Drones: Explore the Landscape (Technical & Physical)
This Session Will Consist of Two Main Components:
1. Showcasing some of the technical challenges and advantages of using Drones as research tools, we will hear brief reports from the following researchers. L Barbieri who has been monitoring the effect different farming techniques have on green house gas emissions, M Messinger who use drones to monitor deforestation, and S Barberie who has been quantifying glaciers in New Zealand. Each will present on the remote sensing techniques used and address some of the challenges of the "Technical Landscape". This component will also contain time for some questions and discussion.
2. NASA intern K Bhakta will present some of the preliminary results from a survey he is conducting answering 2 questions. (1) Who’s using drones for earth science currently and what/how/why/where are they doing it?, and (2) What software is out there for processing drone captured data, what formats does it support and what metadata standards does it meet? His results are being used to build part of a Drones in Earth Science resource catalog the cluster is creating. We will therefore also present to the community our move to using the ESIP Open Science Framework infrastructure as a means of enabling the cluster and community to share resources, code, and data. Finally we hope the results of Bhakta's work will prompt some community discussion around the ongoing question regarding data and metadata standards for Earth Science Drones.
1. Sean Barberie, ESIP SF – “Droning New Zealand”
a. Castle Hill on South Island of New Zealand
b. Flight path was concentric circles
c. 3D model was built using “Structure in Motion”
d. Live version of the model on:
e. Multiple models across time possible to monitor landscape changes
f. Can we use drones and 3D modeling in disaster response?
i. Topic was raised during previous ESRI Drone session at Summer Meeting.
g. CM and MM precision is possible, though depends on a number of factors such as altitude at which pictures are captured.
h. Travel regulations with drones are not too bad, though flight regulations vary a lot.
i. Flight in New Zealand both hobbyists and commercial can fly with permission of land-owner.
ii. Within the US commercial operators need FAA permission.
2. Max Messenger, Wake Forest/Linn Aerospace
a. Examine deforestation to inform predictive model where deforestation hotspots will be in the future.
b. Fine-scale land-cover classification
i. Gold mining disturbance in Peru and differentiate from other disturbances using
c. How are forest understory species affected by deer overpopulation?
3. Jane & Lindsay, - “”
a. Proof of Concept: What can be done with an off-the-shelf drone?
b. Projects can be found at: https://osf.io/nuvem/
c. Instrument review using ESIP funding
d. Multiple test flights show more highly variable data midday, potentially do to mixing.
e. Final report will be coming out shortly to OSF; draft is currently variable.
f. Testbed: Science Standardized Embedded Data infrastructure for Drones (SSEDD)
i. Building a drone platform for scientists
ii. Testbed proposal is up on OSF.
4. Kush Bakata, Missouri University – “Drone Resource Catalog”
a. One stop shop for information on data and uses of drones within science.
b. “Drones in Science” page examines across 9 scientific disciplines
i. The cryospheric sciences has drones to examine questions related to frozen water.
ii. Volcanology uses drones to fly over active plumes.
c. Drones are likely to be used mostly in biogeosciences.
d. Software includes pre and post-data collection and flight (i.e. control and communication).
e. APRS working on aerial data portal that incorporates airplane photography, but drone data may be able to be housed there. (preliminary)
a. What formats do we want to store data in?
i. One flight per file? Per project?
b. How do we store imagery?
c. What is the directory structure?
d. What is file structure?
i. PROV could help deal with multiple files and provenance of those files.
ii. Differentiate level of data, similar to UAV protocols.
1. Multiple formats in airborne community
iii. UAV community is beginning to develop data standards.
1. ASPRS – UAV division; fall conference in Palm Springs (~Nov 2016)
iv. NASA Armstrong working with FAA on commercial standards. Could FAA connect commercial drones with science and utilize same metadata standards?
v. Unique flight identifiers may be helpful
1. Paired with persistent identifier DOI
vi. How are these datasets being queried? May inform data structure and fields.
vii. Standardize flight identifiers by time since calibration.
viii. How can we query in order to location corresponding LANDSAT imagery?
ix. Nomenclature for airborne campaigns from NASA. Files packaged as campaigns, with granules for discrete instrumentation.
1. Separate raw from processed data