Rice Mapping using Sentinel 1, 2 in Earth Engine [GEE]

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  • Опубликовано: 26 авг 2024
  • In this video we follow the codes from the paper for rice mapping process.
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    The basic idea is to include the monthly images from Sentinel 1 and 2 in rice growing period. The monthly images from both the Sentinel 1 and 2 are stacked as the image. The stacked image is clustered from the unsupervised method. The spectra of the clusters are observed, and the rice pixels are identified.
    Challenges during this method might be the presence of the clouds during the rice growing period. Also the method is not suitable for larger area, by larger area meaning the whole country, or even a district of any country.
    This video is likely to be helpful for anyone wishing to build concepts of rice mapping process using Sentinel 1 and 2. You can follow the methods and shared codes from the paper for the study of the methods.
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    paper
    [ Title: High-Resolution Mapping of Paddy Rice Extent and Growth Stages across Peninsular Malaysia Using a Fusion of Sentinel-1 and 2 Time Series Data in Google Earth Engine
    year: 2022
    doi: doi.org/10.339...
    codes shared in the paper: code.earthengi... ]
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    Related Videos in the channel:
    * Crop land classification in Earth Engine
    • Crop Land Classificati...
    * Rice Monitoring using Sentinel-1 in Google Earth Engine [GEE]
    • Rice Monitoring using ...
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    Image from Commons: Vrouwen aan het werk in een rijstveld in Tanahu, Nepal, -26 april 2011 a.jpg
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    Any comments are welcomed.

Комментарии • 45

  • @FOCmr
    @FOCmr 2 месяца назад +1

    Good Explanation, Thanks to make such tutorial, Would you please share MODIS Rice Map Download link?

    • @ksabmagar7
      @ksabmagar7  2 месяца назад

      If you are asking for the MODIS rice map, this is from the article, www.sciencedirect.com/science/article/abs/pii/S0168192321002227. Request them to provide you the maps, but they are mainly for Nepal.

  • @gocha-gocha3705
    @gocha-gocha3705 6 месяцев назад +2

    Thank you very much, nice

  • @ifrokhularya8939
    @ifrokhularya8939 Месяц назад +1

    Great Tutorial Brother! I want to ask, How do u know about the quantity of the pixel, u said 70 right?

    • @ksabmagar7
      @ksabmagar7  Месяц назад

      do you mean the clusters, we specify this at the beginning,
      70? I might not have said that? Can you point the time where I said that?

    • @ifrokhularya8939
      @ifrokhularya8939 Месяц назад +1

      Yes, i just got the issue of kappa accuration asses, on that DOI the total pixel are 740 right? I am wondering where that number of pixel came from

  • @waleedalshafie
    @waleedalshafie 2 месяца назад +1

    Thanks a lot Sir
    I am from Iraq, I need your code to apply it in our region
    Your help will be highly appreciated

    • @ksabmagar7
      @ksabmagar7  2 месяца назад

      Hello sir, please check the description for the codes.

  • @rohithkumarrkm3642
    @rohithkumarrkm3642 4 месяца назад +1

    sir how can i download the clustered ndvi images from GEE

    • @ksabmagar7
      @ksabmagar7  4 месяца назад

      try exporting like other image

  • @MuddasirShah
    @MuddasirShah Год назад +1

    Thank you Brother ❤

  • @JorgeRodriguez-mp1mt
    @JorgeRodriguez-mp1mt Год назад

    ¿Hola, cómo estás? Gracias por compartir, estoy siguiendo todos tus videos tutoriales. Saludos desde México.

    • @ksabmagar7
      @ksabmagar7  Год назад +1

      hola, gracias por ver el video. me alegra ver el comentario.

  • @sumarganalena4651
    @sumarganalena4651 2 месяца назад +1

    thank you for explanation, in the end fo this code are displaying 3 maps: remapped_cluster, remapped_cluster10, and remapped_cluster20; these 3 maps are composite from startdate and enddate, this correct?.
    so how to display remapped_cluster20 in certain month?
    thank you sir

    • @ksabmagar7
      @ksabmagar7  2 месяца назад

      Yes, the three clusters are from the start date and end date, just changing the discrete values, and we are seeing them to get the idea of clusters.
      Clusters only of the certain one month is not possible there. And also not meaningful. Although, we can simply try to use the images only from the month and then start clustering. It also depends on the number of images within one month.
      Thankyou

    • @sumarganalena4651
      @sumarganalena4651 2 месяца назад +1

      @@ksabmagar7 great, i just whant to know the changing of this cluster10 or cluster20 mont by mont, so we can monitor the stage of rice.

  • @w22pegaso
    @w22pegaso 9 месяцев назад +2

    🎯 Key Takeaways for quick navigation:
    00:02 🌾 Introduction to Rice Mapping Process
    - Overview of using Sentinel 1 and 2 in Google Earth Engine (GEE) for rice mapping.
    - Explanation of the process, including monthly data acquisition and clustering.
    02:04 🗺️ Selecting Region of Interest
    - Description of how to select the region of interest in GEE.
    - Importance of choosing a small area for smooth code execution.
    04:02 📅 Filtering Sentinel 2 Images
    - Filtering Sentinel 2 images based on start and end dates.
    - Managing metadata like Cloudy pixels for image selection.
    08:08 🌱 Calculating NDVI
    - Explanation of calculating NDVI (Normalized Difference Vegetation Index).
    - Renaming bands and adding the NDVI to image collection.
    12:45 📊 Generating Monthly NDVI Images
    - Creating monthly NDVI images for the rice growing season.
    - Using a sequence to obtain a series of monthly images.
    17:06 🧩 Combining Sentinel 1 and Sentinel 2 Data
    - Combining Sentinel 1 and Sentinel 2 data into one stacked image.
    - Preparing the data for clustering.
    19:08 📊 Clustering for Unsupervised Classification
    - Clustering the combined data into 30 clusters.
    - Assigning values to clusters based on visual inspection.
    25:21 🗺️ Assigning Rice and Non-Rice Labels
    - Reassigning values to clusters to identify rice and non-rice areas.
    - Mapping the clusters for rice mapping.
    28:57 🌾 Comparing Results with Rice Maps
    - Comparing the generated rice map with a rice map from MODIS data.
    - Discussion on the accuracy of the generated rice map.
    Made with HARPA AI

  • @soknethlim3387
    @soknethlim3387 6 месяцев назад +1

    Thank you very much for your wonderful demonstration. However, I encountered a problem: some clusters were not shown on the graph. for example, I used 30 clusters for my study area but the graph showed only 0, 1, 7, 13 and 16 clusters. May I have your advice to address this issue?

    • @ksabmagar7
      @ksabmagar7  6 месяцев назад

      try reducing the study area or number of clusters, or time duration of the images,

  • @w22pegaso
    @w22pegaso 10 месяцев назад +1

    Hello, congratulations, interesting work. I wonder how clusters present different stages of rice? And at the same time, each pixel of this cluster can be taken as a 10x10 area, and how should we interpret the temporal part with the random colors?

    • @ksabmagar7
      @ksabmagar7  10 месяцев назад

      As per my understanding, the clusters are formed by the temporal similarity as well. The pixels which spectral profile were similar all over the period / due to their closeness were clustered as a cluster. This would mean the rice that were transplanted together or grew together.
      Clusters are not directly representing the stages of rice. The spectral chart we are observing represents the stages of rice. The idea is, as shared in the video, the clusters showing some distinct spectral curve distinct to the rice should be the presence of the rice.
      The observations of more and more clusters will probably refine the rice growing area But large no. of clusters would rather make obsolete for the observations . Regarding 10 * 10m - what's being shown by the pixels can not directly represent the field. It would be the general representation.
      Hope this helps,
      or correct if it doesn't seem logical.
      Thankyou for the question.

    • @w22pegaso
      @w22pegaso 10 месяцев назад +1

      thank you so much...

  • @jodelbautista5394
    @jodelbautista5394 5 месяцев назад +1

    where can I copy the code?

    • @ksabmagar7
      @ksabmagar7  5 месяцев назад

      Please check the description. There is a link which lands you to the code.

  • @omarrodriguez3286
    @omarrodriguez3286 6 месяцев назад +1

    Hello, do you provide private advice? And if so, any contact email?

    • @ksabmagar7
      @ksabmagar7  6 месяцев назад

      There are no such things from my side.

  • @lilyflorence5029
    @lilyflorence5029 6 месяцев назад +1

    What is the image he imported? At the beginning

    • @ksabmagar7
      @ksabmagar7  4 месяца назад

      data from sentinel 1 and 2.

  • @IAKhan-km4ph
    @IAKhan-km4ph Год назад

    Very nice

  • @sophiez7952
    @sophiez7952 Год назад

    hi, thanks your sharing, I have a question, why you set sentinel2 cloudy is less than 100, you want to make up this by sentinel1 or other reasons?

    • @ksabmagar7
      @ksabmagar7  Год назад

      100 is just the value originally used in the paper itself.
      Using 100 would just mean there would be more Sentinel 2 images in the region. It is okay if the area usually has the lower clouds, or the region is smaller such that it won't be greatly shadowed by the clouds.
      Other than this, there are no such specific reasons for this. Thankyou

  • @djebbourimohammed7467
    @djebbourimohammed7467 10 месяцев назад

    Thank you Brother , I have a question,cluster number zero in the chart to which attributes we can their value

    • @ksabmagar7
      @ksabmagar7  10 месяцев назад +1

      we have to look at how the line graph shows for the cluster number zero, we cannot be specific for sure.

  • @sophiez7952
    @sophiez7952 Год назад

    thanks your reply, again sentinel1 we do not need any further processing like correction or calculating coefficients, you just download and use them directly? I am curiosity?

    • @ksabmagar7
      @ksabmagar7  Год назад +1

      If we say about the data from the earth engine, all required processing have been done - readily available for our analysis. So we can directly use it.
      If in other cases, if we are already more aware about what we need based on our purpose OR if we did not like the algorithms used in the earth engine, we can certainly try in the SNAP (which is the other freely available remote sensing software).
      But, more confusingly, sentinel-1 also has other type of data that is SLC type, along with GRD which we see in the earth engine, which might certainly requires other steps, which is complex than what we need.
      SAR data are complex, and the steps of the corrections or processing or any steps are the complex topic to learn or developing our own steps of algorithms might be other topics. There sure are people/resources from whom we can learn more.
      Anyway, what provided from earth engine is sufficient for us, I am sure.
      Thankyou

    • @sophiez7952
      @sophiez7952 Год назад +1

      @@ksabmagar7 thx

    • @ksabmagar7
      @ksabmagar7  Год назад

      @@sophiez7952 thankyou :)

  • @user-gj3xl1tb7t
    @user-gj3xl1tb7t Год назад

    how to output the result?

    • @ksabmagar7
      @ksabmagar7  Год назад

      You can export them using the export functions.

  • @MuddasirShah
    @MuddasirShah Год назад

    Clustering approach. Is it good bro?

    • @ksabmagar7
      @ksabmagar7  Год назад +1

      depends, when there is no training data, it will certainly be used. this can be helpful if we tried comparing with the supervised methods. but I cannot say more.

  • @user-oi1cy1ip4r
    @user-oi1cy1ip4r Год назад

    how to fuse sentinel 1 and 2

    • @ksabmagar7
      @ksabmagar7  Год назад

      It might depend on what fusion mean. The video can be considered an example of using Sentinel 1 and 2 where two different data are handled by the classification.
      - We can try this in the SNAP tool box as well. step.esa.int/docs/tutorials/S1TBX%20Synergetic%20use%20of%20S1%20(SAR)%20and%20S2%20(optical)%20data%20Tutorial.pdf
      There are certain ways/equations that might have been developed integrating vegetation indices with radar indices. I cannot say about that more.