Remote sensing-based global crop monitoring: experiences with China's CropWatch system

B Wu, J Meng, Q Li, N Yan, X Du… - International Journal of …, 2014 - Taylor & Francis
Monitoring the production of main agricultural crops is important to predict and prepare for
disruptions in food supply and fluctuations in global crop market prices. China's global crop …

[HTML][HTML] Use time series NDVI and EVI to develop dynamic crop growth metrics for yield modeling

SA Shammi, Q Meng - Ecological Indicators, 2021 - Elsevier
The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI)
derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery are …

[HTML][HTML] The Evaporative Stress Index as an indicator of agricultural drought in Brazil: An assessment based on crop yield impacts

MC Anderson, CA Zolin, PC Sentelhas, CR Hain… - Remote Sensing of …, 2016 - Elsevier
To effectively meet growing food demands, the global agronomic community will require a
better understanding of factors that are currently limiting crop yields and where production …

Crop height monitoring with digital imagery from Unmanned Aerial System (UAS)

A Chang, J Jung, MM Maeda, J Landivar - Computers and electronics in …, 2017 - Elsevier
Crop height is a very important attribute to assess overall crop condition, irrigation, and
estimation of terminal yield. In this study, a novel method to monitor crop height of Sorghum …

Daily mapping of 30 m LAI and NDVI for grape yield prediction in California vineyards

L Sun, F Gao, MC Anderson, WP Kustas, MM Alsina… - Remote Sensing, 2017 - mdpi.com
Wine grape quality and quantity are affected by vine growing conditions during critical
phenological stages. Field observations of vine growth stages are too sparse to fully capture …

[HTML][HTML] Comparison of vegetation indices derived from UAV data for differentiation of tillage effects in agriculture

J Yeom, J Jung, A Chang, A Ashapure, M Maeda… - Remote Sensing, 2019 - mdpi.com
Unmanned aerial vehicle (UAV) platforms with sensors covering the red-edge and near-
infrared (NIR) bands to measure vegetation indices (VIs) have been recently introduced in …

Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA's-AVHRR

J Huang, X Wang, X Li, H Tian, Z Pan - PloS one, 2013 - journals.plos.org
Grain-yield prediction using remotely sensed data have been intensively studied in wheat
and maize, but such information is limited in rice, barley, oats and soybeans. The present …

Optimal county-level crop yield prediction using MODIS-based variables and weather data: A comparative study on machine learning models

S Ju, H Lim, JW Ma, S Kim, K Lee, S Zhao… - Agricultural and Forest …, 2021 - Elsevier
Accurate crop yield prediction for more precise forecasting of price volatility in crop markets,
better agricultural planning and enhanced national food security is one of the important …

A data-driven crop model for maize yield prediction

Y Chang, J Latham, M Licht, L Wang - Communications Biology, 2023 - nature.com
Accurate estimation of crop yield predictions is of great importance for food security under
the impact of climate change. We propose a data-driven crop model that combines the …

Using NDVI percentiles to monitor real-time crop growth

C Li, H Li, J Li, Y Lei, C Li, K Manevski… - Computers and Electronics …, 2019 - Elsevier
Abstract The Normalized Difference Vegetation Index (NDVI) is a widely used remote
sensing indicator for crop growth monitoring, farmland management and crop production …