Challenges and opportunities in remote sensing-based crop monitoring: A review

B Wu, M Zhang, H Zeng, F Tian… - National Science …, 2023 - academic.oup.com
Building a more resilient food system for sustainable development and reducing uncertainty
in global food markets both require concurrent and near-real-time and reliable crop …

A systematic review of local to regional yield forecasting approaches and frequently used data resources

B Schauberger, J Jägermeyr, C Gornott - European Journal of Agronomy, 2020 - Elsevier
Forecasting crop yields, or providing an expectation of ex-ante harvest amounts, is highly
relevant to the whole agricultural production chain. Farmers can adapt their management …

[HTML][HTML] A comparison of global agricultural monitoring systems and current gaps

S Fritz, L See, JCL Bayas, F Waldner, D Jacques… - Agricultural systems, 2019 - Elsevier
Global and regional scale agricultural monitoring systems aim to provide up-to-date
information regarding food production to different actors and decision makers in support of …

Bridging optical and SAR satellite image time series via contrastive feature extraction for crop classification

Y Yuan, L Lin, ZG Zhou, H Jiang, Q Liu - ISPRS Journal of Photogrammetry …, 2023 - Elsevier
Precise crop mapping is crucial for guiding agricultural production, forecasting crop yield,
and ensuring food security. Integrating optical and synthetic aperture radar (SAR) satellite …

Mapping winter crops using a phenology algorithm, time-series Sentinel-2 and Landsat-7/8 images, and Google Earth Engine

L Pan, H Xia, X Zhao, Y Guo, Y Qin - Remote sensing, 2021 - mdpi.com
With the increasing population and continuation of climate change, an adequate food supply
is vital to economic development and social stability. Winter crops are important crop types …

Estimating crop primary productivity with Sentinel-2 and Landsat 8 using machine learning methods trained with radiative transfer simulations

A Wolanin, G Camps-Valls, L Gómez-Chova… - Remote sensing of …, 2019 - Elsevier
Satellite remote sensing has been widely used in the last decades for agricultural
applications, both for assessing vegetation condition and for subsequent yield prediction …

[HTML][HTML] Automated mapping of soybean and corn using phenology

L Zhong, L Hu, L Yu, P Gong, GS Biging - ISPRS Journal of …, 2016 - Elsevier
For the two of the most important agricultural commodities, soybean and corn, remote
sensing plays a substantial role in delivering timely information on the crop area for …

[HTML][HTML] No pixel left behind: Toward integrating Earth Observations for agriculture into the United Nations Sustainable Development Goals framework

AK Whitcraft, I Becker-Reshef, CO Justice… - Remote Sensing of …, 2019 - Elsevier
Remotely sensed Earth observations (EO) have their history firmly rooted in agricultural
monitoring, and more recently with applications in food production, food security, and …

Crop yield forecasting and associated optimum lead time analysis based on multi-source environmental data across China

L Li, B Wang, P Feng, H Wang, Q He, Y Wang… - Agricultural and Forest …, 2021 - Elsevier
Accurate and timely crop yield forecasts can provide essential information to make
conclusive agricultural policies and to conduct investments. Recent studies have used …

Development of a 10-m resolution maize and soybean map over China: Matching satellite-based crop classification with sample-based area estimation

H Li, XP Song, MC Hansen, I Becker-Reshef… - Remote Sensing of …, 2023 - Elsevier
Spatially explicit information on crop distribution is essential for market information, food
security, and agricultural sustainability. However, high-resolution crop maps are unavailable …