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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 Cycles in China Using MODIS-EVI Time Series
Le Li, M. A. Friedl, Qinchuan Xin, et al.
Remote Sensing (2014) Vol. 6, Iss. 3, pp. 2473-2493
Open Access | Times Cited: 135

Showing 1-25 of 135 citing articles:

Mapping farmland abandonment and recultivation across Europe using MODIS NDVI time series
Stephan Estel, Tobias Kuemmerle, Camilo Alcántara, et al.
Remote Sensing of Environment (2015) Vol. 163, pp. 312-325
Closed Access | Times Cited: 486
Mapping cropping intensity in China using time series Landsat and Sentinel-2 images and Google Earth Engine
Luo Liu, Xiangming Xiao, Yuanwei Qin, et al.
Remote Sensing of Environment (2019) Vol. 239, pp. 111624-111624
Closed Access | Times Cited: 312
Multiple cropping systems of the world and the potential for increasing cropping intensity
Katharina Waha, Jan Philipp Dietrich, F. T. Portmann, et al.
Global Environmental Change (2020) Vol. 64, pp. 102131-102131
Open Access | Times Cited: 215
Mapping sugarcane plantation dynamics in Guangxi, China, by time series Sentinel-1, Sentinel-2 and Landsat images
Jie Wang, Xiangming Xiao, Luo Liu, et al.
Remote Sensing of Environment (2020) Vol. 247, pp. 111951-111951
Open Access | Times Cited: 170
Identifying the spatiotemporal changes of annual harvesting areas for three staple crops in China by integrating multi-data sources
Yuchuan Luo, Zhao Zhang, Ziyue Li, et al.
Environmental Research Letters (2020) Vol. 15, Iss. 7, pp. 074003-074003
Open Access | Times Cited: 148
Annual paddy rice planting area and cropping intensity datasets and their dynamics in the Asian monsoon region from 2000 to 2020
Jichong Han, Zhao Zhang, Yuchuan Luo, et al.
Agricultural Systems (2022) Vol. 200, pp. 103437-103437
Closed Access | Times Cited: 104
Mapping cropland-use intensity across Europe using MODIS NDVI time series
Stephan Estel, Tobias Kuemmerle, Christian Levers, et al.
Environmental Research Letters (2016) Vol. 11, Iss. 2, pp. 024015-024015
Open Access | Times Cited: 148
Mapping Paddy Rice in China in 2002, 2005, 2010 and 2014 with MODIS Time Series
Kersten Clauss, Huimin Yan, Claudia Kuenzer
Remote Sensing (2016) Vol. 8, Iss. 5, pp. 434-434
Open Access | Times Cited: 105
A phenology-based spectral and temporal feature selection method for crop mapping from satellite time series
Qiong Hu, Damien Sulla‐Menashe, Baodong Xu, et al.
International Journal of Applied Earth Observation and Geoinformation (2019) Vol. 80, pp. 218-229
Closed Access | Times Cited: 103
Mapping cropping intensity in Huaihe basin using phenology algorithm, all Sentinel-2 and Landsat images in Google Earth Engine
Li Pan, Haoming Xia, Jia Yang, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 102, pp. 102376-102376
Open Access | Times Cited: 96
Examining rice distribution and cropping intensity in a mixed single- and double-cropping region in South China using all available Sentinel 1/2 images
Yingli He, Jinwei Dong, Xiaoyong Liao, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 101, pp. 102351-102351
Open Access | Times Cited: 87
A new framework to map fine resolution cropping intensity across the globe: Algorithm, validation, and implication
Chong Liu, Qi Zhang, Shiqi Tao, et al.
Remote Sensing of Environment (2020) Vol. 251, pp. 112095-112095
Open Access | Times Cited: 86
GCI30: a global dataset of 30 m cropping intensity using multisource remote sensing imagery
Miao Zhang, Bingfang Wu, Hongwei Zeng, et al.
Earth system science data (2021) Vol. 13, Iss. 10, pp. 4799-4817
Open Access | Times Cited: 72
Exploring the potential of Chinese GF-6 images for crop mapping in regions with complex agricultural landscapes
Tian Xia, Zhen He, Zhiwen Cai, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 107, pp. 102702-102702
Open Access | Times Cited: 50
Genetic diversity of pepper (Capsicum spp.) germplasm resources in China reflects selection for cultivar types and spatial distribution
Xiaomin Zhang, Zhenghai Zhang, Xiaozhen Gu, et al.
Journal of Integrative Agriculture (2016) Vol. 15, Iss. 9, pp. 1991-2001
Open Access | Times Cited: 71
Comparison of country-level cropland areas between ESA-CCI land cover maps and FAOSTAT data
Xiaoxuan Liu, Le Yu, Wei Li, et al.
International Journal of Remote Sensing (2018) Vol. 39, Iss. 20, pp. 6631-6645
Closed Access | Times Cited: 69
Mapping cropping intensity trends in China during 1982–2013
Bingwen Qiu, Difei Lu, Zhenghong Tang, et al.
Applied Geography (2017) Vol. 79, pp. 212-222
Closed Access | Times Cited: 66
Phenology-based classification of crop species and rotation types using fused MODIS and Landsat data: The comparison of a random-forest-based model and a decision-rule-based model
Ruiyuan Li, Miaoqing Xu, Ziyue Chen, et al.
Soil and Tillage Research (2020) Vol. 206, pp. 104838-104838
Closed Access | Times Cited: 62
High resolution crop intensity mapping using harmonized Landsat-8 and Sentinel-2 data
Pengyu Hao, Huajun Tang, Zhongxin Chen, et al.
Journal of Integrative Agriculture (2019) Vol. 18, Iss. 12, pp. 2883-2897
Open Access | Times Cited: 58
Improved representation of agricultural land use and crop management for large-scale hydrological impact simulation in Africa using SWAT+
Albert Nkwasa, Celray James Chawanda, Jonas Jägermeyr, et al.
Hydrology and earth system sciences (2022) Vol. 26, Iss. 1, pp. 71-89
Open Access | Times Cited: 38
Mapping the Northern Limit of Double Cropping Using a Phenology-Based Algorithm and Google Earth Engine
Yan Guo, Haoming Xia, Li Pan, et al.
Remote Sensing (2022) Vol. 14, Iss. 4, pp. 1004-1004
Open Access | Times Cited: 37
Understanding the spatiotemporal patterns of seasonal, annual, and consecutive farmland abandonment in China with time‐series MODIS images during the period 2005–2019
Le Li, Yaozhong Pan, Zheng Rong-bao, et al.
Land Degradation and Development (2022) Vol. 33, Iss. 10, pp. 1608-1625
Closed Access | Times Cited: 36
Mapping Paddy Rice Distribution and Cropping Intensity in China from 2014 to 2019 with Landsat Images, Effective Flood Signals, and Google Earth Engine
Jun Wei, Yuanlai Cui, Wanqi Luo, et al.
Remote Sensing (2022) Vol. 14, Iss. 3, pp. 759-759
Open Access | Times Cited: 33
Do Arctic breeding geese track or overtake a green wave during spring migration?
Yali Si, Qinchuan Xin, Willem F. de Boer, et al.
Scientific Reports (2015) Vol. 5, Iss. 1
Open Access | Times Cited: 64
Applications of satellite ‘hyper-sensing’ in Chinese agriculture: Challenges and opportunities
Alex O. Onojeghuo, George Alan Blackburn, Jingfeng Huang, et al.
International Journal of Applied Earth Observation and Geoinformation (2017) Vol. 64, pp. 62-86
Open Access | Times Cited: 60
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