Back
 GEP  Vol.7 No.2 , February 2019
Research on the Optimal Vegetation Cover for Remote Sensing Assessment of Soil Erosion Risk Using the Temporal Matching Relationship between Rainfall and Vegetation
Abstract: Vegetation cover derived from remote sensing image is widely used for soil erosion risk assessment, but there is no clear guideline to select the most appropriate temporal satellite data. It is common practice that satellite data during growing season are randomly selected and used in soil erosion risk assessment. However, the effectiveness of vegetation in protecting the soil is quite different even if it is the same growing season since vegetation covers change as they grow. This article aims to provide a method of choosing optimal vegetation cover for studying soil erosion risk using remote sensing, that is, the vegetation cover in the most appropriate temporal period. Based on the temporal relationship of the two most active impact factors, rainfall and vegetation, an index of RV is developed and used to indicate the relative erosion risk during the year. The results show that annual variation of rainfall is significant, and vegetation is relatively stable, resulting in their matching relationship is different in each year. The correlation coefficient reaches 0.89 between RV and real sediment transport during the period when rainfall can cause soil erosion. In other words, RV is a good indicator of soil erosion. Therefore, there is a good correlation between RV maximum and the optimal vegetation cover, which can help facilitate erosion research in the future, showing good potential for successful application in other places.
Cite this paper: Liu, J. , Zhang, X. (2019) Research on the Optimal Vegetation Cover for Remote Sensing Assessment of Soil Erosion Risk Using the Temporal Matching Relationship between Rainfall and Vegetation. Journal of Geoscience and Environment Protection, 7, 22-36. doi: 10.4236/gep.2019.72002.
References

[1]   Cai, J. Q., Ren, Z. Y., & Li, Y. C. (2002). Discussion on Related Technical Issues of Remote Sensing Investigation on Soil Erosion (in Chinese, with English Abstract). Bulletin of Soil and Water Conservation, 22, 45-47.

[2]   Carlson, T. N., & Ripley, D. A. (1997). On the Relation between NDVI, Fractional Vegetation Cover, and Leaf Area Index. Remote Sensing of Environment, 62, 241-252.
https://doi.org/10.1016/S0034-4257(97)00104-1

[3]   Cheng, M., Brown, R., & Collier, C. G. (1993). Delineation of Precipitation Areas Using Meteosat Infrared and Visible Data in the Region of the United Kingdom. Journal of Applied Meteorology, 32, 884-898.
https://doi.org/10.1175/1520-0450(1993)032<0884:DOPAUM>2.0.CO;2

[4]   Cohen, M. J., Shepherd, K. D., & Walsh, M. G. (2005). Empirical Reformulation of the Universal Soil Loss Equation for Erosion Risk Assessment in a Tropical Watershed. Geoderma, 124, 235-252.
https://doi.org/10.1016/j.geoderma.2004.05.003

[5]   De Graffenried, J. B., & Shepherd, K. D. (2009). Rapid Erosion Modeling in a Western Kenya Watershed Using Visible near Infrared Reflectance, Classification Tree Analysis and 137Cesium. Geoderma, 154, 93-100.
https://doi.org/10.1016/j.geoderma.2009.10.001

[6]   De Jong, S. M. (1994). Derivation of Vegetative Variables from a Landsat TM Image for Modelling Soil Erosion. Earth Surface Processes and Landforms, 19, 165-178.
https://doi.org/10.1002/esp.3290190207

[7]   De Jong, S. M., Paracchini, M. L., Bertolo, F., Folving, S., Megier, J., & De Roo, A. P. J. (1999). Regional Assessment of Soil Erosion Using the Distributed Model SEMMED and Remotely Sensed Data. Catena, 37, 291-308.
https://doi.org/10.1016/S0341-8162(99)00038-7

[8]   Escadafal, R. (1994). Soil Spectral Properties and Their Relationships with Environmental Parameters: Examples from Arid Regions. In: J. Hill, & J. Mégier (Eds.), Imaging Spectrometry—A Tool for Environmental Observations (pp. 71-87), Dordrecht: Kluwer Academic Publishers,.
https://doi.org/10.1007/978-0-585-33173-7_5

[9]   Gao, Y. H., & Wang, H. Q. (2004). Application of Remote Sensing Technology in Dynamic Monitoring of Soil Erosion (in Chinese, with English abstract). Soil and Water Conservation in China, 1, 33-34.

[10]   Gilly, J. E., & Risse, L. M. (2000). Runoff and Soil Loss as Affected by the Application of Manure. Transaction of the ASAE, 43, 1583-1588.
https://doi.org/10.13031/2013.3058

[11]   Hancock, G. R. (2009). A Catchment Scale Assessment of Increased Rainfall and Storm Intensity on Erosion and Sediment Transport for Northern Australia. Geoderma, 152, 350-360.
https://doi.org/10.1016/j.geoderma.2009.07.003

[12]   Huang, Z. L., Chen, L. D., Fu, B. J., & Wu, X. L. (2004). Effect of Soil Erosion Reduction and Time Changing of Different Vegetation Types in Semi-Arid Loess Hilly and Gully Region (in Chinese, with English Abstract). China Water Resources, 20, 38-40.

[13]   Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002). Overview of the Radiometric and Biophysical Performance of the MODIS Vegetation Indices. Remote Sensing of Environment, 83, 195-213.
https://doi.org/10.1016/S0034-4257(02)00096-2

[14]   Jain, S. K., & Goel, M. K. (2002). Assessing the Vulnerability to Soil Erosion of the Ukai Dam Catchments Using Remote Sensing and GIS. Hydrological Sciences Journal, 47, 31-40.
https://doi.org/10.1080/02626660209492905

[15]   Langbein, L. B., & Schumm, S. A. (1958). Yield of Sediment in Relation to Mean Annual Precipitation. Transactions, American Geophysical Union, 39, 1076-1084.
https://doi.org/10.1029/TR039i006p01076

[16]   Liu, H. P., Yuan, A. P., Lu, B. J., & Qiu, C. (2007). Study on Erosive Ranifall Standard of Beijing (in Chinese, with English Abstract). Research of Soil and Water Conservation, 14, 215-220.

[17]   Menéndez-Duarte, R., Fernández, S., & Soto, J. (2009). The Application of 137Cs to Post-Fire Erosion in North-West Spain. Geoderma, 150, 54-63.
https://doi.org/10.1016/j.geoderma.2009.01.012

[18]   Mutekanga, F. P., Visser, S. M., & Stroosnijder, L. (2010). A Tool for Rapid Assessment of Erosion Risk to Support Decision-Making and Policy Development at the Ngenge Watershed in Uganda. Geoderma, 160, 165-174.
https://doi.org/10.1016/j.geoderma.2010.09.011

[19]   Qiao, Y. L. (2003). The Discussion on Related Technical Issues of Fast Soil Erosion Remote Sensing Investigation (in Chinese, with English Abstract). Geo-Information Science, 5, 97-100.

[20]   Symeonakis, E., & Drake, N. (2004). Monitoring Desertification and Land Degradation over Sub-Saharan Africa. International Journal of Remote Sensing, 25, 573-592.
https://doi.org/10.1080/0143116031000095998

[21]   Tang, Z. H., Cai, Q. G., Li, Z. W. et al. (2001). Study on Interaction among Wind Erosion, Hydraulic Erosion and Gravity Erosion in Sediment-Rock Region of Inner Mongolia. Journal of Soil and Water Conservation, 15, 25-29.

[22]   Verachtert, E., Maetens, W., Van Den Eeckhaut, M., Poesen, J., & Deckers, J. (2011). Soil Loss Rates Due to Piping Erosion. Earth Surface Processes and Landforms, 36, 1715-1725.
https://doi.org/10.1002/esp.2186

[23]   Vrieling, A., De Jong, S. M., Sterk, G., & Rodrigues, S. C. (2008). Timing of Erosion and Satellite Data: A Multi-Resolution Approach to Soil Erosion Risk Mapping. International Journal of Applied Earth Observation and Geoinformation, 10, 267-281.
https://doi.org/10.1016/j.jag.2007.10.009

[24]   Wang, W. Z. (1983). Study on the Relations between Rainfall Characteristics and Loss of Soil in Loess Region. Bulletin of Soil and Water Conservation, 3, 7-13.

[25]   Wilheit, T. T., Chang, A. T. C., Rao, M. S. V. et al. (1977). A Satellite Technique for Quantitatively Mapping Rainfall Rates over the Oceans. Journal of Applied Meteorology, 16, 551-560.
https://doi.org/10.1175/1520-0450(1977)016<0551:ASTFQM>2.0.CO;2

[26]   WMO (1993). The Global Energy and Water Cycle Experiment (GEWEX). WMO Bulletin, 42, 20-27.

[27]   Xie, Y., Liu, B., & Nearing, M. A. (2002). Practical Thresholds for Separating Erosive and Non-Erosive Storms. Transactions of the ASAE, 45, 1843-1847.

[28]   Zhan, X. G., & Wang, P. (2001). Research on Dynamical Supervision Design of Water and Soil Loss in Three Gorges Reservoir Area Based on RS and GIS (in Chinese, with English Abstract). Journal of Yangtze River Scientific Research institute, 18, 41-44.

[29]   Zhang, G. H., & Liang, Y. M. (1996). A Summary of Impact of Vegetation Coverage on Soil and Water Conservation Benefit (in Chinese, with English Abstract). Research of Soil and Water Conservation, 3, 104-110.

[30]   Zhang, W. B., & Fu, J. S. (2003). Rainfall Erosivity Estimation under Different Rainfall amount (in Chinese, with English Abstract). Resources Science, 25, 35-41.

[31]   Zhang, X. C., Shao, M. A., Huang, Z. B., & Lu, Z. F. (2000). An Experimental Research on Soil Erosion and Nitrogen Loss under Different Vegetation Cover (in Chinese, with English Abstract). Acta ecologica Sinica, 20, 1038-1044.

[32]   Zhang, X. W., & Qin, F. (2016). Coupling Relationship of Precipitation and Vegetation and Its Influence for Sediment Yield in Pisha Sandstone Area. Geographical Research, 35, 513-524.

[33]   Zhang, X. W., Qiu, F., & Qin, F. (2019). Identification and Mapping of Winter Wheat by Integrating Temporal Change Information and Kullback-Leibler Divergence. International Journal of Applied Earth Observation and Geoinformation, 76, 26-39.
https://doi.org/10.1016/j.jag.2018.11.002

[34]   Zhang, X. W., Wu, B. F. et al. (2012). Soil Erosion Risk and Its Spatial Pattern in Upstream Area of Guanting Reservoir. Environmental Earth Sciences, 65, 221-229.
https://doi.org/10.1007/s12665-011-1085-x

[35]   Zhang, X. W., Wu, B. F., Ling, F. et al. (2010). Identification of Priority Areas for Controlling Soil Erosion. Catena, 83, 76-86.
https://doi.org/10.1016/j.catena.2010.06.012

[36]   Zhao, H. G., Tang, Y. Y., & Yang, S. T. (2018). Dynamic Identification of Soil Erosion Risk in the Middle Reaches of the Yellow River Basin in China from 1978 to 2010. Journal of Geographical Sciences, 28, 175-192.
https://doi.org/10.1007/s11442-018-1466-0

 
 
Top