Government removes hurdles for mapping and serving of geospatial data in India

A recent essay describes the announcement by the government of India to remove hurdles for mapping and serving of geospatial data in India. Firms can now acquire, collect, generate, disseminate, store, share, distribute and create geospatial data with fewer regulations and approvals, though certainly some will exist especially surrounding sensitive information. The fact that many sectors of society can benefit from geospatial technologies–from agriculture to finance and construction–formed some of the chief arguments used to support this development. The Department of Science and Technology was behind the announcement, according to this post in Geospatial World.

We have always focused on practical applications of using geospatial data in our book and in this blog, and, in keeping with our theme of “being critical of the data”, we have described numerous instances where a bold proclamation has been made and the impact on the data user has been minimal. I truly hope that is not the case here. I hope that at long last, geospatial data for India will be much more open than it was in the past. The GIS community will have to wait and see if the above announcement translates into eventual standing up of geospatial data portals. And certainly, once restrictions are lifted, it will take awhile–possibly several years, for data to be acquired and served. We have written about similar developments elsewhere in the world (in Europe, for example) on numerous occasions. But no matter what happens, the above announcement is a welcome addition to the gradual loosening of restrictions around GIS data acquisition around the globe,

Joseph Kerski

Categories: Public Domain Data

Creative Commons data licensing : 2021 – 2025

February 22, 2021 Leave a comment

Among the main themes in The GIS Guide to Public Domain Data were the issues of copyright, publicly available data versus public domain data, and the range of licensing arrangements available to data publishers.

Public Domain Mark

Public Domain Mark

Our review of the Creative Commons (CC) licensing options in 2012 concluded that although the CC licenses were becoming increasingly popular for geospatial data, the various license categories were never intended for combined geospatial data stores and the volumes of derived data generated from those stores. Many geospatial data publishers opted for the copyright protections provided under such arrangements as the Open Database Licence from the Open Knowledge Foundation or the Open Government Licence (OGL) in the UK.

In December 2020 CC announced a new strategy for 2021 – 2025, with the primary emphasis on better, rather than just simply more, knowledge sharing, and a comprehensive approach to open sharing. CC has recognised the need to consider economical and ethical issues in addition to the existing copyright licensing arrangements.

Although the new strategy is based on a sector-by-sector analysis of content sharing requirements, there’s no specific mention of support for geospatial data publishers and the diverse, integrated data sources they manage. In the absence of tailored licensing arrangements for geospatial data, it’s hard to see at present the new strategy significantly changing how geospatial data publishers license their data.




Updates to Fire Tower Siting Activity

February 15, 2021 Leave a comment

GIS is in a state of unending change and improvement, and any activity or lesson based on such a dynamic technology must also change. I have just updated and improved the fire tower siting activity, and its new location is in the same location as where the other 9 lessons in the collection are located, here.

In this lesson, you will download and use raster and vector spatial data to decide where to site a wildfire observation tower in the Loess Hills near Blair, Nebraska (one of my favorite landscapes). The public domain data used in this lesson include USGS digital line graph roads and hydrography data, and State of Nebraska land cover and elevation.

This is one of my favorite lessons, in part because you use the raster calculator to create slope and aspect maps, you use proximity and other vector and raster analysis tools, and make real decisions using real-world data. I invite you to dig into it.

The lesson is broken down into the following “work packages”:

Work Package 1: Downloading and converting data. Steps 1-9. 
Work Package 2: Viewing and manipulating data. Steps 10-20. 
Work Package 3: Downloading and using elevation and land cover data. Steps 21-33. 
Work Package 4: Working further with the elevation data. Steps 34-37. 
Work Package 5: Converting raster land cover data to vector. Steps 38-46. 
Work Package 6: Further and final analysis. Steps 47-51. 
Work Package 7: Reflection and next steps. Steps 52-54.

Page 1 of the fire tower lesson.

As a reminder, the goal of the 10 lessons in this collection are to work with public domain data of a wide variety of themes and scales, grapple with data portals, and use the data with a logical set of steps and making rigorous use of analysis tools to make key decisions.

I look forward to hearing your reactions, below.

–Joseph Kerski

Categories: Public Domain Data

How much data is out there?

February 1, 2021 4 comments

As this blog is all about data, and about the advent of the truly “Big Data” world, exactly how much data are we talking about? Below is one source of information about how much data actually exists today and how much is projected to exist in the near future.

How much data exists and is projected to exist?

Aydin, O. (2021). Spatial Data Science: Transforming Our Planet [Conference presentation]. 2021 Los Angeles Geospatial Summit, Los Angeles, CA, United States.

Because our blog and book is also about encouraging people to check data sources, I would like to add that the above information came from the following: Seagate’s annual data report: There is an abridged version in this article from Forbes:

These figures are staggering, and from these figures spring many questions: How much of the above data is geospatial data? How much is not geospatial yet, but is potentially mappable? Which data should be mapped? Take a look at the small percentage, say, of tweets that are geotagged. Should more be geotagged? What would we gain by doing so?

More importantly: What will we do with all this data? Will we be able to sort out the important from the trivial to continue to advance society in health, safety, and sustainability? How must geotechnologies evolve to remain viable in the big data world? I look forward to your comments below.

–Joseph Kerski

Urbanization and human settlement data on the UN-HABITAT Open Data Portal

January 18, 2021 Leave a comment

The UN-HABITAT OPEN DATA portal,, is an interesting and useful way to obtain data on urbanization and human settlement.  UN-Habitat, the United Nations Human Settlements Programme, is mandated by the UN General Assembly to promote socially and environmentally sustainable towns and cities. It is the focal point for all urbanization and human settlement matters within the UN System. The creation of sustainable human settlements requires the provision and application of accurate, up to date, timely and reliable data.

The portal’s Compilation of Urban Indicators Data allows the user to explore by SDG Goals, by specific themes such as land and environment, quality of life, governance, and others.  You can also explore all data in the library.

Because the site uses ArcGIS Hub technology, the site is responsive, and you can easily search for data of interest. You can also search for type of document, such as web mapping application or dashboard. I used the site to search for land cover data and was pleased at the variety (scales, locations) and volume of results. At the time of this writing, 132 countries, 77 indicators, and 1500 urban areas are covered in the portal. The chief challenge with this and similar sites is to effectively narrow what you are seeking.

The UN HABITAT open data portal.

–Joseph Kerski

Got UAS (Drone) Data?

January 4, 2021 4 comments

This guest essay was authored by Dr Wing Cheung, Palomar College, California USA. Thank you Dr Cheung for writing this!

The obvious way to get UAS (Unmanned Aircraft Systems) or drone data is to collect it yourself, but this may not be a viable option for everyone due to legal, liability, or resource limitations. And even for those with access to a drone, they may not have access to all the fancy sensors (e.g. near infrared, thermal infrared, LiDAR) that are needed to collect the data that may want to experiment with for their particular use cases.  In this post, I will suggest some ways for you to access drone data in case you want to tinker with it for your personal interest, introduce it in your classes, or experiment with it prior to investing in a drone or a new drone sensor.

There are many academic institutions which currently have a drone program. Have a look at our article [] in Directions Magazine to see a sample of schools with a drone degree/certificate program. Be sure to explore the websites of these different drone programs, as many of them may share case studies, sample drone data, or even curriculum from their programs. An example of these programs is the UAS Operations Technician Program at Palomar College ( []), which offers tutorial videos and case studies in the resources section of its website, as well as ready-to-use curriculum materials. Another example of these programs is the National Center for Autonomous Technology at Northland Community and Technical College ( []), which offers a variety of tutorial videos, webinar recordings, and even an equipment rental program for those who may want to collect their own UAS data. 

Aside from academic institutions, you may also want to contact vendors of various sensor systems, or visit their websites to access sample drone data captured with their hardware. This was how I first obtained multispectral drone data and integrated it in my remote sensing course prior to acquiring a multispectral drone sensor. As an example, MicaSense [], which specializes in UAS multispectral sensors, shares sample imagery from its sensors, such as its 10-band dual camera drone sensor here []. As another example, MAPIR [], which also specializes in UAS multispectral sensors, also has sample drone data collected with different drone platforms available on its website [].  If you are interested in Light Detection and Ranging (LiDAR), you can visit GeoCue Group’s [] website, to see its case studies and download sample drone data from those real-world case studies [].  

While UAS are increasingly accessible as a result of lower cost and greater ease of use, with some fairly capable drones (such as DJI’s Tello []) costing less than $100, there may still be legal or safety considerations that prevent you from acquiring your own drone data. And data from higher-end multispectral and LiDAR sensors continue to be out of reach for many. However, with the tips that I have provided in this post, I have hopefully convinced you that you don’t necessarily need your own drone or your own sensor to start learning about and tinkering with drone data. 

Editor’s Note: For more posts on UAS/UAV/Drones and related data, see our posts on this blog, here. For UAS data from the USGS, see this page. For sample UAS data from Esri, see this page. You can also find sample UAS imagery by searching ArcGIS Online, such as this amazing 0.5 inch imagery near Sacramento. Duke University has served their campus UAV imagery as the default imagery layer in ArcGIS Online, which is clearly visible by going to, typing Duke University into the search box, changing the basemap to imagery, and zooming to the campus (or you can see it on this map as well). Keep an eye on the Spatial Reserves blog, because the field of UAS is in rapid change and there will be additional data in the future that we will inform the community about. –Joseph Kerski

A sample of UAS imagery, over Illinois, showing the detail possible from this platform.

Categories: Public Domain Data

Instructor Use of Hands-on Spatial Reserves Activities

December 14, 2020 Leave a comment

As we wrote when we updated the 10 hands-on activities into the ArcGIS Pro and ArcGIS Online environments in 2020, we invite faculty and others interested in using these activities to use them as is, or to “make them their own” through modification. One of my faculty colleagues has taken the latter approach, modifying them for courses at a major university. With the faculty member’s permission, I am sharing some of the results here. These include a revised version of the “siting an Internet Café in Orange County California” activity that asks the user to examine demographic and transportation data. The professor also graciously shared two of the students answers and maps via a set of slides. All three documents are attached to this essay.

The instructor said, “[The activity] was hard for them – they took a couple of weeks and had a lot of questions. But I think the exercise was really good and thorough.  After finishing it they feel very confident.” If you compare the attached activity to the original exercise, you will note that the instructor removed most of the screen shots and changed some of the language; again, to meet the needs of the instructor and course. This is exactly why we provide the exercises in Word format, so anyone can take the activities and modify them as they see fit. The instructor also remarked that the exercise molded itself well to updated demographic information, which is particularly important in this rapidly evolving GIS world of ours.

How are you using these activities in your own learning or in your own instruction? I look forward to your comments.

Modified version of one of the public domain data activities from a university instructor.

–Joseph Kerski

Categories: Public Domain Data

A review of the Big Ten Academic Alliance Geospatial Data Portal

November 30, 2020 Leave a comment

Not long ago I had the privilege of presenting at the Big Ten Academic Alliance’s GIS Day event. During the event I became familiar with their geospatial data portal, and after further review, wanted to share my findings with the readers of this blog. This project is collectively managed by librarians and geospatial specialists at a group of research institutions from across the Big Ten Academic Alliance, which is a consortium of innovative universities in the north central part of the USA. I think in part because the project is managed by librarians and geospatial specialists, in other words, people who really understand how data can be used and how it should be accessed, that the portal is so useful to the user. It connects users to digital geospatial resources, including GIS datasets, web services, and digitized historical maps from multiple data clearinghouses and library catalogs.

The geoportal serves as a search tool fostering access to externally-hosted data, saves researcher time by centralizing regional geospatial data discovery into a single interface, provides discovery to the most up-to-date resources, allows users to search by What, Where, and When, without needing to know Who or Why, contains GIS data produced in Illinois, Indiana, Iowa, Maryland, Michigan, Minnesota, Nebraska, Pennsylvania, Ohio, and Wisconsin, and historical scanned maps from all across the globe.

This has quickly become one of my favorite data portals. The data are easily discoverable and organized by topic, location, publisher, creator, type, and scale. I found, for example, numerous historical aerial photos, such as the one below. Many of the thousands of layers in this portal are data services, eliminating the need for downloading the layers, though there is certainly no shortage of layers that you can download. From animal feeding operations to transportation alignments, from historical aerials to quarries, from COVID to dams to sinkholes to cemeteries to population, this portal is a wealth of data. I salute the creators of this portal and I encourage you to give it a try.

Manitowoc, Wisconsin, 1938 aerial photograph.

–Joseph Kerski

Google’s BigQuery Public Datasets Program

November 23, 2020 Leave a comment

Another public data resource to consider are the public datasets hosted through Google’s BigQuery program and made available through the Google Cloud Public Dataset program. Under this arrangement, Google hosts the data and provides access to query the data and display the results, subject to creating a Google Cloud account and project.

Account holders can query the datasets using either SQL queries (through Cloud Console), the bq command-line tool, (Python-based command-line tool) or by making calls to the BigQuery REST API using a client library ( for example, Java or  .NET.). The first 1 TB of data processed per month is free; any additional data processing is subject to costs based on either on-demand or flat-rate pricing models.

There are currently over 200 datasets listed including number of NOAA resources, USGS Landsat 4, 5, 7 and 8 and ESA sentinal-2 data.

Google Cloud Public Datasets

Once you’ve selected your dataset and run your query, you have options to visualise the data either using Data Studio (dashboard for charts, tables graphs and so on) or GeoViz for displaying spatial data. You can also save up to 1 GB of data from your queries to Google Drive.

Google Cloud Platform – BigQuery

GeoViz is a fairly limited tool for displaying the results of a BigQuery spatial query on a map, one query at a time. However, apparently it is also possible to display BigQuery spatial data using Google Earth Engine by exporting the results of your BigQuery data to Cloud Storage and then importing it into Earth Engine. Haven’t tried this yet but will have a go at some point. There’s also a fairly useful BigQuery tutorial for working with geospatial data.

Overall, metadata for the various hosted datasets seems generally good and the hosted data/tools package provide a useful sandbox for getting started and polishing your geospatial data analysis skills.

Spatial Data from the North American Environmental Atlas

November 16, 2020 Leave a comment

The North American Environmental Atlas combines and harmonizes geospatial data from Canada, Mexico and the United States to allow for a continental and regional perspective on environmental issues. The Atlas continues to grow in breadth and depth as more thematic maps are created through their work and partnerships. Scientists and map makers from Natural Resources Canada, the United States Geological Survey, Comisión Nacional para el Conocimiento y Uso de la Biodiversidad, Comisión Nacional Forestal, the Instituto Nacional de Estadística y Geografía and other agencies in Canada, Mexico, and the United States produce the information contained in the Atlas. It is in my judgment an excellent resource for exploring a wide variety of mapped data layers for these three countries. Each data layer can be examined on the Atlas’ interactive mapping interface, and even better, can be downloaded into a GIS in a variety of file formats for further analysis. You may download specific layers from the mapping interface as shown below or go to the data layers page.

The Atlas’ premise, stemming from an agreement on environmental cooperation, is that the issues do not stop at national borders, and that a comprehensive international approach is needed for analysis and assessment, and for protection of natural ecosystems. Hence, the data layers in the atlas thankfully do not stop at political boundaries, eliminating the need for dealing with appending data, map projection, and other GIS related challenges. The atlas themes include climate, biomes, ecosystems, specific species’ extents, land use, and much more. The atlas is in English, French, and Spanish!

I have known about the Atlas stemming from my days at the USGS and have great respect for its mission. I wrote about its educational applications here ( I encourage you to give this resource a try!

North American Environmental Atlas.

–Joseph Kerski