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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #316411
Title: Evaluating the temporal stability of synthetically generated time-series for crop types in central Germany

Author
item FORSTER, MICHAEL - Collaborator
item MOLLER, MARKUS - Collaborator
item Gao, Feng
item SCHMIDT, TOBIAS - Collaborator
item GARTNER, PHILIPP - Collaborator
item KLEINSCHMIT, BIRGIT - Collaborator

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 3/15/2015
Publication Date: 7/22/2015
Citation: Forster, M., Moller, M., Gao, F.N., Schmidt, T., Gartner, P., Kleinschmit, B. 2015. Evaluating the temporal stability of synthetically generated time-series for crop types in central Germany [abstract]. 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images, July 22-24, 2015 – Annecy, France.

Interpretive Summary:

Technical Abstract: Synthetically generated Landsat time-series based on the STARFM algorithm are increasingly used for applications in forestry or agriculture. Although successes in classification and derivation of phenological orbiomass parameters are evident, a thorough evaluation of the limits of the method is still needed. A class-wise evaluation of the temporal stability of crop classes could significantly increase the knowledge about the applicability of this type of fusion algorithms.The presented study is evaluating a typical synthetic Landsat-like timeseries derived from MODIS terra daily products of an intensively agriculturally cultivated area in Germany in 2011. The derived NDVI product was compared to RapidEye imagery for the 12 most commonly used agricultural classes in the study area.