[HTML][HTML] Crop yield prediction using multi sensors remote sensing
Pre-harvest prediction of a crop yield may prevent a disastrous situation and help decision-
makers to apply more reliable and accurate strategies regarding food security. Remote …
makers to apply more reliable and accurate strategies regarding food security. Remote …
[HTML][HTML] Application of remote sensors in map** rice area and forecasting its production: A review
MK Mosleh, QK Hassan, EH Chowdhury - Sensors, 2015 - mdpi.com
Rice is one of the staple foods for more than three billion people worldwide. Rice paddies
accounted for approximately 11.5% of the World's arable land area during 2012. Rice …
accounted for approximately 11.5% of the World's arable land area during 2012. Rice …
Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery
Timely and non-destructive assessment of crop yield is an essential part of agricultural
remote sensing (RS). The development of unmanned aerial vehicles (UAVs) has provided a …
remote sensing (RS). The development of unmanned aerial vehicles (UAVs) has provided a …
Predicting wheat yield at the field scale by combining high-resolution Sentinel-2 satellite imagery and crop modelling
Accurate prediction of crop yield at the field scale is critical to addressing crop production
challenges and reducing the impacts of climate variability and change. Recently released …
challenges and reducing the impacts of climate variability and change. Recently released …
[HTML][HTML] Combining spectral and textural information in UAV hyperspectral images to estimate rice grain yield
F Wang, Q Yi, J Hu, L **e, X Yao, T Xu… - International Journal of …, 2021 - Elsevier
The speedy development of UAV (Unmanned Aerial Vehicle) has provided more data
choices for crop yield estimation. In most cases, spectral information derived from …
choices for crop yield estimation. In most cases, spectral information derived from …
A tree based eXtreme Gradient Boosting (XGBoost) machine learning model to forecast the annual rice production in Bangladesh
In this study, we attempt to anticipate annual rice production in Bangladesh (1961–2020)
using both the Autoregressive Integrated Moving Average (ARIMA) and the eXtreme …
using both the Autoregressive Integrated Moving Average (ARIMA) and the eXtreme …
Rice yield estimation based on K-means clustering with graph-cut segmentation using low-altitude UAV images
Predicting the harvest yield enables farm practices to be modified throughout the growing
season, with potential to increase the final yield. Unmanned aerial vehicle (UAV) based …
season, with potential to increase the final yield. Unmanned aerial vehicle (UAV) based …
A comparative analysis of multitemporal MODIS EVI and NDVI data for large-scale rice yield estimation
Rice is one of the most important food crops worldwide, and large-scale rice yield estimation
is thus critical for planners to formulate successful strategies to address food security and …
is thus critical for planners to formulate successful strategies to address food security and …
Panicle-cloud: An open and ai-powered cloud computing platform for quantifying rice panicles from drone-collected imagery to enable the classification of yield …
Z Teng, J Chen, J Wang, S Wu, R Chen, Y Lin… - Plant …, 2023 - spj.science.org
Rice (Oryza sativa) is an essential stable food for many rice consumption nations in the
world and, thus, the importance to improve its yield production under global climate …
world and, thus, the importance to improve its yield production under global climate …
[HTML][HTML] Relationship between MODIS-NDVI data and wheat yield: A case study in Northern Buenos Aires province, Argentina
In countries like Argentina, whose economy depends heavily on crop production, the
estimation of harvests is an elementary requirement. Besides providing objectivity, the use of …
estimation of harvests is an elementary requirement. Besides providing objectivity, the use of …