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Details zur Publikation

Referenztyp Zeitschriften
DOI / URL Link
Titel (primär) Optimising phenological metrics extraction for different crop types in Germany using the Moderate Resolution Imaging Spectrometer (MODIS)
Autor Xu, X.; Conrad, C.; Doktor, D.;
Journal / Serie Remote Sensing
Erscheinungsjahr 2017
Department CLE;
Band/Volume 9
Heft 3
Sprache englisch;
POF III (gesamt) T53; T12;
Keywords crop; phenology; moderate resolution imaging spectrometer (MODIS); normalized difference vegetation index (NDVI); phenological metrics; field observations
UFZ Querschnittsthemen RU1
Abstract Phenological metrics extracted from satellite data (phenometrics) have been increasingly used to access timely, spatially explicit information on crop phenology, but have rarely been calibrated and validated with field observations. In this study, we developed a calibration procedure to make phenometrics more comparable to ground-based phenological stages by optimising the settings of Best Index Slope Extraction (BISE) and smoothing algorithms together with thresholds. We used a six-year daily Moderate Resolution Imaging Spectrometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series and 211 ground-observation records from four major crop species (winter wheat/barley, oilseed rape, and sugar beet) in central Germany. Results showed the superiority of the Savitzky–Golay algorithm in combination with BISE. The satellite-derived senescence dates matched ripeness stages of winter crops and the dates with maximum NDVI were closely related to the field-observed heading stage of winter cereals. We showed that the emergence of winter crops corresponded to the dates extracted with a threshold of 0.1, which translated into 8.89 days of root-mean-square error (RMSE) improvement compared to the standard threshold of 0.5. The method with optimised settings and thresholds can be easily transferred and applied to areas with similar growing conditions. Altogether, the results improve our understanding of how satellite-derived phenometrics can explain in situ phenological observations.
ID 18513
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=18513
Xu, X., Conrad, C., Doktor, D. (2017):
Optimising phenological metrics extraction for different crop types in Germany using the Moderate Resolution Imaging Spectrometer (MODIS)
Remote Sens. 9 (3), art. 254