[HTML][HTML] Map** crop phenology in near real-time using satellite remote sensing: Challenges and opportunities

F Gao, X Zhang - Journal of Remote Sensing, 2021 - spj.science.org
Crop phenology is critical for agricultural management, crop yield estimation, and
agroecosystem assessment. Traditionally, crop growth stages are observed from the ground …

[BOEK][B] Deep learning for the Earth Sciences: A comprehensive approach to remote sensing, climate science and geosciences

G Camps-Valls, D Tuia, XX Zhu, M Reichstein - 2021 - books.google.com
DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep
learning in the field of earth sciences, from four leading voices Deep learning is a …

Global climate

RJH Dunn, JB Miller, KM Willett… - Bulletin of the …, 2023 - journals.ametsoc.org
Global Climate is one chapter from the State of the Climate in 2022 annual report and is
available from https://doi. org/10.1175/BAMS-D-23-0090.1. Compiled by NOAA's National …

Develo** an operational algorithm for near-real-time monitoring of crop progress at field scales by fusing harmonized Landsat and Sentinel-2 time series with …

Y Shen, X Zhang, Z Yang, Y Ye, J Wang, S Gao… - Remote Sensing of …, 2023 - Elsevier
Crop phenology has been widely detected from multiple historical satellite observations.
Conversely, Near-Real-Time (NRT) monitoring of crop progress from timely available remote …

A novel algorithm for the generation of gap-free time series by fusing harmonized Landsat 8 and Sentinel-2 observations with PhenoCam time series for detecting land …

KH Tran, X Zhang, AR Ketchpaw, J Wang, Y Ye… - Remote Sensing of …, 2022 - Elsevier
Vegetation phenology is one of the most sensitive indicators to environmental and climate
changes. In order to characterize the seasonal variation in relatively pure or homogenous …

[HTML][HTML] Monitoring cropland phenology on Google Earth Engine using gaussian process regression

M Salinero-Delgado, J Estévez, L Pipia, S Belda… - Remote sensing, 2021 - mdpi.com
Monitoring cropland phenology from optical satellite data remains a challenging task due to
the influence of clouds and atmospheric artifacts. Therefore, measures need to be taken to …