A new retrieval algorithm for soil moisture index from thermal infrared sensor on-board geostationary satellites over Europe and Africa and its validation - 2019
A new retrieval algorithm for soil moisture index from thermal infrared sensor on-board geostationary satellites over Europe and Africa and its validation
Geostationary; Land surface temperature; SEVIRI; Soil moisture; Thermal infrared; Validation; Meteosat second generations; Soil moisture monitoring; Soil moisture retrievals; Spaceborne remote sensing; Earth and Planetary Sciences (all)
Abstract :
[en] Monitoring soil moisture at the Earth'surface is of great importance for drought early warnings. Spaceborne remote sensing is a keystone in monitoring at continental scale, as satellites can make observations of locations which are scarcely monitored by ground-based techniques. In recent years, several soil moisture products for continental scale monitoring became available from the main space agencies around the world. Making use of sensors aboard polar satellites sampling in the microwave spectrum, soil moisture can be measured and mapped globally every few days at a spatial resolution as fine as 25 km. However, complementarity of satellite observations is a crucial issue to improve the quality of the estimations provided. In this context, measurements within the visible and infrared from geostationary satellites provide information on the surface from a totally different perspective. In this study, we design a new retrieval algorithm for daily soil moisture monitoring based only on the land surface temperature observations derived from the METEOSAT second generation geostationary satellites. Soil moisture has been retrieved from the retrieval algorithm for an eight years period over Europe and Africa at the SEVIRI sensor spatial resolution (3 km at the sub-satellite point). The results, only available for clear sky and partly cloudy conditions, are for the first time extensively evaluated against in-situ observations provided by the International Soil Moisture Network and FLUXNET at sites across Europe and Africa. The soil moisture retrievals have approximately the same accuracy as the soil moisture products derived from microwave sensors, with the most accurate estimations for semi-arid regions of Europe and Africa, and a progressive degradation of the accuracy towards northern latitudes of Europe. Although some possible improvements can be expected by a better use of other products derived from SEVIRI, the new approach developped and assessed here is a valuable alternative to microwave sensors to monitor daily soil moisture at the resolution of few kilometers over entire continents and could reveal a good complementarity to an improved monitoring system, as the algorithm can produce surface soil moisture with less than 1 day delay over clear sky and non-steady cloudy conditions (over 10% of the time).
Disciplines :
Earth sciences & physical geography
Author, co-author :
Ghilain, Nicolas ; Université de Liège - ULiège > Sphères ; Royal Meteorological Institute of Belgium, Brussels, Belgium
Arboleda, Alirio; Royal Meteorological Institute of Belgium, Brussels, Belgium
Batelaan, Okke ; College of Science and Engineering, Flinders University, Adelaide, Australia
Ardö, Jonas ; Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Trigo, Isabel ; Instituto do Mar e Atmosfera, Lisbon, Portugal
Barrios, Jose-Miguel; Royal Meteorological Institute of Belgium, Brussels, Belgium
Gellens-Meulenberghs, Francoise; Royal Meteorological Institute of Belgium, Brussels, Belgium
Language :
English
Title :
A new retrieval algorithm for soil moisture index from thermal infrared sensor on-board geostationary satellites over Europe and Africa and its validation
BELSPO - Belgian Federal Science Policy Office EUMETSAT - European Organization for the Exploitation of Meteorological Satellites
Funding text :
The authors thank the scientists who have contributed to build the soil moisture databases either in the context of FLUXNET or in ISMN and to share this extremely valuable information freely through accessible platforms.This research was funded by EUMETSAT and the European Space Agency through the PRODEX programme of the Belgian Science Policy
Taylor, C.; de Jeu, R.A.M.; Guichard, F.; Harris, P.P.; Dorigo,W. Afternoon rain more likely over drier soils. Nature 2012, 489, 423-426
Massari, C.; Brocca, L.; Barbetta, S.; Papathanasiou, C.; Mimikou, M.; Moramarco, T. Using globally available soil moisture indicators for flood modelling in Mediterranean catchments. Hydrol. Earth Syst. Sci. Discuss. 2013, 10, 10997-11033
Gil, M.; Garrido, A.; Hernandez-Mora, N. Direct and indirect economic impacts of drought in the agri-food sector in the Ebro River basin (Spain). Nat. Hazards Earth Syst. Sci. 2013, 13, 2679-2694
Turner, K.; Georgiou, S.; Clarck, R.; Brouwer, R.; Burke, J. FAO Water Report 27: Economic Valuation of Water Resources in Agriculture: From the Sectoral to a functional Perspective of Natural Resources Management; Technical Report; FAO: Rome, Italy, 2004
Hunsberger, C.; Evans, T.P.; Aide, T.M.; Montoro, J.A.; Borras, S.M.; del Valle, H.F.; Devisscher, T.; Jabbour, J.; Kant, S.; Lopez-Carr, D. et al. The Fifth Global Environmental Outlook Report, Chapter 3: Land; UNEP: Nairobi, Kenya, 2012; 32p. Available online: http://people.uncw.edu/pricopen/documents/GEO5_report_C3_Land. pdf (accessed on 20 August 2019)
Delworth, T.L.; Manabe, S. The influence of potential evaporation on the variabilities of simulated soil wetness and climate. J. Clim. 1988, 1, 523-547
Macauley, M.K. Earth Observations in Social Science Research for Management of Natural Resources and the Environment: Identifying the Landsat Contribution. J. Terr. Obs. 2009, 1, 31-51
Koster, R.D.; Houser, P.R.; Engman, E.T.; Kustas, W.P. Remote sensing may provide unprecedented hydrological data. Eos Trans. AGU 1999, 80, 156
Njoku, E.G.; Entekhabi, D. Passive microwave remote sensing of soil moisture. J. Hydrol. 1996, 184, 101-129
Bartalis, Z.; Wagner, W.; Naeimi, V.; Hasenauer, S.; Scipal, K.; Bonekamp, H.; Figa, J.; Anderson, C. Initial soil moisture retrieval from the METOP-A Advanced Scatterometer. Geophys. Res. Lett. 2007, 34, doi:10.1029/2007GL031088
Owe, M.; de Jeu, R.; Holmes, T. Multisensor historical climatology of satellite-derived global land surface moisture. J. Geophys. Res. 2008, 113, doi:10.1029/2007JF000769
Chesters, D. The Scientific Basis for the Advanced Geosynchronous Studies Program; Technical Report; NASA: Washington, DC, USA, 1998. Available online: http://goes.gsfc.nasa.gov/text/ags_science.html (accessed on 20 August 2019)
Wan, Z.M.; Dozier, J. A generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Trans. Geosci. Remote 1996, 34, 892-905
Sellers, W.D. Physical Climatology; The University of Chicago Press: Chicago, IL, USA, 1965
Blanchard, M.B.; Greeley, R.; Goettelman, R. Use of Visible, near Infrared and Thermal Infrared Remote Sensing; NASA Technical Report TM X-62343; NASA: Washington, DC, USA, 1974
Carlson, T.N.; Boland, F.E. Analysis of urban-rural canopy using a surface heat flux/temperature model. J. Appl. Meteorol. 1978, 17, 998-1013
Watson, K. Geologic applications of thermal infrared images. Proc. IEEE 1975, 63, 128-137
Becker, F. Thermal Infrared Remote Sensing Principles and Applications; Ispre Courses; A. A. Balkema: Varese, Italy, 1980
Price, J.C. On the analysis of thermal infrared imagery: The limited utility of apparent thermal inertia. Remote Sens. Environ. 1985, 18, 59-73
Abdellaoui, A.; Becker, F.; Olory-Hechinger, E. Use of Meteosat for mapping thermal inertia and evapotranspiration over a limited region of Mali. J. Clim. Appl. Meteorol. 1986, 25, 1489-1506
Price, J.C. The Potential of Remotely Sensed Thermal Infrared Data to Infer Surface Soil Moisture and Evaporation. Water Resour. Res. 1980, 16, 787-795
Carlson, T.N.; Dodd, J.K.; Benjamin, S.G.; Cooper, J.N. Satellite estimation of the surface energy balance, moisture availability and thermal inertia. J. Appl. Meteorol. 1981, 20, 67-87
Gillies, K.K.; Carlson, T.N. Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models. J. Appl. Meteorol. 1995, 34, 745-756
Wagner, W.; Naeimi, V.; Scipal, K.; de Jeu, R.; Martinez-Fernandez, J. Soil moisture from operational meteorological satellites. Hydrolgeol. J. 2007, 15, 121-131
Garcia, M.; I. Sandholt, P.C.; Ridler, M.; Mougin, E.; Kergoat, L.; Timouk, F.; Fensholt, R.; Domingo, F. Actual Evapotranspiration in Drylands derived from In-Situ and Satellite Data: Assessing Biophysical Constraints. Remote Sens. Environ. 2014, 131, 103-118
Zhao, W.; Li, A. A Downscaling Method for Improving the Spatial Resolution of AMSR-E Derived Soil Moisture Product Based on MSG-SEVIRI Data. Remote Sens. 2013, 5, 6790-6811
Song, X.; Leng, P.; Li, X.; Li, X.; Ma, J. Retrieval of daily evolution of soil moisture from satellite-derived land surface temperature and net surface shortwave radiation. Int. J. Remote Sens. 2013, 34, 3289-3298
Leng, P.; Song, X.; Li, Z.L.; Ma, J.; Zhou, F.; Li, S. Bare surface soil moisture retrieval from the synergistic use of optical and thermal infrared data. Int. J. Remote Sens. 2014, 35, 988-1003
Dorigo, W.A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Xaver, A.; Gruber, A.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; et al. The International Soil Moisture Network: A data hosting facility for global in situ soil moisture measurements. Hydrol. Earth Syst. Sci. 2011, 15, 1675-1698
Duguay-Tetzlaff, A.; Bento, V.A.; Göttsche, F.; Stöckli, R.; Martins, J.P.A.; Trigo, I.F.; Olesen, F.; Bojanowski, J.S.; da Camara, C.; Kunz, H. Meteosat Land Surface Temperature Climate Data Record: Achievable Accuracy and Potential Uncertainties. Remote Sens. 2015, 7, 13139-13156
Murray, T.; Verhoef, A. Moving towards a more mechanistic approach in the determination of soil heat flux from remote measurements-I. A universal approach to calculate thermal inertia. Agric. For. Meteorol. 2007, 147, 80-87
Mitra, D.S.; Majumdar, T.J. Thermal inertia mapping over the Brahmaputra basin, India using NOAA-AVHRR data and its possible geological applications. Int. J. Remote Sens. 2004, 25, 3245-3260
Coppola, A.; Basile, A.; Menenti, M.; Buonannno, M.; Colin, J.; Mascellis, R.D.; Esposito, M.; Lazzaro, U.; Magliulo, V.; Manna, P. Spatial distribution and structure of remotely sensed surface water content estimated by a thermal inertia approach. In Remote Sensing for Environmental Monitoring and Change Detection; Owe, M., Neale, C., Eds.; IAHS Publisher: Wallingford, UK, 2007; Volume 316; pp. 1-12
Verstraeten, W.W.; Veroustraete, F.; van der Sande, C.J.; Grootaers, I.; Feyen, J. Soil moisture retrieval using thermal inertia, determined with visible and thermal spaceborne data, validated for European forests. Remote Sens. Environ. 2006, 101, 299-314
Petropoulos, G.; Carlson, T.N.; Wooster, M.J.; Islam, S. A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture. Prog. Phys. Geogr. 2009, 33, 224-250
Van Doninck, J.; Peters, J.; De Baets, B.; De Clercq, E.; Ducheyne, E.; Verhoest, N.E.C. The potential of multitemporal Aqua and Terra MODIS apparent thermal inertia as a soil moisture indicator. Int. J. Appl. Earth Obs. 2011, 13, 934-941
Merlin, O.; Malbéteau, Y.; Notfi, Y.; Bacon, S.; Khabba, S.R.; Jarlan, L. Performance Metrics for Soil Moisture Downscaling Methods: Application to DISPATCH Data in Central Morocco. Remote Sens. 2015, 7, 3783-3807
Wetzel, P.J.; Atlas, D.;Woodward, R.H. Determining soil moisture from geosynchronous satellite infrared data: A feasibility study. J. Clim. Appl. Meteorol. 1984, 23, 375-391
Anderson, M.C.; Mecikalski, J.M.N.J.R.; Otkin, J.P.; Kustas,W.P. A climatological study of evapotranspiration and moisture stress across the continental U.S. based on thermal remote sensing: II. Surface moisture climatology. J. Geophys. Res. 2007, 112
Hain, C.R.; Mecikalski, J.R.; Anderson, M.C. Retrieval of an available water-based soil moisture proxy from thermal infrared remote sensing. Part I: Methodology and validation. J. Hydrometeorol. 2009, 10, 663-683
Parinussa, R.M.; Yilmaz, M.T.; Anderson, M.C.; Hain, C.R.; de Jeu, R.A.M. An intercomparison of remotely sensed soil oisture products at various spatial scales over the Iberian Peninsula. Hydrol. Process. 2014, 28, 4865-4876
Stisen, S.; Sandholt, I.; Noergaard, A.; Fensholt, R.; Jensen, K.H. Combining the triangle method with thermal inertia to estimate regional evapotranspiration-Applied to MSG-SEVIRI data in the Senegal River basin. Rem. Sens. Environ. 2008, 112, 1242-1255. doi:10.1016/j.rse.2007.08.013
Trigo, I.F.; DaCamara, C.C.; Viterbo, P.; Roujean, J.L.; Olesen, F.; Barroso, C.; de Coca, F.C.; Carrer, D.; Freitas, S.C.; Garcia-Haro, J.; et al. The Satellite Application Facility on Land Surface Analysis. Int. J. Remote Sens. 2011, 32, 2725-2744
Trigo, I.F.; Monteiro, I.T.; Olesen, F.; Kabsch, E. An assessment of remotely sensed land surface temperature. J. Geophys. Res. 2008, 113, doi:10.1029/2008JD010035
Freitas, S.C.; Trigo, I.F.; Bioucas-Dias, J.M.; Göttsche, F. Quantifying the Uncertainty of Land Surface Temperature Retrievals from SEVIRI/Meteosat. IEEE Trans. Geosci. Remote 2010, 48, 523-534
Göttsche, F. Validation of land surface temperature products with 5 years of permanent in-situ measurements in 4 different climate regions. In Proceedings of the EUMETSAT Meteorological Satellite Conference, Vienna, Austria, 16-20 September 2013
Ermida, S.L.; Trigo, I.F.; DaCamara, C.C.; Göttsche, F.M.; Olesen, F.S.; Hulley, G. Validation of remotely sensed surface temperature over an oak woodland landscape-The probel of viewing and illumination geometries. Remote Sens. Environ. 2014, 148, 16-27
Göttsche, F.; Olesen, F.; Trigo, I.F.; Bork-Unkelbach, A.; Martin, M.A. Long term validation of land surface temperature retrieved from MSG/SEVIRI with continuous in-situ measurements in Africa. Remote Sens. 2016, 8, 410
Rasmussen, M.O.; Pinheiro, A.C.; Proud, S.R.; Sandholt, I. Modeling Angular Dependences in Land Surface Temperatures From the SEVIRI Instrument Onboard the Geostationary Meteosat Second Generation Satellites. IEEE Trans. Geosci. Remote Sens. 2010, 48, 3123-3133
Grant, I.; Heyraud, C.; Breon, F.M. Continental scale hotspot observations of Australia at sub-degree angular resolution from POLDER. Int. J. Remote Sens. 2004, 25, 3625-3636
Prigent, C.; Aires, F.; Rossow, W.B.; Robock, A. Sensitivity of satellite microwave and infrared observations to soil moisture at a global scale: Relationship of satellite observations to in situ soil moisture measurements. J. Geophys. Res. 2005, 110, doi:10.1029/2004JD005094
Ermida, S.; Pires, A.; Trigo, I.F.; da Camara, C. Towards a Harmonized LST Product-The problem of angular anisotropy of LST. In Proceedings of the 6th LSA-SAFWorkshop, Reading, UK, 8-10 June 2015
Vinnikov, K.Y.; Yu, Y.; Goldberg, M.D.; Tarpley, D.; Romanov, P.; Laszlo, I.; Chen, M. Angular anisotropy of satellite observations of land surface temperature. Geophys. Res. Lett. 2012, 39
Vrugt, J.A.; Gupta, H.V.; Bouten,W.; Sorooshian, S. A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters. Water Resour. Res. 2003, 39
Paulik, C.; Dorigo,W.;Wagner,W.; Kidd, R. Validation of the ASCAT SoilWater Index using in situ datafrom the International Soil Moisture Network. Int. J. Appl. Earth Obs. Geoinf. 2014, 30, 1-8
Su, C.H.; Ryu, D.; Western, A.W.; Wagner, W. De-noising of passive and active microwave satellite soil moisture time series. Geophys. Res. Lett. 2013, 40, 3624-3630
Merbold, L.; Ardö, J.; Arneth, A.; Scholes, R.J.; Nouvellon, Y.; de Grandcourt, A.; Archibald, S.; Bonnefond, J.M.; Boulain, N.; Brueggemann, N.; et al. Precipitation as driver of 20 carbon fluxes in 11 African ecosystems. Biogeosciences 2009, 6, 1027-1041
Pellarin, T.; Laurent, J.; Cappelaere, B.; Decharme, B.; Descroix, L.; Ramier, D. Hydrological modelling and associated microwave emission of a semi-arid region in South-western Niger. J. Hydrol. 2009, 375, 262-272
Mougin, E.; Hiernaux, P.; Kergoat, L.; Grippa, M.; de Rosnay, P.; Timouk, F.; Dantec, V.L.; Demarez, V.; Lavenu, F.; Arjounin, M.; et al. The AMMA-CATCH Gourma observatory site in Mali: Relating climatic variations to changes in vegetation, surface hydrology, fluxes and natural resources. J. Hydrol. 2009, 375, 14-33. doi:10.1016/j.jhydrol.2009.06.045
Cappelaere, B.; Descroix, L.; Lebel, T.; Boulain, N.; Ramier, D.; Laurent, J.P.; Favreau, G.; Boubkraoui, S.; Boucher, M.; Moussa, I.B.; et al. The AMMA Catch observing system in the cultivated Sahel of South West Niger-Strategy, Implementation and Site conditions. J. Hydrol. 2009, 375, 34-51
de Rosnay, P.; Gruhier, C.; Timouk, F.; Baup, F.; Mougin, E.; Hiernaux, P.; Kergoat, L.; LeDantec, V. Multi-scale soil moisture measurements at the Gourma meso-scale site in Mali. J. Hydrol. 2009, 375, 241-252
Albergel, C.; Rüdiger, C.; Pellarin, T.; Calvet, J.C.; Fritz, N.; Froissard, F.; Suquia, D.; Petitpa, A.; Piguet, B.; Martin, E. From near-surface to root-zone soilmoisture using an exponential filter: An assessment of the method based on insituobservations and model simulations. Hydrol. Earth Syst. Sci. 2008, 12, 1323-1337
Calvet, J.C.; Fritz, N.; Froissard, F.; Suquia, D.; Petitpa, A.; Piguet, B. In situ soil moisture observations for the CAL/VAL of SMOS: The SMOSMANIA network. In Proceedings of the International Geoscience and Remote Sensing Symposium, Barcelona, Spain, 23-28 July 2007; pp. 1196-1199
Sánchez, N.; Martinez-Fernandez, J.; Scaini, A.; Perez-Gutierrez, C. Validation of the SMOS L2 Soil Moisture Data in the REMEDHUS Network (Spain). IEEE Trans. Geosci. Remote Sens. 2012, 50, 1602-1611
Sánchez-Ruiz, S.; Piles, M.; Sánchez, N.; Martinez-Fernandez, J.; Vall-llossera, M.; Camps, A. Combining SMOS with visible and near/shortwave/thermal infrared satellite data for high resolution soil moisture estimates. J. Hydrol. 2014, 516, 273-283
Bircher, S.; Skou, N.; Jensen, K.; Walker, J.; Rasmussen, L. A soil moisture and temperature network for SMOS validation in Western Denmark. Hydrol. Earth Syst. Sci. Discuss. 2011, 8, 991-10006
Brocca, L.; Hasenauer, S.; Lacava, T.; Melone, F.; Moramarco, T.; Wagner, W.; Dorigo, W.; Matgen, P.; Martinez-Fernandez, J.; Llorens, P.; et al. Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe. Remote Sens. Environ. 2011, 115, 3390-3408
Brocca, L.; Melone, F.; Moramarco, T. On the estimation of antecedent wetness condition in rainfall-runoff modelling. Hydrol. Process. 2008, 22, 629-642
Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R. Antecedent wetness conditions based on ERS scatterometer data. J. Hydrol. 2009, 364, 73-87
Loew, A.; Dall'Amico, J.T.; Schlenz, F.; Mauser, W. The Upper Danube soil moisture validation site: Measurements and activities. In Proceedings of the Earth Observation and Water Cycle Conference, Frascati, Italy, 18 November 2009
Albergel, C.; de Rosnay, P.; Gruhier, C.; Munoz-Sabater, J.; Hasenauer, S.; Isaksen, L.; Kerr, Y.;Wagner,W. Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations. Remote Sens. Environ. 2012, 118, 215-226
Srivastava, P.; Petropoulos, G.P.; Kerr, Y. Satellite Soil Moisture Retrieval, 1st ed.; Techniques and Applications; Elsevier: Amsterdam, The Netherlands, 2016; pp. 1-448
Hahn, S. Product Validation Report: H-SAF H25 Metop ASCAT DR2015 SSM Time Series 12.5 km Sampling. 2016. Available online: http://hsaf.meteoam.it/documents/PVR/H25_ASCAT_SSM_CDR_PVR_v0.1.pdf (accessed on 20 August 2019)
Taylor, K.E. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. 2001, 106, doi:10.1029/2000JD900719
Peel, M.C.; Finlayson, B.L.; McMahon, T.A. Updated world map of the Köppen-Geiger climate classification. Hydrol. Earth Syst. Sci. 2007, 11, 1633-1644
Crow,W.; Berg, A.A.; Cosh, M.H.; Loew, A.; Mohanty, B.P.; Panciera, R.; De Rosnay, P.; Ryu, D.;Walker, J. Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products. Rev. Geophys. 2012, 50, doi:10.1029/2011RG000372
Maton, L. Représentation et Simulation des Pratiques Culturales des Agriculteurs à L'échelle Régionale pour Estimer la Demande en eau D'irrigation. Ph.D. Thesis, Institut National Polytechnique de Toulouse, Toulouse, France, 2006
Veroustraete, F.; Li, Q.; Verstraeten, W.W.; Chen, X.; Bao, A.; Dong, Q.; Liu, T.; Willems, P. Soil moisture content retrieval based on apparent thermal inertia for Xinjiang province in China. Int. J. Remote Sens. 2012, 33, 3870-3885
Piles, M.; Petropoulos, G.P.; Sanchez, N.; Gonzalez-Zamora, A.; Ireland, G. Towards improved spatio-temporal resolution soil moisture retrievals from the synergy of SMOS and MSG SEVIRI spaceborne observations. Remote Sens. Environ. 2016, 180, 403-417
Peng, J.; Niesel, J.; Loew, A. Evaluation of soil moisture downscaling using a simple thermal-based proxy-The REMEDHUS network (Spain) example. Hydrol. Earth Syst. Sci. 2015, 19, 4765-4782
Maltese, A.; Capodici, F.; Ciraolo, G.; Loggia, G.L. SoilWater Content Assessment: Critical Issues Concerning the Operational Application of the Triangle Method. Remote Sens. 2015, 15, 6699-6718
Castaldi, S.; de Grandcourt, A.; Rasile, A.; Skiba, U.; Valentini, R. CO2, CH4 and N2O fluxes from soil of a burned grassland in Central Africa. Biogeosciences 2010, 7, 3459-3471
Legrand, M.; Plana-Fattori, A.; N'doumé, C. Satellite detection of dust using the IR imagery of Meteosat 1. Infrared difference dust index. J. Geophys. Res. 2001, 106, 18251-18274
Kaurila, T.; Hagard, A.; Persson, R. Aerosol extinction models based on measurements at two sites in Sweden. Appl. Opt. 2006, 45, 6750-6761
Mogili, P.K.; Yang, K.H.; Young, M.A.; Kleiber, P.D.; Grassian, V.H. Extinction spectra of mineral dust aerosol components in an environmental aerosol chamber: IR resonance studies. Atmos. Environ. 2008, 42, 1752-1761
Laskina, O.; Young, M.A.; Kleiber, P.D.; Grassian, V.H. Infrared extinction spectra of mineral dust aerosol: Single components and complex mixtures. J. Geophys. Res. 2012, 117
Ben-Ami, Y.; Koren, I.; Rudich, Y.; Artaxo, P.; Martin, S.T.; Andreae, M.O. Transport of North African dust from the Bodélé depression to the Amazon Basin: A case study. Atmos. Chem. Phys. 2010, 10, 7533-7544
Carrer, D.; Roujean, J.L.; Hautecoeur, O.; Elias, T. Daily estimates of aerosol optical thickness over land surface based on a directional and temporal analysis of SEVIRI MSG visible observations. J. Geophys. Res. 2010, 115
Carrer, D.; Ceamenos, X.; Six, B.; Roujean, J.L. AERUS-GEO: A newly available satellite-derived aerosol optical depth product over Europe and Africa. Geophys. Res. Lett. 2014, 41, 7731-7738