Zobrazeno 1 - 10
of 215
pro vyhledávání: '"remote sensing classification"'
Publikováno v:
Ecological Indicators, Vol 166, Iss , Pp 112578- (2024)
Agricultural non-point source pollution threatens the quality of the ecological environment, human health, and safety. This study took the Sixth Drainage Ditch of the Yellow River Irrigation Area in Ningxia as the research area, set up a runoff water
Externí odkaz:
https://doaj.org/article/0c5e2932f53d4663a8432603eec32d9a
Publikováno v:
GIScience & Remote Sensing, Vol 61, Iss 1 (2024)
ABSTRACTMapping detailed wetland types can offer useful information for wetland management and protection, which can strongly support the Global Biodiversity Framework. Many studies have conducted wetland classification at regional, national, and glo
Externí odkaz:
https://doaj.org/article/51e070ecd9a84f22ba7ed18a26492a68
Autor:
Xuanlin Huo, Zhenguo Niu
Publikováno v:
Water, Vol 16, Iss 17, p 2415 (2024)
Accurate wetland classification in the Yellow River Basin (YRB) is crucial for China’s ecological security, sustainable development, and wetland resource management. This calls for more sustained research on regional variations and studies on remot
Externí odkaz:
https://doaj.org/article/d4a922eb3add4a60a72e9368b1021393
Publikováno v:
Remote Sensing, Vol 16, Iss 10, p 1684 (2024)
The efficient and timely identification of oil spill areas is crucial for ocean environmental protection. Synthetic aperture radar (SAR) is widely used in oil spill detection due to its all-weather monitoring capability. Meanwhile, existing deep lear
Externí odkaz:
https://doaj.org/article/aa213368ccdc4f08a226ae836c75159c
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 9231-9245 (2023)
Land cover analysis has received significant attention in remote sensing-related fields. To take advantage of multimodal data, hyperspectral images (HSI) and light detection and ranging (LiDAR) are often combined. However, it is difficult to capture
Externí odkaz:
https://doaj.org/article/a346fd46524b41f18f32c121cb61f69f
Publikováno v:
Sensors, Vol 23, Iss 20, p 8530 (2023)
Selecting training samples is crucial in remote sensing image classification. In this paper, we selected three images—Sentinel-2, GF-1, and Landsat 8—and employed three methods for selecting training samples: grouping selection, entropy-based sel
Externí odkaz:
https://doaj.org/article/689a13d4a284483eb7b780e968a39e20
Publikováno v:
Ecological Indicators, Vol 146, Iss , Pp 109828- (2023)
The Karst Plateau in eastern Yunnan, China (KPEYC) is densely populated. In this area, rocks are widely exposed, and soil erosion and rock desertification are serious issues. Furthermore, the conflict between humans and land is prominent. It is impor
Externí odkaz:
https://doaj.org/article/e1d67cf4576b4525851291c3427bb1c9
Publikováno v:
Remote Sensing, Vol 15, Iss 17, p 4148 (2023)
The fusion-based classification of hyperspectral (HS) and light detection and ranging (LiDAR) images has become a prominent research topic, as their complementary information can effectively improve classification performance. The current methods enc
Externí odkaz:
https://doaj.org/article/60d8b1df4f00454d9d0098351b26c444
Publikováno v:
Remote Sensing, Vol 15, Iss 15, p 3859 (2023)
The rapid advancement of remote sensing technology has significantly enhanced the temporal resolution of remote sensing data. Multitemporal remote sensing image classification can extract richer spatiotemporal features. However, this also presents th
Externí odkaz:
https://doaj.org/article/e5bf7f4868b04ff790ddac5165b19cc9
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