Agricultural landscape-scale C factor determination and erosion prediction for various crop rotations through a remote sensing and GIS approach

摘要: Abstract In arable land management, different crop rotation patterns and sequences, such as changing agricultural use to erosion prone crops, or crops providing less ground cover, can greatly influence soil loss rate through their impact on cover status (C factor value). The of C value is often determined an experimental plot scale, so the results are erroneous when extrapolated large heterogeneous landscapes, where they fail capture spatiotemporal variability beyond sites. present study we have endeavored investigate various subsequent rate, at a landscape level, by combining 28 time-series satellite images (from 2013 2016) along with annually updated land-use data, via integrated administration control system (IACS), from Uckermark district north eastern Germany. total, 21 sequences were investigated. Winter wheat (WW), winter rape (WR), maize (Mz) found be predominant grown in area. highest average annual values estimated involving Mz sugar beet (SB), both pre-crops succeeding crops. 0.39 was computed SB/Mz rotation. On other hand, WR gave significantly lower all years considered, lowest 0.07 calculated parcels preceded cereals. It also apparent that influenced temporally variable manner. Among self-sequencing patterns, WR/WR reduced compared Mz/Mz lesser extent WW/WW. Continuous cultivation increased potential much 72 % 51 possible determine spatial distribution risk within obtained agreed international regional studies. Overall, output this research could contribute towards further efficient investigation agronomic practices environment landscape, without need set up multi-location plots.