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A New Hub for Geospatial Knowledge, Tutorials and Code

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Since its creation in 2012, has stood out as a highly popular online publishing platform, boasting a clean and user-friendly interface, an ad-free policy, and, most notably, the ability for writers to swiftly reach a vast audience. 

Having actively contributed to since April 2020, I embarked on this journey during the pandemic lockdown to share insights gained from my PhD in Remote Sensing. Over time, I’ve authored over 40 technical articles and tutorials primarily centered around Geospatial Intelligence and Deep Learning.

Despite’s initial appeal, the platform has become inundated with attention-grabbing clickbait and low-quality articles savagely competing for resources within the Partner Program. Additionally, while the platform’s simplicity facilitates entry for novice bloggers, it comes at the cost of offering a more customizable experience for those seeking to present richer content.

However, over the time, has been filled with attention-grabbing, clickbait and low-quality articles savagely competing for for resources from the Partner Program. Besides that, the simplicity of the interface, that makes it easy for writers to blog in the first time pays a price when we want to offer a more customizable experience. 

In light of these considerations, I found myself in search of a alternative that not only allows me to share articles but also provides the flexibility to offer tutorials and potentially courses in the future. Collaborating with my friend, Thiaggo Tayer PhD, we envisioned the need for our own publication — free from the constraints and distractions imposed by Hence, was born.

The birth of GeoCorner

GeoCorner emerged from the shared passion of two friends, united by their love for GeoSpatial Analysis, Coding, and the environment. Although we each embarked on distinct academic journeys, we encountered common challenges when delving into Geographic Information Systems (GIS). 

Why a technical publication on geospatial data science?

Geospatial data science is a complex field that requires transversal knowledge from several other fields such as Geographic Information Systems (GIS), Remote Sensing, Earth Sciences and Computer Science fields (Figure 1). 

In this regard, traditional university programs in geography and environmental sciences excel in teaching us how to analyze natural phenomena but often fail to equip us with the essential skills for developing systems and conducting robust data analysis. A single semester of an archaic programming language hardly bridges the gap to real-world application.

On the other hand, computer science programs can be overly consumed by technical minutiae and do not prepare professionals to understand natural phenomena and perform proper geospatial analysis.

Besides that, the lack of examples, tutorials, and documentation makes it hard for someone to become a geospatial analyst on his own. Usually, we learn from colleagues within academia, where basic geospatial software is developed without software engineering concepts in mind, such as ease-of-use, integration, modularization, etc.

Like so, we believe that we currently reside at the intersection of environmental and computer sciences. aims to bridge this landscape and empower you with the knowledge and skills needed to succeed in this ever-evolving field.

To understand why this field is growing so fast and is becoming fundamental in the coming years, don’t miss our article: Why Learn Geospatial Data Science in 2024?


In today’s age of abundant environmental data sourced from satellites, sensors, and more, manual data collection and analysis are no longer viable. Proficiency in tools like QGIS and ArcGIS is essential but no longer sufficient.

Becoming a skilled geospatial analyst requires a multidisciplinary approach to harmonising seemingly disconnected subjects. This includes knowledge of geography, computer science, environmental sciences, and more. Additionally, emerging fields like machine learning and artificial intelligence must not be left aside. They play an increasingly vital role in understanding complex data and natural processes.

The articles from are being migrated to the new platform on a continuous basis and new articles will be added weekly. To keep resources organized, 3 categories are proposed (Figure 2): General (News, opinions, insights), GeoEssentials (beginner’s articles), and GeoWizards (advanced articles and tutorials). 

To be notified about the new additions, don’t forget to subscribe to our mailing list.

Join us at, where we demystify the world of geospatial analysis and help you thrive amidst the merging tides of environmental and computer sciences. 

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