Hyperspatial Thermal Imaging of Surface Hydrothermal Features at Pilgrim Hot Springs, Alaska using a small Unmanned Aerial System (sUAS) University of Alaska Fairbanks. *Corresponding author: [email protected] Christian Haselwimmer * , Rayjan Wilson, Corey Upton, Anupma Prakash, Gwen Holdmann, and Greg Walker Acknowledgements This research is funded by the Department of Energy Geothermal Technologies Programme (CID: DE-EE0002846) and the Alaska Energy Authority Renewable Energy Fund Round III. References 1. Liss, S.A. and Motyka, R.J. (1994) Pilgrim Springs KGRA, Seward Peninsula, Alaska: Assessment of fluid geochemistry. Geothermal Resources Council Transactions, Vol. 18. 2. Haselwimmer, C.E., Prakash, A., and Holdmann, G. (2011) Geothermal Exploration at Pilgrim Hot Springs, Alaska using airborne thermal infrared remote sensing. Geothermal Resources Council 35th Annual Meeting, Oct 23-26, San Diego, California. 3. Haselwimmer, C.E.,Prakash, A., and Holdmann, G., (2013) Quantifying the heat flux and outflow rate of hot springs using airborne thermal imagery: case study from Pilgrim Hot Springs, Alaska, Remote Sensing of Environment, 136, 37-46, http://dx.doi.org/10.1016/j.rse.2013.04.008. 1. Overview • Very high spatial resolution (hyperspatial) thermal remote sensing from small Unmanned Aerial Systems (sUAS) has potential to contribute to mapping and monitoring of geothermal features. • sUAS deployed at Pilgrim Hot Springs, Alaska with the aim of assessing the potential and practicalities of using such a system for geothermal exploration and quantitative resource assessment. • 4 cm thermal imagery provided an unprecedented capability for mapping hot springs, seeps, and the surface flow of geothermal fluids. • Heat budget model was used to estimate the hot spring heat flux and discharge rate for part of the geothermal area from the calibrated FLIR imagery, which was compared against in-situ measurements. 4. Data Preprocessing • Dif ficulties with photogrammetric processing approach led to use of semi-automated mosaicking with PTGui using automatic exposure adjustment. • Mosaic manually registered to high resolution airborne visible image using ArcMap. • FLIR TAU 2 is uncalibrated camera: mosaic calibrated using measured temperatures of ground targets such as hot springs and black body tarps. 5. Mapping Surface Hydrothermal Features • 4cm resolution thermal imagery provides very detailed picture of the locations and extents of hot springs and the surface outflow of geothermal fluids. 6. Hot Spring Heat Flux Estimation • Heat budget model used to estimate hot spring heat flux and outflow rate for part of the geothermal area. Heat budget for a water body (in Watts) is expressed as: • Model inputs: 1) FLIR imagery for hot waters; 2) atmospheric properties; 3) average temperature of non-geothermal surface pools. • sUAS FLIR derived heat flux = 0.53 MW, lower than previous results from airborne FLIR [3] = 0.75 and 0.86 MW for 2010 and 2011 data. • Results compared against heat flux estimates derived from in-situ measurements of the flow rate (see culvert location on panel 5). • In-situ flow rate used to calculate advective heat flux (Ф adv ) through the culvert (at the measured water temp) and total hot spring heat flux (Ф geo at the hot spring temp of 81˚C) using: Ф adv/geo = ṁ(h s -h amb ) where ṁ is the mass flow rate (l/s) and h s , h amb are enthalpies of water (kJ/kg) at the spring (in this case for both the measured temp and hot spring temp) and ambient water temperatures. • Total hot spring heat flux from combined sUAS/in-situ = sUAS FLIR-derived heat flux (0.53 MW) + calculated advective flux (0.42 MW) = 0.95 MW • Total hot spring heat flux from in-situ only = 2.93 MW • Differences due to poor calibration of sUAS FLIR and possible underestimation of FLIR approach when compared to in-situ measurements. 7. Outcomes • sUAS acquired hyperspatial thermal imagery mapped cm-scale hot springs and seeps, and the extents of hot water with much greater detail than airborne thermal imagery. • TIR imagery shows changes in hot springs possibly related to surface hydrological conditions. • sUAS thermal imagery did not provide reliable estimates of the hot spring heat flux due to significant errors in temperature calibration of the data: due to use of uncalibrated camera. • This work highlighted practical issues to be addressed before sUAS can compete with airborne thermal imaging such as sUAS battery life, flight planning, and use of calibrated sensors. 3. sUAS Data Collection • Aeryon Scout quadcopter equipped with FLIR TAU 2: 640 x 480 pixels covering 7.5 - 13.5 μm. • Survey flown over Pilgrim Hot Springs on 24/7/2013: calm day with high cloud cover. • 100m flying height = ~4cm thermal imagery, flight lines planned around extent of hot springs and thermal features mapped from ~1.5m airborne thermal imagery (flown in 2010). • ~20 mins battery life (required frequent returns to base), fully autonomous execution of survey. • Coincident collection of calibration data: hot spring + tarp temperatures, atmospheric variables. 2. Pilgrim Hot Springs, Alaska • Geothermal system located ~75km NE of Nome on Seward Peninsula. • Shallow 90ºC aquifer fed from deeper reservoirs of at least ~110-150ºC [1]. • DOE/AEA funded project to undertake resource exploration and assessment. • Airborne FLIR previously used to map hot spings and quantify heat flux and outflow rate: ~4.7-7 MW th [2,3]. 0 100 200 50 Meters 0 30 60ºC Hot pools Aerial Photograph 09/10/2010 Hot springs Airborne Thermal 09/10/2010 Aerial Photograph 09/10/2010 Airborne Thermal 09/10/2010 Alaska Pilgrim Hot Springs Left: Aeryon Scout quadcopter Top left: calibration target (temperature recorded with FLIR and iButton logger). Top right: temporary weather station y = 0.0008x + 10.298 20 25 30 35 40 45 50 55 60 65 10000 20000 30000 40000 50000 60000 70000 Digital Number Temperature (ºC) Above: linear gain and offset used to calibrate the mosaicked thermal imagery to surface temperature Base image: mosaicked FLIR TAU 2 thermal imagery overlain on high resolution aerial photograph Culvert: in-situ hot spring flow rate 0 50 100 25 Meters 10 60ºC Church Calibration tarp Calibration tarp Airborne thermal (~1.5 m pixels) - 09/10/2010 sUAS thermal (~4 cm pixels) - 07/24/2013 0 10 Meters Small springs (cm scale) Seep in plunge pool Water surface films show subtle temp difference sUAS thermal Airborne thermal 0 5 Meters Springs not seen in airborne data Hot springs not seen from sUAS data • Differences in temperature between airborne and sUAS: poor calibration of TAU 2 data? • Differences in locations of hot springs: lower water table and change in surface outflow? 0 Watts 13 Above: estimated hot spring heat flux for geothermal pools (in units watts/pixel) B41B-0393 Ф total = Ф geo + Ф ppt + Ф adv + Ф evap + Ф sens + Ф rad + Ф sun + Ф sky Ф geo = heat input from geothermal fluids Ф ppt = heat input from precipitation Ф adv = heat flux from advection/seepage Ф evap = heat loss from evaporation Ф sens = heat loss via sensible heat transfer Ф rad = heat loss by radiation Ф sun = heat input from solar radiation Ф sky = heat input from atmospheric radiation Ф geo Ф adv Ф ppt Ф sun Ф evap Ф sens Ф rad Ф sky