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pro vyhledávání: '"Ram C. Sharma"'
Autor:
Ram C. Sharma
Publikováno v:
Ecologies, Vol 3, Iss 3, Pp 323-335 (2022)
This paper presents the Dominant Species-Physiognomy-Ecological (DSPE) classification system developed for large-scale differentiation of plant ecological communities from high-spatial resolution remote sensing images. In this system, the plant ecolo
Externí odkaz:
https://doaj.org/article/18c688dd7f8e46e2beeb472881ac68d7
Autor:
Ram C. Sharma
Publikováno v:
Ecologies, Vol 2, Iss 2, Pp 203-213 (2021)
Vegetation mapping and monitoring is important as the composition and distribution of vegetation has been greatly influenced by land use change and the interaction of land use change and climate change. The purpose of vegetation mapping is to discove
Externí odkaz:
https://doaj.org/article/4089097af9b446a6b29c6a5231bfd685
Autor:
Ram C. Sharma
Publikováno v:
Applied Sciences, Vol 12, Iss 14, p 7125 (2022)
This paper presents next-generation mapping of plant ecological communities including land cover and agricultural types at 10 m spatial resolution countrywide. This research introduces modelling and mapping of land cover and ecological communities se
Externí odkaz:
https://doaj.org/article/4f6c1394578c461087b6f6f580d3f4b3
Autor:
Ram C. Sharma
Publikováno v:
Remote Sensing, Vol 14, Iss 13, p 3145 (2022)
This paper presents two categories of features extraction and mapping suite, a very high-resolution suite and an ultra-resolution suite at 2 m and 0.5 m resolutions, respectively, for the differentiation and mapping of land cover and community-level
Externí odkaz:
https://doaj.org/article/708f1f3b7a47462587ee5c61df8eba0e
Autor:
Ram C. Sharma
Publikováno v:
Journal of Imaging, Vol 7, Iss 5, p 84 (2021)
Utilization of the Bidirectional Reflectance Distribution Function (BRDF) model parameters obtained from the multi-angular remote sensing is one of the approaches for the retrieval of vegetation structural information. In this research, the potential
Externí odkaz:
https://doaj.org/article/3339dfef1e4848a2b7f05a706af7430b
Autor:
Ram C. Sharma, Keitarou Hara
Publikováno v:
Journal of Imaging, Vol 7, Iss 2, p 30 (2021)
Vegetation indices are commonly used techniques for the retrieval of biophysical and chemical attributes of vegetation. This paper presents the potential of an Autoencoders (AEs) and Convolutional Autoencoders (CAEs)-based self-supervised learning ap
Externí odkaz:
https://doaj.org/article/4d3e39da784e4b7ca174bc62436c2cf7
Publikováno v:
Remote Sensing, Vol 7, Iss 10, Pp 13807-13841 (2015)
Monitoring of water cover and shorelines at a global scale is essential for better understanding climate change consequences and modern human disturbances. The level and turbidity of the surface water, and the background objects in which they interac
Externí odkaz:
https://doaj.org/article/7d2c26d2f7824f10bf483cbbf5476ba7
Publikováno v:
Scientifica, Vol 2017 (2017)
This paper presents the performance and evaluation of a number of machine learning classifiers for the discrimination between the vegetation physiognomic classes using the satellite based time-series of the surface reflectance data. Discrimination of
Externí odkaz:
https://doaj.org/article/6da2e7749116443f815fb9674f0a5e9d
Autor:
Nguyen Thanh Hoan, Yuei-An Liou, Kim-Anh Nguyen, Ram C. Sharma, Duy-Phien Tran, Chia-Ling Liou, Dao Dinh Cham
Publikováno v:
Remote Sensing, Vol 10, Iss 12, p 1965 (2018)
Hanoi City of Vietnam changes quickly, especially after its state implemented its Master Plan 2030 for the city’s sustainable development in 2011. Then, a number of environmental issues are brought up in response to the master plan’s implementati
Externí odkaz:
https://doaj.org/article/f6a7088ba4164a56b4ab365dc2971241
Autor:
Ram C. Sharma, Keitarou Hara
Publikováno v:
Geosciences, Vol 8, Iss 11, p 394 (2018)
This paper presents an assessment of the bidirectional reflectance features for the classification and characterization of vegetation physiognomic types at a national scale. The bidirectional reflectance data at multiple illumination and viewing geom
Externí odkaz:
https://doaj.org/article/374268bbef5a406b8f22b4f27347a582