Posts Tagged ‘imagery’

Planet Labs Imagery Now Viewable by the Public

January 29, 2018 2 comments

Back in 2014, we wrote about inexpensive and the miniaturization of remote sensing, as exemplified in Planet Labs then-new small satellites.  A year later, we wrote about the company’s Open Region initiative with the United Nation to share imagery under a Creative Commons license.  As described in this National Geographic post, Planet Labs has now created a web mapping tool that allows users to examine two million images, updated monthly.  The tool, called Planet Explorer Beta, contains images dating back to 2016, at anywhere from 3 to 40 meters.  My favorite feature so far on the Explorer Beta is the ability to drag-and-drop two images to create a swipe map, to compare changes over time for any given area.  If you create an account and log in, you can explore daily, rather than just monthly, imagery.  Whether logged in or not, the tool is an excellent and amazing resource for teaching and research.

As most of the readers of this blog are work in the field of GIS, they will want to know how to use this imagery in a GIS.  The viewer described above is just that–a viewer.  You can only view the images online.  To actually access the data for use in your GIS or remote sensing work, begin with Planet’s Imagery Quickstart document.  As Planet is a professional satellite image company, it comes as no surprise that users have a multitude of options from which to choose–bands, date and time, cloud cover, sun elevation and azimuth, rectification, data format, and much more.  The imagery is available via a Planet Explorer interface and a Data API, which requires installing a Python client.


Comparing imagery from two time periods in Colorado, USA, using Planet Labs’ Planet Explorer Beta.


Accessing and Using Lidar Data from The National Map

January 8, 2018 Leave a comment

We have written about the USGS data portal NationalMap numerous times in this blog and in our book, but since the site keeps getting enhanced, a re-examination of the site is warranted.  One of the enhancements over the past few years is the addition of Lidar data to the site.  I did some recent testing of searching for and downloading Lidar data on the site and wanted to report on my findings.  For videos of some of these procedures, go to the YouTube Channel geographyuberalles and search on Lidar.

From a user perspective, in my view the site is still a bit challenging, where the user encounters moments in the access and download process where it is not clear how to proceed.  However, (1) the site is slowly improving; (2) the site is worth investigating chiefly because of its wealth of data holdings:  It is simply too rich of a resource to ignore.  One challenging thing about using NationalMap is, like many other data portals, how to effectively narrow the search from the thousands of search results.  This in part reflects the open data movement that we have been writing about, so it is a good problem to have, albeit still cumbersome in this portal.  Here are the procedures to access and download the Lidar data from the site:

  1. To begin:  Visit the National Map: > Select “Elevation” from this page.
  2. Select “Get Elevation Data” from the bottom of the Elevation page.  This is one of several quirks about the site – why isn’t this link in a more prominent position or in a bolder font?
  3. From the Data Elevation Products page left hand column:   Select “1 meter DEM.”
  4. Select the desired format.  Select “Show Availability”.   Zoom to the desired area using a variety of tools to do so.  In my example, I was interested in Lidar data for Grand Junction, in western Colorado.
  5. Note that the list of  available products will appear in the left hand column.  Lidar is provided in 10000 x 10000 meter tiles.  In my example, 108 products exist for the Grand Junction Lidar dataset.  Use “Footprint” to help you identify areas in which you need data–the footprints appear as helpful polygon outlines.  At this point, you could save your results as text or CSV, which I found to be quite handy.
  6. You can select the tiles needed one by one to add to your cart or select “Page” to select all items.  Select the Cart where you can download the tiles manually or select the “uGet Instructions” for details about downloading multiple files.  Your data will be delivered in a zip format right away, though Lidar files are large and may require some time to download.



The National Map interface as it appeared when I was selecting my desired area for Lidar data.

Unzip the LAS data for use in your chosen GIS package.  To bring the data into ArcGIS Pro, create a new blank project and name it.  Then, Go to Analysis > Tools > Create LAS dataset from your unzipped .las file, noting the projection (in this case, UTM) and other metadata.  Sometimes you can bring .las files directly into Pro without creating a LAS dataset, but with this NationalMap Lidar data, I found that I needed to create a LAS dataset first.

Then > Insert:  New Map > add your LAS dataset to the new map. Zoom in to see the lidar points.  View your Lidar data in different ways using the Appearance tab to see it as elevation, slope, aspect (shown below), and contours.  Use LAS dataset to raster to convert the Lidar data to a raster.  In a similar way, I added the World Hydro layer so I could see the watersheds in this area, and USA detailed streams for the rivers.


Aspect view generated from Lidar data in ArcGIS Pro.

There are many things you can do with your newly downloaded Lidar data:  Let’s explore just a few of those.  First, create a Digital Elevation Model (DEM) and a Digital Surface Model (DSM).  To do this, in your .lasd LAS dataset > LAS Filters > Filter to ground, and visualize the results, and then use LAS Dataset to Raster, using the Elevation as the value field.  Your resulting raster is your digital elevation model (DEM).  Next, Filter to first return, and then convert this to a raster:  This is your digital surface model (DSM).  After clicking on sections of each raster to compare them visually, go one step further and use the Raster Calculator to create a comparison raster:  Use the formula:  1streturn_raster – (subtract) the ground_raster.  The first return result is essentially showing the objects or features on the surface of the Earth–the difference between “bare earth” elevation and the “first return”–in other words, the buildings, trees, shrubs, and other things human built and natural.  Symbolize and classify this comparison surface to more fully understand your vegetation and structures.  In my study area, the difference between the DEM and the DSM was much more pronounced on the north (northeast, actually) facing slope, which is where the pinon and juniper trees are growing, as opposed to the barren south (southwest) facing slope which is underlain by Mancos Shale (shown below).


Comparison of DEM and DSM as a “ground cover” raster in ArcGIS Pro.

My photograph of the ridgeline, from just east of the study area, looking northwest.  Note the pinon and juniper ground cover on the northeast-facing slopes as opposed to the barren southwest facing slope.

Next, create a Hillshade from your ground raster (DEM) using the hillshade tool.   Next, create a slope map and an aspect map using tools of these respective names.  The easiest way to find the tools is just to perform a search.  The hillshade, slope, and aspect are all raster files.  Once the tools are run, these are now saved as datasets inside your geodatabase as opposed to earlier—when you were simply visualizing your Lidar data as slope and aspect, you were not making separate data files.

Next, create contours, a vector file, from your ground raster (DEM), using the create contours tool.  Change the basemap to imagery to visualize the contours against a satellite image.  To create index contours, use the Contour with Barriers tool.  To do this, do not actually indicate a “barriers” layer but rather use the contour with barrier tool to achieve an “index” contour, as I did, shown below.  I used 5 for the contour interval and 25 (every fifth contour) for the index contour interval.  This results in a polyline feature class with a field called “type”.  This field receives the value of 2 for the index contours and 1 for all other contours.  Now, simply symbolize the lines as unique value on the type field, specifying a thicker line for the index contours (type 2) and a thinner line for all the other contours.


Next, convert your 2D map to a 3D scene using the Catalog pane.  If you wish, undock the 3D scene and drag it to the right side of your 2D map so that your 2D map and 3D scene are side by side.  Use View > Link Views to synchronize the two.  Experiment with changing the base map to topographic or terrain with labels.  Or, if your area is in the USA like mine is, use the Add Data > USA topographic > add the USGS topographic maps as another layer.  The topographic maps are at 1:24,000 scale in the most detailed view, and then 1:100,000 and 1:250,000 for smaller scales.



2D and 3D synced views of the contours symbolized with the Contours with Barriers tool in ArcGIS Pro. 

At this point, the sky’s the limit for you to conduct any other type of raster-based analysis, or combine it with vector analysis.  For example, you could run the profile tool to generate a profile graph of a drawn line (as I did, shown below) or an imported shapefile or line feature class, create a viewshed from your specified point(s), trace downstream from specific points, determine which areas in your study site have slopes over a certain degree, or use the Lidar and derived products in conjunction with vector layers to determine the optimal site for a wildfire observation tower or cache for firefighters.

Profile graph of the cyan polyline that I created from the Lidar data from the National Map in ArcGIS Pro.


Tracing downstream using the rasters derived from the lidar data in ArcGIS Pro.


Slopes over 40 degrees using the slope raster derived from the lidar data in ArcGIS Pro.

I hope these procedures will be helpful to you.




Possible Changes to NAIP Imagery Licensing Model

November 27, 2017 Leave a comment

As this blog and our book make clear, the world of geospatial data is in a continual state of change.  Much of this change has been toward more data in the public domain, but sometimes, the change may move in the opposite direction. The National Agriculture Imagery Program (NAIP) has been a source for aerial imagery in the USA since 2003 and has been in the public domain, available here.  But recently, the Farm Services Agency (FSA) has proposed to move the data model from the public domain to a licensing model.  The collection of this imagery has been under an innovative model wherein state governments and the federal government share the costs.

One reason for the proposed change is that the states have been $3.1 million short over the past several years, and FSA cannot continue “picking up the tab.”  Furthermore, delays in releasing funding from cost-share partners forces contract awards past “peak agriculture growth” season, which thwarts one key reason why the imagery is collected in the first place–to assess agricultural health and practices.  We have discussed this aspect of geospatial data frequently in this blog–that geospatial data comes at a cost.  Someone has to pay, and sometimes, those payment models need to be re-considered with changing funding and priorities.  In this case, agencies and data analysts that rely on NAIP imagery would suffer adverse consequences, but with the expansion of the types and means by which imagery can be acquired nowadays, perhaps these developments will enable those other sources to be explored more fully.  And, possibly, the model could be adjusted so that the data could be paid for and that all could benefit from it.

For more information, see the report by our colleagues at GIS Lounge, and the presentation housed on the FGDC site, here.

Two samples of NAIP imagery, for Texas, left, and North Dakota, right.

New LandViewer Tool for Quickly Finding and Analyzing Satellite Imagery

May 7, 2017 2 comments

The LandViewer tool and data portal quickly and painlessly allows you to browse and access satellite imagery for the planet.  The tool, developed by the Earth Observing System Inc.’s Max Polyakov, currently features Landsat 8 and Sentinel 2 imagery with more image sets soon to arrive.  Landsat 8 carries two instruments: The Operational Land Imager (OLI) sensor includes refined heritage bands, along with three new bands: a deep blue band for coastal/aerosol studies, a shortwave infrared band for cirrus detection, and a Quality Assessment band. The Thermal Infrared Sensor (TIRS) provides two thermal bands. Sentinel 2 is an Earth observation mission developed by the ESA as part of the Copernicus Programme to perform terrestrial observations in support of services such as forest monitoring, land cover changes detection, and natural disaster management.

Using the LandViewer tool, you can quickly zoom on an interactive web map to your area of interest.  You can filter on geography and time, including cloudiness, sun angle, and other parameters. At the time of this writing, 18 filters such as Atmospheric Removal, Panchromatic, NDVI, Thermal Infrared, False Color, and more, are available so that you can obtain the band combinations most suitable to your analysis in the areas of agriculture, geology, or other applications. A very helpful image interpretation screen is available to help you choose the combination that are best for your analysis goals.  You can do some contrast stretching in the web tool itself.  Then after signing in to the site, you can download the images in GeoTIF for further analysis using your favorite GIS tools.

The tool was also reviewed on the Geoawesomeness web site, and I wholeheartedly agree with their sentiments expressed–this is one of the most useful and fastest satellite image portals I have used. It is useful for research but also, given its ease of use, can even be used effectively to teach concepts of remote sensing.  Give it a try and let us know in the comments section what you think.


Landsat scenes with band combinations possible for an area on the southwest side of Costa Rica.


Digital Globe’s Open Data Program

February 26, 2017 1 comment

Open Data continues to make progress as manifested in data portals, organizations adopting it, and associated literature.  Are private companies also involved in Open Data? Yes. As early as two years ago, we wrote about Esri’s initiatives in ArcGIS Open Data. Imagery and geospatial data company DigitalGlobe have created DigitalGlobe’s open data portal, as part of their efforts to provide “accurate high-resolution satellite imagery to support disaster recovery in the wake of large-scale natural disasters”.  This includes pre-event imagery, post-event imagery and a crowdsourced damage assessment. Associated imagery and crowdsourcing layers are released into the public domain under a Creative Commons 4.0 license, allowing for rapid use and easy integration with existing humanitarian response technologies.  For example, their imagery for areas affected by  Hurricane Matthew in 2016 is available here.

On a related note, I have worked with DigitalGlobe staff for years on educational initiatives.  They provided me with high resolution imagery for an area in Africa I was conducting a workshop in, and more recently with imagery in Southeast Asia that I needed in conjunction with helping Penn State prepare exercises for their GEOINT MOOC (Massive Open Online Course in Geointelligence).  They have always been generous and wonderful to work with and I salute their Open Data Portal initiative.  In the MOOC we also used their Tomnod crowdsourcing platform with great success and interest from the course participants.


Digital Globe’s Open Data Program.

Enhancements to Landsat Thematic Bands Web Mapping Application

November 6, 2016 Leave a comment

Last year, we wrote about the Landsat Thematic Bands Web Mapping Application, an easy-to-use but powerful teaching and research tool and data set. It is a web mapping application with global coverage, with mapping services updated daily with new Landsat 8 scenes and access to selected bands that allows the user to visualize agriculture, rock formations, vegetation health, and more.  The Time tool allows for the examination of changes over years, over seasons, or before and after an event.  The identify tool gives a spectral profile about each scene.  I have used this application dozens of times over the past year in remote sensing, geography, GIS, and other courses and workshops, and judging from the thousands of views that this blog has seen, many others have done the same thing.

If that weren’t all, the development team at Esri has recently made the tool even better–one can now save a time sequence or a band combination as a permanent URL that can be shared with others.  The flooding of 20 districts in August and September 2016 in Uttar Pradesh, India, for example, can be easily seen on this link that uses the application, with screenshots below.

Another example is the Fort McMurray summer 2016 wildfire in Alberta, Canada  – the user can change the time to see the region’s vegetation cover before and after fire, and the extent of the smoke during the fire.  Or, you can analyze a different band combination, as is seen here.

To do this, open the application.  Note that the application URL has been updated from the one we wrote about last year.  Move to an area of interest.  Select any one of the available thematic band renderers (such as agriculture, natural color, color infrared, and others available), or create your own band combination using build.  Then, turn on “time” to see your area of interest at different periods using your band combination.  Next, share this image with other people.   Simply click on any one of the social platforms (Facebook or Twitter) in the upper right, which will create a short link that can be shared.  When the person you send this link to opens it, the Landsat app will open in exactly the same state it was in before social platform tool was clicked.  Give it a try!


Landsat 8 Image for Allahabad India on 31 May 2016.


Landsat Thematic Bands Web Mapping Application in ArcGIS Online

December 20, 2015 2 comments

Teaching remote sensing?  Or just want to understand remotely sensed imagery better?  The Landsat Thematic Bands web mapping application can serve as a very useful teaching, learning, and research tool.  It covers the entire planet and the map is updated daily with new Landsat 8 scenes.

You can access many band combinations and indices by hovering over the tools to the left of the map image and selecting among the following:

  • Agriculture: Highlights agriculture in bright green. Bands 6,5,2
  • Natural Color: Sharpened with 25m panchromatic band. Bands 4,3,2+8
  • Color Infrared: Healthy vegetation is bright red. Bands 5,4,3
  • SWIR (Short Wave Infrared): Highlights rock formations. Bands 7,6,4
  • Geology: Highlights geologic features. Bands 7,4,2
  • Bathymetric: Highlights underwater features. Bands 4,3,1
  • Panchromatic: Panchromatic image at 15m. Band 8
  • Vegetation Index: Normalized Difference Vegetation Index (NDVI). (Band5-Band4)/(Band5+Band4)
  • Moisture Index: Normalized Difference Moisture Index (NDMI). (Band5-Band6)/(Band5+Band6)

The Time tool for different indices at larger scales based on a user-selected location enables examination of changes over years or over seasons.  It also provides temporal profiles for NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index) and an Urban Index, dating back to 1973.  The Identify tool enables access to information on the date, cloud cover, and a spectral profile about each scene.  The Bookmark tool allows access to interesting locations such as the “Eye of the Sahara” in Mauritania.

The application is written using Web AppBuilder for ArcGIS accessing image services using the ArcGIS API for JavaScript, with access to the following Image Services:

  • Landsat Multispectral on AWS – 8-band multispectral 30m resolution image services and functions that provide different band combinations and indices.
  • Landsat Pan-sharpened on AWS – Panchromatic-sharpened imagery; 4-band (Red, Green, Blue and NIR); 30m resolution.
  • Landsat Panchromatic on AWS – Panchromatic imagery; 15m resolution.

These services can also be accessed through the public Landsat on AWS group on ArcGIS Online.  Because you can add these services as layers to your own maps or are adding to maps made by others, or if you are simply using the above web mapping application as a standalone map, you truly have “the world at your fingertips” with these maps and apps.  But there is a third option: Use the Unlock Earth’s Secrets page, also useful for instruction, with the above application embedded in it, but also with explanatory text and featured places around the planet as they have changed through time.

Think of the above as solid introductory segments to help your students, customers, or stakeholders see the value in remote sensing.  These maps and applications require very little geospatial technology skills to use, but allow you to focus on building remote sensing concepts and principles while exploring some truly engaging content and places.

To dig deeper, delve into the many powerful remote sensing functions available in ArcGIS Desktop.  One source for engaging, hands-on activities, is Kathryn Keranen and Bob Kolvoord’s book Making Spatial Decisions Using GIS and Remote Sensing:  A Workbook.

Give these resources a try!

Landsat web application

Landsat web application in ArcGIS Online.