Latest Contributions by CodyBenkelman

For those of you who've been using (or wanting to use) oriented imagery in the web, and you'd been waiting for the ability to configure a web app for your organization, the new Oriented Imagery Viewer widget for Experience Builder is here!  (Released today, Feb 26, 2025) With this widget, organizations can now build flexible web apps to maximize the value of their oriented images.  The Experience Builder apps can load and choose from multiple oriented image layers and/or display two or more separate oriented image windows.  If you need to make measurements, horizontal distances and areas on the ground are enabled via this widget, as well as vertical height measurements.  Accuracy estimates are automatically included (based on metadata).       And working with GIS features is now enhanced: feature data can be displayed in the viewer, and new features can be digitized directly within the oriented images.    Build your apps, and let us see what you've accomplished!   ... View more

Introduction The use of thermal infrared (TIR) imagery sensors has seen dramatic growth in the last few decades, addressing many applications for users of mapping and GIS.   The purpose of this blog is to introduce some of the many use cases, and to provide recommendations for ArcGIS users to take advantage of these sensors.  The examples included here will focus on imagery captured from an aerial drone followed by photogrammetric processing to generate a True Ortho composite image, but use of a drone and post-flight processing are not always required - some very powerful applications may also be addressed with single images or video (airborne or ground-based), and for large area studies, satellite sensors may be most appropriate. Note that we’re using the acronym “TIR” here to refer to the thermal infrared region of the electromagnetic spectrum.  This blog does not address properties of near infrared (“NIR”) or shortwave infrared (“SWIR”) energy or sensors. Use Cases Some of the many applications for TIR imagery within ArcGIS include: 1.  Monitoring energy loss from buildings This application is growing rapidly since it provides a low-cost analytical method for a facility to reduce operational costs as well as environmental impact.  Thermal infrared imagery is typically captured by a drone to view the rooftops of buildings under study, and areas that are losing energy can be easily observed as warmer or cooler than their surroundings. That is, if the outdoor weather is warm and the building has air conditioning, energy leaks will appear as cool regions.  If the building is losing interior heat during wintertime, relative warm areas may be visible.  Areas of the building that are noticeably cooler or warmer than their surroundings help building managers prioritize improvements to ventilation systems as well as locate and repair areas of insufficient building insulation.  Examples can be found in this publication from ACCESSiFLY.  An example image (showing false colors applied to the single band TIR image) is shown here, highlighting warm regions around roof vents.   2.  Detecting potential maintenance problems in electrical/mechanical equipment Another application where TIR imagery can provide value is by identifying equipment that appears to be overheating, indicating possible physical wear or failing electronics.  This is applicable for a variety of types of equipment, including but not limited to photovoltaic solar arrays, electrical transformers, industrial motors, and more.  An example image is shown below, provided courtesy of Rocky Mountain Unmanned Systems.  In this image, one section of the photovoltaic (PV) array is noticeably brighter (warmer) than the neighboring panels in the installation, indicating a possible defect in either the array or its control electronics.  With prompt maintenance, the operator can reduce lost productivity and possibly avoid a more serious failure in the future.     3.  Detecting leaks in pipelines Thermal Infrared imagery is also applied to monitoring pressurized pipelines to detect leaks.  A leak can sometimes be observed as an area on or near the pipeline with a temperature anomaly – warmer or cooler than the surrounding region.  If a liquid such as water is leaking, it can cool the local vegetation/soil relative to ambient background temperature.  In the case of other pipelines, such as natural gas, a leak can result in a loss of pressure, and evidence of emerging gas can sometimes be observed as a cold plume (although there are other sensors that are better suited for detecting flammable gas). In the example images below (provided courtesy of EagleHawk) we can clearly see the route of an underground steam pipe (1 in the first image, TIR), with evidence of a condensate leak (2) entering a storm drain.  In top center (3) we can see the warm water condensate running into a nearby ravine.  The second image provides a natural color view of the same site.  Based on this imagery, the leak was promptly located and corrected.     4.  Other Use Cases The use cases listed above are just a sample of the much broader array of applications for thermal infrared imagery.  There are many more – for example: TIR sensors are used on drones as well as crewed aircraft to search for lost hikers or conduct wildlife surveys.  In law enforcement, residual heat can be detected and applied as forensic evidence showing where a vehicle had been parked but then departed the scene prior to image capture – either where heat from an operating vehicle had warmed the pavement, or alternatively where the shadow of a parked vehicle had left evidence as a cooler region, having reduced solar heating of the surface.   Environmental studies focusing on aquatic habitats where narrow temperature ranges are required for successful fish spawning can cover relatively large areas with thermal infrared imagery to supplement in situ temperature sampling.    Interpretation / Analysis For most of the above examples, users can detect thermal anomalies through simple visual assessments of the area of interest to identify regions that appear warmer (or colder) than everything nearby.  As a result, the user can extract useful information with relative (qualitative) observations, but without performing absolute (quantitative) measurements of exact temperatures.  The exception to this in the above examples is an application such as monitoring water temperatures in fish spawning beds, where spawning success may depend on water temperatures within a relatively narrow temperature range.    In use cases that require absolute and accurate temperature measurements, users will need to consider radiometric calibration of their sensor system, and properties of the materials being observed, especially metal surfaces which often show reflections of TIR energy coming from another source – e.g. the sky (which will typically appear very cold) or the sun.    Surface Properties and Emissivity Making accurate remote temperature measurements of an object is challenging.  Images captured by thermal infrared sensors are proportional to the energy received, and those energy measurements are then used to determine the apparent temperature of the surfaces in view.  Some sensor manufacturers provide information to enable conversion of TIR images into energy units, then from energy to surface temperature.   An important consideration is the surface property referred to as Emissivity (represented by ε).  Different surface materials emit thermal energy at different rates.  The difference in emitted energy for two surfaces at the same temperature is characterized by their emissivity, ranging from 0.0 to 1.0.  The apparent temperature of a surface is typically lower than the actual temperature, presuming the surface emissivity is less than 1.0.   Remote temperature measurements can be misleading for low ε surfaces such as most metals, since they emit very little energy and they can also reflect TIR energy coming from another source (e.g. the sky, which will appear to be very cold, or a separate heat source).   A more detailed discussion of this topic is beyond the scope of this blog post, but it is important to understand that calculation of the most accurate temperature of any surface – concrete, water, grass, metal, etc. – would require knowledge of the emissivity of that surface as well as the possibility of observing reflected heat sources.  A table of emissivity values can be found HERE.  Note that, since most natural surfaces have an emissivity value of 0.9 or greater, in most applications described above, correction for emissivity may not be necessary.   Practical Application In practice, the user should consider whether absolute temperature measurements are required for their use case.  Since many applications do not require absolute temperatures, it is reasonable to visually identify thermal anomalies, and thus derive significant value from TIR imagery without needing to calibrate to temperature units.  For TIR sensors carried on a drone, users wishing to generate a True Ortho data product must capture multiple frames (with recommended overlap of 90% due to the low image resolution) and then run photogrammetric processing to create an orthomosaic for visual interpretation.  For satellite sensors, a single image will often cover the full site of interest. If absolute temperature measurements are required, support in Esri software will depend on the sensor. Additional software from the sensor manufacturer may be required to perform the conversion.  Refer to the ArcGIS Help documentation for your software and sensor.  The sensor manufacturer may also have separate tools to apply for temperature calibration. For satellite sensors, the proper Raster Type must be defined, then processing templates can be applied to the TIR bands to convert pixel values into degrees Celsius or Fahrenheit     ... View more

Attention all users!  A new version of ArcGIS Drone2Map is now available in MyEsri, and we encourage everyone to upgrade. We’ve made improvements and additions in many areas of the software, focusing as always on improved quality in your output data products, and more robust review of your data & metadata to help avoid any issues with processing your drone imagery.    Since many Drone2Map users are in the Construction or Utilities industry, an important improvement is for better detail of thin structures in the 3D mesh.  An example is shown below.  We’ve kept this post very brief, but you can see more detail in the What’s New blog at https://esriurl.com/D2M20242whatsNewBlog  You can find a complete listing of new features in Help documentation at https://esriurl.com/D2MwhatsNewHelp and this list of specific issues which have been addressed https://links.esri.com/arcgis-drone2map-issues-addressed-2024-2.  ... View more