The MapScaping Podcast - GIS, Geospatial, Remote Sensing, earth observation and digital geography

Data is what data does  - more about that later on ;)  This episode focuses on designing for privacy, how do we create value from location data without sacrificing personal privacy?  Well, you might start by adhering to the Enhanced Standards For Precise Location Information which means that information about sensitive places like churches, hospitals, military bases, and LGBTQ+ spaces isn't misused or sold. Plus, they protect our exact location from being shared with law enforcement or bounty hunters!  Yes, that's right bounty hunters!  You might also think about adding noise to the data, maybe you want to blur the time stamp and look at everything in aggregate? It turns out the location data is not just classified as personal data but is actually classified as sensitive personal data in privacy law so if you are going to work with it you really need to understand the risks involved. One of the really interesting ideas mentioned by Elizabeth Hein VP of Compliance & Data Protection was the idea of regulating Use, Harm, and Risk instead of sensitive data  Data Is What Data Does: Regulating Use, Harm, and Risk Instead of Sensitive Data If you want to learn more about POI data and why points of interest data are so hard  check out the episode called All of the Places in the World: https://mapscaping.com/podcast/all-of-the-places-in-the-world/ On a side note, I am working on a side project, it's a job board for geospatial people, and you can find it here https://mapscaping.com/jobs/ it's still in the development phase but feel free to check it out!

When comparing multispectral and hyperspectral data it is not simply a case of “more data more better”!  With hyperspectral you have “The curse of Dimensionality” but you also get more flexibility to pick exactly what bands you want to use! With multispectral you have less noise but you also have less data! This episode is designed to be a beginner's guide to the differences between hyperspectral and multispectral satellite data.   You can reach out to Gordon Logie here: https://sparkgeo.com/blog/team/gordon/   Podcast episode with the CEO of Sentinel-Hub https://mapscaping.com/podcast/sentinel-hub/   Here are some courses that focused on hyperspectral and offer further training   https://eo-college.org/courses/beyond-the-visible/ https://eo-college.org/courses/beyond-the-visible-imaging-spectroscopy-for-agricultural-applications/ https://www.enmap.org/events_education/hyperedu/

This week we are going to learn how Foursquare is trying to identify and map all of the places in the world!  Foursquare uses a mixture of crowd source and data conflation to maintain a database of 205 million places ... and it's not easy! Each phone might see the world slightly differently in terms of location accuracies and crowdsourcing data means that people "check-in" at different locations.    Kyle Fowler - Senior Director, Engineering at Foursquare Is going to give a behind-the-scenes look at how the "Orginal location-based social network" is trying to map all of the places in the world.  This episode is the first in a series of episodes I am going to publish in partnership with Foursquare and the idea is to use it as a reference for later episodes about Privacy and location data, Knowledge Graphs, AI, Location Based Marketing and Big geospatial Data in the Browser.       

Protomaps is a serverless system for planet-scale maps, it's an umbrella project consisting of a few different components one of which is PMtiles. PMtiles is “Cloud Optimise Geotiff” for web mapping, what this means is that you can build a base map and host it without the need for a server!  PMtiles is a single file that you can access via HTTP range requests in the same way that you can access data within a Cloud Optimised Geotiff with the important difference that PMtiles can also contain vector data! What this means is that you can create your own base map, and host it on something like Amazon S3 object storage at a fraction of the cost of other base map solutions!    During this episode, you will hear Brandon, the founder, and creator of Protomaps, talk about scarcity, and well I have never really thought about base maps as being a scarce resource I can definitely see how a product like PMtiles could remove some of the barriers to entry for a lot of creativity in terms of base maps.    More information on Protomaps is here:  https://protomaps.com/   Tippecanoe https://github.com/felt/tippecanoe.git https://bertt.wordpress.com/2023/01/06/creating-vector-pmtiles-with-tippecanoe/ Relevant podcast episodes  Cloud Optimized Point Clouds https://mapscaping.com/podcast/cloud-optimized-point-clouds/ Cloud Native Geospatial https://mapscaping.com/podcast/cloud-native-geospatial/ Microsoft’s Planetary computer https://mapscaping.com/podcast/the-planetary-computer/ Stamen Design - Full Stack Cartography https://mapscaping.com/podcast/full-stack-cartography/   If you have any questions or comments, let me know, I would love to hear from you!

Storytelling with point clouds   This is not your typical point clouds episode! Today we are talking about how to use point clouds to tell a story. During this episode, you will hear Benjamin Muller talk about using a point cloud to make a film about the city of St Gallen in Switzerland and you might be tempted to think … what a waste of time! Why not use the data to make better measurements that lead to better decisions?  How many IT projects have failed, not because they were based on bad decisions but because they failed to get people to adopt the changes?  The best decisions are meaningless unless they are adopted.  So, how do we get people to change or adopt the change we are trying to make?  I think the first thing to understand is that packaging matters!  This episode is a case study into wrapping our ideas in a story and visualizing them using geospatial data.   Here is a link to the visualizations that were created using the point cloud data https://www.gruenesgallustal.ch/resume   You can take a look HxDR platform here https://hxdr.com/   If you are interested in more technical episodes about point clouds you might enjoy these!   The Point Data Abstraction Library https://mapscaping.com/podcast/pdal-point-data-abstraction-library/   Cloud Optimized Point Clouds https://mapscaping.com/podcast/cloud-optimized-point-clouds/   Bathymetric Lidar https://mapscaping.com/podcast/bathymetric-lidar-and-blue-carbon/   Lidar from Drones https://mapscaping.com/podcast/lidar-from-drones/   Lidar from Space https://mapscaping.com/podcast/gedi-space-lasers/

Meet Peter Spencer, a Freelance Archaeologist, Surveyor, and Geomatics Specialist, as he discusses how geospatial tech is revolutionizing archaeology through laser scanning, LiDAR, ground penetrating radar, and photogrammetry. He also explains the use of AI and Earth observation data for prospecting new sites. Discover the fascinating world of geospatial archaeology!

Warning! this podcast episode is not as boring as it sounds!   While geospatial standards are boring on purpose ... this episode is not .- If you woke up this morning wanting to listen to a boring podcast episode about geospatial standards this is not for you!    Scott Simmons ( OGC’s Chief Standards Officer )  https://www.ogc.org/about/team/scott-simmons/ helps us understand what a Geopose is and how it might be used, why we need GeoRSS, and something called SensorThings!     You will also learn about the PubSub standard for the syndication of spatial data and why streaming data is not always the answer.   We also discover what the most boring geospatial standard is and when the shapefile "might" die.    All in all, this is a light-hearted look at a very serious topic and I hope you enjoy it!    What to know more about the Open Geospatial Consortium? this is a good place to start! https://mapscaping.com/podcast/the-open-geospatial-consortium/                

It sounds like a clickbait title, right? And to be fair I am trying to capture your attention but this is not clickbait in the sense that the title makes a promise that the episode lives up to!  This is not a “get-rich-quick-scheme” its a story about someone like us who is earning money by using his geospatial skills to teach others. Konrad Hafen is a hydrologist with the USGS and runs two websites and a youtube channel, he is a geospatial content creator who makes money from ads and from selling online courses.     Websites https://geospatialschool.com/ https://opensourceoptions.com/ Youtube channel https://www.youtube.com/@opensourceoptions Each episode I publish has some sort of editorial intent, the intent of this episode is to show you a real-life example of someone like us who is using their geospatial knowledge if a different way.  Not because I think this is for everyone! But because I think the more examples we are exposed to of people doing something different the more options we might see in our own lives.  We don’t have to take advantage of these opportunities but there is some comfort in knowing that they are there. That we are not stuck.   If you listen to this episode and what to learn more about making money with geospatial content, Konrad and I will host a free webinar ( if we get enough interest! )  where we teach you the basics. Sign up here https://geospatialschool.com/webinar/

Distributing Geospatial Data - Every wondered why you might what to do this? Or maybe you understand the why but are unsure about the how?  Perhaps you have heard people talk about partitioning data or sharding data, you might have heard some of these terms used in the context of enterprise-scale geospatial systems and parallel processing and thought … Wow … that sounds daunting! This podcast episode is meant to be a soft introduction to the world of distributed geospatial databases and some of the concepts surrounding them.   Along the way, you will be introduced to something called Apache Sedona which is a cluster computing system for processing large-scale spatial data, and hear the surprising stat that 97% of enterprise data remains unused! … perhaps because of the lack of context?   You can connect with Mo Sarwat on  Twitter https://twitter.com/MoSarwat Or at https://mosarwat.org/ During the conversation, we mention PostgreSQL and PostGIS a few times which are topics that we have covered in previous podcast episodes   Servicing Dynamic Vector Tiles from PostGIS https://mapscaping.com/podcast/dynamic-vector-tiles-straight-from-the-database/   An introduction to PostgreSQL https://mapscaping.com/podcast/postgresql-an-open-source-geospatial-database-for-gis-practitioners/   Spatial SQL https://mapscaping.com/podcast/spatial-sql-gis-without-the-gis/ Toward the end of the conversation, we touch on the idea of cloud-native geospatial formats, and if you are interested in understanding this concept you might find these two previous episodes helpful   Cloud Optimized Point Clouds https://mapscaping.com/podcast/cloud-optimized-point-clouds/   Cloud Native Geospatial https://mapscaping.com/podcast/cloud-native-geospatial/   If you have any questions or comments please feel free to reach out! I would love to hear from you

So you might be wondering why the United Nations World Food Programme needs a geospatial support unit. Let me give you a brief overview,    Basically, they curate and maintain global datasets that they use to model the risk of sudden-onset disasters than might lead to a food security risk. They use this model to send out early warnings to at-risk communities and help with the response when disasters happen.    Of course, there is more to it ...   But I will let Rohini Sampoornam Swaminathan ( The head of the Geospatial Support Unit at the UN World Food Programme)  explain it in more detail.   The Hunger Map https://hungermap.wfp.org/   BeforeAfterMap OSM Before-After Maps is an online tool that allows anyone to easily compare how a particular area looked in terms of OpenStreetMap (OSM) data at two different years, side by side, and get a visual insight into mapping contributions over time. https://beforeafter.baato.io/