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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:

Object-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment
Eduarda Martiniano de Oliveira Silveira, Sérgio Henrique Godinho Silva, Fausto Weimar Acérbi Júnior, et al.
International Journal of Applied Earth Observation and Geoinformation (2019) Vol. 78, pp. 175-188
Closed Access | Times Cited: 97

Showing 1-25 of 97 citing articles:

Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping
Carlos Alberto Silva, Laura Duncanson, Steven Hancock, et al.
Remote Sensing of Environment (2020) Vol. 253, pp. 112234-112234
Open Access | Times Cited: 165
Mapping high-resolution forest aboveground biomass of China using multisource remote sensing data
Qiuli Yang, Chunyue Niu, Xiaoqiang Liu, et al.
GIScience & Remote Sensing (2023) Vol. 60, Iss. 1
Open Access | Times Cited: 44
Mapping paddy rice by the object-based random forest method using time series Sentinel-1/Sentinel-2 data
Yaotong Cai, Hui Lin, Meng Zhang
Advances in Space Research (2019) Vol. 64, Iss. 11, pp. 2233-2244
Closed Access | Times Cited: 131
Comparison of Machine Learning Methods for Estimating Mangrove Above-Ground Biomass Using Multiple Source Remote Sensing Data in the Red River Delta Biosphere Reserve, Vietnam
Tien Dat Pham, Naoto Yokoya, Junshi Xia, et al.
Remote Sensing (2020) Vol. 12, Iss. 8, pp. 1334-1334
Open Access | Times Cited: 109
Accuracy Improvements to Pixel-Based and Object-Based LULC Classification with Auxiliary Datasets from Google Earth Engine
Le’an Qu, Zhenjie Chen, Manchun Li, et al.
Remote Sensing (2021) Vol. 13, Iss. 3, pp. 453-453
Open Access | Times Cited: 98
Machine learning and geostatistical approaches for estimating aboveground biomass in Chinese subtropical forests
Huiyi Su, Wenjuan Shen, Jingrui Wang, et al.
Forest Ecosystems (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 82
Improvement of Mangrove Soil Carbon Stocks Estimation in North Vietnam Using Sentinel-2 Data and Machine Learning Approach
Tien Dat Pham, Naoto Yokoya, Thi Thu Trang Nguyen, et al.
GIScience & Remote Sensing (2020) Vol. 58, Iss. 1, pp. 68-87
Open Access | Times Cited: 76
Estimating the aboveground biomass of coniferous forest in Northeast China using spectral variables, land surface temperature and soil moisture
Fugen Jiang, Mykola Kutia, Kaisen Ma, et al.
The Science of The Total Environment (2021) Vol. 785, pp. 147335-147335
Closed Access | Times Cited: 67
Hybrid model for estimating forest canopy heights using fused multimodal spaceborne LiDAR data and optical imagery
Shufan Wang, Chun Liu, Weiyue Li, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 122, pp. 103431-103431
Open Access | Times Cited: 25
Spatiotemporal dynamics of carbon sinks in China's terrestrial ecosystems from 2010 to 2060
Li Xu, Nianpeng He, Mingxu Li, et al.
Resources Conservation and Recycling (2024) Vol. 203, pp. 107457-107457
Closed Access | Times Cited: 13
A brief overview and perspective of using airborne Lidar data for forest biomass estimation
Dengsheng Lu, Xiandie Jiang
International Journal of Image and Data Fusion (2024) Vol. 15, Iss. 1, pp. 1-24
Closed Access | Times Cited: 12
Forest aboveground biomass estimation by GEDI and multi-source EO data fusion over Indian forest
Jayantrao Mohite, Suryakant Sawant, Ankur Pandit, et al.
International Journal of Remote Sensing (2024) Vol. 45, Iss. 4, pp. 1304-1338
Closed Access | Times Cited: 10
Forest Aboveground Biomass Estimation and Inventory: Evaluating Remote Sensing-Based Approaches
Muhammad Nouman Khan, Yumin Tan, Ahmad Ali Gul, et al.
Forests (2024) Vol. 15, Iss. 6, pp. 1055-1055
Open Access | Times Cited: 9
Mapping Vegetation Changes in Mongolian Grasslands (1990–2024) Using Landsat Data and Advanced Machine Learning Algorithm
Mandakh Nyamtseren, Tien Dat Pham, Thuy Thi Phuong Vu, et al.
Remote Sensing (2025) Vol. 17, Iss. 3, pp. 400-400
Open Access | Times Cited: 1
Evaluation of Fire Severity Indices Based on Pre- and Post-Fire Multispectral Imagery Sensed from UAV
Fernando Carvajal-Ramírez, José Marques da Silva, Francisco Agüera-Vega, et al.
Remote Sensing (2019) Vol. 11, Iss. 9, pp. 993-993
Open Access | Times Cited: 71
Improved Object-Based Estimation of Forest Aboveground Biomass by Integrating LiDAR Data from GEDI and ICESat-2 with Multi-Sensor Images in a Heterogeneous Mountainous Region
Lin Chen, Chunying Ren, Guangdao Bao, et al.
Remote Sensing (2022) Vol. 14, Iss. 12, pp. 2743-2743
Open Access | Times Cited: 30
Spatially continuous estimation of urban forest aboveground biomass with UAV-LiDAR and multispectral scanning: An allometric model of forest structural diversity
Yalin Zhai, Lei Wang, Yunlong Yao, et al.
Agricultural and Forest Meteorology (2024) Vol. 360, pp. 110301-110301
Closed Access | Times Cited: 6
Assessment of land degradation using machine‐learning techniques: A case of declining rangelands
Saleh Yousefi, Hamid Reza Pourghasemi, Mohammadtaghi Avand, et al.
Land Degradation and Development (2020) Vol. 32, Iss. 3, pp. 1452-1466
Closed Access | Times Cited: 44
Mapping the stock and spatial distribution of aboveground woody biomass in the native vegetation of the Brazilian Cerrado biome
Bárbara Zimbres, Pedro Rodríguez‐Veiga, Julia Z. Shimbo, et al.
Forest Ecology and Management (2021) Vol. 499, pp. 119615-119615
Open Access | Times Cited: 36
Heterogeneous effects of climate change and human activities on annual landscape change in coastal cities of mainland China
Ying Li, Yanwei Sun, Jialin Li
Ecological Indicators (2021) Vol. 125, pp. 107561-107561
Open Access | Times Cited: 35
Modeling the topographic influence on aboveground biomass using a coupled model of hillslope hydrology and ecosystem dynamics
Yilin Fang, L. Ruby Leung, Charles D. Koven, et al.
Geoscientific model development (2022) Vol. 15, Iss. 20, pp. 7879-7901
Open Access | Times Cited: 22
An Optimized Object-Based Random Forest Algorithm for Marsh Vegetation Mapping Using High-Spatial-Resolution GF-1 and ZY-3 Data
Peiqing Lou, Bolin Fu, Hongchang He, et al.
Remote Sensing (2020) Vol. 12, Iss. 8, pp. 1270-1270
Open Access | Times Cited: 34
FastForest: Increasing random forest processing speed while maintaining accuracy
Darren Yates, Md Zahidul Islam
Information Sciences (2020) Vol. 557, pp. 130-152
Open Access | Times Cited: 33
Spatiotemporal variation and driving factors of vegetation net primary productivity in a typical karst area in China from 2000 to 2010
Liyi Song, Mingyang Li, Xu Hai, et al.
Ecological Indicators (2021) Vol. 132, pp. 108280-108280
Open Access | Times Cited: 28
A comparative analysis of grid-based and object-based modeling approaches for poplar forest growing stock volume estimation in plain regions using airborne LIDAR data
Ruoqi Wang, Guiying Li, Yagang Lu, et al.
Geo-spatial Information Science (2023) Vol. 27, Iss. 5, pp. 1441-1459
Open Access | Times Cited: 12
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