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ISOTHERM: Ice SnOw vegetation HypERspecTral Measurements

Start date: 01-05-2015 - End date: 30-10-2015

Status: Confirmed

Open to sharing: Yes

Confidential: No

Transnational Access: Yes

Open to training: Yes

Grounded / Maintenance: No

Aircraft:

Aircraft name: DO228 - NERC - ARSF

Airport: Mont-Blanc Massif, French Alps. This is the highest mountain range in the French Alps, where glaciers and perennial snow covered areas can be found in late summer and early autumn. Within the context of the French Observatory of glaciers (GLACIOCLIM), ongoing glaciological measurements initiated forty years ago are conducted on several glaciers of the massif, including the Mer de Glace, Argentiere, Talefre and Leschaux glaciers. Furthermore, a glacio-hydrological scientific program in the Arves river watershed is in progress, involving glaciological, hydrological, meteorological measurements. As a consequence, the measurements acquired by this campaign will bring additional information of important interest for these programs.

Project description

Project theme: Hyperspectral airborne measurements over snow, glaciers and vegetation; intercomparison with ground-based measurements and modelling.

Science context: Our initial goal is to measure the hyperspectral (HS) signature of snow surface in the Mont-Blanc Massif in order to estimate the spatial variability of snow surface properties (albedo, grain size and impurities content). These properties display a strong spatio-temporal variability and constrain the energy budget of the snowpack. The data retrieved during the experiment will be compared to ground measurements and satellite observations. They will provide a unique dataset to better investigate and model the surface radiative and mass balance of snow surfaces. The second objective is to obtain accurate high-resolution characterizations of glacier surface (glacier margins, glacier surface area covered by debris, limit between snow and ice). HS data will provide relevant information to quantify spatio-temporal changes in albedo (a key variable of the surface energy balance governing the ablation processes at the glacier surface) at the moment of the year (late summer) when the snow cover on the glacier surface is minimal. In addition, airborne LiDAR will allow for the elaboration of a fine-grained digital elevation model. Combining HS and LiDAR data will also enable improved modeling and understanding of glacier mass balance through investigation of the effects of small-scale topography on surface radiation and energy balances. Finally, HS imagery has direct applications for questions in alpine plant ecology. Our overall objective is to obtain a fine-grained classification of the land cover, together with spatially distributed parameters of plant canopies (physical and biochemical).

Measurements to be made by aircraft: Airborne hyperspectral remote sensing allows for detailed spectral analysis of the ground surface, but so far has seldom been applied in the context of high mountain environments, e.g. glaciers, snow, due to the high data acquisition costs and the large expertise required for data analysis. As yet, the method has been utilized exclusively for scientific research rather than for applications on an operational level. The following experiments will concern different scientific problems regarding three applications groups: snow, glacier and vegetation. Scientific objectives. Snow and ice are among the most reflective surfaces on Earth. Snow and ice covered surface areas are thus responsible for several significant feedbacks in our climate system. The high spatial variability of snow surface properties responsible for albedo variations makes point measurements inadequate to depict this variability. Remote-sensing measurements are thus the most adequate tool for studying the variability of snow surface properties. However, satellite-base data retrieval methods provide medium resolution and accuracy characterization of snow and ice surfaces properties. Aerial campaigns are consequently necessary to improve these methods and better estimate their accuracy and characterize the surface. For the snow application group, the scientific objectives are: - The characterization of the spatial variability of snow surface properties (albedo, grain size and impurity content and types, liquid water content) from the hyperspectral signatures (Dozier et al., 2009; Green et al., 2006) - The evaluation of current developed methods used to retrieve snow properties from satellite (Painter et al., 2013; Mary et al., 2013) by comparing APEX data with satellite and ground measurements - The evaluation of snow surface properties simulated with the detailed snow model Crocus (Vionnet et al., 2012). For the glacier application group, the main scientific objectives are: - The characterization of glacier surface albedo at very high spatial resolution all over the glacier surface area (Dumont et al., 2011) - The mapping of the different characteristics of the glacier surface state, i.e. snow covered areas, clean ice areas, debris-covered areas with a characterization of the debris types and size e.g., sand, small blocks, rocks (Gardent et al., submitted) - To improve the modeling and understanding of glacier mass balance by investigating the effects of small-scale topography and albedo variations on the surface radiative and energy balances (Six et al., submitted) - The quantification of glacier volume changes by comparing the high-resolution DEM derived from the LiDAR measurements between the two flights and with former high-resolution DEM from the late 2000s derived from photogrammetry (Vincent et al., 2014). For the vegetation group, scientific objectives include: - The elaboration of a high-resolution land cover map representing dominant vegetation types (Asner et al., 2002; Friedl et al., 2010). - The estimation of canopy properties including above ground biomass, leaf chlorophyll content, leaf water content and leaf area index (Fernandes et al., 2004; Schlerf et al., 2010). - The consideration of other sources of snow cover data (Crocus, MODIS, Landsat) as predictors of plant trait distribution, plant community diversity and ecosystem properties (Schaepman et al., 2007). Proposed work and anticipated output. The experiment will consist of dedicated flights of the research aircraft DO228/D-CFFU (hosting the hyperspectral instrument APEX) along the Mer de Glace and Argentière glaciers up to the Dome du Gouter. Furthermore, in order to achieve the goals of the vegetation group, it is essential for the path to cover an altitudinal gradient spanning mountain, sub-alpine and alpine vegetation belts (from approx. 1000 to 3000 m a.s.l.). The priority zone would be a path covering these elevations from the Argentière to the Bossons glaciers. With mean speed about 60 m/s and considering some slow down to 40 m/s, a rough time estimate is 4-5 hours for each flight (including travel from Grenoble - Le Versoud airport to the Mont-Blanc Massif. Thus, a total of 2 flights (for a total of 10 hours flying time) seems sufficient to fulfill the goals of this project. The APEX instrument is an airborne (dispersive push broom) imaging spectrometer developed by a Swiss-Belgian consortium for the European remote sensing community, recording hyperspectral data up to 532 bands in the wavelength range 380.5 - 971.7 nm for VNIR detector and 941.2 - 2501.5 nm for SWIR. The targeted spatial ground resolution is between 0.5 m and 5 m depending of aircraft characteristics. The Field Of View (FOV) is 28 degrees. It is intended as a simulator and a calibration and validation device for future space borne hyperspectral imagers. The LiDAR (Leica-ALS50) is an airborne laserscanner with a maximum range of 3000 m using wavelength adapted for snow and ice (1064 nm). This instrument will allow acquiring a high resolution points cloud of the covered surface with a vertical accuracy of 15-20 cm, ideal to construct a digital elevation model with a 1-m resolution. Moreover, Meteo France shares access with other Grenoble laboratories to an SVC (Spectra Vista Corporation) hyperspectral instrument for foreground experiments and inter-calibration with APEX. For such an aim, the plane will need at some time to adopt a cruiser altitude in the proximity of the surface in order to reduce the source of error associated with the atmospheric layer. References: Asner, G.P., Heidebrecht, K.B., 2002. Spectral unmixing of vegetation, soil and dry carbon cover in arid regions: Comparing multispectral and hyperspectral observations. International Journal of Remote Sensing 23, 3939-3958 ; Dozier, J., Green, R.O., Nolin, A.W., Painter, T.H. (2009). Interpretation of snow properties from imaging spectrometry. Remote Sensing of Environment, 113, S25-S37 ; Dumont, M., Sirguey, P., Arnaud, Y., Six, D. (2011). Monitoring spatial and temporal variations of surface albedo on Saint-Sorlin Glacier (French Alps) using terrestrial photography, The Cryosphere, 5, 759-771, doi: 10.5194/tc-5-759-2011 ; Fernandes, R.A., Miller, J.R., Chen, J.M., Rubinstein, I.G. (2004). Evaluating image-based estimates of leaf area index in boreal conifer stands over a range of scales using high-resolution CASI imagery. Remote Sensing of Environment 89, 200-216 ; Friedl, M.A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., Huang, X. (2010). MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sensing of Environment 114, 168-182 ; Gardent, M., Rabatel, A., Dedieu, J.P., Deline, P. Multitemporal glacier inventory in the French Alps from the late 1960s to the late 2000s. A new insight into glacier shrinkage over the last 40 years. Global and Planetary Change. Submitted ; Green, R.O., Painter, T.H., Roberts, D.A., Dozier, J. (2006). Measuring the expressed abundance of the three phases of water with an imaging spectrometer over melting snow. Water resources research, 42(10) ; Painter, T.H., Seidel, F.C., Bryant, A.C., McKenzie Skiles, S., Rittger, K. (2013). Imaging spectroscopy of albedo and radiative forcing by light‐absorbing impurities in mountain snow. Journal of Geophysical Research: Atmospheres, 118(17), 9511-9523 ; Schlerf, M., Atzberger, C., Hill, J., Buddenbaum, H., Werner, W., Schuler, G. (2010). Retrieval of chlorophyll and nitrogen in Norway spruce (Picea abies L. Karst.) using imaging spectroscopy. International Journal of Applied Earth Observation and Geoinformation 12, 17-26 ; Schaepman, M.E., Malenovsky, Z., Mücher, C.A., Kooistra, L. and Thuiller, W. (2007) Bridging Scaling Gaps for the Assessment of Biodiversity from Space. The Full Picture - A publication for the GEO Ministerial Summit in Cape Town, Earth Observation for Sustainable Growth and Development (ed. E.G. Secretariat), pp. 258-161. Cape Town ; Six D. and Vincent C., Sensitivity of mass balance and equilibrium line altitude to climate change in the French Alps, submitted to journal of Glaciology, 2014 ; Vincent, C., Harter, M., Gilbert, A., Berthier, E., Six, D. (2014). Future fluctuations of Mer de Glace (French Alps) assessed using a paramaterized model calibrated with past thickness changes. Annals of Glaciology, 55(66), 15-24 ; Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Willemet, J.M. (2012). The detailed snowpack scheme Crocus and its implementation in SURFEX v7. 2. Geoscientific Model Development, 5, 773-791

Season: Starting date: 15-09-2014 Ending date: 15-10-2014 Preferred and acceptable dates (season / time windows) The flights requested in the present EUFAR project are to be scheduled in September and October 2014.Agreement to share aircraft time (project clustering, cost sharing)AHSPECT (Agriculture Health SPECTradiometry), proposal led by Jean Louis Roujean (CNRM, Toulouse)

Weather constraints: The weather needs to be clear and stable in order to reduce the variability of reflectance due to variations of solar irradiance and to minimize the effect of atmospheric layers. The wind speed should be low enough to allow for flight close to the surface.

Time constraints: The time schedule for the specific flights requested in the present EUFAR project is the months of September and October 2014. The base of operations for the DO228/D-CFFU - DLR will be Grenoble - Le Versoud airport. Coincident times with the overpasses of MODIS-TERRA scenes are desirable. The time of the flight should be as close as possible to local solar noon (i.e. from 10 AM to 2 PM local time for data acquisition) so as to minimize the effect of the anisotropy of the surface on reflectance measurements.

Flights (number and patterns): Two flights of about 4-5 hours each. Departure from Grenoble - Le Versoud airport (45°20'/05°51'), Grenoble - Chamonix (45°55'/06°52'). Overflight of the region of interest (see maps enclosed), from point 1 to 34 following the line, the distance is about 160 km. Note that this map is indicative. The area of interest is represented with the yellow boxes and the number of lines to cover each box depends on the elevation of the flight and the swath of the APEX. Return to Grenoble - Le Versoud airport.

Instruments: TA instrument: VITO - APEX. APEX hyperspectral instrument for measurements of reflectance in a large number of quite narrow bands. LiDAR Leica ALS50, depending of the availability of this instrument and the possibility to use it or a similar instrument with the aircraft. Thermal camera available at LGGE.

Other constraints: 1.3. Recent relevant publications by application group in last 5 years (up to 5) Glacier Rabatel A., Letreguilly A.,Dedieu J.-P.,Eckert N. 2013. Changes in glacier equilibrium-line altitude in the western Alps over the 1984-2010 period: evaluation by remote sensing and modeling of the morpho-topographical and climate controls. The Cryosphere, 7, 1455-1471. doi:10.5194/tc-7-1455-2013. Rabatel A., and 27 others. 2013. Current state of glaciers in the tropical Andes: a multi-century perspective on glacier evolution and climate change. The Cryosphere, 7, 81-102. doi:10.5194/tc-7-81-2013 Dumont M., Gardelle J., Sirguey P., Guillot A., Six D.,Rabatel A., Arnaud, Y. 2012. Linking glacier annual mass balance and glacier albedo retrieved from MODIS data, The Cryosphere, 6, 1527-1539, doi: 10.5194/tc-6-1527-2012. Rabatel A., BermejoA., LoarteE., SorucoA., GomezJ., LeonardiniG., Vincent C., SicartJ.-E. 2012. Can the snowline be used as an indicator of the equilibrium line and mass balance for glaciers in the outer tropics? Journal of Glaciology, 58 (212), 1027-1036. doi: 10.3189/2012JoG12J027. Rabatel A., CastebrunetH., FavierV., NicholsonL., KinnardC. 2011. Glacier changes in the Pascua-Lama region, Chilean Andes (29°S): recent mass-balance and 50-year surface area variations. The Cryosphere, 5, 1029–1041. doi:10.5194/tc-5-1029-2011. Snow Mary, A., Dumont, M., Dedieu, J.-P., Durand, Y., Sirguey, P., Mihlem, H., Mestre, O., Kokhanovsky, A.A., Negi, H.S., Lafaysse, M. and Morin, S. Intercomparison of retrieval algorithms for the specific surface area of snow from near-infrared satellite data in mountainous terrain, and comparison with the output of a semi-distributed snowpack model, The Cryosphere, 7, 741-761, doi:10.5194/tc-7-741-2013, 2013. Carmagnola, C.M., Domine, F., Dumont, M., Wright, P., Strellis, B., Bergin, M., Dibb, J., Picard, G., Libois, Q., Arnaud, L. and Morin, S. Snow spectral albedo at Summit, Greenland: measurements and numerical simulations based on physical and chemical properties of the snowpack, The Cryosphere, 7, 1139-1160, doi:10.5194/tc-7-1139-2013, 2013. Wright ,P. , Bergin, M. , Dibb, J., Lefer, B., Domine, F., Carman, T. , Carmagnola, C., Dumont, M., Schaaf, C., Wang, Z. and Courville, Z. : Comparing MODIS daily snow albedo to spectral albedo field measurements in Central Greenland, Vol. 140, 118-129, 2014. Dumont, M., Brissaud, O., Picard, G., Schmitt, B., Gallet, J.-C., and Arnaud, Y.: High Accuracy measurement of snow Bidirectional Reflectance Distribution Function at visible and NIR wavelengths, Atm. Chem. and Phys., 10, 2507-2520, doi :10.5194/acp-10-2507-2010, 2010 Libois, Q., Picard, G., France, J.L., Arnaud, L., Dumont, M., Carmagnola, C.M., and King, M.D.: Grain shape influence on light extinction in snow, The Cryosphere,7, 1803-1818, doi : 10.5194/tc-7-1803-2013, 2013. , 2013 Vegetation Boulangeat, I., Georges, D. and Thuiller, W. (2014). FATE-HD: A spatially and temporally explicit integrated model for predicting vegetation structure and diversity at regional scale. Global Change Biology. Dullinger, S., Gattringer, A., Thuiller, W., Moser, D., Zimmermann, N.E., Guisan, A., Willner, W., Plutzar, C., Leitner, M., Mang, T., Caccianiga, M., Dirnbock, T., Ertl, S., Fischer, A., Lenoir, J., Svenning, J.-C., Psomas, A., Schmatz, D.R., Silc, U., Vittoz, P. and Hulber, K. (2012). Extinction debt of high-mountain plants under twenty-first-century climate change. Nature Climate Change,2, 619-622. Pottier, J., Malenovsky, Z., Psomas, A., Homolova, L., Schaepman, M.E., Choler, P.,Thuiller, W., Guisan, A. and Zimmermannn, N.E. Modelling plant species distribution and diversity in alpine grasslands using airborne imaging spectroscopy. Biology Letters (in revision). Carlson, B.Z., Randin, C.F., Boulangeat, I., Lavergne, S., Thuiller, W.,Choler, P.(2013). Working toward integrated models of alpine plant distribution. Alpine Botany, 123(2), 41-53. Carlson, B.Z., Georges D, Rabatel, A., Randin, C.F., Renaud, J., Delestrade, A., Zimmermann, N.E., Choler, P., Thuiller, W. (2014). Accounting for treeline shift, glacier retreat and primary succession in mountain plant distribution models.Diversity and Distributions.

Scientific contact

Name: Antoine RABATEL

PI email: antoine.rabatel@ujf-grenoble.fr

PI website: http://lgge.osug.fr