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Sellaperumal Pazhanivelan, N. S. Sudarmanian, Vellingiri Geethalakshmi, Murugesan Deiveegan, Kaliaperumal Ragunath, A. P. Sivamurugan and P. Shanmugapriya
Synthetic aperture radar (SAR) imagery, notably Sentinel-1A?s C-band, VV, and VH polarized SAR, has emerged as a crucial tool for mapping rice fields, especially in regions where cloud cover hinders optical imagery. Employing multi-temporal characteristi...
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Jhon Lennon Bezerra da Silva, Marcos Vinícius da Silva, Alexandre Maniçoba da Rosa Ferraz Jardim, Pabrício Marcos Oliveira Lopes, Henrique Fonseca Elias de Oliveira, Josef Augusto Oberdan Souza Silva, Márcio Mesquita, Ailton Alves de Carvalho, Alan Cézar Bezerra, José Francisco de Oliveira-Júnior, Maria Beatriz Ferreira, Iara Tamires Rodrigues Cavalcante, Elania Freire da Silva and Geber Barbosa de Albuquerque Moura
Northeast Brazil (NEB), particularly its semiarid region, represents an area highly susceptible to the impacts of climate change, including severe droughts, and intense anthropogenic activities. These stresses may be accelerating environmental degradatio...
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Yang Li, Bo Zhao, Jizhong Wang, Yanjun Li and Yanwei Yuan
Accurate yield estimation before the wheat harvest is very important for precision management, maintaining grain market stability, and ensuring national food security. In this study, to further improve the accuracy of winter wheat yield estimation, machi...
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Antonio Falciano, Marco Anzidei, Michele Greco, Maria Lucia Trivigno, Antonio Vecchio, Charalampos Georgiadis, Petros Patias, Michele Crosetto, Josè Navarro, Enrico Serpelloni, Cristiano Tolomei, Giovanni Martino, Giuseppe Mancino, Francesco Arbia, Christian Bignami and Fawzi Doumaz
Here we show the SAVEMEDCOASTS-2 web-based geographic information system (webGIS) that supports land planners and decision makers in considering the ongoing impacts of Relative Sea Level Rise (RSLR) when formulating and prioritizing climate-resilient ada...
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Qianjing Li, Jia Tian and Qingjiu Tian
The combination of multi-temporal images and deep learning is an efficient way to obtain accurate crop distributions and so has drawn increasing attention. However, few studies have compared deep learning models with different architectures, so it remain...
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Polina Lemenkova and Olivier Debeir
With methods for processing remote sensing data becoming widely available, the ability to quantify changes in spatial data and to evaluate the distribution of diverse landforms across target areas in datasets becomes increasingly important. One way to ap...
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Daiwei Zhang, Chunyang Ying, Lei Wu, Zhongqiu Meng, Xiaofei Wang and Youhua Ma
Timely and accurate extraction of crop planting structure information is of great importance for food security and sustainable agricultural development. However, long time series data with high spatial resolution have a much larger data volume, which ser...
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Jingwu Ma, Renfeng Ma, Qi Pan, Xianjun Liang, Jianqing Wang and Xinxin Ni
With the rapid development of urbanization and industrialization, human activities have caused marine pollution in three ways: land source, air source, and sea source, leading to the problem of marine environments. Remote sensing, with its wide coverage ...
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Manuel Nhangumbe, Andrea Nascetti and Yifang Ban
Floods are one of the most frequent natural disasters worldwide. Although the vulnerability varies from region to region, all countries are susceptible to flooding. Mozambique was hit by several cyclones in the last few decades, and in 2019, after cyclon...
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Hebing Zhang, Hongyi Yuan, Weibing Du and Xiaoxuan Lyu
Although vegetation index time series from optical images are widely used for crop mapping, it remains difficult to obtain sufficient time-series data because of satellite revisit time and weather in some areas. To address this situation, this paper cons...
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