scholarly journals Multi-Temporal Image Analysis for Fluvial Morphological Characterization with Application to Albanian Rivers

2018 ◽  
Vol 7 (8) ◽  
pp. 314 ◽  
Author(s):  
Daniele Spada ◽  
Paolo Molinari ◽  
Walter Bertoldi ◽  
Alfonso Vitti ◽  
Guido Zolezzi
Keyword(s):  
Automatic Monitoring ◽  
Morphological Characterization ◽  
Data Availability ◽  
River Channels ◽  
Automatic Monitoring System ◽  
Digital Elevation ◽  
Multi Temporal ◽  
Surface Subdivision ◽  
Elevation Model ◽  
Sentinel 2

A procedure for the characterization of the temporal evolution of river morphology is presented. Wet and active river channels are obtained from the processing of imagery datasets. Information about channel widths and active channel surface subdivision in water, vegetation and gravel coverage classes are evaluated along with channel centerline lengths and sinuosity indices. The analysis is carried out on a series of optical remotely-sensed imagery acquired by different satellite missions during the time period between 1968 and 2017. Data from the CORONA, LANDSAT and Sentinel-2 missions were considered. Besides satellite imagery, a digital elevation model and aerial ortho-photos were also used. The procedure was applied to three, highly dynamic, Albanian rivers: Shkumbin, Seman and Vjosë, showing a high potential for application in contexts with limitations in ground data availability. The results of the procedure were assessed against reference data produced by means of expert interpretation of a reference set of river reaches. The results differ from reference values by just a few percentage points (<6%). The time evolution of hydromorphological parameters is well characterized, and the results support the design of future studies aimed at the understanding of the relations between climatic and anthropogenic controls and the response of river morphological trajectories. Moreover, the high spatial and temporal resolution of the Sentinel-2 mission motivates the development of an automatic monitoring system based on a rolling application of the defined procedure.

scholarly journals An Improved Method Constructing 3D River Channel for Flood Modeling

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 403 ◽  
Author(s):  
Pengbo Hu ◽  
Jingming Hou ◽  
Zaixing Zhi ◽  
Bingyao Li ◽  
Kaihua Guo
Keyword(s):  
High Resolution ◽  
River Channel ◽  
Hydrodynamic Process ◽  
River Channels ◽  
Section Data ◽  
Terrain Model ◽  
Digital Elevation ◽  
Hydrodynamic Processes ◽  
Hermite Spline ◽  
Elevation Model

The high-resolution topography is very crucial to investigate the hydrological and hydrodynamic process. To resolve the deficiency problem of high resolution terrain data in rivers, the Quartic Hermite Spline with Parameter (QHSP) method constructing the river channel terrain based on the limited cross-section data is presented. The proposed method is able to not only improve the reliability of the constructed river terrain, but also avoid the numerical oscillations caused by the existing constructing approach, e.g., the Cubic Hermite Spline (CHS) method. The performance of the proposed QHSP method is validated against two benchmark tests. Comparing the constructed river terrains, the QHSP method can improve the accuracy by at least 15%. For the simulated flood process, the QHSP method could reproduce more acceptable modeling results as well, e.g., in Wangmaogou catchment, the numerical model applying the Digital Elevation Model (DEM) produced by the QHSP method could increase the reliability by 18.5% higher than that of CHS method. It is indicated that the QHSP method is more reliable for river terrain model construction than the CHS and is a more reasonable tool investigating the hydrodynamic processes in river channels lacking of high resolution topography data.

scholarly journals Potential of Sentinel-2 Images for Estimating of Soil Resistivity over Agricultural Fields

Proceedings ◽  
2019 ◽  
Vol 24 (1) ◽  
pp. 18
Author(s):  
Remy Fieuzal ◽  
Vincent Bustillo ◽  
David Collado ◽  
Gerard Dedieu
Keyword(s):  
Electrical Resistivity ◽  
Near Infrared ◽  
Soil Layers ◽  
Digital Elevation ◽  
Combined Use ◽  
Input Variables ◽  
Elevation Model ◽  
High Level ◽  
Sentinel 2 ◽  
Soil Electrical Resistivity

The aim of this study is to assess the possibilities of the VNIR (Visible and Near InfraRed) and SWIR (Short Wavelength InfraRed) satellite data for estimating intra-plot patterns of soil electrical resistivity consistent with ground measurements. The methodology is based on optical reflectances that constitute the input variables of random forest, alone or in combination with parameters derived from a digital elevation model (DEM). Over a field located in southwestern France, the results show high level of accuracy for the 0–50 and 0–100 cm soil layers (with R² of 0.69 and 0.59, and a relative RMSE of 18% and 16%, respectively), the performances being lower for the 0–170 cm layer (R² of 0.39, relative RMSE of 20%). The combined use of optical reflectances with parameters derived from the DEM slightly improves the performances, whatever the considered layer. The influence of each reflectance on soil electrical resistivity estimates is finally analyzed, showing that the wavelengths acquired in the SWIR have a relative higher importance than VNIR reflectance.

scholarly journals CARTOGRAPHY OF MOROCCAN ARGAN TREE USING COMBINED OPTICAL AND SAR IMAGERY INTEGRATED WITH DIGITAL ELEVATION MODEL

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 211-217
Author(s):  
E. Elmoussaoui ◽  
A. Moumni ◽  
A. Lahrouni
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Digital Elevation Model ◽  
Optical Data ◽  
Support Vector ◽  
Ground Truth Data ◽  
Argan Tree ◽  
Digital Elevation ◽  
Elevation Model ◽  
Sentinel 2

Abstract. Forest tree species mapping became easier due to the global availability of high spatio-temporal resolution images acquired from multiple sensors. Such data can lead to better forest resources management. Machine-learning pixel based analysis was performed to multi-spectral Sentinel-2 and Synthetic Aperture Radar Sentinel-1 time series integrated with Digital Elevation Model acquired over Argan forest of Essaouira province, Morocco. The argan tree constitutes a fundamental resource for the populations of this arid area of Morocco. This research aims to use the potential of the combination of multi-sensor data to detect, map and identify argan tree from other forest species using three Machine Learning algorithms: Support Vector Machine (SVM), Maximum Likelihood (ML) and Artificial Neural Networks (ANN). The exploited datasets included Sentinel-1 (S1), Sentinel-2 (S2) time series, Shuttle Radar Topographic Missing Digital Elevation Model (DEM) layer and Ground truth data. We tested several sets of scenarios, including single S1 derived features, single S2 time series and combined S1 and S2 derived layers with DEM scene acquisition. The best results (overall accuracy OA and Kappa coefficient K) obtained from time series of optical data (NDVI): OA = 86.87%, K = 0.84, from time series of SAR data (VV+VH/VV): OA = 45.90%, K = 0.36, from the combination of optical and SAR time series (NDVI+VH+DEM): OA = 93.01%, K = 0.914, and from the fusion of optical time series and DEM layer (NDVI+DEM): OA = 93.25%, K = 0.91. These results indicate that single-sensor (S2) integrated with the DEM layer led us to obtain the highest classification results.

scholarly journals Quantitative Analysis of Different Environmental Factor Impacts on Land Cover in Nisos Elafonisos, Crete, Greece

2020 ◽  
Vol 17 (18) ◽  
pp. 6437
Author(s):  
Mohamed Elhag ◽  
Silvena Boteva
Keyword(s):  
Land Use ◽  
Environmental Factors ◽  
Land Cover ◽  
Remote Sensing Data ◽  
Mediterranean Ecosystems ◽  
Land Use Land Cover ◽  
Routine Work ◽  
Digital Elevation ◽  
Elevation Model ◽  
Sentinel 2

Land Cover monitoring is an essential task for a better understanding of the ecosystem’s dynamicity and complexity. The availability of Remote Sensing data improved the Land Use Land Cover mapping as it is routine work in ecosystem management. The complexity of the Mediterranean ecosystems involves a complexity of the surrounding environmental factors. An attempt to quantitatively investigate the interdependencies between land covers and affected environmental factors was conducted in Nisos Elafonisos to represent diverse and fragile coastal Mediterranean ecosystems. Sentinel-2 (MSI) sensor and ASTER Digital Elevation Model (DEM) data were used to classify the LULC as well as to draw different vegetation conditions over the designated study area. DEM derivatives were conducted and incorporated. The developed methodology is intended to assess the land use land cover for different practices under the present environmental condition of Nisos Elafonisos. Supervised classification resulted in six different land cover clusters and was tested against three different environmental clusters. The findings of the current research pointed out that the environmental variables are independent and there is a vertical distribution of the vegetation according to altitude.

scholarly journals AN IMPROVED DEM CONSTRUCTION METHOD FOR MUDFLATS BASED ON BJ-1 SMALL SATELLITE IMAGES: A CASE STUDY ON BOHAI BAY

2018 ◽  
Vol XLII-3 ◽  
pp. 1871-1878 ◽  
Author(s):  
D. Wu ◽  
Y. Du ◽  
F. Su ◽  
W. Huang ◽  
L. Zhang
Keyword(s):  
Satellite Images ◽  
Evaluation Model ◽  
Ocean Tide ◽  
Bohai Bay ◽  
Small Satellite ◽  
Detection Model ◽  
Digital Elevation ◽  
Wide Range ◽  
Multi Temporal ◽  
Elevation Model

The topographic measurement of muddy tidal flat is restricted by the difficulty of access to the complex, wide-range and dynamic tidal conditions. Then the waterline detection method (WDM) has the potential to investigate the morph-dynamics quantitatively by utilizing large archives of satellite images. The study explores the potential for using WDM with BJ-1 small satellite images to construct a digital elevation model (DEM) of a wide and grading mudflat. Three major conclusions of the study are as follows: (1) A new intelligent correlating model of waterline detection considering different tidal stages and local geographic conditions was explored. With this correlative algorithm waterline detection model, a series of waterlines were extracted from multi-temporal remotely sensing images collected over the period of a year. The model proved to detect waterlines more efficiently and exactly. (2) The spatial structure of elevation superimposing on the points of waterlines was firstly constructed and a more accurate hydrodynamic ocean tide grid model was used. By the newly constructed abnormal hydrology evaluation model, a more reasonable and reliable set of waterline points was acquired to construct a smoother TIN and GRID DEM. (3) DEM maps of Bohai Bay, with a spatial resolution of about 30&amp;thinsp;m and height accuracy of about 0.35&amp;thinsp;m considering LiDAR and 0.19&amp;thinsp;m considering RTK surveying were constructed over an area of about 266&amp;thinsp;km<sup>2</sup>. Results show that remote sensing research in extremely turbid estuaries and tidal areas is possible and is an effective tool for monitoring the tidal flats.

On the applicability of ICESat-2 and off-nadir SkySAT satellite datasets for the estimation of water storage in medium and small reservoirs at the global scale

2020 ◽  
Author(s):  
Gennadii Donchyts ◽  
Dirk Eilander ◽  
Antonio Moreno-Rodenas ◽  
Maarten Pronk ◽  
Samapriya Roy ◽  
...  
Keyword(s):  
Water Management ◽  
Water Storage ◽  
Global Scale ◽  
Water Dynamics ◽  
Landsat 8 ◽  
Small Reservoirs ◽  
Digital Elevation ◽  
Elevation Model ◽  
And Storage ◽  
Sentinel 2

&lt;p&gt;Accurate and timely information on water storage changes in medium and small size reservoirs is needed for better water management and understanding of water dynamics on a global scale in general. While changes in surface water extent in these reservoirs can be monitored using satellite missions such as Landsat 8, Sentinel-1, and Sentinel-2, the information on water level and storage dynamics on a global scale is still missing. However, for most reservoirs, these storage changes can be estimated given that an accurate digital elevation model (DEM) is available for a dynamic part of the reservoir - the area covered between the minimum and maximum extents of the reservoir. In this research, we will investigate the applicability of data measured by the ICESat-2 lidar sensor and the off-nadir satellite imagery acquired by Planet&amp;#8217;s SkySAT satellites and will evaluate how valuable these datasets are to estimate water storage changes in medium and small size reservoirs.&lt;/p&gt;

Multidisciplinary approach to assess landslide hazards in alpine environment: the geomorphological map of the upper Maira Valley (Western Alps, Italy).

2020 ◽  
Author(s):  
Mauro Bonasera ◽  
Alessandro Petroccia ◽  
Fabiola Caso ◽  
Sara Nerone ◽  
Michele Morelli
Keyword(s):  
Western Alps ◽  
Local Analysis ◽  
Rock Falls ◽  
Stratigraphic Sequence ◽  
Aerial Photos ◽  
Digital Elevation ◽  
Multi Temporal ◽  
Gis Environment ◽  
Elevation Model ◽  
Cover Thickness

&lt;p&gt;The landscape evolution of the U-shaped Maira Valley was mainly led by glacial dynamics during Pleistocene. The Holocene linear fluvial erosion creates higher steepness slopes in a narrow valley in which gravitational phenomena involves buildings and facilities of Acceglio municipality (Piedmont, Italy). A geomorphological survey in an unmapped area of about 12 km&lt;sup&gt;2&lt;/sup&gt; has been carried out and a new map at scale 1:10000 has been realised. In order to improve the accuracy of fieldwork data, several multidisciplinary techniques have been investigated. The landforms and slope evolution were analysed by using a 5-meters resolution ARPA Digital Elevation Model (DEM) in GIS environment. Discontinuities and geomorphological features were recognized and mapped observing aerial-photos provided by Regione Piemonte. Multi-temporal dataset of orthophotos were useful to examine the river pattern behaviour coupled with interdigitating polygenic fan deposition. The stratigraphic sequence knowledge was achieved using boreholes, inclinometers and piezometers evaluating eventual detrital cover thickness. Detailed field investigations allowed to understand the relationship between structural geology and landslide evolution, in particular concerning several detachment zones characterising the slope overlooking Acceglio town. In the uppermost range of that slope, the fracturation is intense and influences the rock-falls and rock avalanches trigger, whilst debris flows were identified throughout the detected area associated with a homogeneous presence of weathered cover. Widespread accumulation bodies suggest how avalanche and debris flow occurrences have affected Acceglio human activities, testified by historical archives documents as well. In the past, several trial to mitigate these risks were performed through engineering activities which could be refined and implemented with further local analysis on landslide susceptibility. Research on this issue, in addition to having a great scientific interest, can provide essential tools for upper Maira Valley Administrations, being the main available support for an appropriate urban planning.&lt;/p&gt;

scholarly journals Review article: Detection of inundation areas due to the 2015 Kanto and Tohoku torrential rain in Japan based on multi-temporal ALOS-2 imagery

2018 ◽  
Vol 18 (7) ◽  
pp. 1905-1918 ◽  
Author(s):  
Wen Liu ◽  
Fumio Yamazaki
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Heavy Rain ◽  
Geospatial Information ◽  
Torrential Rain ◽  
Digital Elevation ◽  
Multi Temporal ◽  
Land Cover Map ◽  
Intensity Images ◽  
Elevation Model

Abstract. Torrential rain triggered by two typhoons hit the Kanto and Tohoku regions of Japan from 9 to 11 September 2015. Due to the record-breaking amount of rainfall, several riverbanks were overflowed and destroyed, causing floods over wide areas. The PALSAR-2 sensor on board the ALOS-2 satellite engaged in emergency observations of the affected areas during and after the heavy rain. Two pre-event and three co-event PALSAR-2 images were employed in this study to extract flooded areas in the city of Joso, Ibaraki Prefecture. The backscattering coefficient of the river water was investigated first using the PALSAR-2 intensity images and a land-cover map with a 10 m resolution. The inundation areas were then extracted by setting threshold values for backscattering from water surfaces in the three temporal synthetic aperture radar (SAR) images. The extracted results were modified by considering the land cover and a digital elevation model (DEM). Next, the inundated built-up urban areas were extracted from the changes in SAR backscattering. The results were finally compared with those from visual inspections of airborne imagery by the Geospatial Information Authority of Japan (GSI), and more than 85 % of the maximum inundation areas were extracted successfully.

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