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Ching-Lung Fan
The emergence of deep learning-based classification methods has led to considerable advancements and remarkable performance in image recognition. This study introduces the Multiscale Feature Convolutional Neural Network (MSFCNN) for the extraction of com...
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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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Nicola Case and Alfonso Vitti
Digital images, and in particular satellite images acquired by different sensors, may present defects due to many causes. Since 2013, the Landsat 7 mission has been affected by a well-known issue related to the malfunctioning of the Scan Line Corrector p...
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Brian Alan Johnson, Ryutaro Tateishi and Nguyen Thanh Hoan
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Haixia Jin, Jingjing Peng, Rutian Bi, Huiwen Tian, Hongfen Zhu and Haoxi Ding
Mapping soil organic carbon (SOC) accurately is essential for sustainable soil resource management. Hyperspectral data, a vital tool for SOC mapping, is obtained through both laboratory and satellite-based sources. While laboratory data is limited to sam...
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Tulsi Patel, Mark W. Jones and Thomas Redfern
We present a novel approach to providing greater insight into the characteristics of an unlabelled dataset, increasing the efficiency with which labelled datasets can be created. We leverage dimension-reduction techniques in combination with autoencoders...
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Yiliang Wan, Yuwen Fei, Rui Jin, Tao Wu and Xinguang He
The effective extraction of impervious surfaces is critical to monitor their expansion and ensure the sustainable development of cities. Open geographic data can provide a large number of training samples for machine learning methods based on remote-sens...
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Alfred de Jager, Christina Corbane and Filip Szabo
The droughts that hit North and North Western Europe in 2018 and 2019 served as a wake-up call that temperate regions are also affected by these kinds of slow progressing or creeping disasters. Long-term drivers, such as land-use changes, may have exacer...
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Mohamed S. Shokr, Yasser S. A. Mazrou, Mostafa A. Abdellatif, Ahmed A. El Baroudy, Esawy K. Mahmoud, Ahmed M. Saleh, Abdelaziz A. Belal and Zheli Ding
For modelling and predicting soil indicators to be fully operational and facilitate decision-making at any spatial level, there is a requirement for precise spatially referenced soil information to be available as input data. This paper focuses on showin...
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Serdar Kizilkaya, Ugur Alganci and Elif Sertel
The classification of maritime boats and ship targets using optical satellite imagery is a challenging subject. This research introduces a unique and rich ship dataset named Very High-Resolution Ships (VHRShips) from Google Earth images, which includes d...
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Chaoyun Yang, Yonghong Zhang, Min Xia, Haifeng Lin, Jia Liu and Yang Li
Cloud and snow recognition technology is of great significance in the field of meteorology, and is also widely used in remote sensing mapping, aerospace, and other fields. Based on the traditional method of manually labeling cloud-snow areas, a method of...
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Jian Guo, Shuchen Wang and Qizhi Xu
The complexity of changeable marine backgrounds makes ship detection from satellite remote sensing images a challenging task. The ubiquitous interference of cloud and fog led to missed detection and false-alarms when using imagery-based optical satellite...
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Pawel Tysiac, Tatiana Strelets and Weronika Tuszynska
In recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extre...
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George Katselis, Konstantinos Tsolakos and John A. Theodorou
The Greek marine aquaculture has a leading role in the Mediterranean mariculture industry, mainly in the export sector and its prominent contribution to the country?s economy. In the present study, the spatial distribution of Greek finfish farming activi...
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Tomá? Rezník, Jan Chytrý and Katerina Trojanová
Land use and land cover are continuously changing in today?s world. Both domains, therefore, have to rely on updates of external information sources from which the relevant land use/land cover (classification) is extracted. Satellite images are frequent ...
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Wei Yi, Yuhao Wang, Yong Zeng, Yaqin Wang and Jianfei Xu
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Kai Zheng, Jiansheng Li, Lei Ding, Jianfeng Yang, Xucheng Zhang and Xun Zhang
The segmentation of cloud and snow in satellite images is a key step for subsequent image analysis, interpretation, and other applications. In this paper, a cloud and snow segmentation method based on a deep convolutional neural network (DCNN) with enhan...
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Claudia Paola Cardozo,Guillermo Toyos,Valérie Baumann
Pág. 75 - 93
On February 2009 intense rainfall triggered landslides in the Tartagal River basin that evolved into a debris flow that caused severe flooding in the town of Tartagal, Salta, Argentina. Based on these events, this paper presents a first attempt to map th...
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Paidamwoyo Mhangara, Willard Mapurisa and Naledzani Mudau
High resolution pansharpened images are used for detailed land use and land cover mapping.
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Ryunosuke Ogawa, Masahiro Hirata, Birhane Gebreanenia Gebremedhin, Satoshi Uchida, Toru Sakai, Kazuhisa Koda and Koichi Takenaka
The search for a sustainable land management has become a universal issue. It is especially necessary to discuss sustainable land management and to secure a site with enough feed supply to improve the lives of the farmers in the Ethiopian Highlands. This...
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