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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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Zijia Zheng, Yizhu Jiang, Qiutong Zhang, Yanling Zhong and Lizheng Wang
The timely monitoring of urban water bodies using unmanned aerial vehicle (UAV)-mounted remote sensing technology is crucial for urban water resource protection and management. Addressing the limitations of the use of satellite data in inferring the wate...
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Xin Zhao, Zeyi Zhao, Fengnian Zhao, Jiangfan Liu, Zhaoyang Li, Xingpeng Wang and Yang Gao
Accurate nitrogen fertilizer management determines the yield and quality of fruit trees, but there is a lack of multispectral UAV-based nitrogen fertilizer monitoring technology for orchards. Therefore, in this study, a field experiment was conducted by ...
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Abdelkrim Lachgar, David J. Mulla and Viacheslav Adamchuk
One of the challenges in site-specific phosphorus (P) management is the substantial spatial variability in plant available P across fields. To overcome this barrier, emerging sensing, data fusion, and spatial predictive modeling approaches are needed to ...
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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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Kevin J. Wienhold, Dongfeng Li, Wenzhao Li and Zheng N. Fang
The identification of flood hazards during emerging public safety crises such as hurricanes or flash floods is an invaluable tool for first responders and managers yet remains out of reach in any comprehensive sense when using traditional remote-sensing ...
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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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Justin Edwards and Mohamed El-Sharkawy
Semantic segmentation is a machine learning task that is seeing increased utilization in multiple fields, from medical imagery to land demarcation and autonomous vehicles. A real-time autonomous system must be lightweight while maintaining reasonable acc...
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Romeu Gerardo and Isabel P. de Lima
Nowadays, Unmanned Aerial Systems (UASs) provide an efficient and relatively affordable remote sensing technology for assessing vegetation attributes and status across agricultural areas through wide-area imagery collected with cameras installed on board...
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Zhan Tan, Jiu Ren, Shaoda Li, Wei Li, Rui Zhang and Tiegang Sun
Remote sensing is widely used for lake-water-quality monitoring, but the inversion of the total nitrogen (TN) and total phosphorus (TP) of rivers and non-optical parameters is still a difficult problem. The use of high spatial and temporal resolution mul...
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