Quantitative and Qualitative Assessment of Soil Erosion Risk in Małopolska (Poland), Supported by an Object-Based Analysis of High-Resolution Satellite Images

被引:0
作者
Wojciech Drzewiecki
Piotr Wężyk
Marcin Pierzchalski
Beata Szafrańska
机构
[1] AGH University of Science and Technology,Department of Forest Ecology, Faculty of Forestry
[2] Faculty of Mining Surveying and Environmental Engineering,undefined
[3] Laboratory of Geomatics,undefined
[4] Agricultural University in Krakow,undefined
[5] ProGea Consulting,undefined
[6] The Marshall Office of Małopolska Voivodeship,undefined
来源
Pure and Applied Geophysics | 2014年 / 171卷
关键词
Soil erosion; Małopolska; USLE; OBIA; RapidEye; erosion control practice factor;
D O I
暂无
中图分类号
学科分类号
摘要
In 2011 the Marshal Office of Małopolska Voivodeship decided to evaluate the vulnerability of soils to water erosion for the entire region. The quantitative and qualitative assessment of the erosion risk for the soils of the Małopolska region was done based on the USLE approach. The special work-flow of geoinformation technologies was used to fulfil this goal. A high-resolution soil map, together with rainfall data, a detailed digital elevation model and statistical information about areas sown with particular crops created the input information for erosion modelling in GIS environment. The satellite remote sensing technology and the object-based image analysis (OBIA) approach gave valuable support to this study. RapidEye satellite images were used to obtain the essential up-to-date data about land use and vegetation cover for the entire region (15,000 km2). The application of OBIA also led to defining the direction of field cultivation and the mapping of contour tillage areas. As a result, the spatially differentiated values of erosion control practice factor were used. Both, the potential and the actual soil erosion risk were assessed quantificatively and qualitatively. The results of the erosion assessment in the Małopolska Voivodeship reveal the fact that a majority of its agricultural lands is characterized by moderate or low erosion risk levels. However, high-resolution erosion risk maps show its substantial spatial diversity. According to our study, average or higher actual erosion intensity levels occur for 10.6 % of agricultural land, i.e. 3.6 % of the entire voivodeship area. In 20 % of the municipalities there is a very urgent demand for erosion control. In the next 23 % an urgent erosion control is needed. Our study showed that even a slight improvement of P-factor estimation may have an influence on modeling results. In our case, despite a marginal change of erosion assessment figures on a regional scale, the influence on the final prioritization of areas (municipalities) according to erosion control needs is visible. The study shows that, high-resolution satellite imagery and OBIA may be efficiently used for P-factor mapping and thus contribute to a refined soil erosion risk assessment.
引用
收藏
页码:867 / 895
页数:28
相关论文
共 35 条
[1]  
Benz U. C.(2004)Multi resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information ISPRS Journal of Photogrammetry & Remote Sensing 58 239-258
[2]  
Hofmann P.(2010)Object based image analysis for remote sensing ISPRS Journal of Photogrammetry and Remote Sensing 65 2-16
[3]  
Willhauck G.(1996)A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units Journal of Soil and Water Conservation 51 427-433
[4]  
Lingenfelder I.(2009)Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete Environmental Monitoring and Assessment 149 19-28
[5]  
Heynen M.(2005)Wybrane zagadnienia przeciwerozyjnej ochrony gleb w świetle wymogów zrównoważonego rozwoju Acta Agrophisica 5 49-55
[6]  
Blaschke T(2011)An empirical approach to estimate soil erosion risk in Spain Science of the Total Environment 409 3114-3123
[7]  
Desmet P.J.(1996)Modeling topographic potential for erosion and deposition using GIS International Journal of Geographic Information Science 10 629-641
[8]  
Govers G.(1992)Length-slope factors for the Revised Universal Soil Loss Equation: Simplified method of estimation Journal of Soil and Water Conservation 47 423-428
[9]  
Karydas C. G.(2011)Soil erosion risk in Korean watersheds, assessed using the revised universal soil loss equation Journal of Hydrology 399 263-273
[10]  
Sekuloska T.(1994)Using monthly precipitation data to estimate R-factor in the revised USLE Journal of Hydrology 157 287-306