Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Mehdi Mokhtarzade"'
Publikováno v:
Environmental Sciences Proceedings, Vol 29, Iss 1, p 28 (2023)
Water plays a vital role in sustaining life and meeting the water needs of various sectors, such as agriculture, industries, and households. As water resources continue to be depleted, several hazards arise for communities. Declining water quality, a
Externí odkaz:
https://doaj.org/article/aa8bf40c9aba47c28fa499edae23f9b0
Publikováno v:
Environmental Sciences Proceedings, Vol 29, Iss 1, p 26 (2023)
Climate change has directly impacted Earth’s habitats, resulting in various adverse effects, such as the desiccation of water bodies. The process of identifying such changes through field observations is time-consuming and costly. By using remote s
Externí odkaz:
https://doaj.org/article/75adf8135a774bb582cfccd6eda526e2
Publikováno v:
Environmental Sciences Proceedings, Vol 29, Iss 1, p 35 (2023)
Identifying changes in the Earth’s phenomena is vital for understanding and mitigating the impacts of environmental issues. Monitoring the Earth’s surface phenomena can be carried out effectively using satellite images acquired at different times
Externí odkaz:
https://doaj.org/article/e8bce111ef4c4216872d3efab4046ae3
Autor:
Farzane Mohseni, Mehdi Mokhtarzade
Publikováno v:
GIScience & Remote Sensing, Vol 58, Iss 3, Pp 455-482 (2021)
In an attempt to retrieve soil moisture content (SMC) from remote sensing techniques, this article suggests and evaluates a developed approach that overcomes three of the most fundamental limitations of the temperature–vegetation (T-V) scatter plot
Externí odkaz:
https://doaj.org/article/e4f9eebf3c0d4293924168f81388ca43
Publikováno v:
Computer and Knowledge Engineering, Vol 2, Iss 2, Pp 2-8 (2020)
Previous studies show that the incorporation of spatial features in the classification process of hyperspectral images (HSI) improves classification accuracy. Although different spatial-spectral methods are proposed in the literature for the classifi
Externí odkaz:
https://doaj.org/article/31737f3c4c88412b8fcc54adf98bfe93
Publikováno v:
Remote Sensing, Vol 14, Iss 18, p 4624 (2022)
SMAP/Sentinel-1 soil moisture is the latest SMAP (Soil Moisture Active Passive) product derived from synergistic utilization of the radiometry observations of SMAP and radar backscattering data of Sentinel-1. This product is the first and only global
Externí odkaz:
https://doaj.org/article/f715d25207b0467fa729c5c83e8518ac
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 89, Iss , Pp 102097- (2020)
In response to the curse of dimensionality in hyperspectral images (HSIs), to date, numerous dimensionality reduction methods have been proposed among which the feature extraction (FE) methods are of particular interest. This paper introduces a new s
Externí odkaz:
https://doaj.org/article/ef7913a60b9542f9916a51289a643257
Publikováno v:
European Journal of Remote Sensing, Vol 51, Iss 1, Pp 436-456 (2018)
Point cloud registration has been a major research challenge in recent years. In this paper, a novel hierarchical method is proposed for registering Aerial and Terrestrial image-based Point Clouds (APC & TPC). This registration aims to yield a comple
Externí odkaz:
https://doaj.org/article/9c74f3ef759c4fa1b2656cef5e64628a
Publikováno v:
Remote Sensing, Vol 7, Iss 7, Pp 8416-8435 (2015)
Soil lead content is an important parameter in environmental and industrial applications. Chemical analysis, the most commonly method for studying soil samples, are costly, however application of soil spectroscopy presents a more viable alternative.
Externí odkaz:
https://doaj.org/article/ec7bdc30158f4b2eb9f6f29a0de2eab1
Publikováno v:
Remote Sensing, Vol 7, Iss 7, Pp 8271-8299 (2015)
The growing availability of high-resolution satellite imagery provides an opportunity for identifying road objects. Most studies associated with road detection are scene-related and also based on the digital number of each pixel. Because images can p
Externí odkaz:
https://doaj.org/article/70ec7ace3991496ea88ca2168eaedec2