Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Jiage Chen"'
Publikováno v:
Remote Sensing, Vol 15, Iss 13, p 3285 (2023)
The timely and accurate mapping of crops over large areas is essential for alleviating food crises and formulating agricultural policies. However, most existing classical crop mapping methods usually require the whole-year historical time-series data
Externí odkaz:
https://doaj.org/article/0c41805651444fe9a006ecb0050ac443
Publikováno v:
Remote Sensing, Vol 13, Iss 24, p 5177 (2021)
Forests play a vital role in combating gradual developmental deficiencies and balancing regional ecosystems, yet they are constantly disturbed by man-made or natural events. Therefore, developing a timely and accurate forest disturbance detection str
Externí odkaz:
https://doaj.org/article/75e7adb47f0f4451bf2f5c9a1890fb6d
Publikováno v:
Remote Sensing, Vol 12, Iss 15, p 2493 (2020)
Timely and accurate agricultural information is essential for food security assessment and agricultural management. Synthetic aperture radar (SAR) systems are increasingly available in crop mapping, as they provide all-weather imagery. In particular,
Externí odkaz:
https://doaj.org/article/9a9ef063f96546038d35435d9eee093b
Publikováno v:
Remote Sensing, Vol 12, Iss 5, p 843 (2020)
Hyperspectral image analysis plays an important role in agriculture, mineral industry, and for military purposes. However, it is quite challenging when classifying high-dimensional hyperspectral data with few labeled samples. Currently, generative ad
Externí odkaz:
https://doaj.org/article/de4fd8280c5a4f438738b7f51705843b
Publikováno v:
Remote Sensing, Vol 10, Iss 11, p 1713 (2018)
Deep learning has become a standard processing procedure in land cover mapping for remote sensing images. Instead of relying on hand-crafted features, deep learning algorithms, such as Convolutional Neural Networks (CNN) can automatically generate ef
Externí odkaz:
https://doaj.org/article/c3b925582c0f40ac98222f8ae7ef5195
Publikováno v:
Remote Sensing, Vol 10, Iss 8, p 1251 (2018)
Spectral and NDVI values have been used to calculate the change magnitudes of land cover, but may result in many pseudo-changes because of inter-class variance. Recently, the shape information of spectral or NDVI curves such as direction, angle, grad
Externí odkaz:
https://doaj.org/article/4c1e27c1f53c48669923e6881c812f70
Publikováno v:
Remote Sensing, Vol 10, Iss 7, p 1020 (2018)
Accurate information on cropland changes is critical for food production and security, sustainable cropland management, and global change studies. The common change detection methods bi-temporal based, using remotely sensed imagery easily generate ps
Externí odkaz:
https://doaj.org/article/a013600c5e9e4a959b03f6ae8bb59621
Publikováno v:
Remote Sensing; Volume 15; Issue 13; Pages: 3285
The timely and accurate mapping of crops over large areas is essential for alleviating food crises and formulating agricultural policies. However, most existing classical crop mapping methods usually require the whole-year historical time-series data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::58d34a27ac01fa5e0e6d764aef8f56c1
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4d848a01effc70fd235287d015f9427
https://doi.org/10.1109/lgrs.2022.3177778
https://doi.org/10.1109/lgrs.2022.3177778
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
Change detection by comparing two bitemporal images is one of the most challenging tasks in remote sensing. At present, most related studies focus on change area detection while neglecting multiple change type identification. In this letter, an atten
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2c5b4a278ca0b4f13e7f7872eea5e15c
https://doi.org/10.1109/lgrs.2020.3035780
https://doi.org/10.1109/lgrs.2020.3035780