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Peng Zhang, Qin Qin, Shijie Zhang, Xiangtian Zhao, Xiaoliang Yan, Wei Wang and Hongbin Zhang
Remote sensing has become an essential tool for geological exploration, disaster monitoring, emergency rescue, and environmental supervision, while the limited number of remote sensing satellites and ground stations restricts the timeliness of remote sen...
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Yacine Mohia, Rafik Absi, Mourad Lazri, Karim Labadi, Fethi Ouallouche and Soltane Ameur
To estimate rainfall from remote sensing data, three machine learning-based regression models, K-Nearest Neighbors Regression (K-NNR), Support Vector Regression (SVR), and Random Forest Regression (RFR), were implemented using MSG (Meteosat Second Genera...
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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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Harry Imantho, Kudang Boro Seminar, Wawan Hermawan and Satyanto Krido Saptomo
Obtaining soil water content and soil workability data using remote sensing technology with passive sensors has some limitations due to cloud cover, cloud shadow, haze and smoke. This study proposes a method for computing soil water content and soil work...
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Venkatesh Thirugnana Sambandham, Priyamvada Shankar and Sayan Mukhopadhaya
Early warning systems help combat crop diseases and enable sustainable plant protection by optimizing the use of resources. The application of remote sensing to detect plant diseases like wheat stripe rust, commonly known as yellow rust, is based on the ...
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Haoteng Zhao, Liping Di and Ziheng Sun
Irrigation is the primary consumer of freshwater by humans and accounts for over 70% of all annual water use. However, due to the shortage of open critical information in agriculture such as soil, precipitation, and crop status, farmers heavily rely on e...
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Charles Whittaker and Robert Leconte
For the past few decades, remote sensing has been a valuable tool for deriving global information on snow water equivalent (SWE), where products derived from space-borne passive microwave radiometers are favoured as they respond to snow depth, an importa...
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Imen Chebbi, Nedra Mellouli, Imed Riadh Farah and Myriam Lamolle
Big data analysis assumes a significant role in Earth observation using remote sensing images, since the explosion of data images from multiple sensors is used in several fields. The traditional data analysis techniques have different limitations on stor...
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Gaurav Tripathi, Bikash Ranjan Parida and Arvind Chandra Pandey
Flooding is one of the most common natural disasters in India. Typically, the Kosi and Gandak river basins are well-known for lingering flood affected basins in North Bihar every year, which lies in the eastern part of India. There were no such comprehen...
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Huihui Mao, Jihua Meng, Fujiang Ji, Qiankun Zhang and Huiting Fang
Leaf area index (LAI) is a crucial crop biophysical parameter that has been widely used in a variety of fields. Five state-of-the-art machine learning regression algorithms (MLRAs), namely, artificial neural network (ANN), support vector regression (SVR)...
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