scholarly journals Bathymetry Time Series Using High Spatial Resolution Satellite Images

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 531 ◽  
Author(s):  
Manuel Erena ◽  
José A. Domínguez ◽  
Joaquín F. Atenza ◽  
Sandra García-Galiano ◽  
Juan Soria ◽  
...  
Keyword(s):  
High Precision ◽  
Spatial Resolution ◽  
Satellite Images ◽  
Environmental Variability ◽  
High Spatial Resolution ◽  
Numerical Models ◽  
Three Dimensional ◽  
Satellite System ◽  
Precision Data ◽  
Mar Menor

The use of the new generation of remote sensors, such as echo sounders and Global Navigation Satellite System (GNSS) receivers with differential correction installed in a drone, allows the acquisition of high-precision data in areas of shallow water, as in the case of the channel of the Encañizadas in the Mar Menor lagoon. This high precision information is the first step to develop the methodology to monitor the bathymetry of the Mar Menor channels. The use of high spatial resolution satellite images is the solution for monitoring many hydrological changes and it is the basis of the three-dimensional (3D) numerical models used to study transport over time, environmental variability, and water ecosystem complexity.

scholarly journals The developement of red mud flood environmental information system and the methodology for the spatial analysis of the degraded area

2015 ◽  
Vol 9 (1) ◽  
pp. 1-11
Author(s):  
Gábor Bakó ◽  
Gábor Kovács ◽  
Zsolt Molnár ◽  
Judit Kirisics ◽  
Eszter Góber ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Red Mud ◽  
High Spatial Resolution ◽  
Three Dimensional ◽  
Environmental Information ◽  
Evaluation Methodology ◽  
Aerial Photogrammetry ◽  
Impact Area ◽  
The Impact

The red mud disaster occurred on 4th October 2010 in Hungary has raised the necessity of rapid intervention and drew attention to the long-term monitoring of such threat. Both the condition assessment and the change monitoring indispensably required the prompt and detailed spatial survey of the impact area. It was conducted by several research groups - independently - with different recent surveying methods. The high spatial resolution multispectral aerial photogrammetry is the spatially detailed (high resolution) and accurate type of remote sensing. The hyperspectral remote sensing provides more information about material quality of pollutants, with less spatial details and lower spatial accuracy, while LIDAR ensures the three-dimensional shape and terrain models. The article focuses on the high spatial resolution, multispectral electrooptical method and the evaluation methodology of the deriving high spatial resolution ortho image map, presenting the derived environmental information database

scholarly journals Insights into (U)HP metamorphism of the Western Gneiss Region, Norway: A high-spatial resolution and high-precision zircon study

2015 ◽  
Vol 414 ◽  
pp. 138-155 ◽  
Author(s):  
Joel W. DesOrmeau ◽  
Stacia M. Gordon ◽  
Andrew R.C. Kylander-Clark ◽  
Bradley R. Hacker ◽  
Samuel A. Bowring ◽  
...  
Keyword(s):  
High Precision ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Western Gneiss Region ◽  
Hp Metamorphism

scholarly journals Mapping the Mangrove Forest Canopy Using Spectral Unmixing of Very High Spatial Resolution Satellite Images

2019 ◽  
Vol 11 (3) ◽  
pp. 367 ◽  
Author(s):  
Florent Taureau ◽  
Marc Robin ◽  
Christophe Proisy ◽  
François Fromard ◽  
Daniel Imbert ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Forest Structure ◽  
Mangrove Forest ◽  
Satellite Images ◽  
Forest Canopy ◽  
High Spatial Resolution ◽  
Spectral Unmixing ◽  
Very High Spatial Resolution ◽  
Very High ◽  
Mangrove Structure

Despite the low tree diversity and scarcity of the understory vegetation, the high morphological plasticity of mangrove trees induces, at the stand level, a very large variability of forest structures that need to be mapped for assessing the functioning of such complex ecosystems. Fully constrained linear spectral unmixing (FCLSU) of very high spatial resolution (VHSR) multispectral images was tested to fine-scale map mangrove zonations in terms of horizontal variation of forest structure. The study was carried out on three Pleiades-1A satellite images covering French island territories located in the Atlantic, Indian, and Pacific Oceans, namely Guadeloupe, Mayotte, and New Caledonia archipelagos. In each image, FCLSU was trained from the delineation of areas exclusively related to four components including either pure vegetation, soil (ferns included), water, or shadows. It was then applied to the whole mangrove cover imaged for each island and yielded the respective contributions of those four components for each image pixel. On the forest stand scale, the results interestingly indicated a close correlation between FCLSU-derived vegetation fractions and canopy closure estimated from hemispherical photographs (R2 = 0.95) and a weak relation with the Normalized Difference Vegetation Index (R2 = 0.29). Classification of these fractions also offered the opportunity to detect and map horizontal patterns of mangrove structure in a given site. K-means classifications of fraction indeed showed a global view of mangrove structure organization in the three sites, complementary to the outputs obtained from spectral data analysis. Our findings suggest that the pixel intensity decomposition applied to VHSR multispectral satellite images can be a simple but valuable approach for (i) mangrove canopy monitoring and (ii) mangrove forest structure analysis in the perspective of assessing mangrove dynamics and productivity. As with Lidar-based surveys, these potential new mapping capabilities deserve further physically based interpretation of sunlight scattering mechanisms within forest canopy.

scholarly journals Estimating 2009–2017 Impervious Surface Change in Gwadar, Pakistan Using the HJ-1A/B Constellation, GF-1/2 Data, and the Random Forest Algorithm

2019 ◽  
Vol 8 (10) ◽  
pp. 443 ◽  
Author(s):  
Bian ◽  
Li ◽  
Zuo ◽  
Lei ◽  
Zhang ◽  
...  
Keyword(s):  
Random Forest ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Satellite Images ◽  
Reference Data ◽  
High Spatial Resolution ◽  
Impervious Surface ◽  
Urbanization Process ◽  
Rapid Urbanization

The China–Pakistan Economic Corridor (CPEC) is the flagship project of the Belt and Road Initiative. At the end of the CPEC, the Gwadar port on the Arabian Sea is being built quickly, providing an important economical route for the flow of Central Asia’s natural resources to the world. Gwadar city is in a rapid urbanization process and will be developed as a modern, world-class port city in the near future. Therefore, monitoring the urbanization process of Gwadar at both high spatial and temporal resolution is vital for its urban planning, city ecosystem management, and the sustainable development of CPEC. The impervious surface percentage (ISP) is an essential quantitative indicator for the assessment of urban development. Through the integration of remote sensing images and ISP estimation models, ISP can be routinely and periodically estimated. However, due to clouds’ influence and spatial–temporal resolution trade-offs in sensor design, it is difficult to estimate the ISP with both high spatial resolution and dense temporal frequency from only one satellite sensor. In recent years, China has launched a series of Earth resource satellites, such as the HJ (Huangjing, which means environment in Chinese)-1A/B constellation, showing great application potential for rapid Earth surface mapping. This study employs the Random Forest (RF) method for a long-term and fine-scale ISP estimation and analysis of the city of Gwadar, based on the density in temporal and multi-source Chinese satellite images. In the method, high spatial resolution ISP reference data partially covering Gwadar city was first extracted from the 1–2 meter (m) GF (GaoFen, which means high spatial resolution in Chinese)-1/2 fused images. An RF retrieval model was then built based on the training samples extracted from ISP reference data and multi-temporal 30-m HJ-1A/B satellite images. Lastly, the model was used to generate the 30-m time series ISP from 2009 to 2017 for the whole city area based on the HJ-1A/B images. Results showed that the mean absolute error of the estimated ISP was 6.1–8.1% and that the root mean square error (RMSE) of the estimation results was 12.82–15.03%, indicating the consistently high performance of the model. This study highlights the feasibility and potential of using multi-source Chinese satellite images and an RF model to generate long-term ISP estimations for monitoring the urbanization process of the key node city in the CPEC.

Chemical Nano-tomography of Self-assembled Ge-Si:Si(001) Islands from Quantitative High Resolution Transmission Electron Microscopy

2009 ◽  
Vol 1184 ◽  
Author(s):  
Luciano Andrey Montoro ◽  
Marina Leite ◽  
Daniel Biggemann ◽  
Fellipe Grillo Peternella ◽  
Kees Joost Batenburg ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
High Resolution ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Three Dimensional ◽  
Precise Knowledge ◽  
Transmission Electron ◽  
Self Consistent ◽  
Chemical Distribution

AbstractThe knowledge of composition and strain with high spatial resolution is highly important for the understanding of the chemical and electronic properties of alloyed nanostructures. Several applications require a precise knowledge of both composition and strain, which can only be extracted by self-consistent methodologies. Here, we demonstrate the use of a quantitative high resolution transmission electron microscopy (QHRTEM) technique to obtain two-dimensional (2D) projected chemical maps of epitaxially grown Ge-Si:Si(001) islands, with high spatial resolution, at different crystallographic orientations. By a combination of these data with an iterative simulation, it was possible infer the three-dimensional (3D) chemical arrangement on the strained Ge-Si:Si(001) islands, showing a four-fold chemical distribution which follows the nanocrystal shape/symmetry. This methodology can be applied for a large variety of strained crystalline systems, such as nanowires, epitaxial islands, quantum dots and wells, and partially relaxed heterostructures.

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