Работы, на которые ссылается эта работа

Работ: 46

Работа: Combining PlanetScope and Sentinel-2 images with environmental data for improved wheat yield estimation

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
Overview of the radiometric and biophysical performance of the MODIS vegetation indices
Alfredo Huete, Kamel Didan, Tomoaki Miura +3
Статья2002Цитирований: 13
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
TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015
John T. Abatzoglou, Solomon Z. Dobrowski, Sean A. Parks +1
Статья2018Цитирований: 9
ABI
Classification and Regression by randomForest
Andy Liaw, Matthew C. Wiener
Статья2007Цитирований: 8
ABI
Без названия
ДругоеЦитирований: 4
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
High resolution wheat yield mapping using Sentinel-2
Merryn Hunt, George Alan Blackburn, Luis Carrasco +2
Статья2019Цитирований: 4
ABI
A modified soil adjusted vegetation index
Jiaguo Qi, Abdelghani Chehbouni, Alfredo Huete +2
Статья1994Цитирований: 4
ABI
Satellite-based soybean yield forecast: Integrating machine learning and weather data for improving crop yield prediction in southern Brazil
Raí Augusto Schwalbert, Telmo Jorge Carneiro Amado, Geomar Mateus Corassa +3
Статья2020Цитирований: 3
ABI
Spectral Reflectance Changes Associated with Autumn Senescence of Aesculus hippocastanum L. and Acer platanoides L. Leaves. Spectral Features and Relation to Chlorophyll Estimation
Anatoly A. Gitelson, Mark N. Merzlyak
Статья1994Цитирований: 3
ABI
Random forests: from early developments to recent advancements
Khaled Fawagreh, Mohamed Medhat Gaber, Eyad Elyan
Статья2014Цитирований: 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
Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture
D. Haboudane
Статья2004Цитирований: 3
ABI
SEN2-AGRI – CROP TYPE MAPPING PILOT STUDY USING SENTINEL-2 SATELLITE IMAGERY IN INDIA
D. Vijayasekaran
Статья2019Цитирований: 3
ABI
Crop Yield Prediction Using Machine Learning Models: Case of Irish Potato and Maize
Martin Kuradusenge, Eric Hitimana, Damien Hanyurwimfura +6
Статья2023Цитирований: 3
ABI
A uniform decimal code for growth stages of crops and weeds
Peter Lancashire, H. Bleiholder, T. van den Boom +4
Статья1991Цитирований: 2
ABI
Random Forests for Global and Regional Crop Yield Predictions
Jig Han Jeong, Jonathan P. Resop, Nathaniel D. Mueller +8
Статья2016Цитирований: 2
ABI
Combining Spatial and Temporal Corn Silage Yield Variability for Management Zone Development
Tulsi P. Kharel, Ángel Maresma, Karl Czymmek +2
Статья2019Цитирований: 2
ABI
Global Food Security: Challenges and Policies
Mark W. Rosegrant, Sarah A. Cline
Статья2003Цитирований: 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
Evaluation of the MERIS terrestrial chlorophyll index (MTCI)
Jadunandan Dash, Paul J. Curran
Статья2006Цитирований: 2
ABI