Scale problem: Influence of grid spacing of digital elevation model on computed slope and shielded extra-terrestrial solar radiation

Nan CHEN

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Front. Earth Sci. ›› 2020, Vol. 14 ›› Issue (1) : 171-187. DOI: 10.1007/s11707-019-0770-z
RESEARCH ARTICLE
RESEARCH ARTICLE

Scale problem: Influence of grid spacing of digital elevation model on computed slope and shielded extra-terrestrial solar radiation

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Abstract

Solar radiation is the primary energy source that drives many of Earth’s physical and biological processes and determines the patterns of climate and productivity on the surface of the Earth. A fundamental proportion of solar radiation is composed of shielded extra-terrestrial solar radiation (SESR), which can be computed using the slope and aspect derived from a digital elevation model (DEM). The objective of this paper is to determine the influence of the grid spacing of the DEM (the influence of the scale of the DEM) on the errors of slope, aspect and SESR. This paper puts forward the concepts of slope representation error, aspect representation error, and SESR representation error and then studies the relations among these errors and the grid spacing of DEMs. We find that when the grid spacing of a DEM becomes coarser, the average SESR increases; the increase in SESR is dominated by the grid cells of the DEM with a negative slope representation error, whereas SESR generally decreases in the grid cells with a positive slope representation error. Although the grid spacing varies, the distribution of the percentages of positive SESR representation errors on the slope, which is classified into 11 slope intervals, is independent of the grid spacing; this distribution is concentrated across some slope intervals. Moreover, the average absolute value and mean square error of the SESR representation error are closely related to those of the slope representation error and the aspect representation error. The findings in this study may be useful for predicting and reducing the errors in SESR measurements and may help to avoid mistakes in future research and in practical applications in which SESR is the data of interest or plays a vital role in an analysis.

Keywords

scale problem / digital elevation model / grid spacing / slope / shielded extra-terrestrial solar radiation

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Nan CHEN. Scale problem: Influence of grid spacing of digital elevation model on computed slope and shielded extra-terrestrial solar radiation. Front. Earth Sci., 2020, 14(1): 171‒187 https://doi.org/10.1007/s11707-019-0770-z

References

[1]
Ambreen R, Qiu X F, Ahmad I (2011). Distributed modeling of extraterrestrial solar radiation over the rugged terrains of pakistan. J Mt Sci, 8(3): 427–436
CrossRef Google scholar
[2]
Bocquet G (1984). Method of study and cartography of the potential sunny periods in mountainous areas. J Climatol, 4(6): 587–596
CrossRef Google scholar
[3]
Chen N (2013). Influence of resolutions of DEM on the error of slope. Geomatics and Information Science of Wuhan University, 38(5): 594–598 (in Chinese)
CrossRef Google scholar
[4]
Chen N (2014). Relationship between dem resolution and average slope derived from DEM. Journal of Geo-Information Science, 16(4): 524–530 (in Chinese)
CrossRef Google scholar
[5]
Chen N, Tang G A, Guo D S, Chen C (2014). Influence of DEM orientation on the error of slope calculation. Earth Sci Inform, 7(4): 277–285
CrossRef Google scholar
[6]
Chow T E, Hodgson M E (2009). Effects of lidar post—spacing and DEM resolution to mean slope estimation. Int J Geogr Inf Sci, 23(10): 1277–1295
CrossRef Google scholar
[7]
Dozier J, Frew J (1990). Rapid calculation of terrain parameters for radiation modeling from digital elevation data. IEEE Trans Geosci Remote Sens, 28(5): 963–969
CrossRef Google scholar
[8]
Gao J (1997). Resolution and accuracy of terrain representation by grid DEM s at a micro-scale. Int J Geogr Inf Sci, 11(2): 199–212
CrossRef Google scholar
[9]
Gao J, Burt J E, Zhu A X (2012). Neighborhood size and spatial scale in raster-based slope calculations. Int J Geogr Inf Sci, 26(10): 1959–1978
CrossRef Google scholar
[10]
Häntzschel J, Goldberg V, Bernhofer C (2005). GIS-based regionalisation of radiation, temperature and coupling measures in complex terrain for low mountain ranges. Meteorol Appl, 12(1): 33–42
CrossRef Google scholar
[11]
Hopkinson C, Chasmer L, Munro S, Demuth M N (2010). The influence of DEM resolution on simulated solar radiation—induced glacier melt. Hydrol Processes, 24(6): 775–788
CrossRef Google scholar
[12]
Horn B K P (1981). Hill shading and the reflectance map. Proc IEEE, 69(1): 14–47
CrossRef Google scholar
[13]
Huang W F, Chen M R, Chen S X (1986). Meteorology and Climatology. Beijing: Higher Education Press (in Chinese)
[14]
Li C, Wang Q, Shi W Z, Zhao S (2018a). Uncertainty modelling and analysis of volume calculations based on a regular grid digital elevation model (DEM). Comput Geosci, 114: 117–129
CrossRef Google scholar
[15]
Li C, Zhao S S, Wang Q, Shi W (2018b). Uncertainty modeling and analysis of surface area calculation based on a regular grid digital elevation model (DEM). Int J Geogr Inf Sci, 32(9): 1–23
CrossRef Google scholar
[16]
Li X, Cheng G, Chen X, Lu L (1999). Modification of solar radiation model over rugged terrain. Chin Sci Bull, 44(15): 1345–1349
CrossRef Google scholar
[17]
Li Z Q, Weng D M (1988). A computer model for calculating the duration of sunshine in mountainous areas. Chin Sci Bull, 33(19): 1624–1627
CrossRef Google scholar
[18]
Liu M, Bárdossy A, Jiang Y (2012). Gis-based modelling of topography-induced solar radiation variability in complex terrain for data sparse region. Int J of Geogr Inf Sci, 26(7): 1281–1308
CrossRef Google scholar
[19]
Pellicciotti F, Raschle T, Huerlimann T, Carenzo M, Burlando P (2011). Transmission of solar radiation through clouds on melting glaciers: A comparison of parameterizations and their impact on melt modelling. J Glaciol, 57(202): 367–381
CrossRef Google scholar
[20]
Piedallu C, Gégout J C (2007). Multiscale computation of solar radiation for predictive vegetation modelling. Ann Sci, 64(8): 899–909
CrossRef Google scholar
[21]
Piedallu C, Gégout J C (2008). Efficient assessment of topographic solar radiation to improve plant distribution models. Agric Meteorol, 148(11): 1696–1706
CrossRef Google scholar
[22]
Qiu X F, Zeng Y, Liu C M, Wu X (2004). Simulation of astronomical solar radiation over yellow river basin based on DEM. J Geogr Sci, 14(1): 63–69
CrossRef Google scholar
[23]
Qiu X F, Zeng Y, Liu S M (2005). Distributed modeling of extraterrestrial solar radiation over rugged terrain. Chin J Geophys, 48(5): 1100–1107
CrossRef Google scholar
[24]
Reuter H I, Kersebaum K C, Wendroth O (2005). Modelling of solar radiation influenced by topographic shading––evaluation and application for precision farming. Phys Chem Earth Parts ABC, 30(1–3): 143–149
CrossRef Google scholar
[25]
Ruiz-Arias J A, Tovar-Pescador J, Pozo-Vázquez D, Alsamamra H, (2009). A comparative analysis of DEM-based models to estimate the solar radiation in mountainous terrain. Int J Geogr Inf Sci, 23(8): 1049–1076
CrossRef Google scholar
[26]
Šúri M, Huld T A, Dunlop E D, Ossenbrink H A (2007). Potential of solar electricity generation in the european union member states and candidate countries. Sol Energy, 81(10): 1295–1305
CrossRef Google scholar
[27]
Tang G A, Strobl J, Gong J Y, Zhao M D, Chen Z J (2001). Evaluation on the accuracy of digital elevation models. J Geogr Sci, 11(2): 209–216
CrossRef Google scholar
[28]
Wang L, Qiu X F, Wang P, Wang X, Liu A (2014). Influence of complex topography on global solar radiation in the Yangtze River Basin. J Geogr Sci, 24(6): 980–992
CrossRef Google scholar
[29]
Yao R M, Luo Q, Li B Z (2011). A simplified mathematical model for urban microclimate simulation. Build Environ, 46(1): 253–265
CrossRef Google scholar
[30]
Zeng Y, Qiu X F, Liu C M, (2005). Distributed modeling of direct solar radiation on rugged terrain of the Yellow River Basin. J Geogr Sci, 15(4): 439–447
CrossRef Google scholar
[31]
Zeng Y, Qiu X F, Miao Q L, Liu C (2003). Distribution of possible sunshine durations over rugged terrains of China. Prog Nat Sci, 13(10): 761–764
CrossRef Google scholar
[32]
Zhang H L, Liu G H, Huang C (2010). Modeling all-sky global solar radiation using modis atmospheric products: a case study in Qinghai-Tibet Plateau. Chin Geogr Sci, 20(6): 513–521
CrossRef Google scholar
[33]
Zhang H L, Xin X Z, Li L, Liu Q (2013). An improved parametric model for simulating cloudy sky daily direct solar radiation on tilted surfaces. IEEE J Sel Top Appl Earth Obs Remote Sens, 6(1): 180–187
CrossRef Google scholar
[34]
Zhang J Y, Zhao L, Deng S, Xu W, Zhang Y (2017). A critical review of the models used to estimate solar radiation. Renew Sustain Energy Rev, 70: 314–329
CrossRef Google scholar
[35]
Zhang S H, Li X G, Chen Y N (2015). Error assessment of grid-based direct solar radiation models. Int J Geogr Inf Sci, 29(10): 1782–1806
CrossRef Google scholar
[36]
Zhang Y L, Li X, Bai Y L (2015). An integrated approach to estimate shortwave solar radiation on clear-sky days in rugged terrain using modis atmospheric products. Sol Energy, 113: 347–357
CrossRef Google scholar
[37]
Zhou Q M, Liu X J (2002). Error assessment of grid-based flow routing algorithms used in hydrological models. Int J Geogr Inf Sci, 16(8): 819–842
CrossRef Google scholar
[38]
Zhou Q M, Liu X J (2004). Analysis of errors of derived slope and aspect related to DEM data properties. Comput Geosci, 30(4): 369–378
CrossRef Google scholar
[39]
Zhou Q M, Liu X J (2008). Assessing Uncertainties in Derived Slope and Aspect from a Grid DEM. Berlin: Springer, 279–306
[40]
Zuo D K (1990). Dictionary of Modern Geography. Beijing: The Commercial Press (in Chinese)
[41]
Zuo D K, Zhou Y H, Xiang Y Q, (1991) Studies on Radiation in the Epigeosphere. Beijing: Science Press (in Chinese)

Acknowledgments

This work is supported by the National Natural Science Foundation of China (Grant Nos. 41771423, 41930102, 41601408 and 41471331) and the Industry University Research Cooperation Project for the Social Development of Fujian Province, China (No. 2018Y0054). The author is thankful to the anonymous reviewers for their helpful comments; the author is indebeted to his students, Wenzhen Zhou, Huange LI, Quanjin LI and Tinmin Lin for retouching the figures.

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2019 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature
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