I'm guessing you never worked with SAR data before, so I'll break your question down into parts I can answer:
1) Create high resolution DEMs in GIS
The process of creating a DEM just from SAR data is quite complex and requires a lot of processing power and memory. I don't know of a GIS software that implements DEM creation due to these constraints.
You can get Sentinel-1 data from scihub.esa. Requires only
registration (And most likely, non-commercial use). As Sentinel-1
has just become operational the archive is not very extensive but
should grow quite quickly.
You can set request data-access propospal on Alaska Satellite
Facility. Some data open access. For ALOS-PALSAR you must be a resident of the ...
Think of the geometry. The incidence angle refers to the angle from nadir, or directly beneath the satellite, which would be 0°. As the sensor looks out to the sides from this nadir, the angle of incidence increases as does the fov (field of view). This is why the resolution decreases with increase in incidence angle. This illustration from the Sentinel ...
Export.image.toDrive is a client-side function, and you cannot call it from a server-side function (the one you are mapping over), so you have to do it all in the client side. I have a repo where you can find a bunch of useful functions: https://github.com/fitoprincipe/geetools-code-editor
There is a function to export all images from an ImageCollection to ...
The intensity image should be used for calibration and subsequent classification of geophysical features. To radiometrically calibrate the intensity, use the Calibrate tool in the Sentinel-1 Toolbox (SAR Processing > Radiometric > Calibrate). The S-1 Level 1 GRD product includes several Look-Up Tables (LUTs) to convert intensity values into sigma or gamma ...
A good alternative to the official Scihub is the mirrored Sentinel-2 data on Amazon Web Services.
Sentinel-2 on AWS
This has the advantage of better uptime and the products are already saved in their MGRS tiles, which makes downloading a lot faster.
The data is stored in a public bucket with the scheme tiles/[UTM code]/latitude band/square/[year]/[month]/[...
Otsu's method does not really care about actual values since it tries to minimize the total variance within classes while maximizing the distance between the classes. So, you could just run Otsu on your original data (no need to rescale) and it will provide you with the optimal threshold to use to achieve the goal listed above.
I don't know what is your ...
Only managed to find a couple of sources for SAR images and data:
You can download SAR images from here which are mostly focused on ecological sites such as forests:
You can download SAR samples from here which contain fairly large datasets (note: the last 4 links at the bottom of the SAR section are dead)
I received help from an application developer at JNCC. I will post their answer here to help others.
My problem was that I needed to escape the $ character before value. so the wget command should read (using the apihub, which you could replace with dhus):
wget --no-check-certificate --user=username --password=usrpass "https://scihub.copernicus.eu/apihub/...
True color images can only be obtained from optical sensors that detect visible light reflected off the Earth's surface. As @jeffrey-evans mentions in the comments, Sentinel 1 is a SAR sensor, which does its measurements using completely different wavelengths.
The measurements are rich enough, however, that they can be combined into several colour ...
I found a pretty exact way to answer this question. It exploits the sentinelsat Python API to extract the desired information directly from ESA's SciHub:
from sentinelsat import SentinelAPI
api = SentinelAPI('yourUsername','yourPassword')
S1 = api.query(date=('2017-01-01T00:00:00Z','2017-12-31T23:59:59Z'),platformname='Sentinel-1',producttype='SLC',...
Sentinel-1 data is published as Open Data, with attribution, see licence here. Registration required. An API is provided. See Scientific Data Hub for details.
Software is also provided to process data.
Here I found an article "Preliminary results of using Sentinel-1 SAR data for DSM generation", 2015. As I understood, the vertical accuracy will not be better than 20m (an average height of a single tree). That is comparable to the SRTMGL1, GDEM2 accuracy.
I didn't find it useful to improve the SRTM DEM, by filling the forest masked areas in the SRTM1GL (to ...
JAXA have made global L-band SAR mosaics at 25 m spatial resolution available from the PALSAR sensor:
Registration is required to download the data.
Based on my own understanding:
In SAR images resolution and pixel spacing are two different things.
Resolution means the maximum ability to distinguish two close scatters. The resolution of one SAR image is usually based on the bandwidth of signal (in Range direction) and the 'synthetic bandwidth' in azimuth direction.
Well Pixel spacing is easier, it ...
Version 0.7.1 of sentinelsat has just been published to Pypi and solves this issue.
Root cause was the change in behaviour of the rows argument in SciHubs OpenSearch protocol. sentinelsat now queries 100 results at a time until no new scenes are returned. (see the documentation for further info).
Discussion of the changes can be found in the related pull ...
As described here, you may want to try a Styled Layer Descriptor. The previous answer also works, but requires you to use getInfo(), which can cause your browser to lock (see Client-Server doc for details). Here's another approach:
var i = ee.Image(ee.ImageCollection('LANDSAT/LC08/C01/T1_TOA')
There is a kml file provided by ESA that shows the location of each Tile. Overlay it with your study area and you will see which is your target tile.
Acquisiton plans are also published by ESA. They are published as KML files. You can download historical data but the complete plan for the next year is not pusblished. ...
It's normal that azimuth and range resolution of SAR sensors differ, because they depend on different variables:
The azimuth resolution (AR) of a SAR system is:
The slant range resolution (SRR) of a SAR system is:
The ground range resolution (GRR) of a SAR system is:
For dowloading the data with their original name, you may use the -JO parameter of curl as in the following example:
curl -u username:password -JO "https://scihub.esa.int/dhus/odata/v1/Products('177db57e-56ca-4588-830a-cfb8712ecf6f')/$value
If you think about listing the products, you could try the following for ten product from the 20th:
curl -u username:...
Rasterio can read and write GCPs and warp with them since version 1.0a3. src.crs returns nothing to make it clear that there is no coordinate reference system associated with the file's affine transformation matrix. If you want to see the file's ground control points and their CRS, do this (one of the project's test files shown for example).
Welcome to the trenches of classification, probability and statistics ;) .
Assuming you used sklearn, it has a detailed user guide on what metrics it provides to evaluate your classifications:
I'll quote the user guide on this:
Intuitively, precision is the ability of the classifier not to label
as positive a sample that is negative, and recall is the ...
If you want to export the original image, set the crs, crsTransform
and dimensions parameters to match the values of the original image. Setting the scale value may get you similar results, but scale is a less direct specification of the coordinate reference system (CRS).
If a different CRS is specified (using the scale or crs and crsTransform parameters), ...
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 ...
This is a known issue and caused by inaccurate access to the SRTM 3Sec (Auto Download) data which is required for the terrain correction. Usually, it is automatically downloaded but the access changed.
Solution: Please install the latest internal updates (see image below) of SNAP and restart the software. Additionally, I recommend using the SRTM 1Sec (Auto ...
First of all, SRTM and SAR should not be opposed, because SRTM was derived by interferometry (C-Band and 60 meter long baseline). Sentinel-1 is also C-Band and a relatively small baseline (50 m RMS orbital tube).
The big difference is that SRTM used a mast on the shuttle for systematic interferometry, while you lose a lot of coherence between two ...
Here's a fuller answer about the synthetic aperture radar (SAR) data available from the Alaska Satellite Facility at no cost to users. The datasets include Seasat (1978 data newly processed in 2013), InSAR, PALSAR (including radiometrically terrain-corrected products), RADARSAT-1, ERS-1, ERS-2, JERS-1, UAVSAR, AirMOSS, AirSAR, and more.
SMAP data will ...
You are probably also getting more backscatter because there is bare rock at the summit instead of vegetation. Vegetation holds moisture, which would absorb microwaves rather than backscattering.
Besides, the foreshortening which affects the fore slope increases its intensity (having more backscatter returned into the same cell yield more intensity.