Open and free access to multifrequent high-resolution data (e.g. Sentinel-2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution.
%0 Conference Paper
%1 isprs-archives-XLI-B2-171-2016
%A Dahms, Thorsten
%A Seissiger, Sylvia
%A Conrad, Christopher
%A Borg, Erik
%B ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
%C Prague, Czech Republic
%D 2016
%K conference conrad dahms inproceedings lsfe seissiger
%P 171-175
%R 10.5194/isprs-archives-XLI-B2-171-2016
%T Modelling Biophysical Parameters Of Maize Using Landsat 8 Time Series
%U http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/171/2016/
%V XLI-B2
%X Open and free access to multifrequent high-resolution data (e.g. Sentinel-2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution.
@inproceedings{isprs-archives-XLI-B2-171-2016,
abstract = {Open and free access to multifrequent high-resolution data (e.g. Sentinel-2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. },
added-at = {2016-09-16T18:17:22.000+0200},
address = {Prague, Czech Republic},
author = {Dahms, Thorsten and Seissiger, Sylvia and Conrad, Christopher and Borg, Erik},
biburl = {https://www.bibsonomy.org/bibtex/2e2cab5c8ed5d7929b4e5bf91fcfc4a90/mschramm},
booktitle = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
day = {12. - 19.},
doi = {10.5194/isprs-archives-XLI-B2-171-2016},
interhash = {8f552270fb4a307ab910a51103ec95b3},
intrahash = {e2cab5c8ed5d7929b4e5bf91fcfc4a90},
keywords = {conference conrad dahms inproceedings lsfe seissiger},
month = jul,
pages = {171-175},
timestamp = {2016-09-21T15:17:24.000+0200},
title = {Modelling Biophysical Parameters Of Maize Using Landsat 8 Time Series},
url = {http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/171/2016/},
volume = {XLI-B2},
year = 2016
}