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Jieyu Liang, Chao Ren, Yi Li, Weiting Yue, Zhenkui Wei, Xiaohui Song, Xudong Zhang, Anchao Yin and Xiaoqi Lin
Normalized difference vegetation index (NDVI) time series data, derived from optical images, play a crucial role for crop mapping and growth monitoring. Nevertheless, optical images frequently exhibit spatial and temporal discontinuities due to cloudy an...
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Laura Recuero, Lilian Maila, Víctor Cicuéndez, César Sáenz, Javier Litago, Lucía Tornos, Silvia Merino-de-Miguel and Alicia Palacios-Orueta
Multiple cropping systems constitute an essential agricultural practice that will ensure food security within the increasing demand of basic cereals as a consequence of global population growth and climate change effects. In this regard, there is a need ...
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Markus C. Casper, Zoé Salm, Oliver Gronz, Christopher Hutengs, Hadis Mohajerani and Michael Vohland
The land-use-specific calibration of evapotranspiration parameters in hydrologic modeling is challenging due to the lack of appropriate reference data. We present a MODIS-based calibration approach of vegetation-related evaporation parameters for two mes...
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Taketo Eguchi and Masahiro Tasumi
This study investigated two popular satellite-derived vegetation indices (VIs), MODIS NDVI and EVI, as tools for monitoring crop growth at the Thapanzeik Dam irrigation district in Myanmar, where quality ground data are difficult to obtain. The time-seri...
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Fa Zhao, Guijun Yang, Hao Yang, Huiling Long, Weimeng Xu, Yaohui Zhu, Yang Meng, Shaoyu Han and Miao Liu
Accurate determination of crop phenology is key to field management and decision making. The existing research on phenology based on remote sensing data is mainly phenology monitoring, which cannot realize the prediction of phenology. In this paper, we p...
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Inder Tecuapetla-Gómez, Gerardo López-Saldaña, María Isabel Cruz-López and Rainer Ressl
Earth observation (EO) data play a crucial role in monitoring ecosystems and environmental processes. Time series of satellite data are essential for long-term studies in this context. Working with large volumes of satellite data, however, can still be a...
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Valery Bondur, Viktor Zamshin, Olga Chvertkova, Ekaterina Matrosova and Vasilisa Khodaeva
In this paper, the causes of the anomalous harmful algal bloom which occurred in the fall of 2020 in Kamchatka have been detected and analyzed using a long-term time series of heterogeneous satellite and simulated data with respect to the sea surface hei...
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Yangnan Guo, Cangjiao Wang, Shaogang Lei, Junzhe Yang and Yibo Zhao
Spatio-temporal fusion algorithms dramatically enhance the application of the Landsat time series. However, each spatio-temporal fusion algorithm has its pros and cons of heterogeneous land cover performance, the minimal number of input image pairs, and ...
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Níckolas Castro Santana, Osmar Abílio de Carvalho Júnior, Roberto Arnaldo Trancoso Gomes and Renato Fontes Guimarães
Monitoring of fire-related changes is essential to understand vegetation dynamics in the medium and long term. Remote sensing time series allows estimating biophysical variables of terrestrial vegetation and interference by extreme fires. This research e...
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Hongzhu Han, Jianjun Bai, Gao Ma and Jianwu Yan
Vegetation phenology is highly sensitive to climate change, and the phenological responses of vegetation to climate factors vary over time and space. Research on the vegetation phenology in different climatic regimes will help clarify the key factors aff...
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