Adding data to EOS Processing

Adding data from LandViewer

There are 3 different ways to add your sourcedata to EOS Processing:

  1. Transfer your dataset from LandViewer to EOS Processing directly
  2. Transfer data, using the mutual integration of EOS products, that is Acquire data in LandViewer, Save it in EOS Storage and Open it EOS Processing
  3. Transfer data from EOS Storage to EOS Processing directly. When you upload your data from local directory to EOS Storage, you can set or not set the bandmapping in advance

1. To detect “Filed Contours”, adding data from LandViewer, one should make the following steps:

1.1. Go to LandViewer and pick Sentinel-2 from the satellite list in the left menu.

1.2. Click Increase zoom in the left menu.

1.3. Select the target terrain and left-click it on the map. Once the pointer shows up, a list of available images of the selected area will appear in the left menu.

1.4. Pick the image with low cloud, if it’s possible, hover over a Processing icon in the bottom left of the image, and once Extract analytics shows up, click it to open the image in EOS Processing.

1.5. Wait for the EOS Processing tab to load and choose a proper algorithm  (if you hover over the algorithm, “Create Processing” button will show up) from the list available for the satellite selected. The algorithms are automatically filtered, according to the satellite; the system suggests the algorithms that fit the task mostly.

1.6. Use scroll or zoom buttons (+) & (-) to get the area zoomed in&out.

1.7. When the prompt message Maximum processing area is 100 km2 shows up, draw the AOI, using the tool on the top left of the screen or select it from the saved My AOI list.

1.8. Select the AOI (not more than 100 km2)

1.9. Click Start to launch processing.

1.10. Wait for the processing to complete

1.11. Once the processing is successfully complete, check the results in the menu on the left. You can also open the outcome files in EOS Storage and download them, if needed.

The result of the processing:

Contour object detection, based on space data, using neural networks. The main advantage of the nets is high noise resistance and computation speed due to data parallel processing.

Input data

Raster image in GeoTIFF format

Output data

Raster image in GeoTIFF format

Vector layer in GEOJSON format

Data Requirements

Input data spatial resolution – not less than 30 cm

Satellite imagery from Sentinel-2, RapidEye is used in contour object detection in the territories of Ukraine, California and Great Britain.

Applied fields

Crops mapping

Сrops classification and condition assessment, separately for each field. Drawing a plan for crops growing in upcoming vegetative seasons.

Operational agricultural monitoring

Change detection in crops growing in different vegetative seasons. Tracking of a crop growing process during one vegetative season.  

Spatial analysis

Polygonal sites (farms, fields) geometry analysis, that is area, perimeter, compactness ratio, etc.      Sites density assessment

Datasource

Satellite systems Sentinel-2

 

 

 

Adding data, using EOS products mutual integration

2. To detect “Filed Contours”, using the mutual integration of EOS products, that is Acquire data in LandViewer, Save it in EOS Storage and Open it EOS Processing one should make the following steps:

2. 1. Go to LandViewer and pick Pick Sentinel-2 from the satellite list in the left menu.

2.2. Click Increase zoom

2.3. Select the terrain and left-click it on the map. Once the pointer shows up, a list of available images of the selected area will appear in the left menu.

2.4. Pick the image with low cloud, if it’s possible, and click downloading icon to save it in EOS  Storage.

2.5. Wait for the notification Show in EOS Storage” to show up in the right bottom of the image and click the hyperlink.

2.6. Wait for the file is ready to open in EOS Processing (usually, it takes up to10 min for Sentinel-2), click Open with and select EOS Processing.

2.7. Wait for the EOS Processing tab to load and choose a proper algorithm  (if you hover over the algorithm, “Create Processing” button will show up) from the list available for the satellite selected. The algorithms are automatically filtered, according to the satellite; the system suggests the algorithms that fit the task mostly.

The next steps are exactly the same  you take, adding data from LandViewer,  the only difference is – the Project will have the name  – EOS_Storage.

2.8. Use scroll or zoom buttons (+) & (-) to get the area zoomed in&out.  

2.9. When the prompt message Maximum processing area is 100 km2  shows up, draw the AOI, using the tool on the top left of the screen or select it from the saved My AOI list.

2.10. Select the AOI (not more than 100 km2)

2.11. Click Start to launch processing.

2.12. Wait for the processing to complete.

2.13. Once the processing is successfully completed, check the results in the menu on the left. You can also open the outcome files in EOS Storage and download them, if needed.

The result of the processing:

Contour object detection, based on space data, using neural networks. The main advantage of the nets is high noise resistance and computation speed due to data parallel processing.

Input data

Raster image in GeoTIFF format

Output data

Raster image in GeoTIFF format

Vector layer in GEOJSON format

Data Requirements

Input data spatial resolution – not less than 30 cm

Satellite imagery from Sentinel-2, RapidEye is used in contour object detection in the territories of Ukraine, California and Great Britain.

Applied fields

Crops mapping

Сrops classification and condition assessment, separately for each field. Drawing a plan for crops growing in upcoming vegetative seasons.

Operational agricultural monitoring

Change detection in crops growing in different vegetative seasons. Tracking of a crop growing process during one vegetative season.  

Spatial analysis

Polygonal sites (farms, fields) geometry analysis, that is area, perimeter, compactness ratio, etc.      Sites density assessment

Datasource

Satellite systems Sentinel-2

Local directory-EOS Storage-EOS Processing

3. To detect “Fileld Contours”, adding data from EOS Storage with Band Mapping set, follow the next steps:

3.1. Go to EOS Storage, Click Upload and select File from the drop-down menu.

3.2. Select file from local directory.

  • or drag-and-drop the target file in EOS Storage tab

3.3. Wait for the image is loaded in EOS Storage.

3.4. Select Band Mapping in the context menu, that will show up once you right-click the image.

3.5. Custom the Band Mapping, that is set the band name according to it’s location on your raster image.

3.6. Go to EOS Processing, or switch to EOS Processing in the Product menu.

3.7. Choose any of the projects or create a new one. Once you click Create Project the modal box will show up. Enter the Project name and click Create. Each Project folder in EOS Processing will have a clone Project folder in EOS Storage, containing processing data results by default.

3.8. Once in Project, click Create Processing.

3.9. Choose the appropriate algorithm from the list suggested or use the search option to quickly find the target algorithm and click Select.

3.10. Click Add to add files from EOS Storage.

3.11. Find the target file, using either EOS Storage modal box or Search box.

3.12. Once the file is found, the suggestion Prepare file for EOS Processing  will show up.

During preprocessing, the image split into bands, each band on the picture is loaded separately into S3 Bucket for further work across EOS Plaform products, meanwhile it  builds a histogram, calculate the intensity range, etc.

3.13. Click the hyperlink; the process of Processing takes some time, depending on the file size. Once preprocessing is completed, click Select to choose the file, it has the name processed_<filename>.TIF

The next steps are exactly the same  you take, adding data from LandViewer

3.14. Use scroll or zoom buttons (+) & (-) to get the area zoomed in&out.  

3.15. When the prompt message Maximum processing area is 100 km2  shows up, draw the AOI, using the tool on the top left of the screen or select it from the saved My AOI list.

3.16. Select the AOI (not more than 100 km2).

3.17.  Click Start to launch processing.

3.18. Wait for the processing to complete.

3.19. Once the processing is successfully completed, check the results in the menu on the left. You can also open the outcome files in EOS Storage and download them, if needed.

The result of the processing:

Contour object detection, based on space data, using neural networks. The main advantage of the nets is high noise resistance and computation speed due to data parallel processing.

Input data

Raster image in GeoTIFF format

Output data

Raster image in GeoTIFF format

Vector layer in GEOJSON format

Data Requirements

Input data spatial resolution – not less than 30 cm

Satellite imagery from Sentinel-2, RapidEye is used in contour object detection in the territories of Ukraine, California and Great Britain.

Applied fields

Crops mapping

Сrops classification and condition assessment, separately for each field. Drawing a plan for crops growing in upcoming vegetative seasons.

Operational agricultural monitoring

Change detection in crops growing in different vegetative seasons. Tracking of a crop growing process during one vegetative season.  

Spatial analysis

Polygonal sites (farms, fields) geometry analysis, that is area, perimeter, compactness ratio, etc.      Sites density assessment

Datasource

Satellite systems Sentinel-2

Local directory-EOS Storage-EOS Processing (without Band Mapping set)

4. To detect “Fileld Contours”, adding data from EOS Storage without Band Mapping set, follow the next steps:

4.1. Go to EOS Storage , Click Upload and select File from the drop-down menu.

4.2. Select file from local directory.

  • or drag-and-drop the target file in EOS Storage tab

4.3. Wait for the image is loaded in EOS Storage.

4.4. Go to EOS Processing, or switch to EOS Processing in the Product menu.

4.5. Choose any of the projects or create a new one. Once you click Create Project the modal box will show up. Enter the Project name and click Create. Each Project folder in EOS Processing will have a clone Project folder in EOS Storage, containing processing data results by default.

 

4.6. Once in Project, click Create Processing.

4.7. Choose the appropriate algorithm from the list suggested or use the search option to quickly find the target algorithm and click Select.

4.8. Click Add to add files from EOS Storage.

4.9. Find the target file, using either EOS Storage modal box or Search box.

4.10. Once the file is found, the suggestion Prepare file for EOS Processing  will show up.

During preprocessing, the image split into bands, each band on the picture is loaded separately into S3 Bucket for further work across EOS Plaform products, meanwhile it  builds a histogram, calculate the intensity range, etc.

4.11. Click the hyperlink; the process of Processing takes some time, depending on the file size. Once preprocessing is completed, click Select to choose the file, it has the name processed_<filename>.TIF

4.12. Once the file is selected, the pop-up window, notifying that Band Mapping is not set.  

4.13. Click the hyperlink to get to File preview and set the bandmapping. Click outside the image to close File preview. Select Band mapping in the context menu, that will show up once you right-click the image.

4.14. Custom the Band mapping, that is set the band name according to it’s location on your raster image.

4.16. Repeat steps 9,10 and 13.

The next steps are exactly the same  you take, adding data from LandViewer.

4.17. Use scroll or zoom buttons (+) & (-) to get the area zoomed in&out.  

4.18. When the prompt message Maximum processing area is 100 km2  shows up, draw the AOI, using the tool on the top left of the screen or select it from the saved My AOI list.

4.19. Select the AOI (not more than 100 km2).

4.20. Click Start to launch processing.

4.21. Wait for the processing to complete.

4.22. Once the processing is successfully completed, check the results in the menu on the left. You can also open the outcome files in EOS Storage and download them, if needed.

The result of the processing:

Contour object detection, based on space data, using neural networks. The main advantage of the nets is high noise resistance and computation speed due to data parallel processing.

Input data

Raster image in GeoTIFF format

Output data

Raster image in GeoTIFF format

Vector layer in GEOJSON format

Data Requirements

Input data spatial resolution – not less than 30 cm

Satellite imagery from Sentinel-2, RapidEye is used in contour object detection in the territories of Ukraine, California and Great Britain.

Applied fields

Crops mapping

Сrops classification and condition assessment, separately for each field. Drawing a plan for crops growing in upcoming vegetative seasons.

Operational agricultural monitoring

Change detection in crops growing in different vegetative seasons. Tracking of a crop growing process during one vegetative season.  

Spatial analysis

Polygonal sites (farms, fields) geometry analysis, that is area, perimeter, compactness ratio, etc.      Sites density assessment

Datasource

Satellite systems Sentinel-2