Mapping a Missing City in Google Street View

As this blog and our book is all about GIS, data, and society, we frequently discuss what areas are mapped, and what areas are NOT mapped with specific tools. Chris The Producer recently set out to map a missing city from Google Street View. His thesis statement included: “Google Maps is one of the most insane projects humans have ever pulled off. Cars, satellites, planes, billions of photos… basically the entire planet, stitched together so you can drop a little yellow pegman guy anywhere and look around. Except for one place… North Oaks, Minnesota.”

As a part of Chris’ quest, I was happy to chat with him. What I didn’t expect is for me to get the title of “The Biggest Map Nerd in the World” in Chris’ video, which was indeed a great honor! I’m not sure if I qualify, but I was glad to be a part of this important conversation!

More importantly, I encourage you to watch Chris’ video, which is here:
https://youtu.be/gtiiHXsnsrY?si=s9cKb9BIHKGD3tsB

After you watch the video, aligned with the themes of what is included and what is left off of maps, and about location privacy, read the following line of text and then the following short entries:

As a 21st Century human, Google Maps is probably one of your most frequently used tools. I use it all the time as well! I use it, as you probably do as well, to measure hiking, biking, or driving distances, to find out what the turning intersections look like, to find local businesses, or my way across campus. I use it to plan new places to explore. I used it this month to determine what the office building looked like from the front where I would be teaching a GIS course.

As a geographer and educator, I also use Google Maps extensively. With its street and imagery basemaps, and the billions of images in its Street View (along with the trails and river views in the same tool), Google Maps and Street View is one of my all time favorite instructional tools. I use it to teach about physical regions (grasslands, lava, deserts, tropical rainforests, etc, physical processes (including climate and weather, rivers, coastal processes, and more), business types and locations, economic health and stagnation, and cultural regions and processes (language, housing type, population change, left-vs-right hand driving, urban forms, agricultural practice and crop type), and much more. I teach some of these same themes in 3D with Google Earth.

However, there are concerns with any mapping tools. Mapping has always been a value-laden enterprise, with many ethical decisions that must be made along the way (which we also discuss in this blog; search the blog for “ethics” for example). With all of this in mind, watching the above video and reading the above texts will provide many fruitful points of discussion with students and colleagues with which you interact, either in formal class settings or during informal chats. Questions you could raise could include:

  • Do you think North Oaks Minnesota had a legitimate reasons for not wanting to be covered by the Street View imagery? Do you think it had the legal right not to be covered?
  • In our book, published 2012, we noted that most of Germany had successfully blocked Google Street View up to that time. At a small scale, pull up Google Maps, set the scale so that you are looking at all of central Europe at once, and click on the Street View icon. Observe Germany. Is Germany still largely uncovered by Google Street View as we reported in 2012, or has the situation changed?
  • What countries in Europe, if any, are still largely uncovered by Google Street View images? At the time of this writing, Belarus seems notably devoid of Google Street View images. Which countries in Asia, Africa, and South America are noticeably absent in these images? Note that Australia has many Street View images, but the interior is lacking–name one reason why this might be the case.
  • What if a person wanted to blur their residence in Google Street View? See my recent essay on this topic, here: Blurring of residences in Google Street View.
  • While still in Google Street View > search and find North Oaks, Minnesota, which is the subject of Chris’ video. What is the Street View coverage there today?
  • In the video, Chris describes how he obtains a UAV license and flies a UAV in the community. With tools such as Drone2Map, SiteScan, and Pix4D, it has become fairly straightforward to bring UAV imagery into a GIS. How is do-it-yourself imagery via UAVs (Drones) becoming a key part of GIS workflows and geotechnologies? See some of our essays on this topic here. On the education side, most community college and university remote sensing/GIS programs include at least one course dedicated to UAVs, and if not, include it in their existing remote sensing courses. Even some secondary schools I work with include this type of imagery in their courses, and a few even fly their own imagery.
  • Perhaps most importantly, who decides what gets mapped?  The crowdsourcing mapping movement, of which Chris provides a good example of, involves ordinary people creating useful mapping content.  One of the earliest examples of mapping making a difference is in the Darfur situation in Chad and Sudan.  Other examples include the ones we describe in this blog, including iNaturalist, OpenStreetMap, and probably the most famous of all, when local people mapped the Kibera neighborhood in Kenya, the government began to take action to supply the community with much needed infrastructure, sanitation, schools, and much else. 

Read and reflect upon the above points and stories and consider that: Mapping is never just about putting things on a map, it is about understanding our world and making positive changes happen in our world, from the global scale to our own communities.


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I look forward to your reactions,

–Joseph Kerski

Categories: Public Domain Data

Location Privacy: Update on Blurring of Images in Ground Photographs

We have been discussing location privacy starting back in 2012 (with a “shining a torch” post here: https://spatialreserves.wordpress.com/2012/06/23/shining-a-torch-on-location-privacy/), and a discussion on big pixel images here (https://spatialreserves.wordpress.com/2019/10/13/teaching-location-privacy-and-resolution-with-a-big-pixel-image/), and more recently from an amazing set of UAV imagery off of a tower in San Francisco (https://spatialreserves.wordpress.com/2025/11/03/a-uav-produced-3d-model-of-sutro-tower-in-san-francisco/). Spanning the years of our posts on this subject, the blurring of faces from various sensor platforms has become commonplace, whether in webcams, Google Street Views, and across other platforms.

License plates, address numbers, and sometimes, even the image of a particular residence in Google Street View and in other tools are often blurred. Your location matters, and it matters to many organizations. Let’s think about other things that can be tied to your own location, starting with the “license plate list” above. Hence the concern and the built-in blurring of many of these items in commonly-used platforms has become commonplace.

But such blurring is by no means ubiquitous. Why not?

I use Google Street View frequently to teach about cultural and physical geography quite often and in my opinions it is one of the most amazing resources ever created. Its billions of photos can be used to teach and learn about language, housing type, plant species, biomes and ecoregions, coastal and glacial processes, land ownership, land use, land cover, age and income, weather and climate, and much more. In other words, much more than in turn-by-turn directions and what the building your final destination is will look like.

Returning to our location privacy discussion: Things to think about: Is your own residence blurred? Do you care if it is? Is your face blurred in webcams and other sensor platforms? How could you check? Is this issue of concern to you?

An example of a blurred residence that I found is below:

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An residence blurred in Google Street View.

One of my colleagues sent me a step-by-step guide for blurring your own residence in Google Maps, below. This can be done at the owner’s request and apparently is a permanent action that cannot be reversed (hence, caution is advised–what are the pros and cons of blurring of your own residence?).

Step-by-step guide for blurring your own residence in Google Maps: Below. Or, start directly here: https://support.google.com/maps/answer/15439776?hl=en-GB

    1    Go to Google Maps: Open Google Maps in your web browser (PC/Mac or mobile).
    2    Find your home: Search for your address and click the Street View image (the little photo icon) that appears.
    3    Report a problem: In the bottom-right corner of the Street View image, click the tiny text that says “Report a problem“. (On mobile, you might need to tap the three dots first).
    4    Adjust the blur area: Use your mouse to move the image so your house is centered in the red box. Use the + and – buttons to zoom in or out for a precise fit.
    5    Fill out the form:
    ◦    Select “My home” as the request type.
    ◦    Provide your email address (required for confirmation).
    ◦    Briefly explain the area to blur in the description box.
    6    Submit: Click Submit. Google will review the request and blur the image permanently. 

Important notes:

    •    Permanent: The blur is irreversible once applied.
    •    Owner/Tenant: Only homeowners or tenants can request a house blur.
    •    Not the app: Use a web browser, not the dedicated mobile app, for the best experience. 

I would be interested to hear your reactions about these issues.

–Joseph Kerski

Categories: Public Domain Data

SparkMap’s Data and Maps

I have been intrigued with my experiments with the SparkMap tool from the University of Missouri, and after speaking with their wonderful developer team, they graciously agreed to write the following description of their tools and data. One of my favorite tools is selecting one of the layers and easily exporting a CSV from that layer; another is the Community Demographic Mapping and Reporting tools.

SparkMap (www.sparkmap.org) is an online data tool featuring a robust Map Room and Community Needs Assessment tool. Built using Esri technologies, the SparkMap Map Room (https://sparkmap.org/map-room/) provides provides public access to over 28,000+ data layers for the USA from over 100 national secondary sources such as the U.S. Census Bureau, CDC, and Bureau of Labor Statistics. To create a map, choose a data layer (or a few!), zoom into locations of interest, and filter data down to geography levels of interest. The SparkMap Map Room is also equipped with a suite of tools to extract additional data from maps — notable examples include the Download Data Tool, the Query Data Tool, and the Vulnerable Populations Footprint Tool. The Community Needs Assessment provides much of the same information in the Map Room, in a table- and graph-based format. If you have any questions as you’re exploring the tools, the team at SparkMap is always happy to provide support and can be reached at sparkmap@missouri.org

SparkMap is supported by the University of Missouri’s Center for Applied Research and Engagement Systems (CARES). Founded in 1992, CARES has over 30 years of experience developing mapping systems to help make data accessible and actionable for public and organizational education and decision-making. Our mission is to integrate data across socio-economic, environmental, business, and health domains to support education and research across the United States.

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Capacity index and average annual temperature.

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Using the feature extraction tool.

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Using the community assessment tool.

SparkMap offers free, intro, Pro, Premium, and Enterprise subscription packages. There is also a SparkMap API!

I look forward to your reactions and salute the development team at SparkMap.

–Joseph Kerski

Categories: Public Domain Data

Sound advice on keeping your GIS data organized

My colleague Megan Engel GISP has written some very sound advice on keeping your GIS data organized, that I thought would be especially useful for the readers of this Spatial Reserves data blog, and with Megan’s permission, I am sharing it here: https://www.linkedin.com/pulse/how-i-keep-my-gis-data-mostly-organized-megan-engel-gisp-cthme/

Megan’s points include documentation and tracking and listing sources, writing something about every data set you use, even if it is just a sentence. I also like Megan’s advice, “And lastly… When it comes to data, TRUST NO ONE👻. Without proper documentation or clear metadata, you can’t assume anything about a dataset. Your map is only as reliable as the information it’s built on. Sometimes the only person who can verify it… is you.”

As this data blog makes clear, with the advent of web GIS tools, servers, and web mapping applications, increasingly, some of “your” data (“your” in quotes here because you use it, but you might not have authored or own it) is in a combination of places, such as–

  • on your own device that you use daily.
  • on your own hard drives that are near to the device you use daily.
  • on media that are increasingly difficult for you to access, but you ‘might need it someday’ such as on ancient hard drives that you bought long ago or on CD-ROM or DVD
  • on file sharing services such as Dropbox, Google Drive, Box.com, and so on.
  • attached to sharing and meeting software such as Teams and Sharepoint.
  • in your own cloud GIS storage such as ArcGIS Online.
  • in someone else’s GIS cloud storage, such as data you are consuming that others own.
  • on a server somewhere in your office or organization.
  • on a government, nonprofit, or industry hub site, library, or server.
  • on computer systems in the cloud that you rent time on such as Microsoft Planetary computer.
  • … and other places you could probably name.

Because of these many locations, being organized is more critical than ever!

I always say in the courses and workshops I teach, that GIS is a system, and is complicated enough on its own, so don’t things more difficult for yourself by not being organized.

Data Closet
Data Closet

I look forward to your reactions,

Joseph Kerski

Categories: Public Domain Data

40 Years of USGS Land Cover Data and App now Available via the ArcGIS Living Atlas

I have just been reading in the current issue of ArcNews about the new data set and app about the 40 years of USGS Land Cover data, and it is a treasure for researchers and also for instructors to look at change over space and time with their students.  As I was working as Cartographer at the USGS at the time of the original USA-wide Land Cover data compilation (hem! … in 1992!), I have had a longstanding interest in this data. It touches right at the heart of the questions, “what’s where, why is it there, and why should we care?”

The USA Annual NLCD land cover layer represents the predominant surface state within the mapping year with respect to broad categories of artificial or natural surface cover. This new 40 year time slice of annual time-enabled service of the National Land Cover Database groups land cover into 16 classes based on a modified Anderson Level II classification system. Classes include vegetation type, development density, and agricultural use. Bodies of water, permanent ice and snow, and barren lands are also identified.

Researchers could use this tool to examine change at many different scales, combining this data with data on weather and climate, zoning, ecoregions and biomes, protected land status, and more. Educators could use this tool and this data to teach about many themes, including:

  • population change
  • Urbanization and suburbanization
  • Construction of massive structures (wind farms, solar arrays, mines, reservoirs, airports)
  • Deforestation and reforestation
  • Agricultural expansion and contraction
  • Changes in rivers (width, meanders, levees, canals)
  • After-effects of hazards (tornadoes, hurricanes, floods)
  • Changes in surface water, snow, and ice from Lake Mead to Glacier National Park
  • Imagery and land cover along the US-Canada and US-Mexico border and changes detected along state boundaries
  • Change in protected (refuges, parks, wilderness areas) vs non-protected land
  • Forces acting locally, regionally, nationally, and internationally that influence these changes (economics, migration, supply and demand, and others).

    These themes could be taught in geography, environmental science, GIScience, data science, economics, and mathematics courses (see link for 65 lessons in mathematics via our book), to name a few. Because of the joint development of an easy-to-use land cover change web mapping application, these themes could be taught at multiple levels of instruction, from university even to primary school.

    To see the same article that I have been examining:

40 Years of USGS Land-Cover Data in ArcGIS Living Atlas | Winter 2026 | ArcNews

To access the app, which features imagery and land cover data, swipe capability, and graph indicating change in land cover categories in the area you are examining:

https://links.esri.com/LCExplorer

With 1 pan, 1 zoom, and 2 clicks, I was already studying urban expansion and Great Salt Lake contraction from 1985 to 2024 in Salt Lake City, Utah:

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Land Cover web mapping application.

Click on land cover classes to isolate any one of them, for example, open water, as I do below, in analyzing changes to reservoirs and rivers near North Platte, Nebraska:

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Analyzing open water changes via the web mapping application.

To access the imagery layer at 30 meter resolution, see below for extensive metadata. Land cover describes general characteristics of the Earth’s surface.  And, of course, you can use the layer in ArcGIS Online and also in ArcGIS Pro:

https://links.esri.com/LCLayer

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Land Cover data.

 There are six annual NLCD science products:

  • Spectral Change Day of Year, which shows the day of the year when a significant change in surface reflectance was detected on a map product.
  • Land Cover, which shows the physical materials on the Earth’s surface, such as forests, water, and bare soil.
  • Land Cover Change, which reveals how these physical materials have changed from one year to the next.
  • Land Cover Confidence, a measure of confidence that the land-cover label matches the training data.
  • Fractional Impervious Surface, the percentage of surface area in a 30-meter map pixel that is covered with impervious materials, such as buildings or concrete.
  • Impervious Descriptor, which distinguishes roads from other built surfaces.

Oh, this is all amazing! I look forward to your reactions,

–Joseph Kerski

Access to Imagery from SkyWatch

This data and society blog Spatial Reserves frequently discusses the rapidly changing environment in which all of us in the geospatial field discover, access, and use data. How we access imagery in a GIS environment is also rapidly transforming, resulting in spending less time searching and formatting, and more time on analysis and decision-making. As announced in 2025, Esri launched the Content Store, a web app developed by Esri and SkyWatch that simplifies the process of accessing commercial satellite imagery. SkyWatch, a geospatial platform, is “on a mission is to democratize access to Earth observation and remote sensing data.”

To learn more, start here. The Content Store is free to use but credits need to be purchased to access the imagery. Search for existing premium Earth Observation Data, using areas of interest (AOIs) or from the ArcGIS Living Atlas of the World. SkyWatch says that you can access “over 90% of commercial Earth Observation satellites with a few clicks.” After finding the imagery you need, you check out with Content Store Credits or a credit card, only paying for the data purchased. You then visualize the data within Content Store, download, and then you could publish Tiled Imagery Layers or Tile Layers via the ArcGIS Transfer App into your own, or your organization’s ArcGIS account.

The above “start here” site provides guidance on provisioning your organization in this document and details on credits you can use to purchase imagery in Content Store in this guide.

This capability touches on a trend we have noted in this blog space for quite some time – the coupling of search tools with ways of integrating the imagery seamlessly into a GIS workflow. It is truly an amazing time to be in GIS and remote sensing with these capabilities.

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I look forward to hearing from anyone using the above tools and your reaction to its ease of use.

Joseph Kerski

Categories: Public Domain Data

Cloud Optimized Data Formats: Explained in Clear and Fun Way

A new resource is very helpful for learning about Cloud Optimized data formats and sharing this information with colleagues:   https://zines.developmentseed.org/zines/cloud-native/#zine/1/  As an educator I particularly like it for its comic-magazine presentation style. I salute the Development Seed folks who put this together and know and think very highly of the authors, Kiri Carini. Through this resource, you will learn about COG, COPC, ZARR, and Geoparquet formats and how they work.

Why do these cloud optimized formats matter? As I hope our Spatial Reserves blog makes clear, data formats, data access methods, data quality, data sources, and the ways we as a community approach, work with, and teach with GIS are all simultaneously and rapidly evolving. Cloud optimized data formats allow information to be accessed and analyzed more quickly than traditional raster and vector formats, enabling sound decision making in increasingly time-sensitive environments.

As one example, a Cloud Optimized GeoTIFF (COG) is a GeoTIFF file with an internal organization that enables more efficient workflows in the cloud environment.  It does this by leveraging the ability of clients issuing ​HTTP GET range requests to ask for just the parts of a file they need.

Per https://guide.cloudnativegeo.org/, these formats offer the following advantages over traditional storage and formats:

Reduced Latency: Subsets of the raw data can be fetched and processed much faster than downloading files. Scalability: Cloud-optimized formats are usually stored on cloud object storage, which is infinitely scalable. Object storage supports many parallel read requests when combined with metadata about where different data bits are stored, making it easier to work with large datasets. Flexibility: Cloud-optimized formats allow for high levels of customization, enabling users to tailor data access to their specific needs. Additionally, advanced query capabilities provide the freedom to perform complex operations on the data without downloading and processing entire datasets. Cost-Effectiveness: Reduced data transfer and storage needs can lower costs. Many of these formats offer compression options, which reduce storage costs.

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One of the pages from this resource. Source: Development Seed.

I wish we had more of these types of graphics to explain complex topics in GIS (and in other fields) in an understandable way!

I look forward to your reactions.

–Joseph Kerski

Categories: Public Domain Data

Fascinating Data Sets and Geovisualizations at Erin D’s “Data Stuff”

Erin on https://erdavis.com/datasets/ has posted some fascinating and unusual data sets that I encourage you to investigate, for teaching, research, visualization, and to learn more about coding-with-mapping.

As a geographer who loves roads, I am particularly fond of Erin’s “road suffixes mileage” data set, and waterfalls, too (who doesn’t love waterfalls?). Erin even posted a set of intriguing visualizations about books read over the past year, which is near and dear to my heart as each New Year’s Day I post a video about the books I have read over the prior year. Erin takes this to the next level entirely!

One of my other favorites is this fall color map and dataset (below). As with other maps and data sets, Erin explains how she worked with the data to clean it, map it, and analyze it. From an instructional standpoint, especially if you are teaching coding-with-GIS courses and looking for intriguing examples, this will be particularly helpful. Erin says “almost all of my work is done in R–from data collection and analysis through visualization. I usually add in text, headers, and legends in AI/PS. I rely heavily on the tidyverse (especially ggplot and dplyr) and the sf package for mapping.”

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You could even take one of the hosted data sets, of the British Bakeoff Competition, for example, and add the places where that food or dish originated, and then map it.

More than an archive of data, Erin’s creative geo-visualizations I trust will spark some ideas of your own about how to communicate geo-information and other information graphically. If you need any help with your projects, Erin is also open to freelancing and partnering with you!

Thank you Erin! Readers, I look forward to your comments.

–Joseph Kerski

Categories: Public Domain Data

Over 3 billion records available through The Global Biodiversity Information Facility

The site https://www.arcgis.com/home/item.html?id=927944e867624504bfd6c489b0d2aec7 gives you access to the Global Biodiversity Information Facility, the world’s largest database of species observations, aggregating over 3 billion records from ~2,500 organizations, including iNaturalist, OBIS, and eBird. This Geoprocessing Tool for ArcGIS Pro (version 3.2.x and newer) queries the GBIF API and returns up to 100,000 records for a single species.

At the moment, you need to use a tool in ArcGIS Pro to access it. To do so, see the above URL, and find the data set by searching Living Atlas for “GBIF” in the Catalog Portal pane. Use the Item ID 927944e867624504bfd6c489b0d2aec7 for a more specific search. Right click the result and select Add To Project. 

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After entering a genus, species, and your study area, you can then filter by time period, and you will receive 23 fields from the data set. This joins other recent truly big data announcements (including iNaturalist, here: https://spatialreserves.wordpress.com/2024/10/14/accessing-and-using-90-million-inaturalist-crowdsourced-data-records/), in rapidly expanding the number and diversity of data on our natural world available to GIS analysts (and others).

Be sure to read the terms of use, which includes ” Under the terms of the GBIF data user agreement, users who download individual datasets or search results and use them in research or policy agree to cite them using a DOI, or Digital Object Identifier” and other important information.

I look forward to your reactions! As for me, my head is still spinning!

–Joseph Kerski

Categories: Public Domain Data

Landsat Surface Temperature Web Mapping Application and Data Now Available

This Landsat Surface Temperature Web Mapping Application and data could be very useful in physical geography, environmental science, and GIS courses in instruction, and for research purposes:

From this application, you can obtain the land or water surface temperature as of the time the Landsat image was generated for any point on the planet, generate a surface profile to look at change over time, use Landsat scenes stretching back to the 1970s, and then use additional maps and data to compare the surface temperature to the air temperature, analyzing the reasons for the differences.  The same data is available as image services in ArcGIS Online and in ArcGIS Pro, too, for further analysis.

Below I show the dynamic function and the profile function in the application. I think this touches on a trend we have highlighted in this blog recently–it is not just data that is being served these days, it is actionable information. It also touches on the increasing global scope of many data sources. It also touches on what I am calling “smart data sets”–the applications allow the user to select the most pertinent data sets for their needs right inside the application, without the need for further processing. The user could, of course, use the data in ArcGIS Pro or another GIS toolset for additional information or projections, but right away in this application, is something useful without doing so.

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I look forward to hearing your reactions.

–Joseph Kerski

Categories: Public Domain Data
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