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How App Creator helps you make Google Earth Engine Apps
At the Geo for Good Summit 2020, David Gibson, Software Engineer at Google, announced the App Creator which allows users to easily build an Earth Engine App interface. Earth Engine Apps are dynamic user interfaces for sharing your Earth Engine analyses and results online. The app can be viewed by anyone, even if they are not Earth Engine…
How to build custom plugins in QGIS
When I needed to change a part on my 4WD expedition truck, there was no spanner known to man that could get the job done. So, I welded one up out of scrap material I had laying around, and while it wasn’t pretty, it did the job. Now, whenever I need to undo that part…
Speedy planning and built environment design with LiDAR
Excellent design is a key measure of success for the public sector, especially when it comes to planning within environments that are already fully or partially developed. Examples of this might be a new shopping mall on a main street, installing traffic lights or roundabouts on a busy thoroughfare, or running a tramway down a…
Harnessing Google Cloud Platform power for geospatial apps
As a GIS professional, I have worked across a range of Geographic Information System (GIS) environments and utilised thousands of different datasets, both spatial and non-spatial. A common theme I noticed while working with spatial data was the significant challenges that traditional GIS tools had when it came to processing very large datasets. Splitting datasets,…
How connected geospatial data is transforming the mining industry
During the lifecycle of a mine, there are large amounts of data being captured across disparate systems. Often, the data that is used to help decision makers operate sites efficiently and sustainably are inherently spatial. Connecting the different geospatial data sources across the mining life cycle enables business units to have valuable situational awareness across…
Choosing the right Machine Learning approach for your geospatial project
Machine learning (ML) helps us find patterns in data through the use of algorithms. By using algorithms to build models that uncover connections, organisations can make better decisions faster and without human intervention. From a geospatial perspective, an example of using ML is via image analysis in remote sensing work. But how do you choose…
Using Terraform to automate Google Cloud deployments
People love to say things like “let’s move to the cloud”, “get started in minutes” or “just put it into BigQuery”, but developers understand that there is much more to it than that. The journey to move completely to the cloud is one that takes a lot of care and consideration. However, in many cases…
Make static maps digital in a few hours with Machine Learning
Some time ago, I was working on a project that required a map to get some geospatial information on the Lithology (the study of rocks) of the Island of San Miguel in Azores, Portugal. When I asked for the data, to my surprise, I was sent a photocopy of the original geological map in a JPG format. …
What’s influencing the spatial industry in 2021?
The spatial industry is relying on, investing in and processing more data than ever before. Businesses are finding new ways to realise the potential of spatial data they’ve collected for years and how they can process this information in new ways to drive their decisions. Last year, we saw organisations adapt to remote working, invest…
No phone reception? No problem with ArcGIS Field Maps
Have you ever been navigating somewhere with Google or Apple Maps when all of a sudden your base map stops updating? Then you look at your phone and realise you are out of mobile reception range? Living in the big state of Western Australia, I’ve had this issue many times. This is where offline capable…
