ArticleScientific reports2018
Monitoring cotton root rot by synthetic Sentinel-2 NDVI time series using improved spatial and temporal data fusion.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Object-oriented multi-scale segmentation and multi-feature fusion-based method for identifying typical fruit trees in arid regions using Sentinel-1/2 satellite images.Scientific reports · 2024Article
- Wildlife habitat mapping using Sentinel-2 imagery of Mehao Wildlife Sanctuary, Arunachal Pradesh, India.Heliyon · 2023Article
- Data Fusion in Agriculture: Resolving Ambiguities and Closing Data Gaps.Sensors (Basel, Switzerland) · 2022Review
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9 authors.
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Abstract
To better understand the progression of cotton root rot within the season, time series monitoring is required. In this study, an improved spatial and temporal data fusion approach (ISTDFA) was employed to combine 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Different Vegetation Index (NDVI) and 10-m Sentinetl-2 NDVI data to generate a synthetic Sentinel-2 NDVI time series for monitoring this disease. Then, the phenology of healthy cotton and infected cotton was modeled using a logistic model. Finally, several phenology parameters, including the onset day of greenness minimum (OGM), growing season length (GLS), onset of greenness increase (OGI), max NDVI value, and integral area of the phenology curve, were calculated. The results showed that ISTDFA could be used to combine time series MODIS and Sentinel-2 NDVI data with a correlation coefficient of 0.893. The logistic model could describe the phenology curves with R-squared values from 0.791 to 0.969. Moreover, the phenology curve of infected cotton showed a significant difference from that of healthy cotton. The max NDVI value, OGM, GSL and the integral area of the phenology curve for infected cotton were reduced by 0.045, 30 days, 22 days, and 18.54%, respectively, compared with those for healthy cotton.
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