StudyHacks

Understanding NDVI and Its Diverse Applications: NDVI map of Colombia 🇨🇴
The Normalized Difference Vegetation Index (NDVI) is a widely used remote sensing tool that quantifies the presence of green vegetation by measuring the difference in reflectance of near-infrared (NIR) and red light. NDVI values range from -1 to 1, with higher values indicating denser and healthier vegetation.

Tutorial Link:
https://youtu.be/LXrTYcUYXgc

Join our Telegram group to get more study about GIS and Remote sensing: https://t.me/gisandremotesenginglearningGEE

Applications of NDVI
NDVI has a wide range of applications in various fields, including:

Agriculture:
Crop Monitoring: NDVI is used to monitor crop health and productivity, identify areas of stress or disease, and optimize irrigation and fertilization.

Forestry:
Forest Monitoring: NDVI is used to assess forest health, detect deforestation, and track changes in forest cover over time.

Drought Monitoring:
Drought Detection: NDVI is used to identify and monitor drought-affected areas by tracking changes in vegetation greenness.

Land Cover Classification:
Vegetation Mapping: NDVI is used to classify land cover types, such as forests, grasslands, and croplands.

Urban Planning:
Urban Green Space Assessment: NDVI is used to assess the distribution and health of urban green spaces, which contribute to environmental quality and human well-being.

Fire Risk Assessment:
Fuel Moisture Mapping: NDVI is used to map fuel moisture in vegetation, which is a crucial factor in fire risk assessment.

Benefits of Using NDVI

NDVI offers several advantages for various applications:

Cost-Effective: NDVI data is readily available from satellite imagery, making it a cost-effective tool for monitoring large areas.

Regular Updates: Satellite imagery provides regular updates of NDVI values, allowing for continuous monitoring of vegetation dynamics.

Scalable Analysis: NDVI data can be analyzed at various scales, from local fields to entire continents, providing insights at different levels.

Tutorial link: https://youtu.be/LXrTYcUYXgc

Recorded class on Machine learning algorithm for Land use and Land cover classification | Accuracy Assessment of LULC
Link: https://youtube.com/live/r5XL8qKgLFY?feature=share
The new batch class will be started from 8th December. Registration is open now
For Registration contact this WhatsApp number: +8801780942798 or Email: [email protected]

1st day:
 Introduction to GEE
 How to use GEE JavaScript and Python API
 Learn the basic principles of JavaScript syntax and python
 Client vs. Server object on GEE
 How you get the server to execute your code?
 Importing Raster and Vector Data: Local storage & GEE Dataset
 Filtering Attribute Table

2nd day:
 Filtering and Displaying Satellite Images: Landsat , Sentinel
 Satellite Composite
 Band combinations
 Export Satellite Imagery: Landsat , Sentinel and Modis
 Import, Filter, Reduce, Clip and display Raster data in GEE
 Time series Chart of NDVI using GEE readymade dataset
 Export Any Shapefile

3rd day:
 Calculating Any Indices from Satellite Images using Landsat and Sentinel
 Filtering and Displaying Satellite Images: Sentinel-2 and Monitoring NDWI , NDVI
 Extract water body using Thresholding
 NDVI , NDWI , SAVI and all indices Time series Chart using Landsat and Sentinel
 Export Any Shapefile from GEE
 How to add Gradient Legend and Title on GEE
 NDWI Calculated from Modis and Landsat data

4th day:
 How to remove cloud and Haze from satellite imagery- Landsat and Sentinel
 Visualization (DEM) of Hill shade and Slope Map in GEE using NASA SRTM and Aster
 Land surface temperature (LST) Monitoring from Landsat satellite imagery and Modis
 How to calculated Average , Maximum, Minimum NDVI any specific region
 GEE: How to make monthly Evapotranspiration

5th day:
 Air Quality Monitoring: all prameters
 How to Download Air Quality parameters Time series data in CSV format using GEE
 Air Quality Monitoring Time Series chart
 Air Quality Monitoring: How to calculate total emission of nitrogen-oxide or any gases in GEE using
sentinel-5
 ArcMap software: How to make research paper map using GEE & ArcMap software

6th day:
 Introduction to Machine Learning in Google Earth Engine
 How to make LULC Map using Machine Learning: Supervised and Unsupervised algorithm
 Random forest, CART, SVM, Minimum distance classifier to make LULC
 How to Check LULC accuracy assessment using Google Earth Engine. (Kappa, Producers & Consumers
accuracy)
 Calculate LULC classes Area
 How to add Legend in LULC Map
 How to Export LULC and make research paper LULC map using ArcMap

7th day:
 Land-Use and Land-Cover Change Detection using Google Earth Engine
 NDVI change detection using Google Earth Engine
 Class-wise LULC change detection in ONE layer using Google Earth Engine
 Hyper parameter Tuning for improving the accuracy of your machine learning model

https://youtube.com/live/r5XL8qKgLFY?feature=share

Machine learning algorithm for Land use and Land cover classification | Accuracy Assessment of LULC Google Earth Engine: 15 days Advanced online training syllabus: https://youtu.be/fhBWHFayadc?si=BFqSTvKs_8rvnNHXOnline training on the R package for interact...

Land surface temperature monitoring using Landsat satellite imagery using Google Earth Engine. If you want to learn from beginner's to advanced level and develop the different types of algorithm for remote sensing then this online training programme is for you👇👇👇
for a new batch of 7 days of Complete online training on for
& Analysis for Beginners to Advanced level.

These classes will teach you all the necessary things to start using GEE for your remote sensing analysis. We mainly focus on these people who don't know any programming language and Earth Engine function. We cover LULC mapping, Change detection Analysis, Air quality Monitoring, Time series analysis, Calculating any Indices, Supervised Classification, Unsupervised Classification, Machine Learning Methods, NDVI change detection and more.

Class Start: 8th December, 2023
Admission Last Date: 6th December (1st 10 registered people get 50% discount). Now 8 seats are available to get this 50% discount.

For registration contact this WhatsApp number: +8801780942798 or email: [email protected]

Total Class: 7 days (Friday and Saturday in Week)
Class Duration: 3 hours (Each day)
Time: 9:00 P.M to 12:00 A.M (GMT +6)

Training language: English

Course Content:
1st day:
 Introduction to GES
 How to use GEE JavaScript and Python API
 Learn the basic principles of JavaScript syntax and python
 Client vs. Server object on GEE
 How you get the server to execute your code?
 Importing Raster and Vector Data: Local storage & GEE Dataset
 Filtering Attribute Table

2nd day:
 Filtering and Displaying Satellite Images: Landsat , Sentinel
 Satellite Composite
 Band combinations
 Export Satellite Imagery: Landsat , Sentinel and Modis
 Import, Filter, Reduce, Clip and display Raster data in GEE
 Time series Chart of NDVI using GEE readymade dataset
 Export Any Shapefile

3rd day:
 Calculating Any Indices from Satellite Images using Landsat and Sentinel
 Filtering and Displaying Satellite Images: Sentinel-2 and Monitoring NDWI , NDVI
 Extract water body using Thresholding
 NDVI , NDWI , SAVI and all indices Time series Chart using Landsat and Sentinel
 Export Any Shapefile from GEE
 How to add Gradient Legend and Title on GEE
 NDWI Calculated from Modis and Landsat data

4th day:
 How to remove cloud and Haze from satellite imagery- Landsat and Sentinel
 Visualization (DEM) of Hill shade and Slope Map in GEE using NASA SRTM and Aster
 Land surface temperature (LST) Monitoring from Landsat satellite imagery and Modis
 How to calculated Average , Maximum, Minimum NDVI any specific region
 GEE: How to make monthly Evapotranspiration

5th day:
 Air Quality Monitoring: all prameters
 How to Download Air Quality parameters Time series data in CSV format using GEE
 Air Quality Monitoring Time Series chart
 Air Quality Monitoring: How to calculate total emission of nitrogen-oxide or any gases in GEE using
sentinel-5
 ArcMap software: How to make research paper map using GEE & ArcMap software

6th day:
 Introduction to Machine Learning in GEE
 How to make LULC Map using Machine Learning: Supervised and Unsupervised algorithm
 Random forest, CART, SVM, Minimum distance classifier to make LULC
 How to Check LULC accuracy assessment using GEE. (Kappa, Producers & Consumers
accuracy)
 Calculate LULC classes Area
 How to add Legend in LULC Map
 How to Export LULC and make research paper LULC map using ArcMap

7th day:
 Land-Use and Land-Cover Change Detection using GEE
 NDVI change detection using GEE
 Class-wise LULC change detection in ONE layer using GEE
 Hyper parameter Tuning for improving the accuracy of your machine learning model

Join the Telegram group: https://t.me/gisandremotesenginglearningGEE

Join our YouTube channel:
https://youtube.com/

Recorded class on Vegetation Condition Index (VCI) using Landsat imagery in Google Earth Engine || Drought Monitoring
Link: https://youtube.com/live/Y5xH82n7ob8?feature=share

The Vegetation Condition Index (VCI) compares the current NDVI to range of values observed in the same period in previous years.

The VCI is expressed in % and gives an idea where the observed value is situated between the extreme values (minimum and maximum) in previous years.

Lower and higher values indicate bad and good vegetation state conditions, respectively. VCI varies from 0 for extremely unfavorable conditions, to 100 for optimal.

Formula : VCI = 100 * (NDVI - NDVI min) / (NDVI max - NDVI min) (Kogan, 1990)

NDVI max and NDVI min are multiple year maximum NDVI and minimum NDVI for a pixel with reference to a specific climatology.

Join our Telegram group:
https://t.me/gisandremotesenginglearningGEE

WhatsApp group: https://chat.whatsapp.com/DJyR6BjhnBaLBrNTrQkYvp



https://youtube.com/live/Y5xH82n7ob8?feature=share

Vegetation Condition Index (VCI) using Landsat imagery in Google Earth Engine || Drought Monitoring Google Earth Engine: 15 days Advanced online training syllabus: https://youtu.be/fhBWHFayadc?si=BFqSTvKs_8rvnNHXOnline training on the R package for interact...

Recorded class on Land surface temperature (LST) monitoring using Landsat surface reflectance imagery in Google Earth Engine
Link: https://youtube.com/live/74MLoSk1sME?feature=share
for a new batch of 7 days of Complete online training on for
& Analysis for Beginners to Advanced level.

These classes will teach you all the necessary things to start using GEE for your remote sensing analysis. We mainly focus on these people who don't know any programming language and Earth Engine function. We cover LULC mapping, Change detection Analysis, Air quality Monitoring, Time series analysis, Calculating any Indices, Supervised Classification, Unsupervised Classification, Machine Learning Methods, NDVI change detection and more.
Class Start: 8th December, 2023
Admission Last Date: 6th December (1st 10 registered people get 50% discount)

For registration contact this WhatsApp number: +8801780942798 or email: [email protected]

Total Class: 7 days (Friday and Saturday in Week)
Class Duration: 3 hours (Each day)
Time: 9:00 P.M to 12:00 A.M (GMT +6)

Training language: English

Check this course module from this website: https://sites.google.com/view/institute-of-gis-rs-hacks/upcoming-classes/google-earth-engine

Join the Telegram group: https://t.me/gisandremotesenginglearningGEE

Join our YouTube channel:
https://youtube.com/




https://youtube.com/live/74MLoSk1sME?feature=share

Land surface temperature monitoring using Landsat surface reflectance imagery in Google Earth Engine Google Earth Engine: 15 days Advanced online training syllabus: https://youtu.be/fhBWHFayadc?si=BFqSTvKs_8rvnNHXOnline training on the R package for interact...

🛑Spatial Estimation of Soil erosion using RUSLE model in Google Earth Engine || RUSLE Model in GEE
Recorded class link: https://www.youtube.com/live/jkl-aXoovOo?si=Wb0tkvH5s8QueFxZ

for a new batch of 7 days of Complete online training on for
& Analysis for Beginners to Advanced level.
These classes will teach you all the necessary things to start using GEE for your remote sensing analysis. We mainly focus on these people who don't know any programming language and Earth Engine function. We cover LULC mapping, Change detection Analysis, Air quality Monitoring, Time series analysis, Calculating any Indices, Supervised Classification, Unsupervised Classification, Machine Learning Methods, NDVI change detection and more.
Class Start: 8th December, 2023
Admission Last Date: 6th December (1st 10 registered people get 50% discount).
For registration contact this WhatsApp number: +8801780942798 or email: [email protected]
Total Class: 7 days (Friday and Saturday in Week)
Class Duration: 3 hours (Each day)
Time: 9:00 P.M to 12:00 A.M (GMT +6)
Training language: English
Course Content:
1st day:
 Introduction to GES
 How to use GEE JavaScript and Python API
 Learn the basic principles of JavaScript syntax and python
 Client vs. Server object on GEE
 How you get the server to execute your code?
 Importing Raster and Vector Data: Local storage & GEE Dataset
 Filtering Attribute Table
2nd day:
 Filtering and Displaying Satellite Images: Landsat , Sentinel
 Satellite Composite
 Band combinations
 Export Satellite Imagery: Landsat , Sentinel and Modis
 Import, Filter, Reduce, Clip and display Raster data in GEE
 Time series Chart of NDVI using GEE readymade dataset
 Export Any Shapefile
3rd day:
 Calculating Any Indices from Satellite Images using Landsat and Sentinel
 Filtering and Displaying Satellite Images: Sentinel-2 and Monitoring NDWI , NDVI
 Extract water body using Thresholding
 NDVI , NDWI , SAVI and all indices Time series Chart using Landsat and Sentinel
 Export Any Shapefile from GEE
 How to add Gradient Legend and Title on GEE
 NDWI Calculated from Modis and Landsat data
4th day:
 How to remove cloud and Haze from satellite imagery- Landsat and Sentinel
 Visualization (DEM) of Hill shade and Slope Map in GEE using NASA SRTM and Aster
 Land surface temperature (LST) Monitoring from Landsat satellite imagery and Modis
 How to calculated Average , Maximum, Minimum NDVI any specific region
 GEE: How to make monthly Evapotranspiration
5th day:
 Air Quality Monitoring: all prameters
 How to Download Air Quality parameters Time series data in CSV format using GEE
 Air Quality Monitoring Time Series chart
 Air Quality Monitoring: How to calculate total emission of nitrogen-oxide or any gases in GEE using
sentinel-5
 ArcMap software: How to make research paper map using GEE & ArcMap software
6th day:
 Introduction to Machine Learning in GEE
 How to make LULC Map using Machine Learning: Supervised and Unsupervised algorithm
 Random forest, CART, SVM, Minimum distance classifier to make LULC
 How to Check LULC accuracy assessment using GEE. (Kappa, Producers & Consumers
accuracy)
 Calculate LULC classes Area
 How to add Legend in LULC Map
 How to Export LULC and make research paper LULC map using ArcMap
7th day:
 Land-Use and Land-Cover Change Detection using GEE
 NDVI change detection using GEE
 Class-wise LULC change detection in ONE layer using GEE
 Hyper parameter Tuning for improving the accuracy of your machine learning model
Join the Telegram group: https://t.me/gisandremotesenginglearningGEE
Join our YouTube channel:
https://youtube.com/



https://www.youtube.com/live/jkl-aXoovOo?si=Wb0tkvH5s8QueFxZ

🛑Spatial Estimation of Soil erosion using RUSLE model in Google Earth Engine || RUSLE Model in GEE Registration is open for 7 days of Complete Google Earth Engine for Remote Sensing & GIS Analysis for Beginners to Advanced.Class Start: 10th February 2023 A...

for a new batch of 7 days of Complete online training on for
& Analysis for Beginners to Advanced level.

These classes will teach you all the necessary things to start using GEE for your remote sensing analysis. We mainly focus on these people who don't know any programming language and Earth Engine function. We cover LULC mapping, Change detection Analysis, Air quality Monitoring, Time series analysis, Calculating any Indices, Supervised Classification, Unsupervised Classification, Machine Learning Methods, NDVI change detection and more.

Class Start: 8th December, 2023
Admission Last Date: 6th December (1st 10 registered people get 50% discount).

For registration contact this WhatsApp number: +8801780942798 or email: [email protected]

Total Class: 7 days (Friday and Saturday in Week)
Class Duration: 3 hours (Each day)
Time: 9:00 P.M to 12:00 A.M (GMT +6)

Training language: English

Course Content:
1st day:
 Introduction to GES
 How to use GEE JavaScript and Python API
 Learn the basic principles of JavaScript syntax and python
 Client vs. Server object on GEE
 How you get the server to execute your code?
 Importing Raster and Vector Data: Local storage & GEE Dataset
 Filtering Attribute Table

2nd day:
 Filtering and Displaying Satellite Images: Landsat , Sentinel
 Satellite Composite
 Band combinations
 Export Satellite Imagery: Landsat , Sentinel and Modis
 Import, Filter, Reduce, Clip and display Raster data in GEE
 Time series Chart of NDVI using GEE readymade dataset
 Export Any Shapefile

3rd day:
 Calculating Any Indices from Satellite Images using Landsat and Sentinel
 Filtering and Displaying Satellite Images: Sentinel-2 and Monitoring NDWI , NDVI
 Extract water body using Thresholding
 NDVI , NDWI , SAVI and all indices Time series Chart using Landsat and Sentinel
 Export Any Shapefile from GEE
 How to add Gradient Legend and Title on GEE
 NDWI Calculated from Modis and Landsat data

4th day:
 How to remove cloud and Haze from satellite imagery- Landsat and Sentinel
 Visualization (DEM) of Hill shade and Slope Map in GEE using NASA SRTM and Aster
 Land surface temperature (LST) Monitoring from Landsat satellite imagery and Modis
 How to calculated Average , Maximum, Minimum NDVI any specific region
 GEE: How to make monthly Evapotranspiration

5th day:
 Air Quality Monitoring: all prameters
 How to Download Air Quality parameters Time series data in CSV format using GEE
 Air Quality Monitoring Time Series chart
 Air Quality Monitoring: How to calculate total emission of nitrogen-oxide or any gases in GEE using
sentinel-5
 ArcMap software: How to make research paper map using GEE & ArcMap software

6th day:
 Introduction to Machine Learning in GEE
 How to make LULC Map using Machine Learning: Supervised and Unsupervised algorithm
 Random forest, CART, SVM, Minimum distance classifier to make LULC
 How to Check LULC accuracy assessment using GEE. (Kappa, Producers & Consumers
accuracy)
 Calculate LULC classes Area
 How to add Legend in LULC Map
 How to Export LULC and make research paper LULC map using ArcMap

7th day:
 Land-Use and Land-Cover Change Detection using GEE
 NDVI change detection using GEE
 Class-wise LULC change detection in ONE layer using GEE
 Hyper parameter Tuning for improving the accuracy of your machine learning model

Join the Telegram group: https://t.me/gisandremotesenginglearningGEE

Join our YouTube channel:
https://youtube.com/

for a new batch of 7 days of Complete online training on for
& Analysis for Beginners to Advanced level.

These classes will teach you all the necessary things to start using GEE for your remote sensing analysis. We mainly focus on these people who don't know any programming language and Earth Engine function. We cover LULC mapping, Change detection Analysis, Air quality Monitoring, Time series analysis, Calculating any Indices, Supervised Classification, Unsupervised Classification, Machine Learning Methods, NDVI change detection and more.

Class Start: 8th December, 2023
Admission Last Date: 6th December (1st 10 registered people get 50% discount). Now 8 seats are available to get this 50% discount.

For registration contact this WhatsApp number: +8801780942798 or email: [email protected]

Total Class: 7 days (Friday and Saturday in Week)
Class Duration: 3 hours (Each day)
Time: 9:00 P.M to 12:00 A.M (GMT +6)

Training language: English

Course Content:
1st day:
 Introduction to GES
 How to use GEE JavaScript and Python API
 Learn the basic principles of JavaScript syntax and python
 Client vs. Server object on GEE
 How you get the server to execute your code?
 Importing Raster and Vector Data: Local storage & GEE Dataset
 Filtering Attribute Table

2nd day:
 Filtering and Displaying Satellite Images: Landsat , Sentinel
 Satellite Composite
 Band combinations
 Export Satellite Imagery: Landsat , Sentinel and Modis
 Import, Filter, Reduce, Clip and display Raster data in GEE
 Time series Chart of NDVI using GEE readymade dataset
 Export Any Shapefile

3rd day:
 Calculating Any Indices from Satellite Images using Landsat and Sentinel
 Filtering and Displaying Satellite Images: Sentinel-2 and Monitoring NDWI , NDVI
 Extract water body using Thresholding
 NDVI , NDWI , SAVI and all indices Time series Chart using Landsat and Sentinel
 Export Any Shapefile from GEE
 How to add Gradient Legend and Title on GEE
 NDWI Calculated from Modis and Landsat data

4th day:
 How to remove cloud and Haze from satellite imagery- Landsat and Sentinel
 Visualization (DEM) of Hill shade and Slope Map in GEE using NASA SRTM and Aster
 Land surface temperature (LST) Monitoring from Landsat satellite imagery and Modis
 How to calculated Average , Maximum, Minimum NDVI any specific region
 GEE: How to make monthly Evapotranspiration

5th day:
 Air Quality Monitoring: all prameters
 How to Download Air Quality parameters Time series data in CSV format using GEE
 Air Quality Monitoring Time Series chart
 Air Quality Monitoring: How to calculate total emission of nitrogen-oxide or any gases in GEE using
sentinel-5
 ArcMap software: How to make research paper map using GEE & ArcMap software

6th day:
 Introduction to Machine Learning in Google Earth Engine
 How to make LULC Map using Machine Learning: Supervised and Unsupervised algorithm
 Random forest, CART, SVM, Minimum distance classifier to make LULC
 How to Check LULC accuracy assessment using Google Earth Engine. (Kappa, Producers & Consumers
accuracy)
 Calculate LULC classes Area
 How to add Legend in LULC Map
 How to Export LULC and make research paper LULC map using ArcMap

7th day:
 Land-Use and Land-Cover Change Detection using Google Earth Engine
 NDVI change detection using Google Earth Engine
 Class-wise LULC change detection in ONE layer using Google Earth Engine
 Hyper parameter Tuning for improving the accuracy of your machine learning model

Join Our Community:
Join the Telegram group: https://t.me/gisandremotesenginglearningGEE

Join our YouTube channel:
https://youtube.com/

Recorded video class on How to create contour lines using Google Earth Engine || Contour Map using GEE || Contour Mapping
Link: https://youtube.com/live/xDmfOuUiJhY?feature=share
The new batch live training class will be started from 10th December. Registration is open now
For Registration contact this WhatsApp number: +8801780942798 or Email: [email protected]

1st day:
 Introduction to GEE
 How to use GEE JavaScript and Python API
 Learn the basic principles of JavaScript syntax and python
 Client vs. Server object on GEE
 How you get the server to execute your code?
 Importing Raster and Vector Data: Local storage & GEE Dataset
 Filtering Attribute Table

2nd day:
 Filtering and Displaying Satellite Images: Landsat , Sentinel
 Satellite Composite
 Band combinations
 Export Satellite Imagery: Landsat , Sentinel and Modis
 Import, Filter, Reduce, Clip and display Raster data in GEE
 Time series Chart of NDVI using GEE readymade dataset
 Export Any Shapefile

3rd day:
 Calculating Any Indices from Satellite Images using Landsat and Sentinel
 Filtering and Displaying Satellite Images: Sentinel-2 and Monitoring NDWI , NDVI
 Extract water body using Thresholding
 NDVI , NDWI , SAVI and all indices Time series Chart using Landsat and Sentinel
 Export Any Shapefile from GEE
 How to add Gradient Legend and Title on GEE
 NDWI Calculated from Modis and Landsat data

4th day:
 How to remove cloud and Haze from satellite imagery- Landsat and Sentinel
 Visualization (DEM) of Hill shade and Slope Map in GEE using NASA SRTM and Aster
 Land surface temperature (LST) Monitoring from Landsat satellite imagery and Modis
 How to calculated Average , Maximum, Minimum NDVI any specific region
 GEE: How to make monthly Evapotranspiration

5th day:
 Air Quality Monitoring: all prameters
 How to Download Air Quality parameters Time series data in CSV format using GEE
 Air Quality Monitoring Time Series chart
 Air Quality Monitoring: How to calculate total emission of nitrogen-oxide or any gases in GEE using
sentinel-5
 ArcMap software: How to make research paper map using GEE & ArcMap software

6th day:
 Introduction to Machine Learning in Google Earth Engine
 How to make LULC Map using Machine Learning: Supervised and Unsupervised algorithm
 Random forest, CART, SVM, Minimum distance classifier to make LULC
 How to Check LULC accuracy assessment using Google Earth Engine. (Kappa, Producers & Consumers
accuracy)
 Calculate LULC classes Area
 How to add Legend in LULC Map
 How to Export LULC and make research paper LULC map using ArcMap

7th day:
 Land-Use and Land-Cover Change Detection using Google Earth Engine
 NDVI change detection using Google Earth Engine
 Class-wise LULC change detection in ONE layer using GEE
 Hyper parameter Tuning for improving the accuracy of your machine learning model

https://youtube.com/live/xDmfOuUiJhY?feature=share

How to create contour lines using Google Earth Engine || Contour Map using GEE || Contour Mapping Google Earth Engine: 15 days Advanced online training syllabus: https://youtu.be/fhBWHFayadc?si=BFqSTvKs_8rvnNHXOnline training on the R package for interact...

QGIS Tutorials 02: Introduction to QGIS Interface for Beginners
Link: https://youtube.com/live/LBHQIwlFTPw?feature=share

Join our training telegram group: https://t.me/gisandremotesenginglearningGEE



https://youtube.com/live/LBHQIwlFTPw?feature=share

QGIS Tutorials 02: Introduction to QGIS Interface for Beginners Google Earth Engine: 15 days Advanced online training syllabus: https://youtu.be/fhBWHFayadc?si=BFqSTvKs_8rvnNHXOnline training on the R package for interact...

for a new batch of 7 days of Complete online training on for
& Analysis for Beginners to Advanced level.

These classes will teach you all the necessary things to start using GEE for your remote sensing analysis. We mainly focus on these people who don't know any programming language and Earth Engine function. We cover LULC mapping, Change detection Analysis, Air quality Monitoring, Time series analysis, Calculating any Indices, Supervised Classification, Unsupervised Classification, Machine Learning Methods, NDVI change detection and more.

Class Start: 10th November, 2023
Admission Last Date: 8th November (1st 10 registered people get 50% discount). Now 2 seats are available to get this 50% discount.

For registration contact this WhatsApp number: +8801780942798 or email: [email protected]

Total Class: 7 days (Friday and Saturday in Week)
Class Duration: 3 hours (Each day)
Time: 9:00 P.M to 12:00 A.M (GMT +6)

Training language: English

Course Content:
1st day:
 Introduction to GES
 How to use GEE JavaScript and Python API
 Learn the basic principles of JavaScript syntax and python
 Client vs. Server object on GEE
 How you get the server to execute your code?
 Importing Raster and Vector Data: Local storage & GEE Dataset
 Filtering Attribute Table

2nd day:
 Filtering and Displaying Satellite Images: Landsat , Sentinel
 Satellite Composite
 Band combinations
 Export Satellite Imagery: Landsat , Sentinel and Modis
 Import, Filter, Reduce, Clip and display Raster data in GEE
 Time series Chart of NDVI using GEE readymade dataset
 Export Any Shapefile

3rd day:
 Calculating Any Indices from Satellite Images using Landsat and Sentinel
 Filtering and Displaying Satellite Images: Sentinel-2 and Monitoring NDWI , NDVI
 Extract water body using Thresholding
 NDVI , NDWI , SAVI and all indices Time series Chart using Landsat and Sentinel
 Export Any Shapefile from GEE
 How to add Gradient Legend and Title on GEE
 NDWI Calculated from Modis and Landsat data

4th day:
 How to remove cloud and Haze from satellite imagery- Landsat and Sentinel
 Visualization (DEM) of Hill shade and Slope Map in GEE using NASA SRTM and Aster
 Land surface temperature (LST) Monitoring from Landsat satellite imagery and Modis
 How to calculated Average , Maximum, Minimum NDVI any specific region
 GEE: How to make monthly Evapotranspiration

5th day:
 Air Quality Monitoring: all prameters
 How to Download Air Quality parameters Time series data in CSV format using GEE
 Air Quality Monitoring Time Series chart
 Air Quality Monitoring: How to calculate total emission of nitrogen-oxide or any gases in GEE using
sentinel-5
 ArcMap software: How to make research paper map using GEE & ArcMap software

6th day:
 Introduction to Machine Learning in Google Earth Engine
 How to make LULC Map using Machine Learning: Supervised and Unsupervised algorithm
 Random forest, CART, SVM, Minimum distance classifier to make LULC
 How to Check LULC accuracy assessment using Google Earth Engine. (Kappa, Producers & Consumers
accuracy)
 Calculate LULC classes Area
 How to add Legend in LULC Map
 How to Export LULC and make research paper LULC map using ArcMap

7th day:
 Land-Use and Land-Cover Change Detection using Google Earth Engine
 NDVI change detection using Google Earth Engine
 Class-wise LULC change detection in ONE layer using Google Earth Engine
 Hyper parameter Tuning for improving the accuracy of your machine learning model

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