Geospatial Video: A Powerful and Underappreciated Tool in UAS

Outside of military surveillance operations, geospatial video is a data format that is likely unheard of for most commercial UAS operators. If not unheard of, at least poorly understood. Geospatial video is the inherent combination of geospatial information and video into a single data product. Essentially, geospatial video allows pilots and data analyst to understand where a UAV is positioned in space at any point along a recorded video. Depending on the video format, even the frame of view of the video can be spatially located along a basemap. At first glance, this may seem like a minor alteration to a given UAV video with little use, but this technology fills an important gap in the capabilities of UAS remote sensing.

Perhaps the most common data product created with UAS data, the orthophoto mosaic, has temporal and computational drawbacks. Comprised of an assortment of images "stitched" together to form a point cloud, orthomosaics take an exceptionally long time to process and can not take into account moving objects within the test area. Within many fields, a target topic of study may act on temporal scales too quick to be assessed in an orthomosaic or even too quick for a UAV flying a standard grid pattern. Two examples that come to mind in my beloved field of ecology are animal surveys and wildfire tracking. Animals that move at all are likely to be subtracted or duplicated from an orthomosaic. This effectively makes animal surveys through this method impossible. Even if you were looking through individual images that are used to generate a mosaic, the non-continuous nature of the data could make repeat observations more likely.  Wildfires, especially if tracking wildfire dynamics in real time, is another topic area that could benefit from the geospatial video technology. Either for the purpose of fire fighting or ecology, many of the concerns and interactions caused by wildfires occur at extremely fine temporal scales. Scales that the drone is capable of flying, but mosaic software can not account for. Many other topics of research could benefit from geospatial video within ecology include algal bloom research, population and community level interactions, and simply using drones as a recon tool to find and locate features ahead of time without the limited scaling on a typical grid transect pattern.

Generally speaking, faster image analysis is possible with geospatial video technology. Shape files could be created based on the aircraft path, so a nadir video following a physical feature could help inform cartographic and volumetric analysis. Real time analysis is possible with this method which could be critical for activities in conservation. Even just allowing for shorter field campaigns by enabling some of the observations to be made in the air makes this technology beneficial for the wildlife biologist.

While payware and better video cameras streamline the processing for this technology, simple UAVs that log GPS data can be used with freeware geospatial video software to produce professional quality product. I used Video GeoTagger FREE to investigate the ease of use of the technology and how it might be useful to the ecological research community.

Guide to use and my Experience

The geotagger software is available for free here.

After the software is downloaded and installed, the intro screen looks like below.

Conveniently,  a Youtube video is included in the top left corner that provides guidance on at least the most basic steps. The software is targeted for ESRI users as this can be used as an extension, but the steps are essentially the same.

The first thing to do is to load data points. Go to file and click "open video for geotagging".

The following prompt will be produced. Fill in the open categories with the desired video and GPS file. The file can be a .txt, .gpx, .SRT, among others.

 

At this point, the video (viewable in the top left panel when the Youtube video is not selected) and GPS data (viewable as points along the base map) are present. However, this data is not yet merged, they are two separate entities. You must select a point (preferably the first or last) from the GPS data on the basement and then select the "Geotag Video" option in the bottom left corner. This effectively merges the data set.

The interface after data has been imported but before it has merged

Once the data is merged, the media browser tab should be selected, and the icon for the video should be selected. Multiple merged videos can be present at one time, so it is important to select the correct video. The following image shows what this should look like. You may also notice the four new icons on the right side of the basemap.

After this step, when the video is played, the active location of the UAS is tracked in time with the video. The green dot on the basemap (in the following image) represents the UAV as it travels across the flight path. As the video plays, the four indicators on the right of the map also change showing heading, time, altitude, as well as general metadata (location in space as well as time and altitude) in descending order. At any point the video can be paused and the information for that point can be recorded. This is a massive advantage of this technology in that observations found in the video can be tied directly with metadata for that individual point in time (and thus feature). The following two images show a zoomed-in perspective of the flight tracker screen and the corresponding video clip.

Use and Weaknesses

As is hopefully apparent, the ability to pair metadata with video is crucial for tasks that need quick assessment or need to be monitored in real time. This tool is even more powerful when using the MISB video format that enables a bounding box of the camera extent to be created along the basemap as well as UAV position. I can also see this as being the primary means of UAV data collection in research groups without the infrastructure to use more expensive software or hardware.

However, there are some weaknesses to this approach, at least with the freeware version. Precision of point is a significant concern. As you may tell in the above image, the gps points in space are not entirely continuous. There is some lag in the continuous video among the stream of points. Meaning that if I pause the video twice in a row within a very short amount of time, both pauses may claim the same GPS point and associated metadata. Obviously this is not possible as the video stream pause locations, while similar, are not exactly the same. This may limit the technology somewhat for observations that require an immensely accurate GPS point. While none come to mind immediately, (perhaps an assessment of extremely heterogeneous landscapes) missions that require that much precision are likely better suited for different data products.

The other issue is scaling and validation of the basemap-GPS combination. While different basemap formats can be selected, including imagery, the natural resolution of UAS video may create a problem. If the drone data, which is extremely high resolution, does not match the lower resolution basemap, it may be difficult to interpret the exact location of points in space. How much this is an issue is difficult to quantify with a freeware software, but should be a consideration. Another problem with this software may come in the form of correcting for differences in the video and the basemap, or identifying differences in the least. This would especially be an issue when the video is taken of homogeneous landscapes. If the video is taken over a coniferous forest away from identifying man made features, for example, it could be extremely difficult to validate if the GPS points on the basemap are accurate at all. In this video, we had access to a road and we can clearly see the road in the basemap is also present in the video. Operators may not always have that luxury.

Strategy Sessions and Project Plan

Over the past few weeks, us capstone students have met to discuss the joint UAS capstone project. These meetings have really been focused on a few components:
 1) Where do we want to perform our capstone project
 2) What types of questions could we answer there
 3) What skills will be needed
 4) What type of Data would we like to collect
 5) What roles we will need and who will fill these roles
This report is the accumulation of the strategy session talks and what will happen going forward.

The Project

As stated in my bibliography and timeline blog post, our project will be based at the amphitheater park in the Lafayette Greater Area (The Tippecanoe County Amphitheater park). This site was chosen for the large variety of features we could analyze. It includes a very large parking lot, a full large scale amphitheater, hardwood forests, large grass areas (which will also help for launching fixed wing aircraft), hilly topography, streams, and a section of the Wabash River. Also, this site is phenologically dynamic because the Wabash river always floods in the Winter and Spring in that general area. We are also fortunate in that, during the week, this site is typically completely empty of pedestrians. This early in the process, we have decided not to make any fundamental decisions regarding what our final paper will answer (as we are mostly setting out to develop standardized practices for collecting extremely high spatial and temporal resolution data for a specific site). However, we are fairly certain we will try to analyze the impact of flooding at this site over time, perhaps developing models to predict flooding and water presence based on topography and land cover class. To do this, we are planning to collect data extremely frequently (several times a week) with a variety of sensors/data-types (multi-spectral, RGB, geospatial video, thermal, and maybe LiDAR) and an assortment of platforms (various multi-rotor aircraft and C-Astral Bramor ppX). Understandably, this will create an enormous quantity of data to analyze and will hopefully allow future groups to ask and answer questions for years. We will be writing a formal research publication to a not yet determined journal. 

Core Skills

- Effective and efficient flight operations and CRM
- Proper and informed data management and analysis
- Multi-faceted group organization 

Roles

We have made two main conclusions regarding roles for this project during our sessions. The first is that we need everyone to have a unique permanent role, but everyone should have a rotating secondary role.

The presence of a permanent role is critical for an assortment of reasons. The first is due to the scale of this project. We are dealing with so many systems, sensors, and data types for a very heterogeneous test site over a large amount of time. We are also the first to use this equipment and lab space so checklists, manuals, procedures, training protocols, tests, and data management structure all need to be developed. To achieve this, permanent roles structured around the skills of our diverse group will allow for standardization for each major component of the project. In effect, each person is in charge of leading all the developments in their section of the project. This will allow our group to finish a successful project by May despite the enormity of tasks that need to be accomplished. The permanent roles are ones that would be confusing, or perhaps even harmful to the overall project, if people switched into that role later in the semester.

Rotating roles are going to be important for each member. The structure of rotation is still yet to be determined, but essentially everyone will have an additional role in addition to their permanent role at any one time. This will allow everyone to get some experience at various aspects of the project and thus the UAS industry. This will also allow some of the permanent roles that are very time intensive to have additional help. Essentially, everyone's secondary rotated role is that of an assistant where they can gain experience at a task (such as data management and analysis) without structurally changing the procedures the permanent members have put in place. Some examples of these roles include being a member of the data team, systems integration, ground control team, or flight training.

In addition to one permanent role and a rotating role, each member will also act as a flight crew member. Each person will likely work in one or two crews at a maximum to promote continuing crew resource management and general operational understanding. This will also simplify scheduling. Each crew may specialize in a particular (or a few types of) aircraft, sensor, mission type, etc. This will likely help repeatability, accurate data collection, ease of training, and safety. However, exactly how this will work is still yet to be determined.

The following is a list of the permanent roles. It is important to recognize that these roles and their descriptions are very much susceptible to change. It is also important to recognize that the role descriptions encompass some, not all, of the tasks a role will strive to complete.

Operations Manager - Kyle Sheehan -
The operations manager is in charge of structuring flight and field operations in a way that is consistent and collects the appropriate data types at the correct time. The operations manager schedules the entirety of the flight operations and works with leaders in other parts of the project to ensure field operations are performing at the requisite level. They are the final authority on many of the documents that will need to be created related to aircraft operations.

Systems Integrator - Ryan Ferguson & Ian Willey -
The systems integrator is the primary member(s) focused on the aircraft and sensor integration and maintenance.  Their job is to fully understand the physical capabilities and limitations of the aircraft, draft appropriate documentation, and prepare the aircraft(s) ahead of each flight. This could include charging batteries, cleaning/maintaining appropriate equipment, integrating sensors to aircraft, performing and staying on top of updates on all equipment, and generally ensuring that flight crews and the data crew have easy access to the aircraft and data when needed. This role will have a rotating assistant member as needed because flight operations may be so frequent that more than two members may need to be present throughout the week. These members are also the primary enforcement for aircraft and aircraft component flight logs.

Lead Pilot/Flight Instructor - Todd Horn -
The lead pilot, otherwise known as flight instructor for this project, is in charge of mastering flight and operation of each aircraft and the required sensors. They will be the authority for determining if each flight crew is appropriately trained on each aircraft and if they could safely fly missions on their own. For that reason, he should work closely with the operations manager so that flight training sessions can be scheduled before the crew is sent on a data gathering flight. The lead pilot is also supposed to maintain knowledge as to the proficiency of each crew and determining if each crew needs more training. For example, if a crew goes several weeks without flying a particular system, it is recommended that the lead pilot goes with the crew to the operation to provide guidance as needed. This role is the critical for long term operational safety. A rotating member may be assigned to this role so that they can become proficient in all systems and then help check to see if other crews are operating correctly and safely.

Data Manager- Evan Hockridge -
This individual is responsible for all components of the data post operation. Tasks include developing a data management, security, processing, and analysis workflows. The data manager must master all the processing and analysis software needed to accomplish the project. This role requires close association with each of the other roles to guarantee the correct data is gathered, placed in the correct location in the correct way, and that the appropriate results can be concluded. Rotating (multiple) members will be assigned to be a part of the data team at any given time. This is because of the massive quantity of data that will be accumulated. The data manager will train the data team to store, process, and analyze the data correctly so that data can be assessed promptly.

Geospatial Crew Leader - Dylan McQueen -
The geospatial crew leader runs a small team of rotating members which perform ground fieldwork. In particular, this individual is responsible for the collect and quality of ground control measurements. The team will collect points at various scales (full-site and sub-site) so that operations can rely on previously collected permanent ground control. Because the site is predicted to be dynamic in nature, the crew leader should plan to recollected ground control at various points in the semester including before and after flood events. They are also in charge of standardizing placement and use of the aeropoint ground control for missions that will use them. Aeropoint procedures are needed because they are non-permanent points, so quality placement recommendations are needed for our site.

Lead Author - Krysta Rolle -
The lead author's primary task is focused towards the back of the semester where they will head the authorship of the inevitable research paper. However, before that point, they will also collect much of the general background research. They may also head up a weekly progress report as collected from each of the permanent group members. They will also help edit all the individual documents generated throughout the semester.

Project Manager - Thoma Gonya -
The project manager may be a semi-permanent role, or have a full rotation where a member who specializes in a particular aspect of the project takes lead when needed (example: Integration PM early on or a Data PM later on). The project manager is to ensure that all the components of the project work together for the common goal. Effectively, they find and minimize weaknesses in our approach and maximize on strengths. They set and adjust the overall project timeline, set subgoals for the various groups within the project, and assign deliverables. The PM also sets important meetings and during meetings, acts as the organizational voice so that all important topics are covered during the meetings.

Likely Early Deliverables

This is a short list of some of the deliverables that will be needed very early in the semester (within the first two weeks or so). By having these finished early, we have the best chance of finishing on time.

1) Pre, during, and post flight checklists
2) data storage and management procedures (including folder pathing)
3) Systems integration guides for each sensor and aircraft (that we have at the beginning of the semester)
4) Flight training procedures and schedule
5) Early flight schedule
6) General semester timeline
7) Early field notes of site
8) preliminary data
9) Ground control point information
10) Preliminary/early flight plans
11) Meta-data saving guide
12) Meeting schedule and plan adjustment points

Annotated Bibliography and Research Timeline for Senior Capstone Project

Introduction

This blog post serves as an initial research document to the group senior capstone project to be completed next semester. Our project, while the inevitable publication is still unknown, will be structured around an extremely-high temporal analysis of a particular site with various sensor and aircraft types. In some of our initial discussion, a potential option was made present to use a local part that includes significant urban features (large parking lot and amphitheater), forested areas, a slopped area, and a nearby water feature. The fact that the water feature, the Wabash River, often floods in the Winter, this site could be very interesting to assess temporally over the Winter and Spring. Thus, the assumed project for this assignment would be an assessment of land cover change penology based on land cover classes and topography.

The following research bibliography is critical going forward with the proposed project because there are many topics that require fundamental understanding. First of all, land cover types must be classified. Thus, research must be collected that would enable us to understand how to delineate between different land cover types. After that, information on how to generate the proper data products must be collected. From there, understanding of how to remotely sense water must be understood. Lastly, how to collect the information for the data types and the proper equipment to do so must also be collected. All of these things are contained within this sample bibliography. A research timeline must also be generated. This is because we will be using an extensive team, collecting many forms of data, with a plethora of equipment, over a long period of time. To keep everything in check and organized, a timeline can help insure we finish on time.

Annotated Bibliography 

Band, Lawrence E. 1986. "Topographic Partition of Watersheds with Digital Elevation Models." Water Resources Research 22 (1):15-24. doi: doi:10.1029/WR022i001p00015.

summary -  an older fundamentals paper on how DEMs can be used to map river bodies and surrounding catchments. This paper comes long before the age of drones, and thus is structured around satellite remote sensing. Essentially finds that one could understand the structure of the topography to understand where water is instead of directly sensing it.

Pros - a great technique we could use to define the parameters of the Wabash River early in our assessment, as well as predict how water will flow during rain events and where the Wabash will extend to during flood events.

Cons - While fundamentally should work, drone data contains more "noise" and this method would need to be tested for effectiveness.

Bohlin, Jonas, Jörgen Wallerman, and Johan E. S. Fransson. 2012. "Forest variable estimation using photogrammetric matching of digital aerial images in combination with a high-resolution DEM." Scandinavian Journal of Forest Research 27 (7):692-699. doi: 10.1080/02827581.2012.686625.

Summary- A method for extracting important forestry variables from forest stands. Dimensions such as basal width and height are extracted with a drone based DEM in a coniferous Sweden forest.

Pros - This could become useful in our analysis and classifications. In particular, where in the flood plane do certain tree characteristics exist or how do trees impact flooding based on variables within trees. This could lead to more particular classifications based on structure of trees (such as a heat map), predictive models of flooding based on tree characteristics, etc. How exactly this will play in is to be seen.

Cons - This method used a coniferous forest, we have hardwood forests in this section of Indiana. When the hardwood trees no longer have leaves in the winter, it may be much more difficult to assess the variables that the study did.

Kong, Zhaodan, and Bernie Mettler. 2011. "Evaluation of Guidance Performance in Urban Terrains for Different UAV Types and Performance Criteria Using Spatial CTG Maps." Journal of Intelligent & Robotic Systems 61 (1):135-156. doi: 10.1007/s10846-010-9485-9.

 Summary - An assessment and guidelines for choosing specific UAV types in an Urban environment. This assessment is performed at different spatial scales and uses a spatial cost-to-go map to make the assessment.

Pros - can inform when and how to use each of our platforms most efficiently.

Cons - while the method used to make an assessment is interesting, it is only one data product being used to inform decision making. We also plan to use all of our aircraft so this paper may only be helpful in determining how to deploy our systems, not whether we will use them at all.

Manfreda, Salvatore, Matthew McCabe, Pauline Miller, Richard Lucas, Victor Pajuelo Madrigal, Giorgos Mallinis, Eyal Ben Dor, David Helman, Lyndon Estes, Giuseppe Ciraolo, Jana Müllerová, Flavia Tauro, M. de Lima, João de Lima, Antonino Maltese, Felix Frances, Kelly Caylor, Marko Kohv, Matthew Perks, Guiomar Ruiz-Pérez, Zhongbo Su, Giulia Vico, and Brigitta Toth. 2018. "On the Use of Unmanned Aerial Systems for Environmental Monitoring." Remote Sensing 10 (4):641. doi: 10.3390/rs10040641.

Summary - A review paper on the uses of drones in environmental monitoring. Covers topics ranging from technological development, trends in environmental papers, technical benefits of drones, technical limitations of drones, trends for drones in environmental science, basic considerations that should be taken when operating UAS, and aircraft-sensor considerations.

Pros - as a review paper, it is fantastic for outlining the environmental remote sensing background and trends. Will likely be looked at again in the future within the group.

Cons- Lacks the specificity to be anything but background.

McFeeters, S. K. 1996. "The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features." International Journal of Remote Sensing 17 (7):1425-1432. doi: 10.1080/01431169608948714.

 Summary - Introduces a water index that can be used to delineate open water features, such as the river and maybe flooding. Mentions that can actually measure water turbidity which would be important in a flood event where water may look like ground.

Pros - important technical considerations for how to use data and the appropriate equations to make indexes to delineate land cover types.  

Cons - Is an older paper, some more recent investigations should be considered. To my limited understanding, does not mention depth very much which may be a factor.

Mills, Jacqueline W., Andrew Curtis, Barrett Kennedy, S. Wright Kennedy, and Jay D. Edwards. 2010. "Geospatial video for field data collection." Applied Geography 30 (4):533-547. doi: https://doi.org/10.1016/j.apgeog.2010.03.008.

Summary - A summary and essentially guide for using geospatial video as a field collection method. Lays out how to use it in drone remote sensing.

Pros - Useful (potentially) as inspiration on geospatial video methods. Also may be an important citation to verify what we are doing in inevitable paper.

Cons - May ultimately be nothing more than a citation to validate our methods.

Renwick, Jason D., Levente J. Klein, and Hendrik F. Hamann. 2016. "Drone-based reconstruction for 3D geospatial data processing." IEEE 3rd World Forum on Internet of Things:729-734. doi: 10.1109/WF-IoT.2016.7845501.

 Summary - similar to above source, a summary of photogrammetry to make 3D models with a drone. 

Pros - An  important citation for paper and maybe a means to maximize quality.

Cons - May only end up being a validating citation.

Singh, Kunwar K., and Amy E. Frazier. 2018. "A meta-analysis and review of unmanned aircraft system (UAS) imagery for terrestrial applications." https://doi.org/10.1080/01431161.2017.1420941. doi: 10.1080/01431161.2017.1420941.

Summary- a meta-analysis of drone papers in academia. Specifically looks at the range of paper topics, methods, and equipment. Finds significant variability among drone papers and calls for a need to standardize.

 

Pros - A great overview of the work that has been done and how it might be pertinent. Perhaps uncovering some potential methods we could adopt and a reason to include standardized methods as an ultimate project goal. Good jumping off point for further research. 

Cons - Perhaps lacking some specificity that would be needed to adapt methods to the paper.

Tauro, Flavia, Maurizio Porfiri, and Salvatore Grimaldi. 2016. "Surface flow measurements from drones." Journal of Hydrology 540:240-245. doi: https://doi.org/10.1016/j.jhydrol.2016.06.012.

Summary- A means to use drones (in this case a consumer level drone) and optical imagery to quantitatively measure surface flow of various sized water bodies (as small as sub-meter). Also assesses that typical concerns, such as vibration, do not impact the observations.

Pros - Show that we could measure surface water flow of very small bodies of water (may be important for pooling in parking lot or small streams that form from flooding) via much cheaper drones than what we will use. This could be a critical aspect of our flood analysis and could provide very interesting insight in how various surface types impact the flooded environment. A comparison of water speed between water cover types could potential be measured with the methods of this paper.

Cons - may expand the scope too much and may require too many residual skills to realistically do. 

Turner, Darren, Arko Lucieer, and Christopher Watson. 2012. "An Automated Technique for Generating Georectified Mosaics from Ultra-High Resolution Unmanned Aerial Vehicle (UAV) Imagery, Based on Structure from Motion (SfM) Point Clouds." Remote Sensing 4 (5):1392-1410. doi: 10.3390/rs4051392.

Summary - An explanation and a method for creating georectified mosaics from drone imagery, especially in reference to point clouds. Has important information regarding image accuracy when comparing GPS and GCP methods.

Pros - The most important functional information will come from the comparison between GPS and GCP accuracy. While we are using PPK which will help accuracy, the accuracy tests in this paper can and will be useful in assessing accuracy and will serve as reasoning to use GCPs. 

Cons - No real cons, is all good information that will absolutely be pertinent. Perhaps only weakness is no test of other forms of GPS so we may need to do ourselves or find another paper concluding accuracy.

Williams, Dudley, and Kent F. Palmer. 1974. "Optical properties of water in the near infrared*." JOSA, Vol. 64, Issue 8, pp. 1107-1110. doi: doi:10.1364/JOSA.64.001107.

Summary - an old remote sensing paper discussing how water interacts with infrared radiation. A very technical piece of all the interactions.

Pros - Important background as well as potentially critical remote sensing information if the previously mentioned water index or NDVI are not sufficient for delineation.   

Research Timeline

This is a very preliminary research timeline

December

Continue project planning, assign permanent and rotating roles to members, identify temporary role rotation, audit complete equipment list, and set up data management plan

Early January

Create first full semester schedule, create flight schedule, begin initial field observations, collect multi-scale permanent ground control points, test various flight plans for ideal data gathering missions, determine repeatable mission plans, create/distribute/present all pertinent workflows, checklists, procedures, data requirements, and schedules

Late January

Begin standard data gathering flights, permanent crew member positions begin creating standardized procedures for rotating members to follow as well as training guidelines, create preliminary data products, create and verify data analysis workflows, identify paper topic

Early February

First rotation of jobs, Sharpen workflows checklists and procedures, data team presents early findings and requests changes to flight crews (begin brief weekly data quality meetings between teams), begin literature review on problem

Late February to Spring Break (Early March)

Continue flight operations and adjust schedule to requisite data volume and environmental changes, mid-term meeting to determine project requirements and direction changes, Finish preliminary literature review

Late March

Second rotation of jobs, managers meet with each team to determine individual needs and recommendations, begin time series analysis if possible, begin creating maps and visuals to use in eventual paper, finalize references and background sections of paper, start/complete methods section of final paper

Early April

Perhaps final rotation of jobs, final scheduled flights, full image analysis and statistics, begin the rest of the final paper writing

Late April
 Any specific flights deemed necessary (emergency data collection), final analyze, finish review and finalize paper

Conclusion

This timeline and research background will likely change, but be useful moving forward. Ultimately there is a significant scope to this project but I believe it is very doable in the allotted amount of time using each of our group members skills. Ultimately, this will only be possible if we all function together efficiently.

November 8th Field Outing

As a lab, we went to Dr. Hupy's property to fly data collection missions. This lab outing served several purposes. First and perhaps most fundamentally, to allow individuals to rotate in roles that they have not yet had throughout the semester. In other words, addition crew resource management practice. We also spent time explaining flight planning software particular to our aircraft and the functionality of the ground control system we were using. My primary role was visual observer, since I had been involved in more core operational positions in previous field outings. This was a good opportunity to interact with my colleagues from the perspective they have had in previous outings. The collected data has not yet been processed, but will be useful after the creation of UAS computer lab in December.

The lab setting ground control

Going over the flight plan and its intricacies 

One of the set Aeropoint ground control pads

Purdue GIS Day: Personal Take

Last week was GIS Day at Purdue University. It is an academic conference with various events where experts can talk about various uses for GIS. Individuals on the sides of land management, digital technology, remote sensing technologies, data management, environmental sciences, and the humanities were all involved. In general, I found the event to be very enjoyable and informative. There were a few major takeaways, positive and negative.

Positive Takeaways

This was one of my first academic conferences where I was not presenting material but was in my general field. It was interesting to experience the event as a observer and allowed me to make several key discoveries. First of all, it was interesting and actually sort of warming to really understand how small but diverse the Purdue GIS community is. Through my years at Purdue, I have run into an assortment of people working with various geospatial tools. It was incredible how many of those people were involved in the conference in some way. I also enjoyed seeing how people use this segment of technology in other fields. While I am certainly not accustom to researcher methods in history or the humanities, it was interesting to see how geospatial methods I am at least a little familiar can be used in those fields. GIS Day also showed me how powerful these sort of conferences can be for networking. Personally, as well as others at the conference, seemed to be successful at interacting with other participants. As a person who tends to think interdisciplinary, this was an exciting component that helps me look forward for the future.

Negative Takeaways 

Something I noticed is that some speakers, including ones with the most impressive backgrounds, truly struggle at communication of their work. Either due to jargon use, poor speaking volume, overly complicated slides, or very poor visualizations. It was interesting to see how some people were not using components in their maps that we have been trained to include, such as scale bars and labeling. Due to the complex nature of the presentations, it was remarkably clear how important those components are. When combining difficult to understand material with poor presentation, the entire point being conveyed can easily be lost. I think that in some ways, understanding what did not work during the conference was more important than what I learned from the good presentations. I am exciting to build my research career, because I want to be a scientist. This conference really solidified to me that good research does not make a good scientist. Science is about contributing to human knowledge and understanding. Being able to communicate discoveries is as important as the discoveries themselves because that is what makes the discoveries important. I have to be understanding that if I want my work to mean something, I have to learn to explain it in an consumable way.

Field Update - October 30th

This field outing was an extension of the work in the last blog post. Essentially, a few key adjustments were made to the same operational area. The flight plans were adjusted to cover the entire area. Using telemetry logs from the last flight, we identified where radio control signal was lost and where the aircraft resorted to a fail-safe return to home mode. By understanding this geospatial information, we readjusted the flight plans so that launch sites and crew spots will remain in visual and radio line of sight the entire time, essentially minimizing the odds of more lost link events. The flight plan became four almost equal flights with operations in each corner of the woodlot. This shrunk the flight area per flight and decreased the total distance between the aircraft and pilot.

During these operations, I acted as pilot. In all cases I flew the missions and other members acted as communications and observer crews. Ryan Ferguson acted as a second flight crew flying geospatial video missions. His aircraft utilized DJI Light-Bridge technology. The advantage of his system is he could actively operate out of a single launch spot utilizing the network of observers. Light-Bridge does not suffer from the same radio telemetry issues as the H520. We coordinated flights so that aircraft were never over the forest at the same time. This was fantastic practice at managing multi-aircraft flight operations and managing airspace.

Ultimately, the mission was more successful and the entire forest was imaged. However, due to an elevation differential between actual ground level and the tops of trees, the center of the forest did not successfully rectify in processing. This is because the drone assumes it is imaging features at ground level. However, the tree canopy is much closer to the aircraft. This means that the drone is collecting images assuming ground level overlap, but is actually collecting much lower overlap. The solution would be to either fly much higher or increase overlap significantly. Overlap is quite high in this mission, but perhaps the small amounts of increase may not be enough. Flying higher is not possible without written permission by the FAA, so in the short term that may not be possible. Thus, additional solutions are being considered such as different geospatial position methods such as PPK.

Field Update - October 23rd

This blog entry is an update of an ongoing project in the McCormick Woodlot, located in W.Lafayette, Indiana. Our group is working with the Purdue University Department of Forestry and Natural Resources to monitor the lot. After further development of methodology, as informed by the fieldwork performed on October 23rd, the FNR department should be able to identify species, forest structure, and biomass within the woodlot.

This particular operation had a few primary goals. The first was to establish adequate ground control that would be firmly viewable in the drone imagery. This would inform future operations around this woodlot regarding ground control should be placed. After rectification of imagery, the impacts of the GPS points will be assessed. Ultimately, we were successful in this goal and are basing future placement of Aeropoint GPS points roughly on the placement of this operation.

The second goal was to capture as much of the woodlot as possible. Through some preliminary flights, it became clear that this step is more difficult than one might assume. Due to the low altitude allowable for our operation of 200ft under the LAANC system, maintaining visual line of sight and radio telemetry is difficult while flying over the tall forest trees. While this flight was good practice for using LAANC, in which we received proper FAA authorization for our operation, we were not able to collect data for the entire woodlot. Based on the flight plans we created, we were not able to maintain line of sight and radio telemetry. However, we did collect good subset data as well as telemetry information that would allow for more successful flight planning of future operations at this woodlot.

This outing was also very important for developing crew resource management skills. We developed a group oriented strategy for maintaining safe operation. This included a central team, called flight crew. This included Ryan Ferguson, the pilot for the flights of this operation, and myself who acted as mission organizer and primary observer. The rest of the class was split into groups of three which included one individual to scan the environment and maintain radio communications, another individual to watch for airtraffic, and a third to maintain line of site with the aircraft. We used a positive exchange of radio communication to insure line of sight was never consistently lost and that the aircraft was flying safely. This aspect was extremely successful.

Ultimately, this field outing was structured around building field skills and fine tuning operations around this woodlot. Further operations should be increasingly successful at gathering data of the entire woodlot and strengthen group efficiency for future operation.

 

Initial setup of ground equipment

 H520 aircraft; Fantastic sensor, but has limitations regarding radio communication connection

 This is the initial takeoff area; the entirety of the Western edge of the woodlot is within visual line of sight

Pilot, Ryan, and graduate remote sensing student, Aish, preparing for takeoff. I was acting as operational organizer and communications organizer, as well as observer

 An example of the radios that were dispersed between ground crews and the flight crew