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CYN Academy
Приєднався 20 сер 2020
From Space to Sea: Using Google Earth Engine to Track Changes in Marine Water Quality
The health of marine ecosystems is intricately linked to the quality of water in which they thrive. Marine water quality is an essential indicator not only of the health of the oceans but also of the broader environmental changes occurring globally. Traditional methods of water quality monitoring often involve in-situ sampling, which can be time-consuming, costly, and limited in spatial coverage. As the need for comprehensive and real-time monitoring grows in the face of global environmental changes, there is an increasing demand for innovative and scalable approaches to assess marine water quality.
Enter the world of remote sensing, a technology that leverages satellite and aerial imagery to observe, measure, and analyze vast areas of the Earth's surface. Google Earth Engine (GEE), in particular, has emerged as a powerful platform for geospatial analysis, harnessing an immense collection of satellite datasets. The application of GEE in monitoring marine water quality represents a convergence of technology and environmental science, offering a revolutionary approach to marine conservation efforts.
GEE's ability to process vast amounts of satellite data in real-time, coupled with advanced algorithms, provides unprecedented insights into marine water quality on a global scale. These insights not only shed light on pollution hotspots and temporal changes but also aid policymakers, researchers, and environmentalists in making informed decisions. This paper delves into the potential of Google Earth Engine as an observational tool for marine water quality assessment, exploring its advantages, methodologies, and implications for the future of marine conservation.
contact for the script: Akkarapon.chaiyana@gmail.com
Thank you for the hard working of the original paper.
@s/10.3389/fmars.2022.871470/full
This video is for only educational purposes.
Enter the world of remote sensing, a technology that leverages satellite and aerial imagery to observe, measure, and analyze vast areas of the Earth's surface. Google Earth Engine (GEE), in particular, has emerged as a powerful platform for geospatial analysis, harnessing an immense collection of satellite datasets. The application of GEE in monitoring marine water quality represents a convergence of technology and environmental science, offering a revolutionary approach to marine conservation efforts.
GEE's ability to process vast amounts of satellite data in real-time, coupled with advanced algorithms, provides unprecedented insights into marine water quality on a global scale. These insights not only shed light on pollution hotspots and temporal changes but also aid policymakers, researchers, and environmentalists in making informed decisions. This paper delves into the potential of Google Earth Engine as an observational tool for marine water quality assessment, exploring its advantages, methodologies, and implications for the future of marine conservation.
contact for the script: Akkarapon.chaiyana@gmail.com
Thank you for the hard working of the original paper.
@s/10.3389/fmars.2022.871470/full
This video is for only educational purposes.
Переглядів: 239
Відео
Environmental Monitoring of Rice Fields: Time Series Classification with Sentinel-2 in GEE
Переглядів 750Рік тому
Utilize the power of Google Earth Engine and Sentinel-2 imagery to monitor and classify rice fields over time, contributing to environmental conservation and sustainable agriculture practices.
Merging Landsat into imagecollection (Landsat 7 8 9) using Google Earth Engine (GEE)
Переглядів 959Рік тому
Step1: The study area is defined as Switzerland using the "USDOS/LSIB_SIMPLE/2017" feature collection. Step2: Landsat imagery for Landsat 7, 8, and 9 is imported using their respective ImageCollections. Step3: Several functions are defined to rename the bands in the Landsat images and to create masks to filter out clouds, shadows, and other unwanted features. Step4: The function "addVIs" is def...
How to download Soil Texture at different depths using Google Earth Engine
Переглядів 4 тис.Рік тому
Citation: Tomislav Hengl. (2018). Soil texture classes (USDA system) for 6 soil depths (0, 10, 30, 60, 100 and 200 cm) at 250 m (Version v02) [Data set]. Zenodo. 10.5281/zenodo.1475451 Contact for script: Akkarapon.Chaiyana@gmail.com
How to extract backscatter from Sentinel-1 by multiple plots, download image in Google earth Engine
Переглядів 944Рік тому
If you need a script, email me: akkarapon.chaiyana@hotmail.com Can you name your institute or University and also your country when you email me to request a script!!! I would like to know my target and improve video quality. Thank you everyone!!!
EP.1 The Introduction of GeoSOS-FLUS for Land Cover Change Simulation
Переглядів 1 тис.Рік тому
Download LINK: www.geosimulation.cn/FLUS.html
How to do zonal statistic in GEE and apply time series data with Wavelet Transform in Rstudio
Переглядів 1,3 тис.2 роки тому
What you will learn from this tutorial!!! - How to do zonal statistic extraction of each feature such as mean, median, minimum, maximum value via GEE - How to understand the basic of wavelet transform visualization - How to read the wavelet figure - How to do wavelet transform from ‘waveletComp’ library in Rstudio - What are the applications of wavelet transform on climate change impacts
Assessing the Impact of Wildfires on Land Cover Using Google Earth Engine
Переглядів 1,3 тис.2 роки тому
- This video was inspired by the Journal, namely, A Google Earth Engine code to estimate properties of vegetation phenology in fire affected areas - A case study in North Evia wildfire event on August 2021 (Alxendra and Nikos, 2020) - That Journal provided a gee script to download the NDVI time-series values in terms of mean, max, std and min. The researchers also showed the shapefile into two ...
An Example of Evaluating Ground Water Storage with GRACE 2.2 Information Using Google Earth Engine
Переглядів 7 тис.2 роки тому
What you will learn from this tutorial? - How to apply GRACE 2.2 for illustrating ground water storage (GWS) map in any locations - How to code for extracting GWS value in certain location - How to download GWS images by averaged monthly to be used as based line - How to calculate Mann Kendall and Sen’s Slope by Python script - How to do yearly GWS anomaly Email me: akkarapon.chaiyana@gmail.com
Climate Change Concept and Bias Correction Approach (Thai Version)
Переглядів 8302 роки тому
Climate Change Concept and Bias Correction Approach (Thai Version)
Remote Sensing Data-Driven Approach for Modelling Puccinia Striiformis Distribution
Переглядів 2432 роки тому
This study was created for educational purposes only, do not use citation or reference. The Rstudio tutorial on the Species Distribution Modelling model: ua-cam.com/video/EzjsZpdQp1w/v-deo.html Contact me for work: akkarapon.chaiyana@gmail.com
Bias Correction by Linear Scaling’ Approach using Python
Переглядів 1,7 тис.2 роки тому
df_result = {} df = pd.DataFrame(dtype = np.float64) for i in zip(TMD.columns, RCM.columns): TMD_station, RCM_station = i Jan_obs_mean = (TMD.loc[1, [TMD_station]]).mean() Feb_obs_mean = (TMD.loc[2, [TMD_station]]).mean() Mar_obs_mean = (TMD.loc[3, [TMD_station]]).mean() Apr_obs_mean = (TMD.loc[4, [TMD_station]]).mean() May_obs_mean = (TMD.loc[5, [TMD_station]]).mean() Jun_obs_mean = (TMD.loc[6...
Computing multiple PET station by Thornthwaite’s method using Python
Переглядів 6412 роки тому
Computing multiple PET station by Thornthwaite’s method using Python
Assessing Soil Salinity based on Remotely-Sensed Data and Random Forest Regression Approach
Переглядів 2,2 тис.2 роки тому
Assessing Soil Salinity based on Remotely-Sensed Data and Random Forest Regression Approach
EP2. How to apply raster data to machine learning model for classification using Python?
Переглядів 2,5 тис.2 роки тому
EP2. How to apply raster data to machine learning model for classification using Python?
EP1. Understanding the concept of number data for classification in Python
Переглядів 4732 роки тому
EP1. Understanding the concept of number data for classification in Python
How to calculate NDVI from Landsat 9 images and Export its into .tiff format using GEE
Переглядів 1,9 тис.2 роки тому
How to calculate NDVI from Landsat 9 images and Export its into .tiff format using GEE
Remotely-Sensed Data and Water Salinity With in Situ Measurements Using Google Earth Engine
Переглядів 1,3 тис.2 роки тому
Remotely-Sensed Data and Water Salinity With in Situ Measurements Using Google Earth Engine
How to plot multiple scatter plots using Python
Переглядів 2,5 тис.2 роки тому
How to plot multiple scatter plots using Python
Spatiotemporal Phenological Metrics Monitoring of Intercropping at Regional Scale using GEE
Переглядів 1 тис.2 роки тому
Spatiotemporal Phenological Metrics Monitoring of Intercropping at Regional Scale using GEE
How to do Anomaly Index Graph in Excel
Переглядів 4,8 тис.2 роки тому
How to do Anomaly Index Graph in Excel
Conversion flat binary format to tiff format using GDAL command which contains DATUM & Projection
Переглядів 6902 роки тому
Conversion flat binary format to tiff format using GDAL command which contains DATUM & Projection
An example: Estimation of Potato Crop Yield using Sentinel2 Data and Google Earth Engine Combination
Переглядів 6 тис.2 роки тому
An example: Estimation of Potato Crop Yield using Sentinel2 Data and Google Earth Engine Combination
Converting flat binary format to another format for analysis in GIS software
Переглядів 5252 роки тому
Converting flat binary format to another format for analysis in GIS software
How to process phenology metrics in TIMESAT
Переглядів 3,7 тис.2 роки тому
How to process phenology metrics in TIMESAT
Bias correction climate data using CMhyd software
Переглядів 6 тис.2 роки тому
Bias correction climate data using CMhyd software
Converting format (.tif) to flat binary format (TIMESAT software)
Переглядів 1,6 тис.2 роки тому
Converting format (.tif) to flat binary format (TIMESAT software)
Please explain the process of creating an NDVI file
Hi, can you share with a code?:)
my country has all 16 land cover in 2003 at some areas where i am investigating researches; but now shifted to nine. how to do the change detection and future change, possible other than land covers being equal?
THANKS
if i keep salinity index 1,2,3 and i see greeen stuff. my entire image is orangeish redish. can you tell me what that means
Could you please share the scripts?
Could you please share the scripts?
Very nice . would it be possible for you to share the codes?
Can your share your email please, I want to contact with you?
Would you please share the codes?
Hello, what do I need if I want to analyze ndvi of two separate locations but not over time? I need it to compare how NDVI varies per location. Thank you
❤
Nice work can I please have the code
the video is blurry and you should have shared the code for people to follow nicely.
สวัสดีครับพี่ช่วยสอนการจัดเตรียม Excel สำหรับนำมาใช้ใน R Studio ได้ไหมครับหรือพี่มีวีดีโอหรือแหล่งสำหรับให้เข้าไปดูไมครับ
Great, Can you please share script
can you please share the code snippet in the description ?
Sir, how to get meteorological station location with latitude and longitude.
when i add slope and elevation maps and click on check geometry, a massage appears stating that the geometries are not equal, how can i fix this problem, please?
Can you share script?
can you please share the code?
please provide the python script
excuse me sir, how can i make the anomaly index graph but using SOI index? are the steps the same like this video? thank you sir
i used your code but this appears (at 0 cm depth: Layer error: Image. visualize: Color is not a valid CSS 3.0 color ('FF0000' or 'red' for red). Found: 'fu6714'.) What does this mean? can you reply, please
how can i export the final classified map to ARCGIS?
Where is the link ?
Thank you for sharing , which version of qgis is compatible with molusce plugin
code pelase sir
please provide the gee code for crop mapping if possible
provide the above code for the conversion from .tpa to .tif for the series of images
Can u share script
Sir, How to obtained 138 output filter images.
Hello. What's the full script below defining the working directory?
Is molusce plug.ins still applicable?
Hello! Yes, MOLUSCE 4 has been released, now with support for the latest versions of QGIS
It was very useful, but it was difficult to see the code as you explan. Can you share the code
My simulation results of 2030,60 n 90 all are showing same
Yeah, that's a great video. Moreover, Please share the part 1 and 2
Good day, are the bias corrected data already good ?
Can you share the code please?
Con you share the code please?
I want the part 2 of this series
can you provide GEE Codes?
please how can i map soil types on google earth engine
Sir, pelase share GEE code link
Thank you very mush for sharing knowledge On data inputs for the prediction, is it just the historical land cover map for the older years or you also considered other factors?
hello, do you offer classes to make predictive maps? i have some doubts about the generation of information of the variables.
Hello Sir can we get the code ??
Thanks for sharing this invaluable learning. Would you please share the code?
Thank you for your nice explained video. I just want to know that does SVM regression model prediction can give some higher predicted value in comparison of training set highest value. For example if the highest value of the dependent variable is 25. So, can SVM regression model give prediction of any test datapoints more than 25?
Can I have the script sir?