Cargando…
Monitoring cotton root rot by synthetic Sentinel-2 NDVI time series using improved spatial and temporal data fusion
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 Vegeta...
Autores principales: | Wu, Mingquan, Yang, Chenghai, Song, Xiaoyu, Hoffmann, Wesley Clint, Huang, Wenjiang, Niu, Zheng, Wang, Changyao, Li, Wang, Yu, Bo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5792467/ https://www.ncbi.nlm.nih.gov/pubmed/29386526 http://dx.doi.org/10.1038/s41598-018-20156-z |
Ejemplares similares
-
Generating Daily Synthetic Landsat Imagery by Combining Landsat and MODIS Data
por: Wu, Mingquan, et al.
Publicado: (2015) -
Combining HJ CCD, GF-1 WFV and MODIS Data to Generate Daily High Spatial Resolution Synthetic Data for Environmental Process Monitoring
por: Wu, Mingquan, et al.
Publicado: (2015) -
Molecular systematics of the cotton root rot pathogen, Phymatotrichopsis omnivora
por: Marek, S.M., et al.
Publicado: (2009) -
Research on Rice Fields Extraction by NDVI Difference Method Based on Sentinel Data
por: Tian, Jinglian, et al.
Publicado: (2023) -
Prediction of Human Brucellosis in China Based on Temperature and NDVI
por: Zhao, Yongqing, et al.
Publicado: (2019)