 reader. After you have done that and opened SNAP go to "File->Open Product....


2

According to me there are three (or four) possible way so far. 1)Leaf Area index from Statistics or water cloud model. 2) Radar Vegetation Index (RVI) from Dual-pol or quad-pol system and Radar degradation forest index from Dual-pol system. However, all these approaches are not simple and have lots of difficulties and limitations. Please try to read some ...


2

No way to calculate NDVI from SAR imagery, like Sentinel-1 images(any polarisations). To calculate NDVI you could get 2 bands (Near Infrared and Red bands) from Sentinel-2 or Landsat-8. So, about SAR. You just only can get some value about biomass or LAI (Leaf Area Index) and after that you can try to search some formulas to indexing vegetation for ...


2

The latest release of ESA SNAP (6 beta) features so-called AOI monitoring. http://step.esa.int/main/download/ It allows you to define a region of interest, schedule searching for the data and apply processing chains (as defined with the graph builder) on the data automatically. And with the new sci-hub integration you can download S1 data directly in SNAP (...


2

I looked into this and was not able to reproduce the exact results you got from SNAP (specifically I'm not sure why your output has a minimum value of 5). However, I was able to confirm that the results from SNAP and GDAL differ significantly. Two insights: GDAL is implementing the 95% clip correctly. I examined the original raster to identify the minimum/...


2

There is information about the spatial resolution (as distinct from the sampling rate) for Sentinel 1 in the technical guide. Most of the data (viz. hi-res GRD in IW mode) is roughly 20m spatial resolution, but is provided with 10m sampling.


2

I would like to draw your attention to Mosaicing tool in Raster | Geometrical Operations menu. (*1) Start Mosaicing tool. There are several tabs (as below) in the dialog window; [I/O Parameters] Read your Sentinel-1 images (.tiff) into Source Products by clicking on small plus icons. Set output directory and filename, along with the output format. [Map ...


2

You can check the processing baseline in the MTD_MSIL2A.xml file (inside .SAFE) under the tag . Sen2Cor v 02.08 started with the processing baseline 02.12. But notice that the S2 PDGS is using more versions than the public sen2cor versions. For example, this is some of the sen2cor versions used in some processing baselines:


2

If your L2A images were processed using Sen2cor, you already have a cloud mask inside the .safe structure at 60m (S2X_MSIL2A_YEARMONBTHDAY.SAFE\GRANULE\IMGNAME\IMG_DATA\R60m). If you don't have this you can apply sen2cor on the same image (Level 1) to obtain it. Otherwise you should use a different method rather than Sen2cor.


2

you can still get Sentinel-2 L1C products here: https://peps.cnes.fr/rocket/ Select Collection: Sentinel-2 Single Tile" Processing Level: LEVEL1C


1

How did you install Sen2cor? Did you follow this procedure? I installed SNAP v 6.0 and download Sen2cor 2.4 stand-alone installer follow the procedure mentioned in STEP forum. I've set environmental variables in SNAP too, it's the most important part to be successful: I was careful, but setting could be: SEN2COR_HOME = $USER_HOME SEN2COR_BIN = $...


1

Which version of SNAP are you using? Which kind of METADATA (*.xml) file have your scenes? From almost a year ago, metadata naming convention changed and old versions of SNAP don't support that kind of structure. The old version was named as S2A_OPER_*.xml, now all scenes have the same metadata name: MTD_MSIL1C.xml (check product description file). In this ...


1

Whatever the software, a generic method : You need to classify clouds into a binary mask (0 - no cloud/1 - clouds) You use your mask as a conditional raster where : if 0 then keep one source of Data (Sentinel 2) if 1 (or else) then keep another source of data (Landsat 8) EDIT : I just saw you use SNAP software. I don't know it but i leave my generic ...


1

sentinelloader is a Python package that attempts to tackle this problem: With this utility you can specify the desired polygon, image resolution, band name and aproximate dates and it will do the best effort to find all tiles needed to satisfy your requirement. Then it will download minimal data by selecting just the needed .jp2 files inside Products, ...


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