Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 569-571, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B7/569/2016/
doi:10.5194/isprs-archives-XLI-B7-569-2016
 
21 Jun 2016
MONITORING PHENOLOGY OF FLOODPLAIN GRASSLAND AND HERBACEOUS VEGETATION WITH UAV IMAGERY
W. K. van Iersel, M. W. Straatsma, E. A. Addink, and H. Middelkoop Utrecht University, Department of Physical Geography, Faculty of Geosciences, Heidelberglaan 2, 3584 CS Utrecht, the Netherlands
Keywords: river floodplains, vegetation height, land cover, multi-temporal data, aerial photography, UAV, DSM Abstract. River restoration projects, which aim at improved flood safety and increased ecological value, have resulted in more heterogeneous vegetation. However, they also resulted in increasing hydraulic roughness, which leads to higher flood water levels during peak discharges. Due to allowance of vegetation development and succession, both ecological and hydraulic characteristics of the floodplain change more rapidly over time. Monitoring of floodplain vegetation has become essential to document and evaluate the changing floodplain characteristics and associated functioning. Extraction of characteristics of low vegetation using single-epoch remote sensing data, however, remains challenging. The aim of this study was to (1) evaluate the performance of multi-temporal, high-spatial-resolution UAV imagery for extracting temporal vegetation height profiles of grassland and herbaceous vegetation in floodplains and (2) to assess the relation between height development and NDVI changes. Vegetation height was measured six times during one year in 28 field plots within a single floodplain. UAV true-colour and false-colour imagery of the floodplain were recorded coincidently with each field survey. We found that: (1) the vertical accuracy of UAV normalized digital surface models (nDSMs) is sufficiently high to obtain temporal height profiles of low vegetation over a growing season, (2) vegetation height can be estimated from the time series of nDSMs, with the highest accuracy found for combined imagery from February and November (RMSE = 29-42 cm), (3) temporal relations between NDVI and observed vegetation height show different hysteresis behaviour for grassland and herbaceous vegetation. These results show the high potential of using UAV imagery for increasing grassland and herbaceous vegetation classification accuracy.
Conference paper (PDF, 4880 KB)


Citation: van Iersel, W. K., Straatsma, M. W., Addink, E. A., and Middelkoop, H.: MONITORING PHENOLOGY OF FLOODPLAIN GRASSLAND AND HERBACEOUS VEGETATION WITH UAV IMAGERY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 569-571, doi:10.5194/isprs-archives-XLI-B7-569-2016, 2016.

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