Predicting LST with Population, Rain, and Elevation using Random Forest Regression in Earth Engine

In this tutorial, you will learn how to use Google Earth Engine to predict Land Surface Temperature (LST) using population, rainfall, and elevation data. We will be using Random Forest Regression, a machine learning algorithm, to create our prediction model.
Script: code.earthengi...
First, we will access and import our data into Google Earth Engine. We will be using the Land Surface Temperature dataset from OpenLandMap, population data from WorldPop, rainfall data from OpenLandMap, and elevation data from NASADEM.
By the end of this tutorial, you will have the skills to use Google Earth Engine to predict LST using Random Forest Regression, as well as the knowledge to apply this technique to other datasets and locations.
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[@IAKhan-km4ph]

Great work. Always learning by you. Allah pak bless you.

[@IAKhan-km4ph]

is this ('random', 0.8) correct for both train and test?

[@ibrahimmuhammed5332]

Can you substitute population with NDBI, NDVI, MNDWI and Albedo because they are the direct dependent variables? Hoping to see that online. Thanks a lot!

[@ErickMhaya]

Hello do you have some codes to calculate MNDWI

[@IAKhan-km4ph]

Would you please guide about regression equation using variables for LST prediction

[@ramiqcom]

You can use ee.Reducer.linearFit to get the y=ax+b

[@IAKhan-km4ph]

@@ramiqcom thank you

[@IAKhan-km4ph]

can we validate. And R² suggest good fit.

[@geologistdinesh]

can not understanding train data sample

[@Userss-c5u]

Great 👍 work. Thanks for sharing your knowledge. Allahumo baarik🎉

[@ramiqcom]

It's my pleasure

[@renitapurwanti7241]

Hi, can i get your contact or your email? i bought your course about Urban Environment held by Geocourse, and running it to make LST Prediction in the Future but there's an error in the script, and i need your assisstance to tell me what is wrong.
Thank you for your consideration

[@ramiqcom]

Check my youtube account profile

[@huihuiKing]

Do we need to set the time range for these features and labels? Should we keep them consistent?

[@alemayehumullatuadashio5350]

Thank you very much ,it is very interesting video.

[@khoirulkasanah9505]

Can this random forest model be used to identify landslide susceptibility?

[@sommiga1279]

great my dear thank you,
after applying this script "var sample = combined.sample({
numPixels: 5000,
region:geometry,
scale: 100,
geometries: true
});
print(sample);
Map.addLayer(sample);"
I had a map of my region in black, not in dot form.
In the feature collection console (5000, 4 columns).
Can you tell me where the problem is?

[@ramiqcom]

Try to zoom in

[@malakben3694]

i have just one question:
for the LST prediction, how does RF understand that high precipitation values mean low temperatures, and low precipitation values mean high temperature values.
Because I want to add road distance as a parameter. Logically, the heat emitted increases considerably as you get closer to the road, and decreases as you get further away.
How does RF work with this?

[@ramiqcom]

Idk, they just learn that from the sampel

[@MansourDIOP-i8v]

great my dear thank you. can you do after the other like Suppor vector regressor k neaighbor, decision tree...............

[@ramiqcom]

Great suggestion!

[@adventhigh6888]

Awesome video. Can you explain me more about Updatemask(pop)? Why is it used and why can't we use updatemask(lst) or say elevation or rain?

[@ramiqcom]

I use pop as mask because i feel it represent the land better

[@Supreman3434]

prediction of which year

[@44556-k]

How we can perform future prediction of Land Surface temperature

[@ramiqcom]

I can make a video in the future

[@ZeeshanZafarzams706]

I thought this video will tell us about future prediction of LST.

[@ramiqcom]

Well it is possible too. Maybe I can make video for it in the future.

[@Arthsinghnita]

Great

[@muhammadabdulrohman6588]

kak kalau data tersebut hasilnya di export ke data yang levelnya desa apakah bisa kak?

[@ramiqcom]

Bisa. nanti shp desanya diupload ke earth engine, terus lakuin reduceRegions. Cek dokumentasi ini developers.google.com/earth-engine/apidocs/ee-image-reduceregions. Nanti saya buat video soal ini juga.

[@naghaviamir]

Hi Ramadhan - May you create TRMM with NDVI, and EVI and LAI using Random Forest Regression in Earth Engine

[@ramiqcom]

What is TRMM?

[@ikadekyogadwiputra7011]

@@ramiqcom Tropical Rainfall Measuring Mission (TRMM) is a joint space mission between NASA and Japan's National Space Development Agency

[@naghaviamir]

TRMM is satellite rainfall data from remote sensing precipitation (version 7 TRMM 3B43 dataset), vegetation indices (NDVI, EVI, and LAI), MCD12Q1 land cover dataset, and SRTM digital elevation model, (DEM). It should be highlighted that all these datasets are available on Google Earth Engine: developers.google.com/earth‐engine/datasets.
👍👍👍👍

[@ramiqcom]

@@ikadekyogadwiputra7011 where can I get the data?

[@nguyenthanh-x9u]

Very great video. Can you ask me 1 question?
Why is population data not available in Vietnam?

[@ramiqcom]

Im pretty sure they area

[@nguyenthanh-x9u]

@@ramiqcom I changed the study area to the one in Vietnam, but no population data.

[@ramiqcom]

@@nguyenthanh-x9u give me the link to your script

[@phuntshophuntsho3300]

Nice😄!

[@ramiqcom]

Nice

[@fakharulislam2519]

Great

[@ZeeshanZafarzams706]

Can we access and utilize GEE in china ?

[@ramiqcom]

Im pretty sure you can

[@geologistdinesh]

could you send me correct script sir

[@ramiqcom]

have you check the description?

[@patrichpapilaya6845]

danke Banyak Bro...terus berkarya...

[@ramiqcom]

thanks