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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Mapping crop phenology using NDVI time-series derived from HJ-1 A/B data
Zhuokun Pan, Jingfeng Huang, Qingbo Zhou, et al.
International Journal of Applied Earth Observation and Geoinformation (2014) Vol. 34, pp. 188-197
Open Access | Times Cited: 245

Showing 1-25 of 245 citing articles:

A review of vegetation phenological metrics extraction using time-series, multispectral satellite data
Linglin Zeng, Brian D. Wardlow, Daxiang Xiang, et al.
Remote Sensing of Environment (2019) Vol. 237, pp. 111511-111511
Closed Access | Times Cited: 600
A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform
Pardhasaradhi Teluguntla, Prasad S. Thenkabail, Adam Oliphant, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2018) Vol. 144, pp. 325-340
Open Access | Times Cited: 462
Automated cropland mapping of continental Africa using Google Earth Engine cloud computing
Jun Xiong, Prasad S. Thenkabail, Murali Krishna Gumma, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2017) Vol. 126, pp. 225-244
Open Access | Times Cited: 455
Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data
Geli Zhang, Xiangming Xiao, Jinwei Dong, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2015) Vol. 106, pp. 157-171
Open Access | Times Cited: 269
High-Throughput Estimation of Crop Traits: A Review of Ground and Aerial Phenotyping Platforms
Xiuliang Jin, Pablo J. Zarco‐Tejada, Urs Schmidhalter, et al.
IEEE Geoscience and Remote Sensing Magazine (2020) Vol. 9, Iss. 1, pp. 200-231
Open Access | Times Cited: 222
ChinaCropPhen1km: a high-resolution crop phenological dataset for three staple crops in China during 2000–2015 based on leaf area index (LAI) products
Yuchuan Luo, Zhao Zhang, Yi Chen, et al.
Earth system science data (2020) Vol. 12, Iss. 1, pp. 197-214
Open Access | Times Cited: 216
Vegetation phenology from Sentinel-2 and field cameras for a Dutch barrier island
Anton Vrieling, Michele Meroni, Roshanak Darvishzadeh, et al.
Remote Sensing of Environment (2018) Vol. 215, pp. 517-529
Open Access | Times Cited: 203
Crop monitoring by multimodal remote sensing: A review
Priyabrata Karmakar, Shyh Wei Teng, Manzur Murshed, et al.
Remote Sensing Applications Society and Environment (2023) Vol. 33, pp. 101093-101093
Open Access | Times Cited: 52
Evaluation of Sentinel-1 & 2 time series for predicting wheat and rapeseed phenological stages
Audrey Mercier, Julie Betbeder, Jacques Baudry, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 163, pp. 231-256
Open Access | Times Cited: 135
Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2
Yan Cheng, Anton Vrieling, Francesco Fava, et al.
Remote Sensing of Environment (2020) Vol. 248, pp. 112004-112004
Open Access | Times Cited: 132
A near real-time deep learning approach for detecting rice phenology based on UAV images
Qi Yang, Liangsheng Shi, Jingye Han, et al.
Agricultural and Forest Meteorology (2020) Vol. 287, pp. 107938-107938
Closed Access | Times Cited: 126
Unmanned Aerial Vehicle to Estimate Nitrogen Status of Turfgrasses
Lisa Caturegli, Matteo Corniglia, Monica Gaetani, et al.
PLoS ONE (2016) Vol. 11, Iss. 6, pp. e0158268-e0158268
Open Access | Times Cited: 116
Fusion of Sentinel-2 and PlanetScope time-series data into daily 3 m surface reflectance and wheat LAI monitoring
Yuval Sadeh, Xuan Zhu, David Dunkerley, et al.
International Journal of Applied Earth Observation and Geoinformation (2020) Vol. 96, pp. 102260-102260
Open Access | Times Cited: 113
Detection of rice phenology through time series analysis of ground-based spectral index data
Hengbiao Zheng, Tao Cheng, Xia Yao, et al.
Field Crops Research (2016) Vol. 198, pp. 131-139
Closed Access | Times Cited: 102
Estimating natural grassland biomass by vegetation indices using Sentinel 2 remote sensing data
Marildo Guerini Filho, Tatiana Mora Kuplich, Fernando Luíz Ferreira de Quadros
International Journal of Remote Sensing (2019) Vol. 41, Iss. 8, pp. 2861-2876
Closed Access | Times Cited: 102
Sentinel-1 time series data for monitoring the phenology of winter wheat
Michael Schlund, Stefan Erasmi
Remote Sensing of Environment (2020) Vol. 246, pp. 111814-111814
Closed Access | Times Cited: 88
Evaluation of Using Sentinel-1 and -2 Time-Series to Identify Winter Land Use in Agricultural Landscapes
Julien Denize, Laurence Hubert‐Moy, Julie Betbeder, et al.
Remote Sensing (2018) Vol. 11, Iss. 1, pp. 37-37
Open Access | Times Cited: 84
Exploiting Time Series of Sentinel-1 and Sentinel-2 Imagery to Detect Meadow Phenology in Mountain Regions
Laura Stendardi, Stein Rune Karlsen, Georg Niedrist, et al.
Remote Sensing (2019) Vol. 11, Iss. 5, pp. 542-542
Open Access | Times Cited: 81
Advances in spaceborne hyperspectral remote sensing in China
Yanfei Zhong, Xinyu Wang, Shaoyu Wang, et al.
Geo-spatial Information Science (2021) Vol. 24, Iss. 1, pp. 95-120
Open Access | Times Cited: 81
Detailed agricultural land classification in the Brazilian cerrado based on phenological information from dense satellite image time series
Hugo do Nascimento Bendini, Leila María García Fonseca, Marcel Schwieder, et al.
International Journal of Applied Earth Observation and Geoinformation (2019) Vol. 82, pp. 101872-101872
Open Access | Times Cited: 80
Improving prediction of soil organic carbon content in croplands using phenological parameters extracted from NDVI time series data
Lin Yang, Xianglin He, Feixue Shen, et al.
Soil and Tillage Research (2019) Vol. 196, pp. 104465-104465
Closed Access | Times Cited: 77
Change Detection Techniques Based on Multispectral Images for Investigating Land Cover Dynamics
Dyah Retno Panuju, David Paull, Amy L. Griffin
Remote Sensing (2020) Vol. 12, Iss. 11, pp. 1781-1781
Open Access | Times Cited: 72
10-m-resolution mangrove maps of China derived from multi-source and multi-temporal satellite observations
Chuanpeng Zhao, Cheng‐Zhi Qin
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 169, pp. 389-405
Closed Access | Times Cited: 72
A systematic method for spatio-temporal phenology estimation of paddy rice using time series Sentinel-1 images
Huijin Yang, Bin Pan, Ning Li, et al.
Remote Sensing of Environment (2021) Vol. 259, pp. 112394-112394
Closed Access | Times Cited: 69
Assimilation of soil moisture and canopy cover data improves maize simulation using an under-calibrated crop model
Yang Lu, Tendai Polite Chibarabada, Matteo G. Ziliani, et al.
Agricultural Water Management (2021) Vol. 252, pp. 106884-106884
Open Access | Times Cited: 58
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