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Hui Deng, Wenjiang Zhang, Xiaoqian Zheng and Houxi Zhang
The accurate and timely identification of crops holds paramount significance for effective crop management and yield estimation. Unmanned aerial vehicle (UAV), with their superior spatial and temporal resolution compared to satellite-based remote sensing...
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Dthenifer Cordeiro Santana, Gustavo de Faria Theodoro, Ricardo Gava, João Lucas Gouveia de Oliveira, Larissa Pereira Ribeiro Teodoro, Izabela Cristina de Oliveira, Fábio Henrique Rojo Baio, Carlos Antonio da Silva Junior, Job Teixeira de Oliveira and Paulo Eduardo Teodoro
Using multispectral sensors attached to unmanned aerial vehicles (UAVs) can assist in the collection of morphological and physiological information from several crops. This approach, also known as high-throughput phenotyping, combined with data processin...
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Shuo Shi, Xingtao Tang, Bowen Chen, Biwu Chen, Qian Xu, Sifu Bi and Wei Gong
Lidar can effectively obtain three-dimensional information on ground objects. In recent years, lidar has developed rapidly from single-wavelength to multispectral hyperspectral imaging. The multispectral airborne lidar Optech Titan is the first commercia...
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Wuttichai Boonpook, Yumin Tan, Attawut Nardkulpat, Kritanai Torsri, Peerapong Torteeka, Patcharin Kamsing, Utane Sawangwit, Jose Pena and Montri Jainaen
Using deep learning semantic segmentation for land use extraction is the most challenging problem in medium spatial resolution imagery. This is because of the deep convolution layer and multiple levels of deep steps of the baseline network, which can cau...
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David Saravia, Lamberto Valqui-Valqui, Wilian Salazar, Javier Quille-Mamani, Elgar Barboza, Rossana Porras-Jorge, Pedro Injante and Carlos I. Arbizu
In Peru, common bean varieties adapt very well to arid zones, and it is essential to strengthen their evaluations accurately during their phenological stage by using remote sensors and UAV. However, this technology has not been widely adopted in the Peru...
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Polina Lemenkova
Automated classification of satellite images is a challenging task that enables the use of remote sensing data for environmental modeling of Earth?s landscapes. In this document, we implement a GRASS GIS-based framework for discriminating land cover type...
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Flavo Elano Soares de Souza and José Inácio de Jesus Rodrigues
With the growing availability of remote sensing orbital spatial data, the applications of machine learning (ML) algorithms have been leveraging the field of process automation in image classification. The present work aimed to evaluate the precision and ...
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Xueliang Wang, Nan Yang, Enjun Liu, Wencheng Gu, Jinglin Zhang, Shuo Zhao, Guijiang Sun and Jian Wang
In order to solve the problem of manual labeling in semi-supervised tree species classification, this paper proposes a pixel-level self-supervised learning model named M-SSL (multisource self-supervised learning), which takes the advantage of the informa...
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Barbara Dobosz, Dariusz Gozdowski, Jerzy Koronczok, Jan ?ukovskis and Elzbieta Wójcik-Gront
The accurate evaluation of crop damage by wild animals is crucial for farmers when seeking compensation from insurance companies or other institutions. One of the game species that frequently cause crop damage in Europe is the wild boar, which often feed...
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Coraline Wyard, Benjamin Beaumont, Taïs Grippa and Eric Hallot
Earth observation technologies offer non-intrusive solutions for monitoring complex and risky sites, such as landfills. In particular, unmanned aerial vehicles (UAVs) offer the ability to acquire data at very high spatial resolution, with full control of...
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