[728] - Analysis of multitemporal and multisensor remote sensing data for crop rotation mapping

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Waldhoff, G., Curdt, C., Hoffmeister, D., Bareth, G., 2012. Analysis of multitemporal and multisensor remote sensing data for crop rotation mapping. In: Shortis, M., Wagner, W., Hyyppä, J. (Eds.): ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Proc. of XXII ISPRS Congress, August 25 - September 01, 2012, Melbourne, Australia, 177 - 182. DOI: 10.5194/isprsannals-I-7-177-2012.
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Title(s):Main Title: Analysis of multitemporal and multisensor remote sensing data for crop rotation mapping
Description(s):Abstract: For accurate regional modelling of (agro-)ecosystems, up-to-date land use information is essential to assess the impact of the permanent changing vegetation cover of agricultural land on matter fluxes in the soil-vegetation-atmosphere (SVA) system. In this regard, officially available land use datasets are mostly inadequate, since they only provide generalised information concerning agricultural land use. In this contribution, we present our work for the year 2008 on the generation of multi temporal, disaggregated land use data with the goal to derive a crop rotation map for the years 2008-2010 for the study area of the research project CRC/TR 32. For this purpose, the Multi-Data Approach (MDA) was used to integrate multitemporal remote sensing classifications with additional spatial information by the means of expert knowledge-based production rules. Our results show that the information content of a land use dataset is considerably enhanced by combining crop type information of multiple observations during each growing season. For a sufficient temporal coverage, the usage of multiple sensors is generally inevitable. Thus, datasets of ASTER, Landsat TM & ETM+ as well as IRS-P6 were incorporated. In terms of classification accuracy our analysis yielded similar results with support vector machines (SVM) and the classical maximum likelihood classifier (MLC) for all sensors, with SVM being mostly only slightly better. For the refinement of land parcel boundaries and the reduction of misclassification, the incorporation of the ‘field block’ (FB) vector information was very effective. ‘Field blocks’, provided by the chamber of agriculture, are coherent agricultural areas with (relatively) permanent boundaries. As a result, a much more accurate differentiation of agricultural land and non- agricultural land was achieved. With the enhanced annual MDA land use data of the three consecutive years containing crop type information sufficient information is available for the derivation of crop rotation. Again, adapted knowledge-based production rules are used for this purpose.
Identifier(s):DOI: 10.5194/isprsannals-I-7-177-2012
Responsible Party
Creator(s):Author: Guido Waldhoff
Author: Constanze Curdt
Author: Dirk Hoffmeister
Author: Georg Bareth
TR32 Topic:Remote Sensing
Related Sub-project(s):Z1
Subject(s):CRC/TR32 Keywords: Multisensor, Multi-Temporal, Remote Sensing, Crop/s, GIS, Land Cover, Classification
File Details
File Name:2012_Waldhoff_ISPRS.pdf
Data Type:Text
Size(s):6 Pages
File Size:1207 kB (1.179 MB)
Date(s):Issued: 2012-08-25
Mime Type:application/pdf
Data Format:PDF
Download Permission:OnlyTR32
General Access and Use Conditions:For internal use only
Access Limitations:For internal use only
Licence:TR32DB Data policy agreement
Measurement Region:RurCatchment
Measurement Location:--RurCatchment--
Specific Informations - Publication
Type:Event Paper
Proceedings Title:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Proceedings Editor:Shortis, M., Wagner, W., Hyyppä, J.
Number Of Pages:6
Page Range:177 - 182
Event Name:XXII ISPRS Congress
Event Type:Conference
Event Location:Melbourne, Australia
Event Period:25th of August, 2012 - 1st of September, 2012
Event Url:http://www.isprs2012.org/
Metadata Details
Metadata Creator:Guido Waldhoff
Metadata Created:2013-12-05
Metadata Last Updated:2013-12-05
Funding Phase:2
Metadata Language:English
Metadata Version:V40
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