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Academic Articles & Research Papers
Showing 20 of 154 academic articles
Wei Zhang, Chao Ren, Haoming Bai, Huada Huang et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2026)
Accurate monitoring of the spatial extent of sugarcane cultivation is critical for optimizing land-use efficiency and regulating the sugar industry. However, sugarcane cultivation areas are characterized by complex topography and fragmented...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JSTARS.2026.3716367
Samane Esmaelzade Kalkhoran, Seyyed Saeed Ghannadpour • Scientific Reports
(2026)
Abstract Porphyry Cu deposits in the Urmia–Dokhtar magmatic belt constitute important exploration targets, yet the heterogeneous and multi-scale nature of geological, geochemical, and remote sensing data introduces substantial uncertainty i...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-026-61085-6
Gustau Camps‐Valls, Devis Tuia, Xiao Xiang Zhu, Markus Reichstein • Wiley eBooks
(2021)
Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only re...
OPENALEX
Open Access
DOI: https://doi.org/10.1002/9781119646181
Hao Shi, Guo Cao, Youqiang Zhang, Zixian Ge et al. • Remote Sensing
(2022)
Deep learning (DL) has recently been a core ingredient in modern computer vision tasks, triggering a wave of revolutions in various fields. The hyperspectral image (HSI) classification task is no exception. A wide range of DL-based methods ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs14174235
Chen Chen, Rufei Fu, Xiaojian Ai, Chengbin Huang et al. • Remote Sensing
(2022)
Water conservancy personnel usually need to know the water level by water gauge images in real-time and with an expected accuracy. However, accurately recognizing the water level from water gauge images is still a complex problem. This arti...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs14236023
Yofri Furqani Hakim, Fuan Tsai • Remote Sensing
(2025)
The demand for large-scale topographic maps in Indonesia has significantly increased due to the implementation of several government initiatives that necessitate the utilization of spatial data in development planning. Currently, the nation...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs17030473
Shutao Li A, Weiwei Song, Leyuan Fang, Yushi Chen et al. • IEEE Transactions on Geoscience and Remote Sensing
(2019)
Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate classification of such data challenging for traditional machine ...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tgrs.2019.2907932
Cyprien Alexandre, Rodolphe Devillers, David Mouillot, Raphael Seguin et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2024)
Detecting and tracking ships remotely is now required in a wide range of contexts, from military security to illegal immigration control, as well as the management of fisheries and marine protected areas. Among the available methods, radar ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JSTARS.2024.3437187
Yihan Chen, Xingyu Gu, Zhen Liu, Jia Liang • Remote Sensing
(2022)
Traditional automatic pavement distress detection methods using convolutional neural networks (CNNs) require a great deal of time and resources for computing and are poor in terms of interpretability. Therefore, inspired by the successful a...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs14081877
Shiyao Duan, Jiaojiao Li, Rui Song, Yunsong Li et al. • Remote Sensing
(2023)
Deep learning networks based on CNNs or transformers have made progress in spectral reconstruction (SR). However, many methods focus solely on feature extraction, overlooking the interpretability of network design. Additionally, models excl...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs15102619
José Padarian, Budiman Minasny, Alex B. McBratney • SOIL
(2020)
Abstract. The application of machine learning (ML) techniques in various fields of science has increased rapidly, especially in the last ten years. The increasing availability of soil data that can be efficiently acquired remotely and proxi...
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DOI: https://doi.org/10.5194/soil-6-35-2020
Masoud Mahdianpari, Bahram Salehi, Mohammad Rezaee, Fariba Mohammadimanesh et al. • Remote Sensing
(2018)
Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs10071119
Zhiqiang Gong, Ping Zhong, Weidong Hu • IEEE Access
(2019)
Machine learning methods have achieved good performance and been widely applied in various real-world applications. They can learn the model adaptively and be better fit for special requirements of different tasks. Generally, a good machine...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/access.2019.2917620
J. W. Njoroge, M. Koeva, M. Farnaghi, D. Petrova-Antonova et al. • ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
(2026)
Digital twins are increasingly used in smart buildings to monitor energy use. This requires reliable sensor data, geospatial information, and semantically rich 3D building geometry. However, building sensor data often has inconsistent sampl...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/isprs-annals-XII-4-W1-2026-251-2026
Zigeng Song, Yan Bai, Difeng Wang, Teng Li et al. • Remote Sensing
(2021)
With the implementation of the 2018–2020 Clean Air Action Plan (CAAP) the and impact from COVID-19 lockdowns in 2020, air pollution emissions in central and eastern China have decreased markedly. Here, by combining satellite remote sensing,...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs13132525
Charles Nickmilder, Anthony Tedde, Isabelle Dufrasne, Françoise Lessire et al. • Remote Sensing
(2021)
Accurate information about the available standing biomass on pastures is critical for the adequate management of grazing and its promotion to farmers. In this paper, machine learning models are developed to predict available biomass express...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs13030408
Mohamad Kazemi, Atefeh Jafarpoor, Youssef Ahmadi, Raoof Mostafazadeh • Scientific Reports
(2026)
Abstract The expansion of human activities and environmental changes in coastal desert and semi-desert ecosystems significantly impact habitat quality. This study used remote sensing data on the Google Earth Engine (GEE) platform to generat...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-026-47305-z
Juliana Aparecida Anochi, Vinícius Albuquerque de Almeida, Haroldo Fraga de Campos Velho • Remote Sensing
(2021)
Many natural disasters in South America are linked to meteorological phenomena. Therefore, forecasting and monitoring climatic events are fundamental issues for society and various sectors of the economy. In the last decades, machine learni...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs13132468
David John Lary, Amir H. Alavi, Amir H. Gandomi, Annette L. Walker • Geoscience Frontiers
(2015)
Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.gsf.2015.07.003
Tianchen Liang, Linqing Zou, Qiaoning He, Lin Sun • Remote Sensing
(2026)
Retrieving aerosol optical depth (AOD) over land remains challenging because the relatively weak aerosol signal in top-of-atmosphere (TOA) observations must be separated from strong and spatially heterogeneous surface reflectance. Here, we ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs18172862