Zobrazeno 21 - 30
of 1 153
pro vyhledávání: '"Liangpei Zhang"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 10091-10100 (2021)
Building footprint information is one of the key factors for sustainable urban planning and environmental monitoring. Mapping building footprints from remote sensing images is an important and challenging task in the earth observation field. Over the
Externí odkaz:
https://doaj.org/article/3d1e75d7e6bb4cd2ad4580ee4151b77d
Publikováno v:
Geoscience Frontiers, Vol 13, Iss 1, Pp 101286- (2022)
Ground-level ozone (O3) is a primary air pollutant, which can greatly harm human health and ecosystems. At present, data fusion frameworks only provided ground-level O3 concentrations at coarse spatial (e.g., 10 km) or temporal (e.g., daily) resoluti
Externí odkaz:
https://doaj.org/article/3948fc224bf9440f9b6fddc000fb0bb1
Autor:
Chen Wu, Yinong Guo, Haonan Guo, Jingwen Yuan, Lixiang Ru, Hongruixuan Chen, Bo Du, Liangpei Zhang
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 103, Iss , Pp 102503- (2021)
In order to mitigate the spread of COVID-19, Wuhan was the first city to implement strict lockdown policy in 2020. Even though numerous researches have discussed the travel restriction between cities and provinces, few studies focus on the effect of
Externí odkaz:
https://doaj.org/article/8281c2849a724a15b4839c51f7481a8d
Autor:
Liangpei Zhang, Fulin Luo
Publikováno v:
Geo-spatial Information Science, Vol 23, Iss 1, Pp 98-106 (2020)
Graph learning is an effective manner to analyze the intrinsic properties of data. It has been widely used in the fields of dimensionality reduction and classification for data. In this paper, we focus on the graph learning-based dimensionality reduc
Externí odkaz:
https://doaj.org/article/92f0641d49a8493aa60171fb3d78cfb1
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 5759-5775 (2020)
Hyperspectral imaging is a significant remote sensing technology for deep space exploration to understand the planetary geological evolution. However, hyperspectral images (HSIs) usually suffer from various noises because of the complicated environme
Externí odkaz:
https://doaj.org/article/3c1239d2fb2e4ac6812a76f91e7dfdae
Publikováno v:
Journal of Geodesy and Geoinformation Science, Vol 2, Iss 2, Pp 78-89 (2019)
This paper deals with the massive point cloud segmentation processing technology on the basis of machine vision, which is the second essential factor for the intelligent data processing of three dimensional conformation in digital photogrammetry. In
Externí odkaz:
https://doaj.org/article/4459c08c3a9b42b0bc7545603cf4f20a
Publikováno v:
IEEE Access, Vol 7, Pp 142339-142352 (2019)
Missing data reconstruction for remote sensing images, such as dead-pixel recovery and cloud removal, is important for remote sensing data applications. Missing information reconstruction is well known as being an ill-posed inverse problem. In this p
Externí odkaz:
https://doaj.org/article/79adba9c7fce446e836e0d08a190c3ae
Autor:
Yonghao Xu, Bo Du, Liangpei Zhang, Daniele Cerra, Miguel Pato, Emiliano Carmona, Saurabh Prasad, Naoto Yokoya, Ronny Hansch, Bertrand Le Saux
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 12, Iss 6, Pp 1709-1724 (2019)
This paper presents the scientific outcomes of the 2018 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society. The 2018 Contest addressed the problem of urban observa
Externí odkaz:
https://doaj.org/article/6ce6ad9a15214671b8ac31fe0b53def6
Publikováno v:
Environmental Research Letters, Vol 17, Iss 3, p 034014 (2022)
Fine particulate matter (PM _2.5 ) is widely concerned for its harmful impacts on global environment and human health, making air pollution monitoring so crucial and indispensable. As the world’s first open, real-time, and historical air quality pl
Externí odkaz:
https://doaj.org/article/71ed69ffa21a4d6c896f7a7543ae0dcf
Publikováno v:
Geo-spatial Information Science, Vol 21, Iss 1, Pp 21-32 (2018)
Research on unmanned aerial vehicles (UAV) has been increasingly popular in the past decades, and UAVs have been widely used in industrial inspection, remote sensing for mapping & surveying, rescuing, and so on. Nevertheless, the limited autonomous n
Externí odkaz:
https://doaj.org/article/b8d2246b53ab4b1daf89f9569b8b489a