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Aircraft name: CASA 212 RS - INTA
Airport: The study area is located in the Brussels capital region and partially in the Brabant province of the Flanders region (Belgium). The study site (see below for coordinates) covers the upper part of the Woluwe river catchment, a confluent of the Senne river. The Woluwe river is groundwater-fed (sources situated in the Sonian forest), the central part is highly fragmented with. It is an urbanized catchment of great ecological interest due to the presence of extensive forest and pond ecosystems. An advantage of this study area is the fact that has been the object of study of extencive hydro-ecological and hyperspectral research (CASI) during the past years, for which a lot of field measurements, a hyperspectral acquisition (CASI) as well as simulations have been carried out. Coordinates (Geographic, WGS84): ULcorner : 50°52'0"N, 4°21'50"E URcorner : 50°52'0"N, 4°33'10"E Llcorner : 50°46'10"N, 4°21'50"E Lrcorner : 50°46'10"N, 4°33'10"E Bibliografic references: Canters F., Chormansky J., Van de Voorde T. and Batelaan O., 2006. Effects of different methods for estimating impervious surface cover on runoff estimation at catchment level. In proceedings of Accuracy 2006, 7th International Symposium on Spatial Accuracy Assesment in Natural Resources and Environmental Sciences. Edited by M. Caetano and M. Painho, pp. 557-566. Chormanski J., Van de Voorde T., De Roeck T., Batelaan O. and Canters F., 2008. Improving distributed runoff prediction in urbanized catchments with remote sensing based estimates of impervious surface cover. Sensors, 8: 910-932. Chormanski J., 2005. Tools for hydrological modelling of the Woluwe catchment. Upper-Woluwe report (Research in Brussels 2004), VUB. Pirnay J. P., Matthijs S., Colak H., Chablain P., Bilocq F., Van Eldere J., De Vos D., Zizi M., Triest L. and Cornelis P., 2005. Global Pseudomonas aeruginosa biodiversity as reflected in a Belgian river. Environmental Microbiology, 7:969-980. Rimaviciute E., 2003. Tools for integrated water management of the Woluwe catchment: hydro-geological model and ecological indicators for sustainable management of the river-pond system (Blue plan) Project Final Report (Research in Brussels 2002), VUB Triest L., Kaur P., Heylen S. and De Pauw N., 2001. Comparative monitoring of diatoms, macroinvertebrates and macrophytes in the Woluwe River (Brussels, Belgium). Aquatic Ecology, 35: 183-194
Project theme: The use of hyperspectral data to characterize and monitor the (ecological) status of water and forest ecosystems in the Woluwe valley (Brussels, Belgium).
Science context: Monitoring of water and energy fluxes is a requirement for the assessment of climate and anthropogenic effects on natural ecosystems. These fluxes are the result of the physical functioning and interaction between the soil, vegetation and atmosphere transfers (SVAT). Measurements and models are needed to describe this interaction on different scales. In physically based, distributed hydrological models SVATâs schemes play an important role. Essential in these SVATâs are the state of water and energy levels in a spatially distributed way. Due to the high spectral and spatial resolution, imaging spectroscopy is seen as a promising technique for assessing some of the required parameters for the distributed modelling. In particular remotely sensed thermal infrared information has proven to be useful for (1) evapotranspiration estimation and (2) the evaluation of ecosystem physiological activity, functioning and health. However these analyses are often just a snapshot of the situation at a certain moment in time. Therefor a temporal analysis, using several thermal data acquisitions with the same sensor, is proposed. Hyperspectral analysis of diurnal and seasonal variations would significantly improve the understanding of water and forest ecosystem functioning, state and dynamics in the Woluwe valley. In addition the experiment will be closely linked to the on-going HyperEnv project (Hyperspectral remote sensing for environment and water management), which will broaden at the same time the users group and applications, i.e. (1) Land-cover mapping in the urban fringe, (2) hyperspectral RS assimilation for hydrological modeling and (3) characterization of turbidity and aquatic vegetation of pond ecosystems.
Measurements to be made by aircraft: Kustas and Norman (1996) stated the necessity to monitor water and energy fluxes for the assessment of climate and anthropogenic effects on natural ecosystems. These water and energy levels are essential in describing the SVATâs. Due to its importance especially the evapotranspiration flux deserves to receive the necessary attention. Surface temperature and vegetation indices have successfully been used for the estimation of remotely sensed evapotranspiration (Kustas and Norman, 1996 & 2000; Bastiaansen et al., 1998; Su, 2001). However these analyses are often just a snapshot of the situation at a certain moment in time. A temporal analysis, using several thermal data acquisitions of the same sensor, would significantly improve the understanding of the ecosystem functioning, state and dynamics (Sticksel et al., 2004). Therefor an experiment is proposed, using hyperspectral imagery with thermal bands, to estimate the energy and water fluxes for the Woluwe valley in a spatially distributed way and for different moments in time. This temporal analysis is proposed for different temporal scales, considering diurnal and seasonal variation. This will be done on a scale, which allows discriminating local wetness and vegetation heterogeneity in relation to differences in soil and vegetation condition. Additionally, this thermal data will also be used to derive a number of ecosystem parameters/indicators for the state (health) of the forest area in the southern part of the Woluwe valley. Within the framework of previous hyperspectral projects thermal data from the ATM (Airborne Thematic Mapper) and the AHS (Airborne Hyperspectral Scanner) sensors were already successfully used for surface temperature estimation in a groundwater-fed wetland (Batelaan, Hung & Verbeiren, 2005; Palmans & Batelaan, In preparation). The results of this IS interpretation served as an input for an evapotranspiration simulation with the Surface Energy Balance Algorithm for Land (SEBAL). SEBAL is an image-processing model, meaning that the main input data consists of spectral radiance data, more specifically spectral bands in the visible, near-infrared and thermal infrared part of the electromagnetic spectrum. Next to the spectral data, the SEBAL model also requires routine weather data parameters; the wind speed, humidity, solar radiation and air temperature (Bastiaansen et al., 1998). To enable the study of the diurnal and seasonal variation of the evapotranspiration for different landcover types a temporal analysis is proposed. This analysis implies a surface temperature estimation and evapotranspiration simulation with SEBAL for all datasets acquired at different moments in time, with the AHS. As stated by Moran (2000) and Samson and Lemeur (2000), the use of thermal infrared information can also play a useful role in the evaluation of ecosystem physiological activity, functioning and health. The surface temperature of an ecosystem is believed to give a spatially integrated response of all factors, which influence the physiological and physical canopy behavior. Several authors (Allen et al., 2001; Kay et al., 2001; Kutsch et al., 2001; Muys et al., 2003; Nichol, 1995; Wagendorp et al., 2003; Luvall & Holbo, 1989) used surface temperature and other derived parameters as indicators for the organizational state and functioning of ecosystems. Based on the thermal AHS data 3 thermal indicators for the ecosystem state and functioning of the forest area in the Woluwe valley will be derived: (1) surface temperature T, (2) Thermal Response Number - TRN and (3) Solar exergy dissipation - SED (Wagendorp et al., 2006). The proposed temporal approach will enable the estimation of possible diurnal and seasonal variation and effects, improving significantly the understanding of the ecosystem functioning in the Woluwe valley and forest area. In addition the requested airborne data (AHS) will also be used by a wider user group within the framework of the linked HyperEnv project (Hyperspectral remote sensing for environment and water management). The applications from the HyperEnv project, using hyperspectral CHRIS-PROBA data, completely fit into the experiment set-up of monitoring water and energy fluxes, but are very complemenary to those proposed in the experiment above. The HyperEnv research topics are: (1) land-cover mapping using novel approaches for image information extraction, (2) monitoring and modeling urban change in urbanized catchments, (3) RS supported hydrological modeling using RS information on land cover, imperviousness, wetness and thermal conditions, (4) assessing water turbity of ponds in Woluwe valley, (5) characterizing and mapping aquatic vegetation. (For details see âHyperEnv_Project-summary.pdfâ in section âRelated documentsâ). The link with the HyperEnv project does not only offer the asset of clustering efforts and creating a large set of ground truth data for the moment of requested airborne acquisition, but also creates a significant added value due to the possibility of combining both hyperspectral datasets with different spatial resolutions (CHRIS-PROBA: 18m - AHS: 2.5-10m) for sub-pixel and/or sharpening applications. Bibliografic references Allen TFH, Havlicek T, Norman J. Wind tunnel experiments to measure vegetation temperature to indicate complexity and functionality. In: Ulgiati S, editor. Advances in energy studies 2000: exploring supplies, constraints, and strategies, Porto Venere, Italy, 2001. p. 135â45. Bastiaanssen W.G.M., Menenti M., Feddes R.A., Holtslag A.A.M. (1998). A remote sensing surface energy balance algorithm for land (SEBAL) 1. Formulation. Journal of Hydrology, 213: 198-212 Batelaan, O., Hung, L.Q. and Verbeiren, B., 2005, CASI-ATM observed and simulated ecohydrological relevant water and energy fluxes. In Zagajewski, B. and Sobczak, M. (Eds.), New quality in environmental studies, Proceedings of 4th EARSeL Workshop on Imaging Spectroscopy, pp. 309-316. Kay JJ, Allen T, Fraser R, Luvall JC, Ulanowicz R. Can we use energy based indicators to characterize and measure the status of ecosystems, human, disturbed and natural?. In: Ulgiati S, editor. Advances in energy studies 2000: exploring supplies, constraints, and strategies, Porto Venere, Italy, 2001. p. 121â33. Kustas, W.P. and Norman, J.M., 1996. Use of remote sensing for evapotranspiration monitoring over land surfaces. Hydrological Sciences Journal, 41(4): 495-516. Kutsch WL, Steinborn W, Herbst M, Baumann R, Barkmann J, Kappen L. 2001. Environmental indication: a field test of an ecosystem approach to quantify biological self-organization. Ecosystems 2001;4:49â66. Luvall JC, Holbo HR. Measurements of short-term thermal responses of coniferous forest canopies using thermal scanner data. Remote Sensing Environ 1989;27:1â10. Moran MS. Thermal infrared measurements as an indicator of plant ecosystem health. ASDA-ARS Southwest Watershed Research Center, 2000 E. Allen Rd. Tucson, Arizona 85719; 2000. Muys B, Wagendorp T, Aerts R, Garcia Quijano J. Ecological sustainability assessment of carbon conservation, sequestration and substitution projects using the exergy concept. In: Conference internationale sous la Presidence belge de lâUnion Europeenne, Liege, October 2001. Region Wallonne, Direction generale des resources naturelles et de lâenvironment, Division de la nature et des foreËts, Namur, Belgium, vol. 26. Travaux; 2003. p. 67â85. Nichol JE. Monitoring tropical rain forest microclimate. Photogrammetric Eng Remote Sensing 1995;61(9):1159â65. Palmans, T. & Batelaan O. (In preparation), Estimating evapotranspiration with the SEBAL Model for the Doode Bemde Wetland in Belgium: An Application of AHS Sensor Data. Samson R, Lemeur R. The role of surface temperature in the simulation of forest canopy photosynthesis. In: Ceulemens R, editor. Forest ecosystem modeling, upscaling and remote sensing. The Hague: SPB Academic Publishing; 2000. p. 69â86. Sticksel, E. Schächtl, J., et al. (2004). Diurnal Variation in Hyperspectral Vegetation Indices Related to Winter Wheat Biomass Formations. Precision Agrilculture, 5 (5): 509-520. Su, Z. (2002). The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes, Hydrol. Earth Syst. Sci., 6, 85â100. Wagendorp T, Rodriguez-Urbieta TI, Devriendt K, Gulinck H, Coppin P, Muys B. Thermal characterisation of land use impact at landscape scale. 3rd EARSeL workshop on imaging spectroscopy, Oberpfaffenhofen, Germany 2003 p. 284â96.
Season: The time windows were chosen in function of: (1) the planned CHRIS-PROBA acquisitions (2009 and 2010) and related extensive field campaign in the summer of 2009, (2) need for cloudfree summer days with unlimited incoming sun-radition for a successful retrieval of the surface temperature. (3) the growing season and bloom period of algae, cyanobacteria and submerged aquatic vegetation. Originally proposed dates: > Period 1: 18 June - 08 July 2009 (3 data acquisitions on 1 day) > Period 2: 01 - 20 August 2009 (3 data acquisitions on 1 day) After discussion with TA Coordinator Phil Brown who raised some issues on the short notice of the requested acquisitions, we extended the acceptable dates to the year 2010 (same periods). The related project will still be ongoing. However, we still would like to stress the strong added value of an aquisition during the already planned and confirmed extensive field campaign and therefor we hope that acquisitions would still be possible in August 2009.
Weather constraints: The proposed remote sensing activities require clear sky conditions, although some Cumulus clouds can be accepted if not positioned on the crucial target area. Windless conditions are preferable, as high wind velocities may influence the heat transfer and as such disturb the measurements.
Time constraints: The chosen time windows in summer were mainly motivated by: 1) Planned CHRIS-PROBA acquisitions (ESA Data Cat1 proposal was approved) in the summer of 2009 (Second half of June AND First half of August), including an extensive field campaign for ground truthing (HyperEnv Project). Most probably these will be repeated in the summer of 2010. 2) As stated by Kutsch et al. (2001), surface temperature data are very sensitive to 'abiotic noise', mainly wind and sudden changes in air temperature and cloud cover. Therefore, cloudless and windless summer days with unlimited incoming sun-radiation are to be preferred for taking surface temperature measurements (Wagendorp et al., 2006). 3) Growing season of aquatic vegetation (summer) and bloom of algae in June and cyano-bacteria in August (HyperEnv Project) - Under-pass CHRIS-PROBA: a flight-date as close a possible to the CHRIS-PROBA under-passes is preferred (re-visit time: 7 days). - For the DIURNAL analysis a comparison of an early flight ('minimum' energy conditions) with a flight around solar noon ('maximum' energy conditions) is crucial, enabling the study of diurnal variation of surface temperature and indirectly evapotranspiration. Therefor following data acquisitions (3) are requested: 1/ Early morning (close to sunrise) Flights 2/ and 3/ should be flown around solar noon. In order to be able to determine the thermal inertia data acquisitions 2 and 3 should be flown within a short time span! e.g. 12 pm and 1 am. A small shift in flight times is acceptable. - For the SEASONAL analysis 2 flight periods are requested: 1/ start summer (2nd half of June) 2/ mid/end summer (1st half of August) For BOTH periods the above diurnal scheme is requested. If only 1 of the flight period is possible preference is given to the period in August. Bibliografic references Kutsch WL, Steinborn W, Herbst M, Baumann R, Barkmann J, Kappen L. 2001. Environmental indication: a field test of an ecosystem approach to quantify biological self-organization. Ecosystems 2001;4:49â66. Wagendorp, T., H. Gulinck, P. Coppin and B. Muys, 2006. Land use impact evaluation in life cycle assessment based on ecosystem thermodynamics. Energy 31: 112-125.
Flights (number and patterns): For the temporal approach (seasonal AND diurnal) 2 x 3 acquisitions are proposed: 1/ JUNE (2nd half): early morning, 12 pm, 1 pm 2/ AUGUST (1st half): early morning, 12 pm, 1 pm So, SIX acquisitions in total. If it would appear that this scheme is not completely feasible a downscaling of the flight campaign can of course be discussed. In that case the period of August is preferred. Due to the high level of fragmentation (numerous narrow ponds, urban elements, etc.) in the urbanized Woluwe catchment a high spatial resolution (2.5 to 10m) is required. As a result the flight height will vary between 975m and 4000m (see also section âOther constraints or requirementsâ). The number of flight lines will of coarse depend on the flight height, but the study site to cover is 10 km long and 13 km wide. The orientation of the flight lines preferably should be as much as possible into the solar plane (+/- N-S, S-N flight pattern) for homogenous illumination.
Instruments: AHS-160 and of course any instruments needed for geometric and/or atmospheric correction (e.g. POSAV410 which offers data on aircraft position, velocity, pitch, roll, etc.) No extra needed inside aircraft
Other constraints: Due to the vicinity of the airport of Zaventem (in the north) there might be some restricitions towards the flight plan (height, orientation). However, a flight should not be a problem as in 2002 an airborne CASI capaign took place for the Woluwe valley! But this issue should be taken into account during the flight planning.
Name: Okke BATELAAN
PI email: batelaan@vub.ac.be
PI website: http://homepages.vub.ac.be/~batelaan/