Работы, на которые ссылается эта работа

Работ: 84

Работа: A Novel Fusion Method for Soybean Yield Prediction Using Sentinel-2 and PlanetScope Imagery

Random Forests
Leo Breiman
Статья2001Цитирований: 67
ABI
A soil-adjusted vegetation index (SAVI)
Alfredo Huete
Статья1988Цитирований: 23
ABI
Red and photographic infrared linear combinations for monitoring vegetation
Compton J. Tucker
Статья1979Цитирований: 19
ABI
Use of a green channel in remote sensing of global vegetation from EOS-MODIS
Anatoly A. Gitelson, Yoram J. Kaufman, Mark N. Merzlyak
Статья1996Цитирований: 10
ABI
Big Data in Smart Farming – A review
J. Wolfert, Lan Ge, C.N. Verdouw +1
Обзорная статья2017Цитирований: 8
ABI
Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications
Jinru Xue, Baofeng Su
Обзорная статья2017Цитирований: 7
ABI
Без названия
ДругоеЦитирований: 7
ABI
Без названия
ДругоеЦитирований: 5
ABI
A survey of deep neural network architectures and their applications
Weibo Liu, Zidong Wang, Xiaohui Liu +3
Статья2016Цитирований: 5
ABI
Application of Vegetation Indices for Agricultural Crop Yield Prediction Using Neural Network Techniques
Sudhanshu Panda, Daniel P. Ames, Suranjan Panigrahi
Статья2010Цитирований: 5
ABI
Support vector regression
Fan Zhang, Lauren J. O’Donnell
Глава2019Цитирований: 5
ABI
Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans
Thomas J. Jackson, Daoyi Chen, Michael H. Cosh +5
Статья2003Цитирований: 4
ABI
Importance of phenological observations and predictions in agriculture
M. Ruml, Todor Vulić
Статья2005Цитирований: 4
ABI
Combining PlanetScope and Sentinel-2 images with environmental data for improved wheat yield estimation
Nizom Farmonov, Khilola Amankulova, József Szatmári +4
СтатьяRemote Sensing in AgricultureInternational Journal of Digital Earth2023Цитирований: 3
ABI
Crop Yield Prediction Using Deep Neural Networks
Saeed Khaki, Lizhi Wang
Статья2019Цитирований: 3
ABI
Time-series analysis of Sentinel-2 satellite images for sunflower yield estimation
Khilola Amankulova, Nizom Farmonov, László Mucsi
Статья2022Цитирований: 3
ABI
A comparison of random forest regression and multiple linear regression for prediction in neuroscience
Paul F. Smith, Siva Ganesh, Ping Liu
Статья2013Цитирований: 3
ABI
SEN2-AGRI – CROP TYPE MAPPING PILOT STUDY USING SENTINEL-2 SATELLITE IMAGERY IN INDIA
D. Vijayasekaran
Статья2019Цитирований: 3
ABI
Без названия
ДругоеЦитирований: 3
ABI
Spatial patterns of seed dispersal, their determinants and consequences for recruitment
Ran Nathan, Helene C. Muller‐Landau
Статья2000Цитирований: 2
ABI
Use of Remote‐Sensing Imagery to Estimate Corn Grain Yield
John F. Shanahan, James S. Schepers, D. D. Francis +5
Статья2001Цитирований: 2
ABI
Studying the Feasibility of Assimilating Sentinel-2 and PlanetScope Imagery into the SAFY Crop Model to Predict Within-Field Wheat Yield
V. S. Manivasagam, Yuval Sadeh, Gregoriy Kaplan +2
Статья2021Цитирований: 2
ABI
Global estimation of crop productivity and the impacts of global warming by GIS and EPIC integration
Guoxin Tan, Ryosuke Shibasaki
Статья2003Цитирований: 2
ABI
Post-processing methods to eliminate erroneous grain yield measurements: review and directions for future development
Greg Lyle, Brett A. Bryan, Bertram Ostendorf
Статья2013Цитирований: 2
ABI
Soybean yield prediction from UAV using multimodal data fusion and deep learning
Maitiniyazi Maimaitijiang, Vasit Sagan, Paheding Sidike +3
Статья2019Цитирований: 2
ABI