One of the basic methods for #Mapflow building heights estimation workflow. The model segments rooftops + shadows + walls. The next algorithm calculates the building 3D model based on the known parameters of the satellite image: sun elevation + camera off-nadir angle + camera target azimuth. Simple yet effective when it comes to large area processings. (The basic performance is around 1min per 1km2)
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🌲🌳 Uzbekistan is Counting Every Tree!
The State Committee of the Republic of Uzbekistan for Ecology and Environment Protection recently hosted a workshop to discuss the ambitious goal of counting every tree in the country. This is a vital step in protecting Uzbekistan's forests, which are essential for the country's environment and economy.
During the workshop, we demonstrated our #AI-Mapping technology for extracting forest masks. Our #Mapflow AI Platform uses ML methods to identify trees in VHR satellite imagery and can be used to count trees over large areas.
We shared insights on how to use ML technology to protect forests, discussed different approaches and tools, and debated verification methods.
Uzbekistan is leading the way in the fight to protect forests. By counting every tree, the country is taking a major step towards a more sustainable future.
Every tree matters! 🌲🌳
The State Committee of the Republic of Uzbekistan for Ecology and Environment Protection recently hosted a workshop to discuss the ambitious goal of counting every tree in the country. This is a vital step in protecting Uzbekistan's forests, which are essential for the country's environment and economy.
During the workshop, we demonstrated our #AI-Mapping technology for extracting forest masks. Our #Mapflow AI Platform uses ML methods to identify trees in VHR satellite imagery and can be used to count trees over large areas.
We shared insights on how to use ML technology to protect forests, discussed different approaches and tools, and debated verification methods.
Uzbekistan is leading the way in the fight to protect forests. By counting every tree, the country is taking a major step towards a more sustainable future.
Every tree matters! 🌲🌳
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#GeoQuiz No.9 You never know what you will find in some user images 😳 (sharing here with the user's permission).
BTW can you guess what kind of animals are there and where this image was captured?
And here is some teaser of what we working on now as we are looking forward to covering more specific cases like this. If you didn't find the solution for your case with the default AI models in Mapflow, maybe it will be solved in the upcoming release. Reach out and we will include you in beta-testing with enough of a free limit 👆😉
BTW can you guess what kind of animals are there and where this image was captured?
And here is some teaser of what we working on now as we are looking forward to covering more specific cases like this. If you didn't find the solution for your case with the default AI models in Mapflow, maybe it will be solved in the upcoming release. Reach out and we will include you in beta-testing with enough of a free limit 👆😉
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A new #Mapflow #QGIS #plugin version 2.0.0 is just released. 🎉
You may notice some improvements in UI and a more compact window, but why change the major version?
The reason is - there are API changes planned that will require the new version: Integrated Billing.
Both of our mainly used applications Mapflow Web and Mapflow Plugin will have billing in credits, which brings a better experience to our pay-as-you-go customers, as the additional credits will be available in the QGIS plugin moments after payment.
And yet there is some time for you to update the plugin before we switch the billing type to the credits, so this is a bit of a teaser for what is coming soon!
See the full changelog on github.
You may notice some improvements in UI and a more compact window, but why change the major version?
The reason is - there are API changes planned that will require the new version: Integrated Billing.
Both of our mainly used applications Mapflow Web and Mapflow Plugin will have billing in credits, which brings a better experience to our pay-as-you-go customers, as the additional credits will be available in the QGIS plugin moments after payment.
And yet there is some time for you to update the plugin before we switch the billing type to the credits, so this is a bit of a teaser for what is coming soon!
See the full changelog on github.
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Finally we started to showcase #Mapflow AI solutions where we've contributed a lot to deliver it to the end-customer analytical workflow. Check our page to showcase the solution for 🌿 Vegetation management 🌿 near power lines: Mapflow AI for utility monitoring
If you are related to utility assets management / risk control, etc. we would love to hear from you and to set up an evaluation account. As a test of our technology data analysts can get started with the free Mapflow plugin for #QGIS and 🌲 Forest and 🌲↕️ Forest with heights AI models that are available by default.
If you are related to utility assets management / risk control, etc. we would love to hear from you and to set up an evaluation account. As a test of our technology data analysts can get started with the free Mapflow plugin for #QGIS and 🌲 Forest and 🌲↕️ Forest with heights AI models that are available by default.
geoalert.io
Geoalert Imagery Analysis Platform
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Announcement! We are moving all our applications to the credit based billing.
You may have noticed that the Mapflow credits which can be bought online and used in web version of the platform, are not applicable to Mapflow QGIS and API, where we measure processing in square kilometers and need to transfer credits to area manually.
To make it consistent and more flexible we have united the billing system for Web and QGIS / API moving to credits for all our users (except for selected commercial clients who are specifically assigned to area-based billing). This means the following:
☑️ your credits will be visible in Mapflow QGIS and will be spent on processing
☑️ you will see the actual cost of the processing in the plugin before the launch of the processing
☑️ cost calculation breakdown documentation is updated at https://docs.mapflow.ai/userguides/prices.html
☑️ “Free” starter square kilometers in Mapflow QGIS will be discarded in favor of credits that are on you account, but if you have purchased a processing area for API/QGIS in square km, they will be converted back to credits
❗ You should upgrade to Mapflow-QGIS 2.0.0, older versions are not compatible with the new API.
One of the main advantages of the integrated billing is that from now on you will be able to spend your credits for the processing of commercial satellite imagery starting from the minimum package of $50. (See more in docs about calculation of data prices)
This is yet a long way to get to the full integration of the web- and gis- UX, as currently model options selection is not available in QGIS but in web, and some of the models are web-only or QGIS-only, so we are working on it to make your experience with the Mapflow platform even more seamless.
This change will take effect today, 22 June 2023, 22-24 GMT. If you have any questions or problems, feel free to contact our support ([email protected]) at any time.
You may have noticed that the Mapflow credits which can be bought online and used in web version of the platform, are not applicable to Mapflow QGIS and API, where we measure processing in square kilometers and need to transfer credits to area manually.
To make it consistent and more flexible we have united the billing system for Web and QGIS / API moving to credits for all our users (except for selected commercial clients who are specifically assigned to area-based billing). This means the following:
☑️ your credits will be visible in Mapflow QGIS and will be spent on processing
☑️ you will see the actual cost of the processing in the plugin before the launch of the processing
☑️ cost calculation breakdown documentation is updated at https://docs.mapflow.ai/userguides/prices.html
☑️ “Free” starter square kilometers in Mapflow QGIS will be discarded in favor of credits that are on you account, but if you have purchased a processing area for API/QGIS in square km, they will be converted back to credits
❗ You should upgrade to Mapflow-QGIS 2.0.0, older versions are not compatible with the new API.
One of the main advantages of the integrated billing is that from now on you will be able to spend your credits for the processing of commercial satellite imagery starting from the minimum package of $50. (See more in docs about calculation of data prices)
This is yet a long way to get to the full integration of the web- and gis- UX, as currently model options selection is not available in QGIS but in web, and some of the models are web-only or QGIS-only, so we are working on it to make your experience with the Mapflow platform even more seamless.
This change will take effect today, 22 June 2023, 22-24 GMT. If you have any questions or problems, feel free to contact our support ([email protected]) at any time.
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🌳 Australia and New Zealand urban green patterns powered by #Mapflow.
Which other cities you might be interested to analyze?
Check out open data updates on our github page.
Which other cities you might be interested to analyze?
Check out open data updates on our github page.
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🎉 Today we introduce the public beta release of the ✨ "Segment Anything Model" featured in Mapflow dashboard.
While studying and being inspired by some of these open-source repos we found out that it's worth implementing SAM into our platform while adjusting it to the geospatial imagery processing workflows on a large scale.
- If you run this model using a GeoTIFF file , the original input resolution of the image will be used
- If you run it via TMS (e.g. Imagery providers like #Mapbox Satellite) , you need to select the Zoom level (image resolution) from the model options which will be used for the input.
Depending on the input resolution, the #SAM model will interpret it and generate different objects. It can be empirically and semantically classified by the zoom levels.
Share with us your samples if you manage to obtain some nice (or not-so-nice) results with SAM by rating your results. We review all your ratings and get back with promo codes and support to thank you for it.
Read a full article here
While studying and being inspired by some of these open-source repos we found out that it's worth implementing SAM into our platform while adjusting it to the geospatial imagery processing workflows on a large scale.
- If you run this model using a GeoTIFF file , the original input resolution of the image will be used
- If you run it via TMS (e.g. Imagery providers like #Mapbox Satellite) , you need to select the Zoom level (image resolution) from the model options which will be used for the input.
Depending on the input resolution, the #SAM model will interpret it and generate different objects. It can be empirically and semantically classified by the zoom levels.
Share with us your samples if you manage to obtain some nice (or not-so-nice) results with SAM by rating your results. We review all your ratings and get back with promo codes and support to thank you for it.
Read a full article here
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#GeoQuiz No.10
Some of us are used to calling Segment-Anything implementation "SAMSA" (short form of "Segment Anything Model for Spatial Analysis"). Do you know the association and how it's related geographically? ))
BTW try SAMSA in #Mapflow for free, contact us if you need some special serving set.
Some of us are used to calling Segment-Anything implementation "SAMSA" (short form of "Segment Anything Model for Spatial Analysis"). Do you know the association and how it's related geographically? ))
BTW try SAMSA in #Mapflow for free, contact us if you need some special serving set.
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