Plant Soil Environ., 2013, 59(9):423-431 | DOI: 10.17221/188/2013-PSE

Airborne laser scanning data as a source of field topographical characteristicsOriginal Paper

J. Kumhálová1, F. Kumhála2, P. Novák2, ©. Matějková3
1 Department of Applied Geoinformatics and Spatial Planning, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic
2 Department of Agricultural Machines, Faculty of Engineering, Czech University of Life Sciences Prague, Prague, Czech Republic
3 Department of Biomathematics and Databases, Crop Research Institute, Prague, Czech Republic

One of the factors frequently affecting yields is topography. Topographic data can be obtained from various sources with different precision. This work evaluates suitability of airborne laser scanning data for use as another source of topographical characteristics creation in a smaller scale in regards to precision agriculture needs. Simple models of elevation, slope and flow accumulation were created and the correlation between yield and topography was determined over a seven-year period in relation to precipitations and temperature. The suitability of airborne laser scanning data was proved with certain limitations. Flow accumulation model derived from original airborne laser scanning data indicated the right trend of flow accumulation but not as clearly compared to other models. In drier years the correlation coefficients between flow accumulation and yield reached up to 60-70%.

Keywords: GIS; digital terrain models; flow accumulation; yield; weather conditions

Published: September 30, 2013  Show citation

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Kumhálová J, Kumhála F, Novák P, Matějková ©. Airborne laser scanning data as a source of field topographical characteristics. Plant Soil Environ. 2013;59(9):423-431. doi: 10.17221/188/2013-PSE.
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    References

    1. ESRI (2006): ArcView Spatial Analyst. Environmental Systems Research Institute, Redlands.
    2. Guo W., Maas S.J., Bronson K.F. (2012): Relationship between cotton yield and soil electrical conductivity, topography, and Landsat imagery. Precision Agriculture, 13: 678-692. Go to original source...
    3. Hodgson M.E., Jensen J.R., Schmidt L., Schill S., Davis B. (2003): An evaluation of LiDAR-and IFSAR- derived digital elevation models in leaf-on conditions with USGS level 1 and level 2 DEMs. Remote Sensing of Environment, 84: 295-308. Go to original source...
    4. Hudak A.T., Lefsky M.A., Cohen W.B., Berterretche M. (2002): Integration of LiDAR and Landsat ETM+ data for estimating and mapping forest canopy height. Remote Sensing of Environment, 82: 397-416. Go to original source...
    5. Huising E.J., Gomes Pereira L.M. (1998): Errors and accuracy estimates of laser data acquired by various laser scanning systems for topographic applications. ISPRS Journal of Photogrammetry and Remote Sensing, 53: 245-261. Go to original source...
    6. Iqbal J., Read J.J., Thomasson A.J., Jenkins J.N. (2005): Relationships between soil-landscape and dryland cotton lint yield. Soil Science Society America Journal, 69: 872-882. Go to original source...
    7. Kraus K., Pfeifer N. (1998): Determination of terrain models in wooden areas with airborne laser scanner data. ISPRS Journal of Photogrammetry and Remote Sensing, 53: 193-203. Go to original source...
    8. Kravchenko A.N., Bullock D.G. (2000): Correlation of corn and soybean grain yield with topography and soil properties. Agronomy Journal, 92: 75-83. Go to original source...
    9. Kravchenko A.N., Bullock D.G. (2002): Spatial variability of soybean quality data as a function of field topography: I. spatial data analysis. Crop Science, 42: 804-815. Go to original source...
    10. Kroulík M., Kumhálová J., Kvíz Z., Zlínský M., Mimra M., Proąek V. (2010): Spatial variability and pattern of selected properties of agricultural soils in the Czech Republic measured by indirect proximal and remote sensing. In: Proximal Soil Sensing. Springer Science + Business Media B.V., Dordrecht, Heidelberg, London, New York, 397-409. Go to original source...
    11. Kumhálová J., Kumhála F., Kroulík M., Matějková ©. (2011a): The impact of topography on soil properties and yield and the effects of weather conditions. Precision Agriculture, 12: 813-830. Go to original source...
    12. Kumhálová J., Kumhála F., Matějková ©., Kroulík M. (2011b): The relationship between topography and yield in different weather conditions. In: Precision Agriculture 2011, Czech Centre for Science and Society, Prague, 606-616.
    13. Marques da Silva J.R., Silva L.L. (2008): Evaluation of the relationship between maize yield spatial and temporal variability and different topographic attributes. Biosystems Engineering, 101: 183-190. Go to original source...
    14. Meyer T.H. (2007): Fast algorithm using minimal data structures for common topological relationship in large, irregularly spaced topographic data sets. Computers Geosciences, 33: 325-334. Go to original source...
    15. Nasset E., Okland T. (2002): Estimating tree height and tree crown properties using airborne scanning laser in boreal nature reserve. Remote Sensing of Environment, 79: 105-115. Go to original source...
    16. Petzold B., Reiss P., Stössel W. (1999): Laser scanning - surveying and mapping agencies are using a new technique for the derivation of digital terrain models. ISPRS Journal of Photogrammetry Remote Sensing, 54: 95-104. Go to original source...
    17. Schmidt F., Persson A. (2003): Comparison of DEM data capture and topographic wetness indices. Precision Agriculture, 4: 179-192. Go to original source...
    18. Straatsma M.W., Middelkoop H. (2006): Airborne laser scanning as a tool for lowland floodplain vegetation monitoring. Hydrobiologia, 565: 87-103. Go to original source...
    19. Suárez J.C., Ontiveros C., Smith S., Snape S. (2005): Use of airborne LiDAR and aerial photography in the estimation of individual tree heights in forestry. Computers and Geosciences, 31: 253-262. Go to original source...
    20. Thoma D.P., Gupta S.C., Bauer M.E., Kirchoff C.E. (2005): Airborne laser scanning for riverbank erosion assessment. Remote Sensing of Environment, 95: 493-501. Go to original source...
    21. Wehr A., Lohr U. (1999): Airborne laser scanning - an introduction and overview. ISPRS Journal of Photogrammetry and Remote Sensing, 54: 68-82. Go to original source...
    22. Zhang X., Liu J. (2004): Analysis of systematic error influences on accuracy of airborne laser scanning altimetry. Geo-spatial Information Science, 7: 218-224. Go to original source...

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