scholarly journals Transformation of different reaches of the Niida River (Japan) after extreme flood

2017 ◽  
Vol 19 (1) ◽  
pp. 75-87
Author(s):  
GOLOSOV Valentin ◽  
BOTAVIN Dmitry ◽  
KONOPLEV Alexei ◽  
WAKIYAMA Yoshifumi
Keyword(s):  
Satellite Images ◽  
Bank Erosion ◽  
River Channel ◽  
Lower Reach ◽  
High Resolution Satellite Images ◽  
Extreme Flood ◽  
Active Processes ◽  
Total Sedimentation ◽  
River Bottom ◽  
Floodplain Sedimentation

Extreme floods can have different effects on the river bottom relief depending on several factors. The geomorphological impact of the extreme flood occurring in the Niida River basin (Fukushima prefecture, Honshu inland, Japan) on the channels and river bottom of different reaches of the river is analyzed. High-resolution satellite images and field assessments were used for quantitative evaluation of river bottom transformation which mainly occurred in the lower reach of the Niida river. The lower reach of the Niida River was divided on three subzones according the channel gradient changes. Each sub-zones is correspond with the dominance of a certain type of channel (straight, meandering and wandering). It was found that bank erosion exceeded in- channel deposition in 1,7-2,7 times for all types of river channel in the low reach located within the coastal floodplain. However, floodplain sedimentation is the most active processes for the river sections with meandering and wandering types of the river channel. Floodplain sedimentation exceed bank-erosion in 2.2 times for river sections with the meandering type of channel and in 2.9 time for the river sections with wandering type of channel. It was found that bank erosion exceeded in- channel deposition in 1,7-2,7 times for all types of river channel in the low reach located within the coastal floodplain. However, floodplain sedimentation is the most active processes for the river sections with meandering and wandering types of the river channel. Floodplain sedimentation exceed bankerosion in 2.2 times for river sections with the meandering type of channel and in 2.9 time for the river sections with wandering type of channel. The bank erosion exceeds floodplain deposition in 1,2 times only within the river sections with straight type of channel. Total sedimentation (in-channel + floodplain) in 2.6 times higher than bank erosion in the lower reach of the Niida River after extreme flood event with probability 4-5%.

Organic and Trace Metal Pollution in the Sediments of the Kishon River (Israel) and Possible Influence on the Marine Environment

1993 ◽  
Vol 27 (7-8) ◽  
pp. 439-447 ◽  
Author(s):  
Y. Cohen ◽  
N. Kress ◽  
H. Hornung
Keyword(s):  
Trace Metals ◽  
Marine Environment ◽  
River System ◽  
River Channel ◽  
Disposal Site ◽  
Lower Reach ◽  
Deposition Area ◽  
Long Time ◽  
Water Disposal ◽  
Sediment Particles

The sediments of the lower reach of the Kishon river, its harbors and estuary, sampled in 1989-1991, were highly polluted by trace metals and petroleum derived compounds released by the adjacent industries. The contamination was highest in the sediment deposition area of the Kishon fishing harbor and decreased seaward. River-borne pollution was also evident in Haifa Bay opposite the Kishon estuary. Contaminants trapped in the sediments of the lower Kishon river system can reach the marine environment through bottom transport of sediment particles and also as a result of disposal at sea of dredge spoils from the river channel and harbors. On the basis of the findings of the study, it was recommended to stop the long-time practice of dumping dredge spoils from the Kishon fishing harbor into the relatively clean Haifa Bay and to use instead an offshore deep water disposal site.

3D NUMERICAL SIMULATION OF ALTERNATE BAR FORMATION AND RIVER CHANNEL PROCESS WITH BANK EROSION

2018 ◽  
Vol 74 (5) ◽  
pp. I_991-I_996
Author(s):  
Shinichiro ONDA ◽  
Masaharu YASUBA ◽  
Takashi HOSODA
Keyword(s):  
Numerical Simulation ◽  
Bank Erosion ◽  
River Channel ◽  
3D Numerical Simulation ◽  
Channel Process ◽  
Bar Formation

scholarly journals Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images

2019 ◽  
Vol 75 ◽  
pp. 01003 ◽  
Author(s):  
Egor Dmitriev ◽  
Vladimir Kozoderov ◽  
Sergey Donskoy ◽  
Petr Melnik ◽  
Anton Sokolov
Keyword(s):  
Satellite Images ◽  
High Spatial Resolution ◽  
Texture Features ◽  
Forest Species ◽  
Effective Learning ◽  
Estimated Parameters ◽  
High Resolution Satellite Images ◽  
Automated Processing ◽  
Tver Region ◽  
Remote Sensing Methods

A method for automated processing high spatial resolution satellite images is proposed to retrieve inventory and bioproductivity parameters of forest stands. The method includes effective learning classifiers, inverse modeling, and regression modeling of the estimated parameters. Spectral and texture features are used to classify forest species. The results of test experiments for the selected area of Savvatievskoe forestry (Russia, Tver region) are presented. Accuracy estimates obtained using ground-based measurements demonstrate the effectiveness of using the proposed techniques to automate the process of updating information for the State Forest Inventory program of Russia.

SateLoc: A Virtual Fingerprinting Approach to Outdoor LoRa Localization Using Satellite Images

2021 ◽  
Vol 17 (4) ◽  
pp. 1-28
Author(s):  
Yuxiang Lin ◽  
Wei Dong ◽  
Yi Gao ◽  
Tao Gu
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Satellite Images ◽  
Low Cost ◽  
Tracking Error ◽  
Location Based Services ◽  
Distance Constraint ◽  
Combination Strategy ◽  
Land Cover Types ◽  
High Resolution Satellite Images

With the increasing relevance of the Internet of Things and large-scale location-based services, LoRa localization has been attractive due to its low-cost, low-power, and long-range properties. However, existing localization approaches based on received signal strength indicators are either easily affected by signal fading of different land-cover types or labor intensive. In this work, we propose SateLoc, a LoRa localization system that utilizes satellite images to generate virtual fingerprints. Specifically, SateLoc first uses high-resolution satellite images to identify land-cover types. With the path loss parameters of each land-cover type, SateLoc can automatically generate a virtual fingerprinting map for each gateway. We then propose a novel multi-gateway combination strategy, which is weighted by the environmental interference of each gateway, to produce a joint likelihood distribution for localization and tracking. We implement SateLoc with commercial LoRa devices without any hardware modification, and evaluate its performance in a 227,500-m urban area. Experimental results show that SateLoc achieves a median localization error of 43.5 m, improving more than 50% compared to state-of-the-art model-based approaches. Moreover, SateLoc can achieve a median tracking error of 37.9 m with the distance constraint of adjacent estimated locations. More importantly, compared to fingerprinting-based approaches, SateLoc does not require the labor-intensive fingerprint acquisition process.

An Approach for Building Rooftop Border Extraction from Very High-Resolution Satellite Images

2021 ◽  
pp. 1-11
Author(s):  
Yasser Mostafa ◽  
Mahmoud Nokrashy O. Ali ◽  
Faten Mostafa ◽  
Mohamed Yousef
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
High Resolution Satellite Images ◽  
Very High

scholarly journals Accelerate disaster risk mapping using an automated zonal change detection model for loss estimation and recovery: a flood case study

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Ali Amasha
Keyword(s):  
Change Detection ◽  
Satellite Images ◽  
Flash Flood ◽  
Disaster Risk ◽  
Loss Estimation ◽  
Risk Mapping ◽  
Detection Model ◽  
Applied Model ◽  
High Resolution Satellite Images ◽  
Before And After

Abstract Background The flash flood still constitutes one of the major natural meteorological disasters harmfully threatening local communities, that creates life losses and destroying infrastructures. The severity and magnitude of disasters always reflected from the size of impacts. Most of the conventional research models related to flooding vulnerability are focusing on hydro-meteorological and morphometric measurements. It, however, requires quick estimate of the flood losses and assess the severity using reliable information. An automated zonal change detection model applied, using two high-resolution satellite images dated 2009 and 2011 coupled with LU/LC GIS layer, on western El-Arish City, downstream of Wadi El-Arish basin. The model enabled to estimate the severity of a past flood incident in 2010. Results The model calculated the total changes based on the before and after satellite images based on pixel-by-pixel comparison. The estimated direct-damages nearly 32,951 m2 of the total mapped LU/LC classes; (e.g., 11,407 m2 as 3.17% of the cultivated lands; 6031 m2 as 7.22% of the built-up areas and 4040 m2 as 3.62% of the paved roads network). The estimated cost of losses, in 2010 economic prices for the selected three LU/LC classes, is nearly 25 million USD, for the cultivation fruits and olives trees, ~ 4 million USD for built-up areas and ~ 1 million USD for paved roads network. Conclusion The disasters’ damage and loss estimation process takes many detailed data, longtime, and costed as well. The applied model accelerates the disaster risk mapping that provides an informative support for loss estimation. Therefore, decision-makers and professionals need to apply this model for quick the disaster risks management and recovery.

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