[HTML][HTML] High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques

S Li, L Xu, Y **g, H Yin, X Li, X Guan - International Journal of Applied …, 2021 - Elsevier
Normalized difference vegetation index (NDVI) derived from satellites has been ubiquitously
utilized in the field of remote sensing. Nevertheless, there are multitudinous contaminations …

A review of vegetation phenological metrics extraction using time-series, multispectral satellite data

L Zeng, BD Wardlow, D ** platforms
X **, PJ Zarco-Tejada, U Schmidhalter… - … and Remote Sensing …, 2020 - ieeexplore.ieee.org
Crop yields need to be improved in a sustainable manner to meet the expected worldwide
increase in population over the coming decades as well as the effects of anticipated climate …

Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods

E Kamir, F Waldner, Z Hochman - ISPRS Journal of Photogrammetry and …, 2020 - Elsevier
Closing the yield gap between actual and potential wheat yields in Australia is important to
meet the growing global demand for food. The identification of hotspots of the yield gap …

Assessing the robustness of Random Forests to map land cover with high resolution satellite image time series over large areas

C Pelletier, S Valero, J Inglada, N Champion… - Remote Sensing of …, 2016 - Elsevier
New remote sensing sensors will acquire High spectral, spatial and temporal Resolution
Satellite Image Time Series (HR-SITS). These new data are of great interest to map land …

Impacts of climate change on vegetation phenology and net primary productivity in arid Central Asia

L Wu, X Ma, X Dou, J Zhu, C Zhao - Science of the Total Environment, 2021 - Elsevier
Vegetation is highly sensitive to climate changes in arid regions. The relationship between
vegetation and climate changes can be effectively characterized by vegetation phenology …

Missing information reconstruction of remote sensing data: A technical review

H Shen, X Li, Q Cheng, C Zeng, G Yang… - … and Remote Sensing …, 2015 - ieeexplore.ieee.org
Because of sensor malfunction and poor atmospheric conditions, there is usually a great
deal of missing information in optical remote sensing data, which reduces the usage rate …