Random forest in remote sensing: A review of applications and future directions
A random forest (RF) classifier is an ensemble classifier that produces multiple decision
trees, using a randomly selected subset of training samples and variables. This classifier …
trees, using a randomly selected subset of training samples and variables. This classifier …
A review of remote sensing applications in agriculture for food security: Crop growth and yield, irrigation, and crop losses
The global population is expected to reach 9.8 billion by 2050. There is an exponential
growth of food production to meet the needs of the growing population. However, the limited …
growth of food production to meet the needs of the growing population. However, the limited …
Satellite-based soybean yield forecast: Integrating machine learning and weather data for improving crop yield prediction in southern Brazil
Soybean yield predictions in Brazil are of great interest for market behavior, to drive
governmental policies and to increase global food security. In Brazil soybean yield data …
governmental policies and to increase global food security. In Brazil soybean yield data …
Winter wheat yield prediction at county level and uncertainty analysis in main wheat-producing regions of China with deep learning approaches
Timely and accurate forecasting of crop yields is crucial to food security and sustainable
development in the agricultural sector. However, winter wheat yield estimation and …
development in the agricultural sector. However, winter wheat yield estimation and …
Seasonal crop yield forecast: Methods, applications, and accuracies
The perfect knowledge of yield before harvest has been a wish puzzling human being since
the beginning of agriculture because seasonal forecast of crop yield plays a critical role in …
the beginning of agriculture because seasonal forecast of crop yield plays a critical role in …
Prediction of crop yield using phenological information extracted from remote sensing vegetation index
Z Ji, Y Pan, X Zhu, J Wang, Q Li - Sensors, 2021 - mdpi.com
Phenology is an indicator of crop growth conditions, and is correlated with crop yields. In this
study, a phenological approach based on a remote sensing vegetation index was explored …
study, a phenological approach based on a remote sensing vegetation index was explored …
Pre-and within-season crop type classification trained with archival land cover information
DM Johnson, R Mueller - Remote Sensing of Environment, 2021 - Elsevier
Crop type maps were created without the traditional need for in-season training data across
the Corn Belt and Great Plains regions of the United States. This was accomplished through …
the Corn Belt and Great Plains regions of the United States. This was accomplished through …
Map** winter crops using a phenology algorithm, time-series Sentinel-2 and Landsat-7/8 images, and Google Earth Engine
L Pan, H ** using MODIS NDVI data, growing degree days information and a Gaussian mixture model
Abstract Knowledge on geographical location and distribution of crops at global, national
and regional scales is an extremely valuable source of information for many applications …
and regional scales is an extremely valuable source of information for many applications …
Early-season map** of winter wheat in China based on Landsat and Sentinel images
J Dong, Y Fu, J Wang, H Tian, S Fu… - Earth System …, 2020 - essd.copernicus.org
Early-season crop identification is of great importance for monitoring crop growth and
predicting yield for decision makers and private sectors. As one of the largest producers of …
predicting yield for decision makers and private sectors. As one of the largest producers of …