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Impact of STARFM on Crop Yield Predictions: Fusing MODIS with Landsat 5, 7, and 8 NDVIs in Bavaria Germany

Dhillon, Maninder Singh; Dahms, Thorsten; Kübert-Flock, Carina; Liepa, Adomas; Rummler, Thomas; Arnault, Joel 1; Steffan-Dewenter, Ingolf; Ullmann, Tobias
1 Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT)

Abstract:

Rapid and accurate yield estimates at both field and regional levels remain the goal of sustainable agriculture and food security. Hereby, the identification of consistent and reliable methodologies providing accurate yield predictions is one of the hot topics in agricultural research. This study investigated the relationship of spatiotemporal fusion modelling using STRAFM on crop yield prediction for winter wheat (WW) and oil-seed rape (OSR) using a semi-empirical light use efficiency (LUE) model for the Free State of Bavaria (70,550 km2), Germany, from 2001 to 2019. A synthetic normalised difference vegetation index (NDVI) time series was generated and validated by fusing the high spatial resolution (30 m, 16 days) Landsat 5 Thematic Mapper (TM) (2001 to 2012), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) (2012), and Landsat 8 Operational Land Imager (OLI) (2013 to 2019) with the coarse resolution of MOD13Q1 (250 m, 16 days) from 2001 to 2019. Except for some temporal periods (i.e., 2001, 2002, and 2012), the study obtained an R2 of more than 0.65 and a RMSE of less than 0.11, which proves that the Landsat 8 OLI fused products are of higher accuracy than the Landsat 5 TM products. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000160896
Veröffentlicht am 25.07.2023
Originalveröffentlichung
DOI: 10.3390/rs15061651
Scopus
Zitationen: 4
Web of Science
Zitationen: 3
Dimensions
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 18.03.2023
Sprache Englisch
Identifikator ISSN: 2072-4292
KITopen-ID: 1000160896
HGF-Programm 12.11.33 (POF IV, LK 01) Regional Climate and Hydrological Cycle
Erschienen in Remote Sensing
Verlag MDPI
Band 15
Heft 6
Seiten Art.-Nr. 1651
Nachgewiesen in Scopus
Web of Science
Dimensions
Globale Ziele für nachhaltige Entwicklung Ziel 2 – Kein HungerZiel 8 – Menschenwürdige Arbeit und WirtschaftswachstumZiel 12 – Nachhaltiger Konsum und ProduktionZiel 17 – Partnerschaften zur Erreichung der Ziele
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