Using Thermal Time and Pixel Purity for Enhancing Biophysical Variable Time Series: An Interproduct Comparison
| Autor: | Gregory Duveiller, Frédéric Baret, Pierre Defourny |
|---|---|
| Přispěvatelé: | Earth and Life Institute [Louvain-La-Neuve] (ELI), Université Catholique de Louvain = Catholic University of Louvain (UCL), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Global Agricultural Monitoring systems by integration of earth observation and modelling techniques (GLOBAM) Project, Belgian Federal Science Policy Office with the STEREO II Program [SR/00/101], Belgian Fond de la Recherche Scientifique, FNRS, Université Catholique de Louvain (UCL) |
| Rok vydání: | 2013 |
| Předmět: |
010504 meteorology & atmospheric sciences
leaf area index (LAI) 0211 other engineering and technologies 02 engineering and technology temporal smoothness 01 natural sciences Electrical and Electronic Engineering Leaf area index Image resolution 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing 2. Zero hunger Spatial filter Pixel spatial purity Enhanced vegetation index 15. Life on land Canopy structural dynamic model (CSDM) thermal time Temporal resolution [SDE]Environmental Sciences General Earth and Planetary Sciences Environmental science green area index (GAI) Moderate-resolution imaging spectroradiometer Scale (map) crop monitoring |
| Zdroj: | IEEE Transactions on Geoscience and Remote Sensing IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2013, 51 (4), pp.2119-2127. ⟨10.1109/TGRS.2012.2226731⟩ IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2013, ⟨10.1109/TGRS.2012.2226731⟩ |
| ISSN: | 1558-0644 0196-2892 |
| DOI: | 10.1109/tgrs.2012.2226731 |
| Popis: | This study presents a multi-annual comparison at regional scale of currently available 1 km global leaf area index (LAI) products with crop specific green are index (GAI) retrieved from MODIS 250 m imagery. The crop specific GAI product benefits from extra processing steps of (i) spatial filtering of time series based on pixel purity; (ii) transforming the time scale to thermal time; and (iii) fitting a canopy structural dynamic model (CSDM) to smooth out the signal. In order to perform a rigorous comparison, these steps were also applied to the 1 km LAI products, namely MODIS LAI (MCD15) and CYCLOPES LAI. The results confirm that, for winter wheat, the 250 m GAI product provides a more realistic description of the time course of the biophysical variable in terms of reaching higher values, grasping the variability and providing smoother time series. However, the use of thermal time and pixel purity also improves the temporal consistency and coherence of the 1 km products. Overall, the results of this study suggest that these techniques could be valuable in harmonizing remote sensing data coming from different sources with varying spatial and temporal resolution for enhanced vegetation monitoring. JRC.H.4-Monitoring Agricultural Resources |
| Databáze: | OpenAIRE |
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