I'm using this code in gee and using whole Banggladesh map as an area of interest.

Code :

var collection = ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3') .select('O3_column_number_density') .filterDate('2023-01-01', '2023-12-31') .mean() .clip(table);

var band_viz = { min: 0.12, max: 0.15, palette: ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red'] };

Map.addLayer(collection, band_viz, 'Ozone Concentration'); Map.centerObject(table, 10);

Export.image.toDrive({ image: collection, description: 'Sentinel5P_Ozone_2023', scale: 10000, region: table.geometry(), fileFormat: 'GeoTIFF', crs: 'EPSG:4326' });

but when I run it to export the geotiff file it says, 'Request payload size exceeds the limit: 10485760 bytes' How can I solve it?

I'm working on a small class project, where I depict elevation change / difference in the Everglades. To do this, I'm trying out data from the SRTM DEM and the 3DEP datasets. Both seem to have some scan issues though, I'm still relatively new to RS so I wanted to check if this is closer to a dataset issue or an issue with how I am processing the data, any advice?

Coding done in GEE

SRTM | Random Diagonal line in South Florida, does not correspond to any highway or anything

3DEP | I expected to see a more gradual decline here instead of rectangles, other errors also seem to be present

I am an international masters student in Germany looking to enter the industry. I’ve been thinking and looking at the market now to see how it looks like.(not too good). I’m abut concerned that I might not be looking in the right places mostly LinkedIn and https://github.com/chrieke/awesome-geospatial-companies. Are there any other current and active job portals anyone knows to look for jobs ?

And is there any other advice any one with experience in the field can give to someone looking to enter the GIS/RS field in Germany pretty soon?

Wrt to the language I am learning the language(it’s pretty stressful ) but hopefully by next August I should start B1 classes. I have however seen posts (not related to the GIS field ) where others say even sometimes a C1 is not enough so I’m pretty confused.

Basically I’m looking for advice on how to navigate the German GIS market and how to gain an advantage.

I’m pretty versatile and can move in between GIS, photogrammetry, remote sensing and GeoAI… I did have about 5 years of professional experience in my home country before starting my masters

Hello!! I’m taking a remote sensing and analysis course at university and I have a few questions that my professor isn’t able to help me with, would anyone be able to have a pm chat?

EVE (Earth Virtual Expert) is an upcoming LLM virtual expert from the European Space Agency (ESA) and is designed to enhance Earth Observation and Earth Sciences. We want to hear from you!

Please take a moment to complete our user requirement survey https://rk333.wufoo.com/forms/earth-virtual-expert-eve. Your feedback will help us customise Eve to better serve your needs and contribute to the platform's development.

This survey is implemented by Imperative Space and Pi School on behalf of the European Space Agency (ESA). Eve is a consortium led by Pi School in partnership with Imperative Space.

I was wondering if what are some major differences between these two. I looks like the both offer data, api and compute capabilities.

Hi,
I want to map the coastline/shoreline that is highly susceptible to erosion or is visible as eroded in Google Earth pro but, I am struggling to trace it. I aim to look out for the LIDAR data for the same area over different time scale that I marked over Google Earth, every time I try to download the desired polygon from Defra database I tend to download too many grids. How am I suppose to do with the long coastline if I cant get it right for a small area?

PS this is the first time I am trying to work with the LIDAR data.

#coastal #remotesensing

https://preview.redd.it/lq0yes6kxe2e1.png?width=360&format=png&auto=webp&s=445aa16815cd78a483b1c6e390546918b90709ba

Someone help me. I've been ding this for hours. What should I do?

I’ve been having some difficult feelings lately, and I don’t really have anyone in my immediate circle—especially not anyone in the sciences—to talk to. (Except for chatgpt). So here I am, hoping for some words of support or a reality check.

I’m 36 and have spent my whole career in marketing as a content creator. After several years of existential crisis, I’ve felt a deep need to change careers.

I’ve always been fascinated by science but never seriously considered the possibility of being part of it. But in times of crisis, many things become questionable, including this long-standing limitation. That’s why I decided to try: I started auditing courses at a science university, curious to see how much of a latent scientist I might be. Well, it turns out, not all that much. Most of the classes I attend are difficult for me, as I often struggle with abstract concepts.

At the same time, I’m tech-savvy, have basic knowledge of Python and machine learning, and am stubborn enough to spend hours debugging and tackling challenging tasks. That’s why one class in particular—remote sensing of the environment—feels suspiciously accessible.

It’s still early days, but I’ve already found myself imagining that this field could open an entirely new world to me—one I never thought I could be part of. Compared to this, my old career seems so bleak—I can’t imagine going back.

I see a community of people doing something meaningful, and I imagine myself playing my small humble role in it.

But is this fantasy I have at all realistic? The idea that it might be possible to focus very narrowly—to study remote sensing, machine learning, and bits of other related fields like spectrometry and geology, but only as they relate to remote sensing—and then find a job in the field without a science degree?

Am I kidding myself?

I’m not looking to take opportunistic shortcuts or avoid hard work, but I’m also honest about my situation: I don’t have 4–6 unpaid years to dedicate to a degree, nor do I think I have the kind of brain needed to fully master traditional science.

Thank you for taking the time to read this. Whether you have words of support or of realistic discouragement, I’d deeply appreciate your honest thoughts.

And here are some more specific questions:

• Has anyone here transitioned into a field like remote sensing without a scientific background?

• Do roles exist where such a narrow focus might be enough? If so, where should I look?

• Are there other specific areas in science I should explore if I pursue Earth remote sensing?

TL;DR: A humanitarian with experience in digital image processing and basic coding skills wants to transition into remote sensing. Wondering if it’s realistic to do so without a full science degree. Seeking advice and reality checks.

I am a beginner in remote sensing. I noticed in tropical countries there are a lot of clouds blocking the satellite images I downloaded from Earth Explorer. I was wondering how do people remove the clouds in the images? Are there any recommended tutorials, books, or forum posts (anything) that could help me understand this topic? I am just really curious about how removing clouds works. I would love to understand what is going on instead of just clicking buttons on the software. I know I have a lot to learn but I don't know where to start. I have read Fundamentals of Remote Sensing by Canada Centre for Remote Sensing. But I don't think I have fully understood what was written. I really appreciate some recommendations from the pros here. Thank you in advanced.

Hi, I want to train a network on a dataset of multispectral imagery, but I don't have a lot of labels. So I was thinking about doing some transfer learning, but most lreday trained networks are on RGB datasets like Imagenet on not on the same spectral bands that I have. That means doing some pretraining on an unsupervised task on my dataset is probably a better idea (I have a lot of images). Did anybody come accross the same problem and found a solution that was working well?

I have a data with RGB bands with lots of sunglint. Now, i want to detect and classify the area with sunglint. After that, I want to remove those area with sunglint. How do I remove that the area with sunglint?

Imagine a sensor (let's call it sensor A) that captures images in two viewing angles, near-nadir (NN) and off-nadir (ON). The task is to downscale (DS) the images. Assuming, for validation, there is another sensor (sensor B) that captures images in the same wavelength as the sensor A. Sensor's B images are not regular in terms of temporal resolution and it can acquire images for a specific region from different viewing angles (VA). In the metadata of sensor B images, the VA is not mentioned.

How would you approach the task of validating the DS images from sensor A using the sensor B? What I'm trying to say is that "traditional" validation tests (i.e., r-squared or RMSE) might not be appropriate because (to me at least) it's like comparing apples to oranges. What I mean is that if I am to compare the DS image from the NN VA against the image from sensor B, and the later image is taken from a NN position, then it makes sense that the r-squared will be higher compared to the ON vs Sensor B.

What are your recommendations? How would you approach this task?

Hi, All:

I’m curious if you guys can help me. I’m iso a new laptop that has the ability to process large data sets in ENVI & Arc, with room for a few (applications/softwares) others to run simultaneously.

In addition, I’ve looked into commercial drones w DJI and w recent creative pursuits am considering one w a larger payload / more options. I have not revisited the drones for some months now, so perhaps new tech has been released that you guys would suggest one over the other. For ref, I would be using use the drone(s) for precision agriculture projects, environmental remediation, and film projects. The PAg and EnvRem would have sensors attached to the payloads, whereas the film projects would obviously be using cameras. On the off chance anyone has good suggestions for those items too, that would be stellar.

Thank you guys. In between things right now, but these are things I want to sort out before spending the coin. I built a Dell laptop earlier in the year and it was ~$10-12k, which I’m not sure is necessary. I can post details of that later. Hoping this finds you all well. Thanks in advance.

I need help with a college project to create a deforestation alert system. Experts please guide me. Thanks in advance.

Hey everyone,

I am currently working on my Master’s thesis, where I am comparing different supervised classification approaches (RF, CART, SVM) using Sentinel-1 and Sentinel-2 data, as well as a combination of these two products. My study area is Santa Cruz Island, Galapagos. My results are quite promising, but as we know, nothing is perfect. :)

My models are trained with training data (polygons) that I created in Google Earth Engine. Due to a lack of validation data for my accuracy assessment, I had to create my own validation data in the same way I created my training data.

The ‘problem’ is that my accuracies range from 0.93 to 0.99 (with Sentinel-1 classification between 0.7 and 0.84). While the classification looks good, this seems very unrealistic to me.

Do you have any suggestions on how to address this issue?

Do you think combining polygons and points for the validation data would be helpful? Currently, I created the validation data in the same way as the training data (polygons in areas where the class is obvious). Should I focus more on the transition areas between classes in my validation data? Or do you think my results are acceptable as they are?

I hope my problem is clear.

Thanks!

Training sessions will be available in English and Spanish (disponible en español).

English (November 19 & 21): https://go.nasa.gov/3BefXOl

Spanish (7 y 9 de enero [January]): https://go.nasa.gov/47zcAxD

Hi all, I am considering a post-doc in remote sensing and machine learning. I'm wondering what good labs would be in Europe, and primarily, if people could share some experiences on whether it is nice to work there (atmosphere in lab, workload, are professor's nice, ...)? Thanks y'all!

I am an absolute beginner in gis, with no mentor to guide me or tell me if my steps are correct or not. I hope you guys can guide me.

I am trying to do a land use classification to detect urban land change, after a lot of learning trial and error I was able to download landsat 8 data with all of its bands, then do a supervised classification in Arcgis pro. I have seen many tutorials where the result is almost perfect, and I don't see that in my project (maybe because the area is too small). I'm not sure if my result's accuracy is acceptable or not, or what other steps I can do to increase accuracy. I would appreciate any help or guidance you can give me.

In this link there is the classification I did and for comparison an Arcgis base map of thee same area (better quality than the landsat data I used) : https://imgur.com/a/9n2pyxL
Urban areas are red, water is blue, forest is green and empty field are both yellow and that other colour

I'm working on a project involving 21 field sites where I've collected data on two grass species (let's call them Grass A and Grass B). For each site, I have recorded biomass, leaf area index (LAI), and cover percentage. I also have hyperspectral reflectance data for each site, collected using a FieldSpec Pro.

Here's where I'm at:

• I've performed significance tests and found that LAI and cover percentage differ significantly between Grass A and Grass B.
• I've calculated hyperspectral vegetation indices for each site based on literature related to LAI and cover.
• In my initial analysis (e.g., plotting LAI vs NDVI and cover vs NDVI), I've observed distinct clusters for Grass A and Grass B.

My Goals:

• I want to classify the species type (Grass A or Grass B) based on the relationship between vegetation properties (LAI and cover percentage) and hyperspectral vegetation indices.
• I also plan to do similar classifications using multispectral vegetation indices.
• Ultimately, I aim to create a spatial distribution map of Grass A and Grass B.

My Background:

• I'm relatively new to remote sensing and have limited experience with machine learning.

Questions:

• What classification methods would you recommend for this type of problem?
• Are there any specific resources or tutorials that could help a beginner understand and implement these methods?

Any suggestions or guidance would be greatly appreciated!

Thanks in advance!

The paper aims to shorten acquisition time, reduce costs, and accelerate the deployment of imaging devices.

https://openreview.net/pdf?id=MloaGA6WwX

Contributions:

• A novel method for supervised feature selection that performs task-based image channel selection.
• Results shorten the acquisition time in MRI, reconstruct image cubes of remotely-sensed multispectral ground images with few sensors, estimate tissue oxygenation from hyperspectral medical devices.
• Results show improvement on i) classical experimental design, ii) recent application-specific published results, iii) state-of-the-art approaches in supervised feature selection.

We expect further applications to similar datatypes e.g. data efficiency on multi-channel images, other hyperspectral/multispectral application, cell microscopy, weather and climate data et.c

Code is available, PM me if interested.

Hello good people, hope you all are doing well.

I will be facing my PhD interview in remote sensing within a couple of days. I worked on LULC change analysis in my Master's thesis. Is there any suggestions on what types of questions might be there or how should I prepare for it?

Any sort of insight on PhD interviews in remote sensing will be much appreciated as it will be my first PhD interview.

Thanks for your time.

You can now define your own band groups and use them when defining a product subset or filtering bands for the spectrum.

https://preview.redd.it/p2epsp93zuxd1.png?width=618&format=png&auto=webp&s=8f9c9e10c1065cdab85be2b167766e39848052ff

Also the support for several data formats has been enahnced and others have been added. Like PRISMA, PACE OCI L1B/L1C, and ECOSTRESS.
https://www.eomasters.org/post/snap-11-what-s-new

SNAP can be downloaded from https://step.esa.int/main/download/snap-download/