Essential skills to transition from GIS to Spatial Data Science. — 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…

Install hustle free geospatial libraries with one line of code in Anaconda. — I have had my share of frustration installing geospatial packages. The same is also true for my students. Mismatching dependency libraries can sometimes be challenging. Lately, I have had a smooth transition into Installing packages through Conda and with almost no failure. …

Ingest, process, and Visualize 3D Point Cloud Data in Python — Working with 3D point cloud data is challenging. The collection of the points in one Lidar image is usually extensive and might reach millions of points depending on the image size. Handling the height dimension also poses other complexities. A point cloud is a set of data points in space…

Learn LiDAR Point Cloud Data, its applications and Sources. — LiDAR Point Cloud data is widely used in Geospatial and Earth observation applications. This blog post will look into what Lidar data is, where and how to access it freely, and the open-source tools you can use to work with point cloud data. In the next blog post, I will…

Worldwide availability through many platforms. — Landsat 9 satellite was launched last year, and USGS made the first scenes of Landsat 9 data available on Feb 10 2022. You can now access and download the data through USGS Earth Explorer. …

Progress, best practices & Gaps. — Spatial data is often inappropriately handled or even ignored in Machine learning. Compared to other datasets, like time-series data, spatial data integration into machine learning algorithms is lagging. A recent review paper highlights the current state of machine learning in spatial data, the trends, and the gaps. I enjoyed reading…

What is MAUP, and how to tackle it? — Maps are spatial representations in the real world. Modifiable Areal Unit Problem (MAUP) is one of the most challenging problems in Spatial data analysis. We face MAUP when performing grouped/aggregated spatial data analysis. The modifiable areal unit problem (MAUP) is a source of statistical bias that can significantly impact the…

Cartography and Web Mapping Resources — GIS Web development Skills are high in demand, and the open-source tools have become abundant and mature. If you want to build the next generation GIS web applications, there are so many frameworks, applications, and languages you have to master. Luckily, as we are already stepping into 2022, the availability…

Reflectins, Stats and Planning next year — We are finally putting 2021 to its end. It has been a wonderful year with a lot of discoveries. This will be my last post for the year, spending the last few days of the year reflecting and planning. It has become a habit to write the end of the…