Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7, 101-108, 2014
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7/101/2014/
doi:10.5194/isprsarchives-XL-7-101-2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
19 Sep 2014
Fusion of high resolution remote sensing images and terrestrial laser scanning for improved biomass estimation of maize
C. Hütt1, H. Schiedung2, N. Tilly1, and G. Bareth1 1Institute of Geography (GIS & Remote Sensing Group), University of Cologne, 50923 Cologne, Germany
2Institute of Crop Science and Resource Conservation, University of Bonn, 53121 Bonn, Germany
Keywords: Agriculture, Crop, Change Detection, TLS, Fusion, Multispectral, High resolution, Monitoring Abstract. In this study, images from the satellite system WorldView-2 in combination with terrestrial laser scanning (TLS) over a maize field in Germany are investigated. Simultaneously to the measurements a biomass field campaigns was carried out. From the point clouds of the terrestrial laser scanning campaigns crop surface models (CSM) from each scanning date were calculate to model plant growth over time. These results were resampled to match the spatial resolution of the WorldView-2 images, which had to orthorectified using a high resolution digital elevation model and atmosphere corrected using the ATCOR Software package. A high direct correlation of the NDVI calculated from the WorldView-2 sensor and the dry biomass was found in the beginning of June. At the same date, the heights from laser scanning can also explain a certain amount of the biomass variation (r2 = 0.6). By combining the NDVI from WorldView-2 and the height from the laser scanner with a linear model, the R2 reaches higher values of 0.86. To further understand the relationship between CSM derived crop heights and reflection indices, a comparison on a pixel basis was performed. Interestingly, the correlation of the NDVI and the crop height is rather low at the beginning of June (r2 = 0,4, n = 1857) and increases significantly (R2 = 0,79, N = 1857) at a later stage.
Conference paper (PDF, 20462 KB)


Citation: Hütt, C., Schiedung, H., Tilly, N., and Bareth, G.: Fusion of high resolution remote sensing images and terrestrial laser scanning for improved biomass estimation of maize, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7, 101-108, doi:10.5194/isprsarchives-XL-7-101-2014, 2014.

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