Zobrazeno 1 - 10
of 2 172
pro vyhledávání: '"cloud detection"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Highly accurate nighttime cloud detection in satellite imagery is challenging due to the absence of visible to near-infrared (0.38–3 μm, VNI) data, which is critical for distinguishing clouds from other ground features. Fortunately, Machi
Externí odkaz:
https://doaj.org/article/ef329be1f4ba420aa181854cd900d514
Publikováno v:
Geo-spatial Information Science, Pp 1-18 (2024)
To enhance the adaptability and application capability of the cloud detection model in different remote sensing satellite domains, unsupervised domain adaptation methods are employed to improve the model’s robustness and transferability. However, c
Externí odkaz:
https://doaj.org/article/c6300786f6af4475a1884f901bd73b58
Autor:
Mohammed Alae Chanoui, Ilyas El wafi, Imane Khalil, Mohammed Sbihi, Zine El Abidine Alaoui Ismaili, Zouhair Guennoun
Publikováno v:
Results in Engineering, Vol 24, Iss , Pp 103324- (2024)
Optimizing Earth observation nanosatellite missions requires careful orbit selection to ensure global coverage and high image quality. The main challenge is to define an optimal orbit that maximizes image quality while achieving comprehensive Earth c
Externí odkaz:
https://doaj.org/article/8541b643720748edbbaed00b94dfed21
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
Cloud cover is a significant factor affecting the effectiveness of satellite-based Earth observations. Existing cloud detection algorithms primarily rely on imaging data from satellite sensors in the visible to near-infrared spectral range, making it
Externí odkaz:
https://doaj.org/article/db16f457d4c34104a3f1b19a1ac627a4
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 19853-19863 (2024)
Sea surface temperature (SST) is a vital oceanic parameter that significantly influences air–sea heat flux and momentum exchange. SST datasets are crucial for identifying and describing both short-term and long-term climate perturbations in the oce
Externí odkaz:
https://doaj.org/article/ba9ac650d2b9494aacb3e394b0995014
Autor:
Cesar Aybar, Gonzalo Mateo-Garcia, Giacomo Acciarini, Vit Ruzicka, Gabriele Meoni, Nicolas Longepe, Luis Gomez-Chova
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 19518-19529 (2024)
Nano and microsatellites have expanded the acquisition of satellite images with higher spatial, temporal, and spectral resolutions. Nevertheless, downlinking all this data to the ground for processing becomes challenging as the amount of remote sensi
Externí odkaz:
https://doaj.org/article/31318ccf698d41c4b3e5cf4807997b16
Autor:
Nicolas Longepe, Isabella Petrelli, Nika Oman Kadunc, Devis Peressutti, Roberto Del Prete, Mauro Casaburi, Irina Babkina, Nathan Vercruyssen, Elisa Callejo Luis, Alvaro Moron, Valentina Marchese, Agne Paskeviciute Kidron, Nicola Melega
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 17651-17665 (2024)
Over the past decade, there has been a rapid acceleration in the development of Artificial Intelligence (AI) for Earth Observation (EO), driven by the exponential growth in collected data and advances in algorithms and computing. This revolution exte
Externí odkaz:
https://doaj.org/article/c80fa15de12d4fdd90cca5edafa23de5
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 7490-7500 (2024)
Himawari-8 satellite, equipped with an advanced Himawari imager (AHI), has been widely employed for cloud detection tasks due to its high-spatiotemporal resolution. In this article, we propose a deep learning model named dual-branch deformable convol
Externí odkaz:
https://doaj.org/article/c093967ab87a4df4a879f6ad4f32d7d9
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 4538-4551 (2024)
Clouds in remote sensing images inevitably affect information extraction, which hinders the following analysis of satellite images. Hence, cloud detection is a necessary preprocessing procedure. However, most existing methods have numerous calculatio
Externí odkaz:
https://doaj.org/article/5ffd08dcc97c40bb88599aab63c8eee2
Publikováno v:
IEEE Access, Vol 12, Pp 9229-9242 (2024)
Cloud cover is a phenomenon that inevitably exists in remote sensing images, and ground information is lost due to the presence of clouds. To a large extent, it causes degradation of the remote sensing image quality. Therefore, the detection of cloud
Externí odkaz:
https://doaj.org/article/dec089254ca548efa61907bbc9576e6d