I am currently working on a project that needs average NDVI values of zipcodes across the US.
When I download images from sentinal hub (sentinal 2, geotiff 32bitt, custom 10x 10 y). I then open it on my QGIS account.
I find two issues, one is that the scale is from 0-1, I know how to use the raster calculator and by doing this expression: (“NDVI_Layer@1” * 2) - 1 the scale would be -1 to 1.
My real issue though is that when i use the identify feature tool and hover over the image (whether it is the original or the rescaled). I get wrong values, areas of vegetation are -1, and the average ndvi value of an area would be -0.2 when i know that the most frequent values should be around 0.4-0.6.
So, my question is what is the easiest way to download NDVI values and then open them on qgis? I do not want to export individual bands, i just want the ndvi image to be correct when i open it on qgis. The crs i use is 4326.
Hi Fatma, Please can you share the request (or screenshot) and the evalscript that is used to calculate NDVI. It sounds like you might be using a visualisation script for analysis but without seeing what you are doing I can only guess.
Thank you for responding! I realized that I was downloading ‘NDVI images’ and not using a custome script to get the NDVI values.
Can you please let me know if my process is correct now?
I used this custom script:
//VERSION=3
function setup() {
return {
input: [“B04”, “B08”],
output: { bands: 1, sampleType: “UINT16” }
};
}
function evaluatePixel(sample) {
let ndvi = index(sample.B08, sample.B04);
return [10000 * ndvi + 10000];
}
Then i re-scaled it to -1 to 1 on qgis using:
(“ndvi_layer” - 10000) / 10000
And then, I reprojected geospatial layers to the ESRI:102003 - USA Contiguous Albers Equal Area Conic coordinate reference system to ensure accurate area calculations. (Area zipcode polygons i downloaded from nhgis were ESRI:102003. Sentinel-2 images with overlapping coverage were merged into a single raster layer, which was subsequently clipped to the boundaries of each polygon. Mean NDVI values were calculated for each area using the zonal statistics tool in QGIS, integrating raster-based data with vector polygons for area-specific statistical analysis (the mean from zonal statistics)
It is my first time doing this for a research project so I would be grateful for your input! Thank you.
You should be using FLOAT32 as your Sample Type in your output. You cannot obtain NDVI values with UNIT16 as this will only output unsigned integers and not float values which spectral indices require.
You can remove your scaling calculations after this. You don’t need to multiply your NDVI output and add 10000 too.
Hi William,
Thank you for your response, so would the full script look like this?
//VERSION=3
function setup() {
return {
input: [“B04”, “B08”],
output: { bands: 1, sampleType: “FLOAT32” }
};
}
function evaluatePixel(sample) {
let ndvi = index(sample.B08, sample.B04);
return [ndvi];
}
It still gave me an error to obtain the image, I am not sure what I am missing.
Assuming I will be using the right script and then download the images with ESPG:4326 will I then be correct in my strategy if I reproject the layers to ESRI:10200 to fit the polygons CRS from the zipcodes? I would then merge the layers and then clip it to the polygon and run zonal statistics to get the mean (which I assume is the NDVI).
I do appreciate your follow up and look forward to a reply, if it is possible to continue this over email as well I am more than happy to receive guidance as it has been a challenge to ensure my NDVI scores are accurate.