April 16, 2012 5 comments

Welcome to the Spatial Reserves blog.

The GIS Guide to Public Domain Data was written to provide GIS practitioners and instructors with the essential skills to find, acquire, format, and analyze public domain spatial data. Some of the themes discussed in the book include open data access and spatial law, the importance of metadata, the fee vs. free debate, data and national security, the efficacy of spatial data infrastructures, the impact of cloud computing and the emergence of the GIS-as-a-Service (GaaS) business model. Recent technological innovations have radically altered how both data users and data providers work with spatial information to help address a diverse range of social, economic and environmental issues.

This blog was established to follow up on some of these themes, promote a discussion of the issues raised, and host a copy of the exercises that accompany the book.  This story map provides a brief description of the exercises.


Teaching about spatial data quality

July 26, 2020 2 comments

It is important to be critical of data, including, and perhaps especially, spatial data. I frequently receive inquiries from professors seeking resources on the best resources to teach about data quality and foster related discussions with students. Here is one of my recent responses to such an inquiry.

  1. If you need a fun and engaging set of maps and discussion, use my presentation on Good Maps, Bad Maps, and why it all matters: https://sway.office.com/HqKUCu2ib60rkijh?ref=Link. Scroll down to 30% of the way down in this presentation, in the “Maps Tend to Believed” section.  Here you will see a whole set of BAD MAPS. They are misleading, erroneous, or just plain bad for many different reasons – the projection is unsuitable, the data is questionable or impossible (for example, I know it gets hot in Texas but there is a temperature reading from a data feed that is over 3,000 degrees as one example), the legend is misleading, places are blatantly shown in the wrong location, or some other reason.
  2. A short reading on the above topic, why data quality still matters now more than ever:  https://spatialreserves.wordpress.com/2017/12/04/why-data-quality-still-matters-now-more-than-ever/
  3. More food for thought, presented as the “best available data” “BAD data”:  https://spatialreserves.wordpress.com/2017/08/14/best-available-data-bad-data/
  4. A guide for deciding which data will be useful for your needs:  https://spatialreserves.wordpress.com/2018/11/26/a-graphical-aid-in-deciding-whether-geospatial-data-can-be-used/
  5. An essay reflecting on the 30 checks for data errors:  https://spatialreserves.wordpress.com/2015/03/22/gis-gigo-garbage-in-garbage-out-30-checks-for-data-errors/

I hope these resources will be useful to many!

Data quality is a major theme of this blog.

–Joseph Kerski

Categories: Public Domain Data Tags:

Ordnance Survey’s new data hub and APIs

July 20, 2020 Leave a comment

Ordnance Survey, Great Britain’s national mapping agency, recently launched a new OS Data Hub, replacing their existing online data portals.

Screenshot 2020-07-17 10.33.24.png

OS Data Hub

In addition to providing up to £1,000 per month of free access some datasets, including 1:25 000 leisure mapping and road network data, through a series of new APIs, the new hub will also provide free access (up to a monthly threshold) to their flagship 1:1250 MasterMap product. 

The new APIs include:

  • OS Maps API: Integrating OS mapping into apps and websites (includes OS MasterMap Topography Layer and 1:25 000 Scale colour raster data)
  • OS Vector Tile API: Fully customisable vector maps 
  • OS Features API: Numerous layer of OS MasterMap data layers including greenspace, highways network, topography and water network.
  • OS Names API: Look-up service including place names, postcodes and roads.
  • OS Linked Identifiers API: Linking properties, streets and OS MasterMap features.

The release of these new APIs and the data hub are part of a wider objective, outlined in the UK’s Geospatial Strategy, to create a national location data framework by 2025.




Be Critical of the Data: Imagery too!

As we have written about many times in this blog and in our book, being a critical consumer of data is essential for successful, wise decision making in the modern world.  Geospatial data offers a vast array of capabilities, but also offers numerous examples of discrepancies that often are found only through paying attention to details.  Even imagery is not immune to offsets and discrepancies, as we have detailed here and here.  The following represents another example of why this all matters.

A colleague of mine was working on a project outside of the town of Redcliff, in western Colorado USA.   In the first image, the red point on the older World Imagery (Esri Clarity) layer is at the corner of the house, and its coordinates (in WGS84) were calculated on that image.  In the second image, the white point at the corner of the house is on the current Esri World Imagery layer, and the coordinates (in WGS84) that were calculated based on that image.


Below are the same points on Google Earth. They match up pretty well with the World Imagery (Clarity) imagery.


Further investigating the extent of what seems to be an offset between the two image layers are three screen captures below in the Paonia, Colorado area. These show a Delta County local road crossing the North Fork Gunnison River.   The map is cast in NAD83 UTM Zone 13.  The roads shapefile is from the Colorado Department of Transportation, Delta County Local and Major Roads (2019), and also in NAD83 UTM13.  The intersection point shows WGS1984 Lat-Long coordinates.   The two Esri World Imagery layers are both in WGS_1984_Web_Mercator_Auxiliary_Sphere.   The latest USDA NAIP (2019) is in NAD83 UTM13.   The World Imagery (Clarity) basemap and the NAIP both line up well with the Colorado DOT roads shapefile. The Esri World Imagery basemap does not.


After reading these notes from my colleague, I spent some time looking at this, and then, along the lines of “being critical of the data” I did some of my own investigating.  I drew the yellow line in ArcGIS Online on the image along the bridge following the Clarity layer, and a cream-colored line along the bridge following the base imagery layer, noting that about a 12 meter offset exists, largely along a north-south axis, here.  But, I panned to other locations in Colorado and outside Colorado and found no offset.


I relayed this to my Esri colleagues who upon investigation, told me that this is not a projection issue, but likely a shift introduced in Maxar’s orthorectification process (related to ground control or DEM or both).   They told me that they will be publishing CONUS wide updates over the next several months which should resolve this particular localized shift.   Hence, repeat my above experiment whenever you happen to be reading this essay, and you may find different (and hopefully better) results!

I think at least five take-away points are important here (feel free to add more in the comments section).

(1)  GIS and remote sensing tools and data are continually evolving particularly in our data-as-services world.

(2)  Sometimes a wealth of information can be obtained by asking questions of the data and services providers.  Sometimes they can even hasten changes that need to be made.

(3)  The user needs to determine “fitness for use” regarding the spatial accuracy, completeness, date, and other characteristics for their project:  The project’s needs determine whether the data under consideration will be useful.  In the above example, if you were laying water or gas pipe or conducting land surveying for the assessor’s department, the above offsets would likely require you to use the Clarity layer or seek another source.  But if you are assessing regional or even local land use patterns, either layer would likely be just fine.

(4) Be critical of the data.   Be curious and ask questions.

(5)  Pay attention to detail.  Investigate.

–Joseph Kerski

Categories: Public Domain Data Tags: ,

Best practice guidance and tools for geospatial data managers and onwards to 2025…

Following on from their search engine optimisation recommendations for data publishing, the UK Government Cabinet Office and Geospatial Commission have combined forces to produce a comprehensive set of best practice guides and tools for geospatial data managers. Included in the set are:

Also recently published by the Geospatial Commission is the UK’s geospatial strategy 2020 to 2025 – Unlocking the power of location. The report identifies four critical mission objectives and nine opportunities to pursue with the end goal of a  ‘coherent national location data framework‘ by 2025. Highlighted in the report is the importance of open data sources/formats and collaboration with organisations such as the Open Geospatial Consortium, as key components for meeting those objectives.


Earth Surveillance Tech changing everything, including us?

A recent article claiming that new Earth surveillance technology is about to change everything, including us, merits a review because it touches on many themes common to our book and this blog.  First, as one of the themes of this blog is to foster a critical view of data, recognizing its utility but also recognizing its limitations, I encourage you as I did to investigate the source of any piece of information you find, in this case, Vice.com, the platform where this article is hosted.  Vice content is shown on their website, through their news division, a creative agency called Virtue, and their history from 1994 to today.  I was glad to discover that the author of this article, Becky Ferreira, focuses on technology and science.

In this article, Becky begins with the Earthrise photo taken on 24 December 1968 from Apollo 8, which I also have found so intriguing that I included it and its impact in a chapter of its own in my book Interpreting the World as one of the 100 most revolutionary discoveries in geography.   Becky then asks how we will deal with the subsequent deluge of information that we have about Planet Earth that began (in some ways) with that day in 1968.  The author discusses initiatives that I was not aware of, such as ICARUS, that monitors animal populations from instruments aboard the International Space Station, along with initiatives we have discussed in this blog, such as CIESIN, crowdsourcing such as after the 2010 Haiti earthquake, ethics in geospatial technology, sensitivity regarding locations shown on maps and imagery, crowdsourcing initiatives such as OpenStreetMap, and more recently, dashboards for the COVID-19 outbreak.

The Earth surveillance article I mention above in my view is an interesting summary of some technological and societal aspects of geospatial technology, though I wish it provided a look into the future, perhaps accompanied by interviews with some leaders in the field.  Perhaps the author ran out of space for this and so I look forward to future installments.  I also was hoping the article would discuss more location privacy issues, as the title indicated.  I also am intrigued by the notion of how geospatial technologies are changing us as people, a topic that we will continue in this blog and that I encourage others to explore.  And while change-behavior topics such how we navigate with phones vs. paper maps and the spatial cognition part of the brains of London taxi drivers have been interesting in the past, in the future I would like to see analyses examining those initiatives where geotechnology is specifically applied to do something good for people and the planet:   Hundreds of such initiatives have existed, from Ushahidi crowdsourcing in Haiti, to OpenStreetMap, to Mapillary’s street views, to monitoring trash or invasive species or water quality.  What were the benefits?  What were the costs?  What difference did these initiatives make?

–Joseph Kerski

Earth Surveillance Tech changing everything–including us?

Testing positional accuracy underwater, revisited

June 14, 2020 1 comment

I had the opportunity to test positional accuracy while underwater.  Amazingly, I did not even have to get wet!  While I was doing some GIS work with the excellent faculty at the University of Hamburg, I walked through the St. Pauli Elbe Tunnel while collecting a track.  As I did so, I reflected on the fascinating cultural and physical geography of this 1911 engineering masterpiece that is still in use:  The tunnel is 426 m (1,398 ft) long; it was a technical sensation when constructed; photos at the entrance show Kaiser Wilhelm II dedicating it.  It connected central Hamburg on the north side of the river with the docks and shipyards on the south side of the River Elbe.  The most amazing part was the four massive elevators, capable of carrying bikes and whole vehicles, and of course, 100 years ago, carriages and horses.  These elevators and tunnel are still functional and being used today!  For more information on this experiment, see my new video on the Our Earth channel here.

While pondering these thoughts, I collected a track in the Runkeeper app, and mapped it as a GPX file in ArcGIS Online as a 2D webmap and as a shapefile in a 3D scene.  I wanted to test how spatially accurate a track underwater would be, in the x and y dimensions, but also in the z dimension.  First, let’s consider the x and y:  As I walked through the tunnel 24 m (80 ft) beneath the surface through one of the two 6 m (20 ft) diameter tubes, I expected the my app to lose sight of the GPS, Wi-Fi, and cell phone towers, but I did not know how far off my position would be.   My recent experiments on an above-ground track gave me a ray of hope that perhaps my position would be recorded as somewhere in Germany rather than in the North Sea or the Atlantic Ocean.

I was told by a local source who said that the tunnels are 8 m below the bottom of the river, and the depth of the river is 8 m here as well (this depth here allowed Hamburg to become of the largest container ports in the world).  Thus, above me was about 4 meters of airspace, 8 meters of sediment (glacial, in this area), and 8 meters of water for a total of 20 meters above me.  The elevation at the water surface here is approximately 5 m above sea level.  Thus, my elevation in the tunnel should be 5 – 20 = -15 meters.

My results as a 2D webmap and as a 3D scene are shown below.  As is evident, the recorded elevations are all above sea level, at around 4 meters, so they were 15+4=19 meters off of my actual elevation in the tunnel.

hamburg1A 2D map in ArcGIS Online showing the results of my experiment, with elevations in meters above sea level shown as labels. 

Feel free to open and interact with the data!  For example, to test the X and Y:  Using the measure tool, measure the distance between the tunnel as shown on the OpenStreetMap basemap and the position recorded by my track.  As I left the train station on the north side, my position was fairly accurately recorded, but once I descended the stairs into the tunnel, my position was off to the east by about 140 meters, and then shifted to the west and was off by about 240 meters.  But as I continued walking south, for the last 1/3 of my trek through the tunnel, my XY positional accuracy was only off by 50 meters.   I ascended the stairs and circled the parking lot on the south side, and was only 1 to 2 meters off once more.  I descended into the tunnel and walked north.  This time, my position was about 100 meters off, becoming worse as I kept walking.  My position overcorrected 80 meters to the north as I ascended the stairs, and “settled back” to being a few meters off as I walked to the train station.

To test the Z position:  The elevations were, as I suspected, not displaying their correct number below sea level; that is, 15 meters below sea level. However, you can see that the elevations are actually quite close to the elevation of the surface of the river in this area; at about 4.5 meters.

hamburg2A 3D scene in ArcGIS Online showing the results of my experiment, with elevations in meters above sea level shown as labels and symbolized as cylinders.   Feel free to open and interact with this 3D scene!

Overall, with only a smartphone and a fitness app, displaying the data in ArcGIS Online, I was rather pleased with the fact that my positions all around were usually only in the tens or a few dozen meters off of true. This aligns with my recent reports of above-ground experiments and is further evidence of the improvements in spatial accuracy with all location based services.

Interested in further exploration?  See the evidence of my field trip in the photographs below.


The Elbe River as it appears near the tunnel.


Part of the enormous container port on the south bank of the Elbe.

hamburg3The very large elevators that carry pedestrians, bicycles, and even vehicles from the street level to the level of the tunnels.  This one is at the north side of the river with a photo of the opening ceremony with Kaiser Wilhelm II dedicating it.


Standing at the entrance to the tunnel; this photo also shows a few of the glazed terra cotta art sculptures on the left, and in the distance on the right.

Now, go conduct your own accuracy experiments!

–Joseph Kerski

Be critical of the data even in a time of crisis

May 31, 2020 2 comments

The article that recently appeared about the discrepancies in COVID-19 cases and tests fits squarely into the theme of our book and this blog.  I invite you to read or skim the article, but just in case the article is no longer available by the time you read this essay, or you would just like a synopsis, it is essentially about this:   Some discrepancies about the same data on the same date existed between two data sources.   To the readers of this blog and to users of GIS, this is not unexpected: The geospatial data community is trained to examine multiple sources when mapping and making decisions, and collectively, the community has probably encountered this same situation on a weekly if not a daily basis.

Why did the situation in the recent article merit attention?  In this case, it was about COVID-19 cases and testing, already a topic intertwined with many emotions, and for good reason.  But another reason is that high ranking government officials were quoting one website, Worldometer, and other sources were quoting and using Johns Hopkins University’s site, and others.  Why were there differences in the data among the sites?

I have used sites like Worldometer that contain little metadata at times for teaching purposes, but obviously with caution.  Worldometer’s population “clock” or “gauge” style of presenting data on world population, for example, makes for compelling teaching, as the population ticks up by several people every second, lending a sense of urgency that can frame discussions about the need for effective planning for agriculture, transportation, water, energy, and other aspects of society.  But again, I always use these sites with a wary eye.

The difficulty of discovering how the Worldometer COVID-19 data was derived is the focus of this article.  The article’s “sleuthing” style, even going so far to determine the author(s) of the organization behind the data sites, makes for, in my view, interesting and important reading for students or anyone who is working in GIS or data science.

My key takeaways from this story are:  (1) As we rely increasingly on real-time and near-real time data feeds, whether about health, or flood stage, or wildfire perimeters, or any other data that is used to make daily decisions, and (2) as the data is increasingly being shared and reported on almost instantly to millions of people, it is more important than ever to understand the source, scale, date, attributes, and other characteristics of the data.

Perhaps the title of this essay needs to be changed from “Be critical of the data even at a time of crisis” to “Be critical of the data especially at a time of crisis”.  But I would take it a step farther:  “Be critical of the data even when there is no crisis!”

–Joseph Kerski

10 New ArcGIS Pro Lesson Activities, Learn Paths, and Migration Reflections

May 14, 2020 5 comments

A new set of 10 ArcGIS Pro lessons empowers GIS practitioners, instructors, and students with essential skills to find, acquire, format, and analyze public domain spatial data to make decisions.  Described in this video, this set was created for 3 reasons:  (1) to provide a set of analytical lessons that can be immediately used, (2) to update the original 10 lessons created by my colleague Jill Clark and I to provide a practical component to our Esri Press book The GIS Guide to Public Domain Dataand (3) to demonstrate how ArcGIS Desktop (ArcMap) lessons can be converted to Pro and to reflect upon that process.  The activities can be found here.  This essay is mirrored on the Esri GeoNet education blog and the reflections are below and in this video.

Summary of Lessons:

  • Can be used in full, in part, or modified to suit your own needs.
  • 10 lessons.
  • 64 work packages.  A “work package” is a set of tasks focused on solving a specific problem.
  • 370 guided steps.
  • 29 to 42 hours of hands-on immersion.
  • Over 600 pages of content.
  • 100 skills are fostered, covering GIS tools and methods, working with data, and communication.
  • 40 data sources are used, covering 85 different data layers.
  • Themes covered: climate, business, population, fire, floods, hurricanes, land use, sustainability, ecotourism, invasive species, oil spills, volcanoes, earthquakes, agriculture.
  • Areas covered:  The Globe, and also:  Brazil, New Zealand, the Great Lakes of the USA, Canada, the Gulf of Mexico, Iceland, the Caribbean Sea, Kenya, Orange County California, Nebraska, Colorado, and Texas USA.
  • Aimed at university-level graduate and university or community college undergraduate student.  Some GIS experience is very helpful, though not absolutely required.  Still, my advice is not to use these lessons for students’ first exposure to GIS, but rather, in an intermediate or advanced setting.

Why use these lessons?  The lessons offer 8 unique advantages:  (1)  The lessons engage students by focusing on the geographic inquiry processbeginning with the problem to be solved, such as the optimal site for siting a new business in a metropolitan area, the rate and pattern of the spread of an invasive species, the ideal locations for growing tea in Kenya, assessing reservoir and dam vulnerability in the event of a hurricane, and more.

(2)  While those working through the lessons build solid GIS skills (building expressions, joining data layers, intersecting, projecting, georegistering imagery), skills are not limited to “learning more GIS.  Skills in data management and communication are a prominent part of these lessons.  At the end of each lesson, students are asked to communicate the results of their research in a variety of ways, including sharing to ArcGIS Online, making a short video, and creating a web mapping application such as a story map.

(3) A significant proportion of each lesson touch on accessing, formatting, projecting; i.e. developing data competencies.  Helping people make wise decisions about the data, and giving them practical skills in doing so, is one of our chief goals with these lessons and the book.  A balance is struck between engaging with enough data to provide a realistic scenario, but recognizing that “more is not always better.”

(4)  The same lesson is available in an ArcGIS Desktop (ArcMap) format and an ArcGIS Pro format, so that those still hesitating about migrating from ArcGIS Desktop to ArcGIS Pro can use these as an example that it is not only possible, but there are many advantages to doing so.

(5)  Questions posed in each lesson focus on thoughtful reflection about the data and the process, such as, “what difference would data at a different scale have on your analysis results?”, “what was the most significant thing you learned about natural hazards in this lesson?” and “if you had more time, what data set might you have also wanted to include in your analysis?  Where do you think you could obtain such data?”

(6) These lessons have been tested and refined over several terms with students across many universities.

(7) An answer key is available for each lesson.   But in keeping with the reflective nature of these lessons, often, there is no “single correct answer.”

(8)  A lesson on building an ecotourism map in New Zealand allows students to use their gained skills in an independent project where they decide what themes to choose, what data to use, how to process it, and what problems to solve.

How to access the lessons:   The ideal way to work through the lessons is in a Learn Path which bundle the readings of the book’s chapters, selected blog essays, and the hands-on activities..  The Learn Path is split into 3 parts, as follows:

Solving Problems with GIS and public domain geospatial data 1 of 3:  Learn how to find, evaluate, and analyze data to solve location-based problems through this set of 10 chapters and short essay readings, and 10 hands-on lessons:  https://learn.arcgis.com/en/paths/the-gis-guide-to-public-domain-data-learn-path/

Solving Problems with GIS and public domain geospatial data 2 of 3:   https://learn.arcgis.com/en/paths/the-gis-guide-to-public-domain-data-learn-path-2/

Solving Problems with GIS and public domain geospatial data 3 of 3:   https://learn.arcgis.com/en/paths/the-gis-guide-to-public-domain-data-learn-path-3/

The Learn Paths allow for content to be worked through in sequence, as shown below:



Sample Learn Path for the public domain data activities.

You can also access the lessons by accessing this gallery in ArcGIS Online, shown below.  If you would like to modify the lessons for your own use, feel free!  This is why the lessons have been provided in a zipped bundle as PDF files here and as MS Word DOCX files here.    This video provides an overview.


Appearance of content items in the public domain data activities and reading gallery.  The gallery includes lessons, data, readings, and the answer keys. 

While the intent is for learners to actually download or stream the data from the original sources as an important part of the learning experience, the data for each lesson in zip file format are also included, in this ArcGIS Online gallery.  The reason the data is provided is because we recognize that sometimes, bandwidth is limited and/or the data portals are slow, change, or are temporarily offline.

Titles of the 10 Lessons:   See below.  For more information, see the detailed metadata for the lessons here.
Lesson 1: Assessing impacts of climate change on coasts, ecoregions, and population globally.
Lesson 2: Siting an internet café in Orange County, California.
Lesson 3: Siting a fire tower in the Loess Hills, Nebraska.
Lesson 4: Analyzing floods and floodplains along the Front Range, Colorado.
Lesson 5: Assessing potential hurricane hazards in Texas.
Lesson 6: Analyzing land use and sustainability in Brazil.
Lesson 7: Creating a map for an ecotourism company in New Zealand.

Lesson 8: Assessing citizen science portals and analyzing data about invasive species.
Lesson 9: Investigating 3 hazards: Gulf oil spill, Eyjafjallajokull volcano, and Haiti earthquake.
Lesson 10: Selecting the most suitable locations for tea cultivation in Kenya.

The intent of the lessons was that they were to be used in conjunction with reading the book.  Therefore, the contents of the book have also been placed online.  The book chapters are in this gallery. The book not only discusses sources and types of spatial data, but also issues such as assessing data quality, open data access, spatial law, the fee vs. free debate, data and national security, the efficacy of spatial data infrastructures, and the impact of cloud computing and the emergence of GIS as a Software-as-a-Service (SaaS) model.

Since the book was published, ongoing social and technological innovations and issues continue to change how data users and data providers work with geospatial information to help address a diverse range of social, economic and environmental needs.  Therefore, we established the Spatial Reserves blog to promote a current, ongoing dialogue with data users and providers and post frequent assessments of new tools, data portals, books and articles, curriculum, and issues surrounding spatial data.  Recent entries include “Imagery–It is what it is–well, not always.”, “Be a wise consumer of fun posts, too“, “The Application for Extracting and Exploring Analysis Ready Samples (AppEEARS)”, reflections on a new article about the geospatial data fabricfacial recognition technology, and a list of the top 12 sites for Landsat data.  A selection of these blog essays are listed in the book’s resources page at Esri Press.

Reflections on Migrating Lessons from ArcMap to ArcGIS Pro.  Readers of this blog and the GeoNet education blog are familiar with the rapid change of the field of geospatial technologies, coupled with rapidly changing educational and workplace needs.  I contend that given these changes, the content and skills we must teach, and the means by which we teach, must also change.  Given the wide variety of tutorials and help files containing graphics and videos, networks and the tools to collaborate, ask questions, and share ideas, students, faculty, and GIS professionals have an amazing variety of learning options at their fingertips.

Thus, I do not believe we need to be focused on tool-based approaches, such as how to geocode, how to georegister, and so on, but rather, how to solve problems using GIS.  (For a related discussion, see David DiBiase’s Stop Teaching GIS essay).  We need to help students “learn how to learn” whether in GIS (and, I contend, in any other field), emulating the kind of resource gathering, networking, and problem solving that they will assuredly use in the workplace.  Some might argue that writing and asking students to go through lessons such as the 10 I describe above is no longer needed.  In my experience in teaching for over 25 years at the university level, I still find that this style of lesson still has a place in learning, as students using these go through an entire workflow of geographic inquiry, including asking geographic questions, gathering data, analyzing data, making decisions, making assessments, and communicating the results of their research.  Another reason why I created the above lessons is so that you can place each lesson side-by-side to compare the ArcMap version and the ArcGIS Pro version.

My observations after creating ArcGIS Pro versions of each of the ArcMap lessons are as follows:

  1. I have used these lessons in several different universities, including at the University of Denver, and always pose a survey question about ArcGIS Pro at the end of the course.  In 95% of the responses, students have stated that they found ArcGIS Pro to be easier to learn from than ArcMap, more intuitive, and more powerful.  Several students each term tell me that the use of Pro was one of their primary reasons for taking the course, because their employer asked them to learn it.  And moving forward into the 2020s, Pro will see further adoption and more importantly, further evolution. Every time it evolves, it becomes more powerful and easier to use at the same time.
  2. As an instructor, you have a choice of either creating your own lessons or using existing lessons.  There are no shortage of existing lessons, ranging from the ArcGIS Learn library to shared higher education resources (such as GeoTech Center and iGETT), Esri and university MOOCs, and many other resources.  Many of us, however, became instructors because we enjoy creating and customizing curriculum for specific courses and programs.  If you are keen on migrating some of your existing ArcMap lessons to ArcGIS Pro, I did it, and so can you.  Yes, it will take some time, but I find migrations (migrations is plural here, as I have lived through many such software migrations!) are like when you get rid of things while moving your own residence–it is a good opportunity to purge old content and make things even better.  Perhaps you can get a graduate student to assist you in this effort!
  3. I found that my ArcGIS Pro lessons were shorter than the ArcMap lessons for several reasons.  The first reason is that the workflows in ArcGIS Pro are so much more logical and straightforward than in ArcMap.  In ArcMap, for example, when you needed to georegister an unprojected historical map or aerial photo, you are cast into a zone that sometimes left students wondering, “what step do I do first?” whereas with ArcGIS Pro, you are placed into wizard-driven “Step 1–do this, make these choices, satisfied?  If not, here are some adjustments you can make.  OK – on to Step 2…”  Ditto for hundreds of other tools and processes:  These are much easier to follow and learn from using ArcGIS Pro. The second reason is you don’t need to screen shot everything any longer, and in fact, I implore you to please not screen shot very much, because (1) There are many good existing resources for use if a student gets stuck on a certain section.  In the past, I admit that all of us did have to create our own graphics and screenshots because these were by and large all the students could use as instructional resources, but no longer!  (2) Students, being the resourceful people they are, will not read your precious screen shots very much if at all.  They know there are other resources and will find them if they have difficulty.  Of course you can provide guidance as to where these resources are, but just like anything else these days that people want to learn, such as fixing a faucet or playing the ukulele, there is a video, a graphic, a tutorial, on everything from geocoding to writing Arcade expressions and more.  (3) If you do screen shot to excess and make your lessons consequently long, you will remain in a continuous cycle of having to update and curate your lessons.  Please, don’t do this!  Rather, spend less time updating curriculum, and that new-found time creating new curricular ideas, teaching techniques, and furthering your own research.

Metadata for Public Domain Data Lessons

Metadata for Public Domain Data lessons.  I look forward to your comments below.

–Joseph Kerski

City and County of Denver ArcGIS Online hosted feature services now available from open data catalog

May 3, 2020 5 comments

The City and County of Denver have long been a leader in providing a wide variety of useful geospatial data.  When I was working as a geographer at the US Census Bureau, I remember they were one of the few local governments actively maintaining their GBF/DIME file, even before TIGER existed!  They continue to be innovative today, as evidenced in this recent announcement:  “All publicly available GIS layers from the Denver Open Data Catalog are now accessible as Hosted Feature Services in ArcGIS Online via REST Endpoints. These layers are classified as authoritative organization data. Dynamic layers are updated nightly and all others as needed.”

Each layer is provided in multiple formats, and there are multiple ways to access and find these layers, as follows:

  1. Start with the open data catalog and choose the format you desire–shapefile, geodatabase, dwg, csv, or REST endpoint.  The first formats will allow you to download the data to your device and add it to your GIS; the latter format will allow you to directly stream in the data to your GIS.   This blog essay will focus on the latter.
  2. Search for content directly in a web map inside ArcGIS Online:   Search ArcGIS online for “Denver” with any word after that, making sure to filter by what is authoritative and provided by “geospatialDenver” as the owner.


3.  In ArcGIS Online, search the Open Data Catalog group for content, as shown below:



4.  To your existing content in ArcGIS Online, use the Add Data tool, and use a REST Endpoint URL from the Open Data Catalog:  https://www.denvergov.org/opendata




I salute the good folks at the City and County of Denver for making this happen and I encourage other local government agencies to consider doing something similar.

–Joseph Kerski

Top 7 Satellite Imagery Sources

April 19, 2020 4 comments

My colleagues at EOS.com recently wrote a summary of what they consider to be the top 7 satellite imagery sources:  https://eos.com/blog/7-top-free-satellite-imagery-sources-in-2019/.

These include sources that we have reviewed on this Spatial Reserves blog, here:  https://spatialreserves.wordpress.com/2019/02/18/the-top-10-most-useful-geospatial-data-portals-revisited/   as well as the top Landsat sites that we reviewed, here:  https://spatialreserves.wordpress.com/2019/08/04/the-top-10-landsat-image-sites/, but it also includes a few we have not reviewed, such as EOS’ own Landviewer.

It is good to see reviewed collections such as these that have an aim to make life a bit easier for us as data consumers and analysts.


Landviewer data portal, from EOS.  

–Joseph Kerski