A comparison — choosing the right option for the right project.

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Numbers do not speak for themselves!. We make them talk.

An essential part of data analysis is communication. We need to arrange information in a comfortable and digestible way to communicate, highlight and visualise critical areas.

Dashboards take your data visualisation to the next level. They connect different visualisation components and make a whole and integrated data visualisation stories. Web application Dashboards also allow users to interact with the data and the visualisation, offering them to see and adjust what they want or need.

It has never been easier to create a dashboard in Python. We have several dashboard tools…

Essential skills to transition from GIS to Spatial Data Science.

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GIS skills and education have changed over the past years. “I’ve been GIS. Now I’m geospatial.” writes Will Cadell in a recent article titled Geospatial Is Not GIS.

As a GIS person typically produces cartographic and analytical products using desktop software, Geospatial data scientist creates code and runs pipelines that produce analytical products and cartographic representations. The difference might seem subtle, but it requires a new set of tools and mindset.

The GIS skills are still relevant, but there are a lot of other skillsets necessary for geospatial data scientists to succeed, some obvious while others are less known. A…

Platforms, Tools and Packages for Geospatial/Earth Observation Data Scientists

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The satellite-based earth observation data is increasing at a rapid base, thanks to technological development in remote sensing platforms, and breakthroughs in data collection and storage. Today, we have more than 768 earth observation satellites in orbit, compared with only 150 in 2018.

As a Geospatial or earth observation data scientist, you have a vast array of tools and resources to choose. In this article, I highlight the best open source tools in the market that are integrated into the data science ecosystem.

1. Google Earth Engine (GEE)

Your wish granted. GEE is all in one package. Google Earth Engine(GEE) is by far the complete…

A tutorial on efficient and quick spatial joining for a large dataset.

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Recently, I thought back to a few years ago, when I tried to process a large geospatial dataset with Python. You can only guess how it ended. My laptop refused to cooperate and froze spectacularly without failing.

Frustration ensued.

Fast forward today, I was experimenting with RAPIDS AI Suite and came across the same dataset. I immediately knew what to do. So I jumped into coding.

The RAPIDS suite of open source software libraries and APIs gives you the ability to execute end-to-end data science and analytics pipelines entirely on GPUs.

In this tutorial, I will go through a complete…

Threats of Location-based data and mechanisms to mitigate them

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Location data provides an unparalleled opportunity to understand our environments, mobility, and how we use space over time. In times of this pandemic, we have seen again and again how crucial component location data is to track disease spread, combat it, and design policies to enforce distancing policies.

Today, we collect continuous and up-to-date timestamped geolocation data from IoT and smartphone devices that are precise. The utility of these datasets is undeniable. However, we must also think about the privacy issues inherent in these datasets.

Location data reveals a lot of information, and it is often treated as a special…

Step by Step tutorial using Streamlit, Exif, and Pandas

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“Talk is cheap. Show me the code.”
Linus Torvalds

Creating web applications and sharing with the world is both enriching to your learning experience and a great way to showcase your skills and differentiate yourself from the rest.

In this article, follow me as I build a helpful web application using Python. The Photo Geolocating application can help the user to get metadata from any image, including the camera used to take the picture, its model, when it was taken, and where it was taken.

Uploading Images with Streamlit

We will go through building the geolocating application step by step. First, we need…

Geolocating Photos and Extracting Coordinates in Python.

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The pictures you take with your smartphone or digital camera have rich metadata of additional information about the photo. They store this metadata in a format called EXIF, short for Exchangeable Image File Format, which has different standard versions.

Exchangeable image file format (officially Exif, according to JEIDA/JEITA/CIPA specifications) is a standard that specifies the formats for images, sound, and ancillary tags used by digital cameras (including smartphones), scanners and other systems handling image and sound files recorded by digital cameras.

The EXIF metadata might have information about the model of the device, dimensions, the date of the picture, and…

Trends, Skills, Learning Resources & Project Ideas

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This is an ongoing series highlighting Geospatial Data Science Projects. In the first part of this series, I have highlighted the different types of geospatial data scientists and the diverse skillsets required in each subfield.

In this second article of this series, we cover Geospatial Front End, the skills needed, and project ideas.

| Trends

Front End Geospatial (Web GIS) Developer creates Geospatial applications in the browser to allow the users to see and interact with the applications on the browser.

As more people use browsers, the demand for Front End Geospatial Developers is increasing. …

Easy EDA with One line Of code

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Data visualization and exploration is a critical task in Data science. However, it takes a lot of tinkering, time, and writing at least few lines of code to produce a single visualization.

What if you had an intelligent data visualization tool that automatically suggests relevant and aesthetically beautiful data visualizations to enable you to discover and explore your data quickly.

I am not talking about suggesting a single bar chart or a couple of visuals. I am talking about a whole set of data visuals to set your intention in one line of code and get back interactive data visuals…

Through AI, Cloud Computing & Satellite Imagery

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In partnership with Microsoft AI for Earth and ESRI, Impact Observatory released a new and the first 10-m high-resolution Land Use/ Land Cover (LULC) map for the whole world.

The data uses imagery from Sentinel-2 in the year 2020 and can freely be downloaded from the ESRI portal, making it the most recent land cover map you can use for your project.

The clever use of cloud technology, Machine Learning, open-source satellite imagery, and the new Microsoft Planetry platform enabled the rapid global Land cover mapping. …


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