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Francisco Leitão, Vânia Baptista, Vasco Vieira, Patrícia Laginha Silva, Paulo Relvas and Maria Alexandra Teodósio
Coastal upwelling has a significant local impact on marine coastal environment and on marine biology, namely fisheries. This study aims to evaluate climate and environmental changes in upwelling trends between 1950 and 2010. Annual, seasonal and monthly ...
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Daniela Castagna, Luzinete Scaunichi Barbosa, Charles Campoe Martim, Rhavel Salviano Dias Paulista, Nadja Gomes Machado, Marcelo Sacardi Biudes and Adilson Pacheco de Souza
The Amazon biome plays a crucial role in the hydrological cycle, supplying water vapor for the atmosphere and contributing to evapotranspiration (ET) that influences regional humidity across Brazil and South America. Remote sensing (RS) has emerged as a ...
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Abdul-Wadood Moomen, Lily Lisa Yevugah, Louvis Boakye, Jeff Dacosta Osei and Francis Muthoni
This paper assesses evidence-based applications of Remote Sensing for Sustainable and Precision Agriculture in the Northern Savanna Regions of Ghana for three decades (1990?2023). During this period, there have been several government policy intervention...
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Karma Tempa, Masengo Ilunga, Abhishek Agarwal and Tashi
Gelephu, located in the Himalayan region, has undergone significant development activities due to its suitable topography and geographic location. This has led to rapid urbanization in recent years. Assessing land use land cover (LULC) dynamics and Norma...
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Vanessa Gonçalves, Antonio Albuquerque, Pedro Gabriel Almeida, Luís Ferreira Gomes and Victor Cavaleiro
The risk of aquifer contamination is determined by the interaction between the pollutant load and the vulnerability of an aquifer. Owing to the decomposition of bodies and degradation of artefacts, cemeteries may have a negative impact on groundwater qua...
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Wenqi Gao, Ninghua Chen, Jianyu Chen, Bowen Gao, Yaochen Xu, Xuhua Weng and Xinhao Jiang
Geospatial data, especially remote sensing (RS) data, are of significant importance for public services and production activities. Expertise is critical in processing raw data, generating geospatial information, and acquiring domain knowledge and other r...
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Shihao Ma, Jiao Wu, Zhijun Zhang and Yala Tong
Addressing the limitations, including low automation, slow recognition speed, and limited universality, of current mudslide disaster detection techniques in remote sensing imagery, this study employs deep learning methods for enhanced mudslide disaster d...
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Mohamad Mahmoud Al Rahhal, Yakoub Bazi, Hebah Elgibreen and Mansour Zuair
Zero-shot classification presents a challenge since it necessitates a model to categorize images belonging to classes it has not encountered during its training phase. Previous research in the field of remote sensing (RS) has explored this task by traini...
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Ahram Song
Deep learning techniques have recently shown remarkable efficacy in the semantic segmentation of natural and remote sensing (RS) images. However, these techniques heavily rely on the size of the training data, and obtaining large RS imagery datasets is d...
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Kingsley Kanjin, Richard Adade, Julia Quaicoe and Minxuan Lan
Despite water being a basic human need, the residents of Sibi in Ghana?s Nkwanta North District struggle to obtain potable water, which negatively influences their livelihoods. This study aimed to evaluate the impacts on households? livelihoods due to di...
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