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Mariann Merz, Dário Pedro, Vasileios Skliros, Carl Bergenhem, Mikko Himanka, Torbjørn Houge, João P. Matos-Carvalho, Henrik Lundkvist, Baran Cürüklü, Rasmus Hamrén, Afshin E. Ameri, Carl Ahlberg and Gorm Johansen
Emerging precision agriculture techniques rely on the frequent collection of high-quality data which can be acquired efficiently by unmanned aerial systems (UAS). The main obstacle for wider adoption of this technology is related to UAS operational costs...
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Thaís R. Benevides T. Aranha, Jean-Michel Martinez, Enio P. Souza, Mário U. G. Barros and Eduardo Sávio P. R. Martins
In this paper, the authors use remote-sensing images to monitor the water quality of reservoirs located in the semiarid region of Northeast Brazil. Sentinel-2 MSI TOA Level 1C reflectance images were used to remotely estimate the concentration of chlorop...
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Prashant K. Srivastava, George P. Petropoulos, Rajendra Prasad and Dimitris Triantakonstantis
Soil Moisture Deficit (SMD) is a key indicator of soil water content changes and is valuable to a variety of applications, such as weather and climate, natural disasters, agricultural water management, etc. Soil Moisture and Ocean Salinity (SMOS) is a de...
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Tianqi Qiu, Xiaojin Liang, Qingyun Du, Fu Ren, Pengjie Lu and Chao Wu
Emergency remote sensing mapping can provide support for decision making in disaster assessment or disaster relief, and therefore plays an important role in disaster response. Traditional emergency remote sensing mapping methods use decryption algorithms...
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Hongwei Zhao, Lin Yuan and Haoyu Zhao
Recently, with the rapid growth of the number of datasets with remote sensing images, it is urgent to propose an effective image retrieval method to manage and use such image data. In this paper, we propose a deep metric learning strategy based on Simila...
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