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:

Towards improved land use mapping of irrigated croplands: performance assessment of different image classification algorithms and approaches
Amit Kumar Basukala, Carsten Oldenburg, J. Schellberg, et al.
European Journal of Remote Sensing (2017) Vol. 50, Iss. 1, pp. 187-201
Open Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

Application of the Random Forest Classifier to Map Irrigated Areas Using Google Earth Engine
James Magidi, Luxon Nhamo, Sylvester Mpandeli, et al.
Remote Sensing (2021) Vol. 13, Iss. 5, pp. 876-876
Open Access | Times Cited: 120

Identifying the land use land cover (LULC) changes using remote sensing and GIS approach: A case study at Bhaluka in Mymensingh, Bangladesh
Md Mahadi Hasan Seyam, Md. Rashedul Haque, Md. Mostafizur Rahman
Case Studies in Chemical and Environmental Engineering (2023) Vol. 7, pp. 100293-100293
Open Access | Times Cited: 94

Flood susceptibility assessment using extreme gradient boosting (EGB), Iran
Sajjad Mirzaei, Mehdi Vafakhah, Biswajeet Pradhan, et al.
Earth Science Informatics (2020) Vol. 14, Iss. 1, pp. 51-67
Closed Access | Times Cited: 82

Crop mapping using supervised machine learning and deep learning: a systematic literature review
Mouad Alami Machichi, Loubna El Mansouri, Yasmina Imani, et al.
International Journal of Remote Sensing (2023) Vol. 44, Iss. 8, pp. 2717-2753
Open Access | Times Cited: 23

Crop type mapping from pansharpened Landsat 8 NDVI data: A case of a highly fragmented and intensive agricultural system
Jamal-Eddine Ouzemou, Abderrazak El Harti, Rachid Lhissou, et al.
Remote Sensing Applications Society and Environment (2018) Vol. 11, pp. 94-103
Open Access | Times Cited: 61

Scalable pixel-based crop classification combining Sentinel-2 and Landsat-8 data time series: Case study of the Duero river basin
Laura Piedelobo, David Hernández‐López, Rocío Ballesteros, et al.
Agricultural Systems (2019) Vol. 171, pp. 36-50
Closed Access | Times Cited: 60

Towards precision irrigation management: A review of GIS, remote sensing and emerging technologies
Erion Bwambale, Zita Naangmenyele, Parfait Iradukunda, et al.
Cogent Engineering (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 31

A systematic review on the application of UAV-based thermal remote sensing for assessing and monitoring crop water status in crop farming systems
Helen S. Ndlovu, John Odindi, Mbulisi Sibanda, et al.
International Journal of Remote Sensing (2024) Vol. 45, Iss. 15, pp. 4923-4960
Closed Access | Times Cited: 7

Mapping Maize Area in Heterogeneous Agricultural Landscape with Multi-Temporal Sentinel-1 and Sentinel-2 Images Based on Random Forest
Yansi Chen, Jinliang Hou, Chunlin Huang, et al.
Remote Sensing (2021) Vol. 13, Iss. 15, pp. 2988-2988
Open Access | Times Cited: 33

Assessing the effectiveness of potential best management practices for science-informed decision support at the watershed scale: The case of the Mar Menor coastal lagoon, Spain
Adrián López-Ballesteros, Dennis Trolle, Raghavan Srinivasan, et al.
The Science of The Total Environment (2022) Vol. 859, pp. 160144-160144
Open Access | Times Cited: 25

Regional-scale monitoring of cropland intensity and productivity with multi-source satellite image time series
Fabian Löw, Çhandrashekhar Biradar, Olena Dubovyk, et al.
GIScience & Remote Sensing (2017) Vol. 55, Iss. 4, pp. 539-567
Closed Access | Times Cited: 47

Deep learning U-Net classification of Sentinel-1 and 2 fusions effectively demarcates tropical montane forest's deforestation
Richard Dein D. Altarez, Armando Apan, Tek Maraseni
Remote Sensing Applications Society and Environment (2022) Vol. 29, pp. 100887-100887
Closed Access | Times Cited: 18

GIS-based flood susceptibility mapping of the lower Bagmati basin in Bihar, using Shannon’s entropy model
Sohidul Islam, Mary Tahir, Shahnaz Parveen
Modeling Earth Systems and Environment (2021) Vol. 8, Iss. 3, pp. 3005-3019
Closed Access | Times Cited: 22

Irrigated Crop Types Mapping in Tashkent Province of Uzbekistan with Remote Sensing-Based Classification Methods
Elbek Erdanaev, Martin Kappas, Daniel Wyss
Sensors (2022) Vol. 22, Iss. 15, pp. 5683-5683
Open Access | Times Cited: 14

Using Multi-Temporal Landsat Images and Support Vector Machine to Assess the Changes in Agricultural Irrigated Areas in the Mogtedo Region, Burkina Faso
Farid Traoré, Joachim Bonkoungou, Jérôme Compaore, et al.
Remote Sensing (2019) Vol. 11, Iss. 12, pp. 1442-1442
Open Access | Times Cited: 25

Remote Sensing for Agricultural Water Management in Jordan
Jawad Al‐Bakri, Guido D’Urso, Alfonso Calera, et al.
Remote Sensing (2022) Vol. 15, Iss. 1, pp. 235-235
Open Access | Times Cited: 12

Bi-temporal characterization of terrestrial temperature in relation to urban land use land cover dynamics and policies in Kozhikode Urban Area, India
Ashique Vadakkuveettil, Aakriti Grover
Land Use Policy (2023) Vol. 132, pp. 106782-106782
Closed Access | Times Cited: 6

Informing Equitable Water and Food Policies through Accurate Spatial Information on Irrigated Areas in Smallholder Farming Systems
James Magidi, Barbara van Koppen, Luxon Nhamo, et al.
Water (2021) Vol. 13, Iss. 24, pp. 3627-3627
Open Access | Times Cited: 15

Remote Sensing-Based Agricultural Water Accounting for the North Jordan Valley
Jawad Al‐Bakri, Guido D’Urso, Charles Batchelor, et al.
Water (2022) Vol. 14, Iss. 8, pp. 1198-1198
Open Access | Times Cited: 10

Spatio-Temporal Heterogeneity of Ecological Quality in Hangzhou Greater Bay Area (HGBA) of China and Response to Land Use and Cover Change
Zhenjie Yang, Chao Sun, Junwei Ye, et al.
Remote Sensing (2022) Vol. 14, Iss. 21, pp. 5613-5613
Open Access | Times Cited: 10

Investigating the Ability to Identify New Constructions in Urban Areas Using Images from Unmanned Aerial Vehicles, Google Earth, and Sentinel-2
Fahime Arabi Aliabad, Hamid Reza Ghafarian Malamiri, Saeed Shojaei, et al.
Remote Sensing (2022) Vol. 14, Iss. 13, pp. 3227-3227
Open Access | Times Cited: 8

Comparison of Google Earth Engine Machine Learning Algorithms for Mapping Smallholder Irrigated Areas in a Mountainous Watershed, Upper Blue Nile Basin, Ethiopia
Yilkal Gebeyehu Mekonnen, Tena Alamirew, Abebe Demissie Chukalla, et al.
Journal of the Indian Society of Remote Sensing (2024) Vol. 52, Iss. 3, pp. 569-582
Closed Access | Times Cited: 1

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