Abstract
This study presents the SALBEC – Soil ALBEdo Calculator – a Python library and Graphical User Interface designed to predict the diurnal variation of the clear-sky albedo based on the soil surface properties. Such predictions are becoming more and more necessary with the increasing role of remote measurements. The software uses the following input parameters: the soil spectrum, soil roughness, day of the year (DOY) and sample location. It returns the diurnal albedo variation and, as a unique feature, optimal observation time in the form of tables and graphs as out-puts. Models created with the SALBEC were compared with the data acquired under near clear-sky conditions. The comparison shows that the differences between the models and measured data do not exceed the variation of input parameters. The software is directed towards scientists and professionals who require precise estimations of the albedo of soils for different field observation times. Our software is issued as free and open source software (FOSS) and is publicly available at https://github.com/jarekj71/salbec.
References
Ben-Dor E., Goldlshleger N., Benyamini Y., Agassi M., Blumberg D.G., 2003. The spectral reflectance properties of soil structural crusts in the 1.2 to 2.5-μm spectral region. Soil Science Society of America Journal 67(1): 289–299. DOI 10.2136/sssaj2003.2890.
Boudoire G., Liuzzo M., Cappuzzo S., Giuffrida G., Cosenza P., Derrien A., Falcone E.E., 2020. The SoilExp software: an open-source Graphical User Interface (GUI) for post-processing spatial and temporal soil surveys. Computers and Geosciences 142(September): 104553. DOI 10.1016/j.cageo.2020.104553.
Bunting P., Clewley D., Lucas R.M., Gillingham S., 2014. The Remote Sensing and GIS Software Library (RSGISLib). Computers and Geosciences 62(January): 216–226. DOI 10.1016/j.cageo.2013.08.007.
Canisius F., Wang S., Croft H., Leblanc S.G., Russell H.A.J., Chen J., Wang R., 2019. A UAV-based sensor system for measuring land surface albedo: tested over a boreal peatland ecosystem. Drones 3(1): 27. DOI 10.3390/ drones3010027.
Cao C., Lee X., Muhlhausen J., Bonneau L., Xu J., 2018. Measuring landscape albedo using unmanned aerial vehicles. Remote Sensing 10(11) 1820. DOI 10.3390/rs10111812.
Chimklai P., Hagishima A., Tanimoto J., 2004. A computer system to support Albedo Calculation in urban areas. Building and Environment 39(10): 1213–1221. DOI 10.1016/j.buildenv.2004.02.006.
Cierniewski J., Ceglarek J., 2018. Annual dynamics of short-wave radiation of bare arable lands on a global scale incorporating their roughness. Environmental Earth Sciences 77(23). DOI 10.1007/s12665-018-7956-7.
Cierniewski J., Ceglarek J., Karnieli A., Ben-Dor E., Królewicz S., Kaźmierowski C., 2018a. Shortwave radiation affected by agricultural practices. Remote Sensing 10(3): 419. DOI 10.3390/rs10030419.
Cierniewski J., Ceglarek J., Kaźmierowski C., 2018b. Estimating the diurnal blue-sky albedo of soils with given roughness using their laboratory reflectance spectra. Journal of Quantitative Spectroscopy and Radiative Transfer 217(September): 213–223. DOI 10.1016/j.jqsrt.2018.06.003.
Cierniewski J., Ceglarek J., Kaźmierowski C., Roujean J.-L., 2019. Combined use of remote sensing and geostatistical data sets for estimating the dynamics of shortwave radiation of bare arable soils in Europe. International Journal of Remote Sensing 40(5-6): 2359–2374. DOI 10.1080/01431161.2018.1474530.
Cierniewski J., Jasiewicz J., 2020. Optimizing the observation time for bare arable land to determine mean diurnal albedo in relation to roughness. International Journal of Remote Sensing. DOI 10.1080/01431161.2020.1828661.
Cierniewski J., Karnieli A., Kuśnierek K., Goldberg A., Herrmann I., 2013. Approximating the average daily surface albedo with respect to soil roughness and latitude. International Journal of Remote Sensing 34(9–10): 3416–3424. DOI 10.1080/01431161.2012.716530.
Cierniewski J., Kaźmierowski C., Królewicz S., 2015. Evaluation of the effects of surface roughness on the relationship between soil BRF data and broadband albedo. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8(4): 1528–1533. DOI 10.1109/ JSTARS.2014.2361924.
Cierniewski J., Roujean J.-L., Jasiewicz J., Królewicz S., 2021 Seasonal net shortwave radiation of Bare Arable Land in Poland and Israel according to roughness and atmospheric irradiance. Remote Sensing 13: 1897. DOI 10.3390/ rs13101897.
Enriquez R., Zarzalejo L., Jiménez M.J., Heras M.R., 2012. Ground reflectance estimation by means of horizontal and vertical radiation measurements. Solar Energy 86(11): 3216–3226. DOI 10.1016/J.SOLENER.2012.07.020.
Farmer G.T., Cook J., 2013. Climate change science: a modern synthesis: volume 1-the physical climate. Vol. 1. Springer Science & Business Media, Dordrecht. DOI 10.1007/978-94-007-5757-8.
Frasner R.S., 1975. Interaction mechanisms – within the atmosphere. In: Manual of remote sensing. American Society of Photogrammetry, Falls Church: 181–233.Cierniewski J., Roujean J.-L., Jasiewicz J., Królewicz S., 2021 Seasonal net shortwave radiation of Bare Arable Land in Poland and Israel according to roughness and atmospheric irradiance. Remote Sensing 13: 1897. DOI 10.3390/ rs13101897.
Farmer G.T., Cook J., 2013. Climate change science: a modern synthesis: volume 1-the physical climate. Vol. 1. Springer Science & Business Media, Dordrecht. DOI 10.1007/978-94-007-5757-8.
Frasner R.S., 1975. Interaction mechanisms – within the atmosphere. In: Manual of remote sensing. American Society of Photogrammetry, Falls Church: 181–233.
Govaerts Y.M., Lattanzio A., 2007. Retrieval error estimation of surface albedo derived from geostationary large band satellite observations: application to meteosat-2 and meteosat-7 data. Journal of Geophysical Research 112(D5): D05102. DOI 10.1029/2006JD007313.
Grant I.F., Prata A.J., Cechet R.P., 2000. The impact of the diurnal variation of albedo on the remote sensing of the daily mean albedo of grassland. Journal of Applied Meteorology 39(2): 231–244. DOI 10.1175/1520-0450(2000)039<0231:TI-OTDV>2.0.CO;2.
Gueymard C., 1987. An anisotropic solar irradiance model for tilted surfaces and its comparison with selected engineering algorithms. Solar Energy 38(5): 367–386. DOI 10.1016/0038-092X(87)90009-0.
Gueymard C., 1993. Mathermatically integrable parameterization of clear-sky beam and global irradiances and its use in daily irradiation applications. Solar Energy 50(5): 385–397. DOI 10.1016/0038-092X(93)90059-W.
Gueymard C.A., 2009. Direct and indirect uncertainties in the prediction of tilted irradiance for solar engineering applications. Solar Energy 83(3): 432–444. DOI 10.1016/J. SOLENER.2008.11.004.
Hastie, T., Tibshirani R., Friedman J., 2009. The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media, New York.
Hay J.E., 1993. Calculating solar radiation for inclined surfaces: practical approaches. Renewable Energy 3(4–5): 373– 380. DOI 10.1016/0960-1481(93)90104-O.
He T., Gao F., Liang S., Peng Y., 2019. Mapping climatological bare soil albedos over the contiguous United States using MODIS data. Remote Sensing 11(6): 666. DOI 10.3390/rs11060666.
Ineichen P., Guisan O., Perez R., 1990. Ground-reflected radiation and albedo. Solar Energy 44(4): 207–214. DOI 10.1016/0038-092X(90)90149-7.
Leroy M., Deuzé J.L., Bréon F.M., Hautecoeur O., Herman M., Buriez J.C., Tanré D., Bouffiès S., Chazette P., Roujean J.L., 1997. Retrieval of atmospheric properties and surface bidirectional reflectances over land from POLDER/ADEOS. Journal of Geophysical Research: Atmospheres 102(D14): 17023–17037. DOI 10.1029/96JD02662.
Liang S., Wang K., Zhang X., Wild M., 2010. Review on estimation of land surface radiation and energy budgets from ground measurement, remote sensing and model simulations. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 3(3): 225–240. DOI 10.1109/JSTARS.2010.2048556.
Liu B.Y., Jordan R.C., 1963. The long-term average performance of flat-plate solar-energy collectors: with design data for the US, its outlying possessions and Canada. Solar energy 7(2): 53–74. DOI 10.1016/0038-092X(63)90006-9.
Lucht W., Schaaf C.B., Strahler A.H., 2000. An algorithm for the retrieval of albedo from space using semiempirical BRDF models. IEEE Transactions on Geoscience and Remote Sensing 38(2 II): 977–998. DOI 10.1109/36.841980.
Monteith J.L., Szeicz G., 1961. The radiation balance of bare soil and vegetation. Quarterly Journal of the Royal Meteorological Society 87(372): 159–170. DOI 10.1002/ qj.49708737205.
Nkemdirim L.C., 1972. A note on the albedo of surfaces. Journal of Applied Meteorology 11(5), 867–874. DOI 10.1175/1520-0450(1972)011<0867:ANOTAO>2.0.CO;2.
Oguntunde P.G., Ajayi A.E., van de Giesen N., 2006. Tillage and surface moisture effects on bare-soil albedo of a tropical loamy sand. Soil and Tillage Research 85(1–2): 107–114. DOI 10.1016/j.still.2004.12.009.
Oren M., Nayar S.K., 1995. Generalization of the Lambertian Model and implications for machine vision. International Journal of Computer Vision V14(3): 227–251. DOI 10.1007/ BF01679684.
Ortega-Farías S., Ortega-Salazar S., Poblete T., Kilic A., Allen R., Poblete-Echeverría C., Ahumada-Orellana L., Zuñiga M., Sepúlveda D., 2016. Estimation of energy balance components over a drip-irrigated olive orchard using thermal and multispectral cameras placed on a helicopter-based unmanned aerial vehicle (UAV). Remote Sensing 8(8). DOI 10.3390/rs8080638.
Peddle D.R., Peter White H., Soffer R.J., Miller J.R., LeDrew E.F., 2001. Reflectance processing of remote sensing spectroradiometer data. Computers and Geosciences 27(2): 203–213. DOI 10.1016/S0098-3004(00)00096-0.
Qu Y., Liu Q., Liang S., Wang L., Liu N., Liu S., 2014. Direct-estimation algorithm for mapping daily land-surface broadband albedo from modis data. IEEE Transactions on Geoscience and Remote Sensing 52(2): 907–919. DOI 10.1109/TGRS.2013.2245670.
Rossel R.A.V., 2009. The soil spectroscopy group and the development of a global soil spectral library. In: EGU general assembly conference abstracts, Vienna, 19–24 April 2009, 14021.
Rossel R.A.V., Behrens T., Ben-Dor E., Brown D.J., Demattê J.A.M., Shepherd K.D., Shi Z., et al., 2016. A global spectral library to characterize the world’s soil. Earth-Science Reviews 155:198–230. DOI 10.1016/j.earscirev.2016.01.012.
Schaepman-Strub G., Schaepman M.E., Painter T.H., Dangel S., Martonchik J.V., 2006. Reflectance quantities in optical remote sensing-definitions and case studies. Remote Sensing of Environment 103(1): 27–42. DOI 10.1016/j.rse.2006.03.002.
Sellers P.J., Meeson B.W., Hall F.G., Asrar G., Murphy R.E., Schiffer R.A., Bretherton F.P., et al., 1995. Remote sensing of the land surface for studies of global change: models – algorithms – experiments. Remote Sensing of Environment 51(1): 3–26. DOI 10.1016/0034-4257(94)00061-Q.
Stevens A., Nocita M., Tóth G., Montanarella L., van Wesemael B., 2013. Prediction of soil organic carbon at the European Scale by visible and near infrared reflectance spectroscopy. PloS One 8(6): e66409. DOI 10.1371/journal.pone.0066409.
Stoner E.R., Baumgardner M.F., 1981. Characteristic variations in reflectance of surface soils. Soil Science Society of America Journal 45(6): 1161–1165. DOI 10.2136/sssaj1981.03615995004500060031x.
Taconet O., Ciarletti V., 2007. Estimating soil roughness indices on a ridge-and-furrow surface using stereo photogrammetry. Soil and Tillage Research 93(1): 64–76. DOI 10.1016/j.still.2006.03.018.
Temps R.C., Coulson K.L., 1977. Solar radiation incident upon slopes of different orientations. Solar Energy 19(2): 179–184. DOI 10.1016/0038-092X(77)90056-1.
van Leeuwen W.J.D., Roujean J.-L., 2002. Land surface albedo from the synergistic use of polar (EPS) and geostationary (MSG) observing systems. Remote Sensing of Environment 81(2–3): 273–289. DOI 10.1016/S0034-4257(02)00005-6.
Wang K., Liu J., Zhou X., Sparrow M., Ma M., Sun Z., Jiang W., 2004. Validation of the MODIS global land surface albedo product using ground measurements in a semide-sert region on the Tibetan Plateau. Journal of Geophysical Research 109(D5): D05107. DOI 10.1029/2003JD004229.
Wind G. (Gala), Platnick S., Meyer K., Arnold T., Amarasinghe N., Marchant B., Wang C., 2020. The CHIMAERA system for retrievals of cloud top, optical and microphysical properties from imaging sensors. Computers and Geosciences 134(April): 104710. DOI 10.1016/j.cageo.2019.104345.
Zhou H., Liang S., He T., Wang J., Bo Y., Wang D., 2019. Evaluating the spatial representativeness of the MODerate resolution image spectroradiometer albedo product (MCD43) at ameriflux sites. Remote Sensing 11(5). DOI 10.3390/rs11050547.
Ziar H., Fatih Sönmez F., Isabella O., Zeman M., 2019. A comprehensive albedo model for solar energy applications: geometric spectral albedo. Applied Energy 255(September): 113867. DOI 10.1016/j.apenergy.2019.113867.