Relevant bibliographies by topics / UAV multispectral images

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'UAV multispectral images'

Author: Grafiati
Published: 5 June 2025
Last updated: 1 August 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'UAV multispectral images.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "UAV multispectral images"

1

Rossi, Lorenzo, Irene Mammi, and Filippo Pelliccia. "UAV-Derived Multispectral Bathymetry." Remote Sensing 12, no. 23 (2020): 3897. http://dx.doi.org/10.3390/rs12233897.

Full text
Abstract:
Bathymetry is considered an important component in marine applications as several coastal erosion monitoring and engineering projects are carried out in this field. It is traditionally acquired via shipboard echo sounding, but nowadays, multispectral satellite imagery is also commonly applied using different remote sensing-based algorithms. Satellite-Derived Bathymetry (SDB) relates the surface reflectance of shallow coastal waters to the depth of the water column. The present study shows the results of the application of Stumpf and Lyzenga algorithms to derive the bathymetry for a small area
APA, Harvard, Vancouver, ISO, and other styles
2

Xing, Jian, Chaoyong Wang, Ying Liu, et al. "UAV Multispectral Imagery Predicts Dead Fuel Moisture Content." Forests 14, no. 9 (2023): 1724. http://dx.doi.org/10.3390/f14091724.

Full text
Abstract:
Forest floor dead fuel moisture content (DFMC) is an important factor in the occurrence of forest fires, and predicting DFMC is important for accurate fire risk forecasting. Large areas of forest surface DFMC are difficult to predict via manual methods. In this paper, we propose an unmanned aerial vehicle (UAV)-based forest surface DFMC prediction method, in which a UAV is equipped with a multispectral camera to collect multispectral images of dead combustible material on the forest surface over a large area, combined with a deep-learning algorithm to achieve the large-scale prediction of DFMC
APA, Harvard, Vancouver, ISO, and other styles
3

Oliveira, Romário Porto de, Marcelo Rodrigues Barbosa Júnior, Antônio Alves Pinto, Jean Lucas Pereira Oliveira, Cristiano Zerbato, and Carlos Eduardo Angeli Furlani. "Predicting Sugarcane Biometric Parameters by UAV Multispectral Images and Machine Learning." Agronomy 12, no. 9 (2022): 1992. http://dx.doi.org/10.3390/agronomy12091992.

Full text
Abstract:
Multispectral sensors onboard unmanned aerial vehicles (UAV) have proven accurate and fast to predict sugarcane yield. However, challenges to a reliable approach still exist. In this study, we propose to predict sugarcane biometric parameters by using machine learning (ML) algorithms and multitemporal data through the analysis of multispectral images from UAV onboard sensors. The research was conducted on five varieties of sugarcane, as a way to make a robust approach. Multispectral images were collected every 40 days and the evaluated biometric parameters were: number of tillers (NT), plant h
APA, Harvard, Vancouver, ISO, and other styles
4

Mateen, Ahmed. "LEGION BASED WEED EXTRACTION FROM UAV IMAGERY." Pakistan Journal of Agricultural Sciences 56, no. 04 (2019): 1045–52. http://dx.doi.org/10.21162/pakjas/19.8053.

Full text
Abstract:
Multispectral images are the types of images which consist of many different bands of data for further processing. Vegetation Indexing has Different bands which are combined in the multispectral images and are used to accentuate the vegetated areas. In this one combination is most commonly used LIKE Ratio Vegetation Indexing (RVI). But using UAV imagery this problem has been solved because in UAV the area covered or captured by the cameras would be very wide so that the whole plot or crop can be viewed or captured from the UAV imagery. Legion is a Model used to do Scene Analysis Task, Image Se
APA, Harvard, Vancouver, ISO, and other styles
5

Sun, Mingyue, Qian Li, Xuzi Jiang, Tiantian Ye, Xinju Li, and Beibei Niu. "Estimation of Soil Salt Content and Organic Matter on Arable Land in the Yellow River Delta by Combining UAV Hyperspectral and Landsat-8 Multispectral Imagery." Sensors 22, no. 11 (2022): 3990. http://dx.doi.org/10.3390/s22113990.

Full text
Abstract:
Rapid and large-scale estimation of soil salt content (SSC) and organic matter (SOM) using multi-source remote sensing is of great significance for the real-time monitoring of arable land quality. In this study, we simultaneously predicted SSC and SOM on arable land in the Yellow River Delta (YRD), based on ground measurement data, unmanned aerial vehicle (UAV) hyperspectral imagery, and Landsat-8 multispectral imagery. The reflectance averaging method was used to resample UAV hyperspectra to simulate the Landsat-8 OLI data (referred to as fitted multispectra). Correlation analyses and the mul
APA, Harvard, Vancouver, ISO, and other styles
6

Kazemi, F., and E. Ghanbari Parmehr. "EVALUATION OF RGB VEGETATION INDICES DERIVED FROM UAV IMAGES FOR RICE CROP GROWTH MONITORING." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-4/W1-2022 (January 13, 2023): 385–90. http://dx.doi.org/10.5194/isprs-annals-x-4-w1-2022-385-2023.

Full text
Abstract:
Abstract. The unmanned aerial vehicles (UAVs) are widely used for agricultural monitoring due to reduce the cost and time of crop monitoring via the acquisition of images with high spatial-temporal resolution. The normalized difference vegetation index (NDVI) is the most widely studied and used for mapping crop growth. A relatively expensive multispectral sensor is required to produce an NDVI map. The visible vegetation indices (VIs) derived from UAV images showed potential capabilities for predicting crop growth. The purpose of this paper is to evaluate the RGB indices to monitor the growth o
APA, Harvard, Vancouver, ISO, and other styles
7

Yang, Bo, Timothy L. Hawthorne, Hannah Torres, and Michael Feinman. "Using Object-Oriented Classification for Coastal Management in the East Central Coast of Florida: A Quantitative Comparison between UAV, Satellite, and Aerial Data." Drones 3, no. 3 (2019): 60. http://dx.doi.org/10.3390/drones3030060.

Full text
Abstract:
High resolution mapping of coastal habitats is invaluable for resource inventory, change detection, and inventory of aquaculture applications. However, coastal areas, especially the interior of mangroves, are often difficult to access. An Unmanned Aerial Vehicle (UAV), equipped with a multispectral sensor, affords an opportunity to improve upon satellite imagery for coastal management because of the very high spatial resolution, multispectral capability, and opportunity to collect real-time observations. Despite the recent and rapid development of UAV mapping applications, few articles have qu
APA, Harvard, Vancouver, ISO, and other styles
8

Xu, Sizhe, Xingang Xu, Clive Blacker, et al. "Estimation of Leaf Nitrogen Content in Rice Using Vegetation Indices and Feature Variable Optimization with Information Fusion of Multiple-Sensor Images from UAV." Remote Sensing 15, no. 3 (2023): 854. http://dx.doi.org/10.3390/rs15030854.

Full text
Abstract:
LNC (leaf nitrogen content) in crops is significant for diagnosing the crop growth status and guiding fertilization decisions. Currently, UAV (unmanned aerial vehicles) remote sensing has played an important role in estimating the nitrogen nutrition of crops at the field scale. However, many existing methods of evaluating crop nitrogen based on UAV imaging techniques usually have used a single type of imagery such as RGB or multispectral images, seldom considering the usage of information fusion from different types of UAV imagery for assessing the crop nitrogen status. In this study, GS (Gram
APA, Harvard, Vancouver, ISO, and other styles
9

Huo, Langning, Iryna Matsiakh, Jonas Bohlin, and Michelle Cleary. "Estimation of Tree Vitality Reduced by Pine Needle Disease Using Multispectral Drone Images." Remote Sensing 17, no. 2 (2025): 271. https://doi.org/10.3390/rs17020271.

Full text
Abstract:
Multispectral imagery from unmanned aerial vehicles (UAVs) can provide high-resolution data to map tree mortality caused by pests or diseases. Although many studies have investigated UAV-imagery-based methods to detect trees under acute stress followed by tree mortality, few have tested the feasibility and accuracy of detecting trees under chronic stress. This study aims to develop methods and test how well UAV-based multispectral imagery can detect pine needle disease long before tree mortality. Multispectral images were acquired four times through the growing season in an area with pine tree
APA, Harvard, Vancouver, ISO, and other styles
10

Shin, Jung-il, Won-woo Seo, Taejung Kim, Joowon Park, and Choong-shik Woo. "Using UAV Multispectral Images for Classification of Forest Burn Severity—A Case Study of the 2019 Gangneung Forest Fire." Forests 10, no. 11 (2019): 1025. http://dx.doi.org/10.3390/f10111025.

Full text
Abstract:
Unmanned aerial vehicle (UAV)-based remote sensing has limitations in acquiring images before a forest fire, although burn severity can be analyzed by comparing images before and after a fire. Determining the burned surface area is a challenging class in the analysis of burn area severity because it looks unburned in images from aircraft or satellites. This study analyzes the availability of multispectral UAV images that can be used to classify burn severity, including the burned surface class. RedEdge multispectral UAV image was acquired after a forest fire, which was then processed into a mo
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "UAV multispectral images"

1

Maier, Kathrin. "Direct multispectral photogrammetry for UAV-based snow depth measurements." Thesis, KTH, Geoinformatik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254566.

Full text
Abstract:
Due to the changing climate and inherent atypically occurring meteorological events in the Arctic regions, more accurate snow quality predictions are needed in order to support the Sámi reindeer herding communities in northern Sweden that struggle to adapt to the rapidly changing Arctic climate. Spatial snow depth distribution is a crucial parameter not only to assess snow quality but also for multiple environmental research and social land use purposes. This contrasts with the current availability of affordable and efficient snow monitoring methods to estimate such an extremely variable para
APA, Harvard, Vancouver, ISO, and other styles
2

Larson, Matthew David. "Monitoring Multi-Depth Suspended Sediment Loads in Lake Erie's Maumee River using Landsat 8 and Unmanned Aerial Vehicle (UAV) Imagery." Bowling Green State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1496484122311721.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

MUSCI, MARIA ANGELA. "Service robotics and machine learning for close-range remote sensing." Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2903488.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Silva, Joelen Cruz da. "Use of multispectral UAV images for classification and biomass assessment of seaweed in intertidal rocky shores." Master's thesis, 2021. https://hdl.handle.net/10216/139405.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

(9833933), Tej Shahi. "Utilising Drone Imagery to Assess the Peanut Quantity and Quality with Machine Learning Approaches." Thesis, 2023. https://figshare.com/articles/thesis/Utilising_Drone_Imagery_to_Assess_the_Peanut_Quantity_and_Quality_with_Machine_Learning_Approaches/28976015.

Full text
Abstract:
Precision agriculture relies on the efficient measurement of temporal and spatial variability in crop information for a smarter farming management strategy. Variability in crops in terms of their growth rates, size, and yield potentials can exist even within a single field, whereas traditional in-field sampling techniques are unable to represent such crop variability, thereby making precise decisions on crop management more challenging. Hence, alternative non-destructive ways of gathering crop information have been explored, including field-based sensors, satellite imagery and unmanned aerial
APA, Harvard, Vancouver, ISO, and other styles
6

Vong, André Agostinho Cheang do Rosário. "Digital Multispectral Map Reconstruction Using Aerial Imagery." Master's thesis, 2021. http://hdl.handle.net/10362/133295.

Full text
Abstract:
Advances made in the computer vision field allowed for the establishment of faster and more accurate photogrammetry techniques. Structure from Motion(SfM) is a photogrammetric technique focused on the digital spatial reconstruction of objects based on a sequence of images. The benefit of Unmanned Aerial Vehicle (UAV) platforms allowed the ability to acquire high fidelity imagery intended for environmental mapping. This way, UAV platforms became a heavily adopted method of survey. The combination of SfM and the recent improvements of Unmanned Aerial Vehicle (UAV) platforms granted greater fl
APA, Harvard, Vancouver, ISO, and other styles
7

Salvado, Ana Beatriz de Tróia. "Aerial Semantic Mapping for Precision Agriculture using Multispectral Imagery." Master's thesis, 2018. http://hdl.handle.net/10362/59924.

Full text
Abstract:
Nowadays constant technological evolution cover several necessities and daily tasks in our society. In particular, drones usage, given its wide vision to capture the terrain surface images, allows to collect large amounts of information with high efficiency, performance and accuracy. This master dissertation’s main purpose is the analysis, classification and respective mapping of different terrain types and characteristics, using multispectral imagery. Solar radiation flow reflected on the surface is captured by the used multispectral camera’s different lenses (RedEdge-M, created by Mic
APA, Harvard, Vancouver, ISO, and other styles
8

Adama, Traore, and 茶奥. "Estimation of chlorophyll content with multispectral high-resolution imagery from an unmanned aerial vehicle (UAV) for paddy rice fields under alternate wetting and drying irrigation and system of rice intensification." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/bv24tz.

Full text
Abstract:
碩士<br>國立屏東科技大學<br>土壤與水工程國際碩士學位學程<br>105<br>Chlorophyll content, a good indicator for plant healthy state and important biophysical parameters, is important significance for precision agriculture. To estimate the spatial variability of chlorophyll content over fields, traditional method using chlorophyll meter requires many point samples. Because of relationship between chlorophyll content and spectral reflectance of certain bands, remote sensing techniques have the potential to predict the chlorophyll content over large fields. In this study, the use of multispectral resolution imagery using u
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "UAV multispectral images"

1

Catania, Pietro, Massimo Vincenzo Ferro, Eliseo Roma, Santo Orlando, and Mariangela Vallone. "Olive Tree Canopy Assessment Based on UAV Multispectral Images." In AIIA 2022: Biosystems Engineering Towards the Green Deal. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-30329-6_48.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Lu, Bing, and Yuhong He. "UAV-Based Multispectral Images for Investigating Grassland Biophysical and Biochemical Properties." In High Spatial Resolution Remote Sensing. CRC Press, 2018. http://dx.doi.org/10.1201/9780429470196-12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Roma, Eliseo, Pietro Catania, Marco Canicattì, Massimo Vincenzo Ferro, Santo Orlando, and Mariangela Vallone. "Olive Tree Canopy Assessment by UAV Multispectral Images Before and After Pruning." In Lecture Notes in Civil Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63504-5_35.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Cini, Elena, Flavio Marzialetti, Marco Paterni, Andrea Berton, Alicia Teresa Rosario Acosta, and Daniela Ciccarelli. "Mapping Yucca gloriosa in coastal dunes: evaluating the cost and time efficiency of photointerpretation, machine learning and field detection approaches." In Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques. Firenze University Press, 2024. https://doi.org/10.36253/979-12-215-0556-6.14.

Full text
Abstract:
Biological invasions threaten biodiversity and cause significant economic and ecological costs. Effective management of invasive species is crucial, as highlighted by the European Community's Regulation 1143/2014 on Invasive Alien Species (IAS). This study focuses on coastal dune ecosystems, particularly assessing the time and cost-effectiveness of three monitoring methods for detecting and mapping alien plants: photointerpretation, machine learning classification, and field monitoring. Yucca gloriosa L., an invasive species in Regional Park of Migliarino-San Rossore-Massaciuccoli (Tuscany, It
APA, Harvard, Vancouver, ISO, and other styles
5

Manzano, Julio Mejía, Jhon Guerrero Narvaez, José Guañarita Castillo, Diego Rivera Vásquez, and Luis Gutiérrez Villada. "Analysis of Normalized Vegetation Index in Castile Coffee Crops, Using Mosaics of Multispectral Images Acquired by Unmanned Aerial Vehicle (UAV)." In Communications in Computer and Information Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42520-3_43.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Camilleri, Leanne, and Sandro Lanfranco. "Using multispectral UAV imagery and ground truthing to assess the success of vegetation reinforcement in a coastal area – the case of Inwadar National Park, Malta." In Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques. Firenze University Press, 2024. https://doi.org/10.36253/979-12-215-0556-6.09.

Full text
Abstract:
Ground-based methods of vegetation survey are slow and expensive, but recent technological developments have made UAVs (Unoccupied Aerial Vehicles or drones) accessible to consumer budgets, facilitating their use in vegetation monitoring. We propose a method for using UAVs to evaluate a vegetation reinforcement programme in a coastal area in Malta and compare its accuracy and cost-effectiveness with that of ground-based methods (including walkthrough-surveys and measurements of chlorophyll-a content). Multi-seasonal imaging of the site was captured using a DJI Phantom 4 drone equipped with sen
APA, Harvard, Vancouver, ISO, and other styles
7

Bereska, Damian, Krzysztof Daniec, Karol Jędrasiak, and Aleksander Nawrat. "Gyro-Stabilized Platform for Multispectral Image Acquisition." In Vision Based Systemsfor UAV Applications. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00369-6_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Messina, Gaetano, Vincenzo Fiozzo, Salvatore Praticò, et al. "Monitoring Onion Crops Using Multispectral Imagery from Unmanned Aerial Vehicle (UAV)." In New Metropolitan Perspectives. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48279-4_154.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Messina, Gaetano, Salvatore Praticò, Biagio Siciliani, Antonio Curcio, Salvatore Di Fazio, and Giuseppe Modica. "Monitoring Onion Crops Using UAV Multispectral and Thermal Imagery: Preliminary Results." In Lecture Notes in Civil Engineering. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39299-4_94.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Niu, Haoyu, and YangQuan Chen. "Reliable Tree-Level ET Estimation Using Lysimeter and UAV Multispectral Imagery." In Towards Tree-level Evapotranspiration Estimation with Small UAVs in Precision Agriculture. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-14937-5_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "UAV multispectral images"

1

He, Jia, Hongli Zhang, Yan Zhang, et al. "Wheat yellow rust remote monitoring based on UAV multispectral images." In Sixth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2024), edited by Zhiliang Qin, Jun Chen, and Huaichun Wu. SPIE, 2025. https://doi.org/10.1117/12.3057499.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Nuradili, Pakezhamu, Ji Zhou, and Farid Melgani. "Wetland Segmentation Method for UAV Multispectral Remote Sensing Images Based on SegFormer." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642790.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Chang, Haoyu, Yulong Liu, Hui Zhang, and Shizhuang Weng. "Detection of Rice Leaf Area Index Based on Multispectral Images of UAV." In 2025 5th International Conference on Neural Networks, Information and Communication Engineering (NNICE). IEEE, 2025. https://doi.org/10.1109/nnice64954.2025.11064324.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Qin, Zhenqiang, Xian Li, Yanfeng Gu, and Xiangrong Zhang. "An Automated Workflow for Pixel-Level BRDF Extraction Using UAV-Based Multispectral Images." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10641809.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Pe, Steven, Jazzie Jao, Jumar Cadondon, et al. "The characterization of multispectral images of the Batangas coastline using machine learning and UAV imaging." In Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VIII, edited by Ryoichi Imasu, Li-Hsueh Chang, and Fuan Tsai. SPIE, 2024. https://doi.org/10.1117/12.3042579.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Pe, Steven, Jazzie Jao, Jumar Cadondon, et al. "The characterization of multispectral images of the Batangas coastline using machine learning and UAV imaging (Erratum)." In Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VIII, edited by Ryoichi Imasu, Li-Hsueh Chang, and Fuan Tsai. SPIE, 2025. https://doi.org/10.1117/12.3065990.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Llenque, Jose C. Eche, Marco Miranda Valiente, Jose Carlos Coello Fababa, et al. "Identification of the Marine Coast Area Affected by Oil Spill Using Multispectral Satellite and UAV Images in Ventanilla - Callao, Perú." In 2024 IEEE Biennial Congress of Argentina (ARGENCON). IEEE, 2024. http://dx.doi.org/10.1109/argencon62399.2024.10735911.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Zhao, Dan, Hao Yang, Guijun Yang, Xingang Xu, and Bo Xu. "Maize Leaf Biomass Retrieval at Multi-growing Stage Using UAV Multispectral Images Based on 3D Radiative Transfer Process-guided Machine Learning." In 2024 12th International Conference on Agro-Geoinformatics (Agro-Geoinformatics). IEEE, 2024. http://dx.doi.org/10.1109/agro-geoinformatics262780.2024.10660808.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Tejasri, N., S. Praneela, P. Rajalakshmi, M. Balram, and Uday B. Desai. "Panicle Segmentation on UAV Captured Multispectral Paddy Crop Imagery." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10641770.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Athar, Usama, Muhammad Ali, Zuhair Zafar, Karsten Berns, and Muhammad Moazam Fraz. "Analyzing Phenological Progression in Wheat Genotypes Through UAV Multispectral Imagery." In 2024 19th International Conference on Emerging Technologies (ICET). IEEE, 2024. https://doi.org/10.1109/icet63392.2024.10935250.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'UAV multispectral images' for particular source types:
Journal articles
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography