Archive for November, 2019

Application for Extracting and Exploring Analysis Ready Samples (AρρEEARS)

November 24, 2019 Leave a comment

Imagine a data site where you can upload your own data for processing and spatial analysis, using tools that you do not own!  The Application for Extracting and Exploring Analysis Ready Samples (AρρEEARS) allows you to do just that.  I recently attended a presentation about this application at the Applied Geography Conference on AppEEARS and was very impressed.  AppEEARS offers a simple, efficient way to access and transform geospatial data from a variety of federal data archives, and hence merits highlighting in this Spatial Reserves data blog. AppEEARS enables data users to subset and extract geospatial datasets using spatial, temporal, and band/layer parameters.

Two types of sample requests are available: point samples for geographic coordinates and area samples for spatial areas via vector polygons.  Results stay on the LP DAAC site for 30 days, during which time you can archive them somewhere else or download them to your own device or server.

You need to have an Earthdata free account to use the site, but once you get one here, you can be off and running.  AppEEARS is tied to the LP DAAC (Land Processes Distributed Active Archive Center), in which there is no shortage of data.  Sample requests submitted to AρρEEARS provide users not only with data values, but also associated quality data values. Interactive visualizations with summary statistics are provided for each sample within the application, which allow users to preview and interact with their samples before downloading their data.

What’s more, you can also access the AρρEEARS API. This API allows users to write programs to interact with AρρEEARS. This is largely the same API that powers the AρρEEARS user interface.

My favorite part of AppEEARS is the tutorials and lessons that are in the e-learning resources zone, here.   Presentations, videos, and webinars are housed there, but my favorite part is the tutorials.  These are detailed, clear, and can be used as self-contained lessons for you, your colleagues, or students to learn about analysis methods, spatial data, and earth phenomena such as wildfires.  For example, using a tutorial written by Danielle Golon from Innovate Inc (a USGS contractor), you can generate remote sensing-derived environmental descriptors to monitor Yosemite National Park, without downloading the remotely sensed data itself:  All of your processing is done on the AppEEARS site, and you will use imagery, box plots, whisker plots of NDVI values, and other tools and data to analyze several fires from 2013 to 2018 over space and time.   You will use NASA Visible Infrared Imaging Radiometer Suite data (VIIRS) and MODIS data (Moderate Resolution Imaging Spectroradiometer).

Using another tutorial, you will generate environmental descriptors of bus stops in the Phoenix metro area to determine which bus stops could benefit from heat relief shelters.  This tutorial uses MODIS data and daily surface weather data.



Sample AppEEARS temporal data for fire analysis.  

I highly recommend giving the AppEEARS resources and tools a try.

–Joseph Kerski

An introduction to Ethics in GIS

November 10, 2019 7 comments

One of the objectives of this blog and our book is to not only help you gain technical knowledge about GIS and data, but also to help you understand the societal issues surrounding data.  Ethics is central to many of these societal issues.  We have written about ethics in geospatial decision making, ethics in using images in mapping projects, company ethics vs. technical reputation, and ethics surrounding data quality issues.  But here let us discuss one way of introducing ethics to co-workers and to students with an example of how I have integrated ethics into one of my own courses on cartography and geo-visualization.  The following is the actual text and readings that I use in this course.  I look forward to your reactions.

Ethics in GIS.  Ethics in science is an expansive topic; it is introduced here, but you will have the opportunity to explore it further later in this course.  Ethics matter in GIS because:  (1) Knowing that maps are powerful means of communication, you should take that responsibility as map author seriously.  (2) Knowing from our brief discussion on crowdsourcing and citizen science that everyone is now a potential map producer, and no longer just a map consumer, there are more maps in existence than ever before–with a wide variety of quality and purposes–some well documented, some not so.  That said, maps still have an aura of authenticity–they tend to be believed.  Again, take that responsibility seriously, and do not intentionally mislead your audience.

The Social implications for GIS began to be examined during the mid-1990s with books such as Ground Truth.  (Links to an external site.) Another oft-cited book on this topic is How to Lie with Maps (Links to an external site.) by geographer Mark Monmonier, which examined the ways that maps are distortions–intentionally and unintentionally–of reality.

Code of Ethics.  There are several key items that are generally thought to be included in a code of ethics for people working in the field of GIS.  The first is to have a straightforward agenda, ensuring that the purpose of your map is evident to the map reader.  It should not be deceiving or confusing, but rather, transparent in its purpose.  The second code is to get to know your intended audience as much as you can, so you can effectively communicate through maps.  The third code is to not intentionally lie with data–do not symbolize or classify the data with the intent to deceive.  The fourth code is that a map should show all relevant data as completely as possible–do not intentionally leave things or context out that could help the reader understand the phenomenon, again, balancing this with the guidelines about abstracting and generalizing.

The fifth code is that a map should not discard contrary data just because it is contrary.  Rather, your map should be as much as possible a neutral representation of reality, just as your research often should be.   The sixth code is that the map should strive for an accurate portrayal of the data, where the data is not diminished or exaggerated.  The seventh code is to avoid plagiarizing.  Just like your research, you should always properly cite your sources of information. You can cite sources via the map’s metadata.  The eighth code is to select symbols that will not bias the map. The symbols should be neutral representation of features.  The classification and projection, too, should be chosen so that potential bias is minimized.  Code nine is that the map should be repeatable, such that another GIS professional should be able to independently create a similar map using the same data and focusing on the same message.  Code 10 is to be sensitive to different cultural values and principles when making your map, such as color and symbols.  In summary, when creating a map, you should strive to provide a truthful, neutral representation of reality targeted specifically for your audiences’ level of knowledge so that your map can effectively convey your intended message.

(Source: (Links to an external site.) for the 10 cartographer’s codes of ethics in this document, with modifications by Joseph Kerski).

For more on geospatial ethics, (1) see the GIS Certification Institute’s Code of Ethics: and (2) see these articles:

(1) (Links to an external site.)  – The GIS Professional Ethics Project:  Practical Ethics Education for GIS Pros.  by David DiBase et al. 2009).

(2) A new National Academy of Sciences report:  National Academy of Sciences.  2018.  Data Matters.  Ethics, Data, and International Research Collaboration in a Changing World: Proceedings of a Workshop. (Links to an external site.)

Joseph Kerski


–Photograph by Joseph Kerski at a high school that is active in preparing students for business careers.   It is my hope that ethics are included in the discussion here and in all other science, business, GIS, and all other academic programs.

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