Determination of cover management factor (C-Factor) in agricultural lands and its relationship with NDVI

Year 2018, 1. Uluslararası Tarımsal Yapılar ve Sulama Kongresi Özel Sayısı, 83 - 90, 31.12.2018

Melis Özge Pınar , Günay Erpul

Abstract

Cover and management factor (C-factor), in USLE (Universal Soil Loss Equation) and RUSLE (Revised Universal Soil Loss Equation) technologies, states protective effect against soil losses by water erosion. In terms of managing land and soil, Sustainable Land and Soil Management should take place in agricultural lands. Hence, C-factor expresses the effect of the plant and the soil cover, showing a relationship between soil losses and bare soils and diverse soil surface conditions including vegetation cover during plant development period. This condition presents how mitigation measures affect soil losses annually and how soil losses affect crop rotation and other management plans, reciprocally. The aim of this research is to examine the relationships between C-factor and NDVI and investigate the spatial and temporal practicality of the NDVI as a remote sensing tool over large areas. Sub-factors of the C factor –prior land use, soil roughness, soil moisture, canopy cover and surface cover- were determined directly from sample points designed systematically and randomly in the sugar beet planted-study area and average C-factor was 0,060 (±0,070). NDVI values were obtained by using portable spectro-radiometer for in-situ measurements and calculated from the satellite data (Pleiades) and average NDVI values were 0.6212 (±0.042) and 0.6209 (±0.0258), respectively. With the interactive regression analysis among methods, the spatial and temporal changes on the land cover patterns and their effects on soil loss were rapidly determined in the semi-arid watershed of Eskisehir.

Keywords

C-factor, NDVI, remote sensing, geo-statistics

Tarım Arazilerinde Bitkisel Örtü ve Ürün Yönetimi Faktörünün (C-Faktörü) Belirlenmesi ve NDVI ile İlişkisi

Abstract

Bitkisel
örtü ve ürün yönetimi faktörü (C-faktörü), hem Evrensel Toprak Kaybı Eşitliği (ETKE)
hem de Yenilenmiş Evrensel Toprak Kaybı Eşitliği (YETKE) teknolojisinde
yağışların meydana getirdiği toprak kayıplarına karşı koruyucu bir etkiyi ifade
etmektedir. Sürdürülebilir arazi ve toprak yönetimi açısından koruyucu bitkisel örtünün
yıl içerisindeki değişiminin belirlenmesi gerekmektedir. Dolayısıyla bu faktör, bitki gelişme dönemi
boyunca koruma planlarının yıllık toprak kaybına etkisini, toprak kaybının ürün
münavebesini ve diğer yönetimsel planları nasıl etkilediğini göstermektedir. Bu
çalışmadaki amaç, NDVI (Normalleştirilmiş fark bitki örtüsü indeksi) ve
C-faktörü arasındaki ilişkileri araştırmak ve C-faktörünün belirlenmesinde
uzaktan algılama yöntemiyle belirlenen bitki örtüsü indeksinin kullanımının
önemini incelemektir. Pancar bitkisi ekili parselde, ölçümler uydu
görüntüleriyle yersel ölçümlerin eş zamanlı olduğu, sistematik ve rastlantısal
örnek noktalarında gerçekleşmiştir. YETKE-C değişkenleri -önceki arazi
kullanım, toprak pürüzlülüğü, toprak nemi, kanopi kapalılığı ve yüzey
kapalılığı- ölçümü ile C-faktörü belirlenmiş ve ortalama C-faktörü 0,060 (±0,070)
olarak bulunmuştur. NDVI değerleri ise hem portatif spektroradyometreyle yersel
ölçümlerden hem de uydu görüntülerinden (Pleiades) hesaplanarak elde
edilmiştir. NDVI değerleri sırasıyla 0,6212 (±0,042) ve 0,6209 (±0,0258) dur.
Bu türdeki bağlantısal çalışmalarla, konumsal ve zamansal olarak yarı-kurak
Eskişehir koşullarındaki havzalarda arazi örtü desenlerindeki değişimler ve
toprak kayıpları üzerine olan etkileri daha çabuk bir şekilde
belirlenebilecektir.

Keywords

C-faktörü, NDVI, uzaktan algılama, jeo-istatistik.

References

• De Jong, S.M., 1994. Derivation of vegetative variables from a Landsat TM image for modelling soil erosion. Earth Surf. Processes Landforms 19, 165–178.
• Durigon, V.L., Carvalho, D.F., Antunes, M.A.H., Oliveira, P.T.S. and Fernandes, M.M. 2014. NDVI time series for monitoring RUSLE cover management factor in a tropical watershed. International Journal of Remote Sensing, 2014 Vol. 35, No. 2,441–453, http://dx.doi.org/10.1080/01431161.2013.871081.
• Gabriels D, Ghekiere G, Schiettecatte W, Rottiers I. 2003.Assessments of USLE cover management C factors for 40crop rotation systems on arable farms in the Kemmelbeek watershed, Belgium. Soil Tillage Research, 74, 47–53.
• Karaburun A. 2010. Estimation of C factor for soil erosion modeling using NDVI in Buyukcemece watershed. Ozean Journal of Applied Sciences, 3, 77–85.
• Lu H, Prosser I P, Moran C J, Gallant J C, Priestley G, Stevenson J G. 2003. Predicting sheet wash and rill erosion over the Australian Continent. Australia Journal of Soil Research, 41, 1037–1062.
• Meusburger, K., D. Bänninger, and C. Alewell. 2010. “Estimating Vegetation Parameter for Soil Erosion Assessment in an Alpine Catchment by Means Of QuickBird Imagery.” International Journal of Applied Earth Observation and Geoinformation 12: 201–207.
• Morgan, R. P. C. 2005. Soil Erosion and Conservation. Malden-MA-USA. 3rd ed. Oxford: Resources Institute, Granfield University, Blackwell.
• Panagos, P., Borelli, B., Meusburger, K., Alewell, C., Lugato, E., Montanarella, L. 2015. Estimating the soil erosion cover-management factor at the European scale. Land Use Policy 48 (2015) 38–50. http://dx.doi.org/10.1016/j.landusepol.2015.05.021.
• Patil, R. J. and Sensing S. K. GIS based modeling ofcrop/cover management factor (C) of USLE in Shakker river watershed. International Conference on Chemical, Agricultural and Medical Sciences (CAMS-2013) Dec. 29-30, 2013 Kuala Lumpur (Malaysia). http://dx.doi.org/10.15242/IICBE.C1213023.
• Renard, K.G., C.R. Foster, G.A. Weesies, D.K. McCool, and D.C. Yoder, 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE), USDA, Agriculture Handbook Number 703, Government Printing Office, Washington, D.C., 404 p.
• Schönbrodt S, Saumer P, Behrens T, Seeber C, Scholten T.2010. Assessing the USLE crop and management factor Cfor soil erosion modeling in a large mountainous watershedin central China. Journal of Earth Science, 21, 835–845.
• Suriyaprasita, M. and Shrestha, D. P. 2008. Deriving Land Use and Canopy Cover Factor from Remote Sensing and Field Data in Inaccessible Mountainous Terrain for Use in Soil Erosion Modelling. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008. Technical Session TS-34:SS-7 Global Monitoring For Environment and Security (GMES).
• Ustin, S. L., M. O. Smith, S. Jacquemoud, M. Verstraete, and Y. Govaerts. 1999. “Geobotany: Vegetation Mapping for Earth Sciences.” In Remote Sensing for the Earth Sciences, edited by A. N. Rencz, 251–307. New York: John Wiley and Sons.
• Van der Knijff, J. M., R. J. A. Jones, and L. Montanarella. 2000. Soil Erosion Risk Assessment in Europe. Ispra: European Soil Bureau. Joint Research Centre. EUR 19044 EN.
• Wischmeier, W.H., and D.D. Smith, 1978. Predicting Rainfall Ero- sion Loss: A Guide to Conservation Planning, USDA, Agricul- ture Handbook Number 537, Government Printing Office, Washington, D.C., 58 p.
• Zhou, P., O. Luukkanen, T. Tokola, and J. Nieminen. 2008. “Effect of Vegetation Cover on Soil Erosion in a Mountainous Watershed.” Catena 75: 319–325.