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Hi everyone, I’m studying historical land cover change from 1984 to 2020, I need to calculate NDVI for every image, can anyone help me with a python script to do the task? considering all 3 sensors of Landsat. Thank you

I am curently trying to follow this Tutorial and I can’t seem to understand the following sample code: raster_value = { '0%': (0, [0, 0, 0, 0]), '10%': (1, [163, 235, 153, 255]), '30%': (2, [119, 195, 118, 255]), '50%': (3, [85, 160, 89, 255]), '70%': (4, [58, 130, 64, 255]), '90%': (5, [36, 103, 44, 255]) }

Hello, I would like to implement this project ( sentinel-hub/field-delineation: Field delineation with Sentinel-2 data from Sentinel-Hub and a ResUnet-a architecture. (github.com)) into my Area of Interest. However, I would like to skip this workflow without using Batch Processing API which is located in 01-data-download jupyter notebook. Instead I would like to download data with only Sentinel HUB configuration. Has anybody done this before?

I have downloaded some planet data using the Example-8-:-Multiple-timestamps-data script (link) and that works fine. However, as I plan to download the last 7 days of images, every week, it would be useful to know what date the image was taken. There is a simlar question here however it uses WmsRequest() and with that solution I am able to open the url in the json that the function (see below) looks at, however the json file that I have does not contain a date aspect in the url. It contains a timestamp, but that is when I created it, not when the image was taken.

As a new user I was wondering if any the wavelength bands can be used on inland lakes to see temperature, depth, or vegetation variations / differences in the lake. As SWIR has a high absorption, it might be some combination of the reddish wavelength bands. Especially on mountain lakes with high water clarity. So far in all my attempts water is only black. Complete absorption.

Hello there, Excuse me, I am wondering about how can I download directly monthly data of Sentinel5P, L2 by selecting an interesting country and how to export the data in order to use it in my research? Best regards

Hi Folks I would like to carry out a PCA on images. This requires collection of image stats including eigenvalues and eigenvectors. Would be the basis of a decorrelation stretch (reverse transformation necessary). Can anyone help out an aged EO scientist (worked with Landsat MSS! and FORTRAN). javascript really new to me. Many thanks Andrew

Hi, relative to S-2 images, I would ask if is possible to “quantify” the “dominance effect” of one pixel on another if we considered ONE pixel. This effect produces a not true value of DN (one for each spectral band). This effect, I have read elsewhere, can be minimized if we considered an array of (minimun) 8x8 pixels. It’s true? There is some official documents of ESA attesting this? Thank you. Nicola

class CustomUrlParam(Enum): Does not have the parameter PRIORITY. I want the data in EOPatch in order of cloud coverage by using PRIORITY as leastCC. Please let me know how to use custom URL Parameter “PRIORITY”. Thanks, Tushar

we would like to detect any change in the landbank for any activities, especially encroachment issues and notify them internally. We plan to take high-resolution images and compare using AWS computer vision for any suspicious activity in a week. We seek solutions and guidance on how to achieve this task… specially how to take high-resolution pictures once a week automatically and compare the same.

I am trying to configure CLIENT_ID and CLIENT_SECRET as indicated in the tutorial In my dashboard I configured a new OAuth (ID: db24bd9f-94ea-45d1-9a1b-0f91b73d4b4b), however when I type in the cell this data, and executed (img = request.get_data()[0]) ) gives me this error: ValueError: The configuration parameters ‘sh_client_id’ and ‘sh_client_secret’ must be set to authenticate with the Sentinel Hub service I have written the parameters correctly in the following script in the documentation and if you allow me to connect, but as I mentioned before, in the tutorial code cell it generates an error. from oauthlib.oauth2 import BackendApplicationClient de requests_oauthlib import OAuth2Session client_id = 'db24bd9f-94ea-45d1-9a1b-0f91b73d4b4b client_secret = 'mytoken client = BackendApplicationClient(client_id=client_id) oauth = OAuth2Session(client=client) token = oauth.fetch_token(token_url=‘

Hi Ever one. I need to know whats is the best configuration to get the best and atualizated images from Sentinel - L2A. I m atual layers in use is: #### Bathymetric ID: BATHYMETRIC #### False color (urban) ID: FALSE_COLOR_URBAN #### False color (vegetation) ID: FALSE_COLOR #### Geology ID: GEOLOGY #### Moisture Index ID: MOISTURE_INDEX #### Natural color (true color) ID: TRUE_COLOR #### NDVI ID: NDVI #### NDVI_TESTE ID: NDVI_TESTE #### SWIR I will be very glad if some can help me! Thanks comunity! =)

Hi! I am doing my master thesis on whitecap detection and eventually atmosphere - ocean interaction and wind forecasting based on this. Therefore, I am wondering if anyone have experience using s2cloudless for this application? Any modification of the segmentation process that could be recommended etc. Thankful for any input from the community.

Kindly suggest how to download datasets in batch from Sentinel-1 s3 on AWS (via aws cli ). Is there any way we can query the s3 for a list of datasets and download them ? Kindly suggest.

Hi, I have been running the EO-learn Land Cover Map Jupyter Notebook, which uses the LightGBM algorithm for creating the land cover map. As I have access to a machine with a dedicated GPU I thought it would be interesting run a test of this algorithm, first using the CPU only, secondly with a GPU included. After some tweaking the algorithm (https://lightgbm.readthedocs.io/en/latest/GPU-Performance.html), I expected a considerable speed-up with the GPU. However, not so much changed (4.41 min wall time for GPU vs. 6.46 min wall time for CPU), I expected more like 2-3x speed up. As I not an expert on GPU tuning, or IT hardware in the first place, I am wondering if someone on this forum has experience with the use of GPUs for classifications, or could provide some information on what I did actually made sense.

I was trying to do image co-registration of two images using arosics and eo-learn. What is the difference in the methodology of both library. I tried co-registering MODIS and Landsat-8 using arosics. But it takes a lot of time on whole raster. Any example of co-registering specific bands of two images without downloading them and only download co-registered band of image.

Qué procedimiento seguir para conocer indices SIPI y NDWI?, estoy interesada en conocerlos en fincas de Colombia.

I do not have much experience for the analysis of the data. I need to see if someone can help me in the following cases: I need to download some data table from a specific region, an excel format would work for me. In the EO Browser, I have doubts about the Moisture Index, does that index show the humidity present in the plant? or how does it differ from the NDWI index? regards…No tengo mucha experiencia para el análisis de los datos. Necesito ver si alguien me puede ayudar en los siguientes casos: Necesito descargar alguna tabla de datos de una región en especifico, un formato de excel me funcionaría. En el EO Browser, tengo dudas con el índice de Moisture Index, ¿ese índice muestra la humedad presente en la planta? o en que se diferencia con el índice de NDWI?  

Hello , I am using google colab (python) to fetch images from sentinel-hub …it was working fine and all but the next day when I ran the code again I got an error in the get_data() command … UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x7fb0c3f0c9b0> Its weird to me that when I restarted the run session as a whole and closed and reopened the note it worked … (not an efficient solution ) So does anyone know what is this issue and how can I solve it ?

Hi folks,I read about your Landsat 8 cloud segmentation approach here:Medium – 31 Mar 21Clouds Segmentation in Landsat 8 imagesGetting more valuable data from Landsat-8 missionReading time: 7 min read  … and here:

Accessing Sentinel data from the Earth on AWS Open Public Dataset

Dear experts, I am working on a project to detect fire based on the multi-spectral data. My current process is manual - reviewing, based on the actual fire infirmation or based on data from MODIS, each image for the specific location and time period and flag them accordingly. Besides being time consuming, this has scope for many errors. Is there a better option to download the fire and no-fire data (either image or the underlying bands). There are some eval script that does the fire masking (which I am following to revalidate), but I want to minimize the false positives. Without proper labeling, the rest of the code will not function properly. Any pointer would be highly appreciated. My preference is to use the non-visible spectrum, but I am not able to find the right way to label them. Also, when downloading .png or .jpg, what would be an ideal resolution, especially if you only have longitude and latitude? Does it make sense to add a bigger buffe

Hi all,I try to use “batch” in Request Builder and followed all the cascading guides to set up a bucket at Creodias cloudferro. I updated the policy and the response is:result = s3.get_bucket_policy(Bucket=bucket_name)pprint(result[“Policy”])('{“Version”: “2012-10-17”, “Statement”: [{“Sid”: “Sentinel Hub permissions”, ’'“Effect”: “Allow”, “Principal”: {“AWS”: ’‘“arn:aws:iam::ddf4c98b5e6647f0a246f0624c8341d9:root”}, “Action”: [“s3:"], ’'“Resource”: [“arn:aws:s3:::JensContainer2”, ’'"arn:aws:s3:::JensContainer2/”]}]}’)But in Request Builder i get this error “Bucket does not exist”.Does this mean, that the connection to the cloud is okay ?What could be the most likely next thing to check ?Best wishes! 

Hi, I’d like to find right post-processing parameters values without having to do lots of tests (and then compare the results). I didn’t found any table in documentation. In the notebook, one can find these values for 10m Sentinel-2 bands : threshold=0.4, average_over=4, dilation_size=2. But on this forum, i read “average_over=22, dilation_size=11” (still for 10m resolution images). I suppose I should use the ones from the notebook (which is ~2 years newer), but is there any table with up-to-date parameters values for multiple resolutions out there ? Thanks !

olá, não consigo gerar as imagens através da api utilizando o javascript. Quando utilizo o cURL consigo normalmente, mas com o javascript não consigo de jeito nenhum. Teria como me enviar um código javascript de requisição de imagens NDVI?