scholarly journals The contribution of remote sensing in hydraulics and hydrology, analysis and evaluation of digital terrain model for flood risk mapping

2018 ◽  
Vol 39 (1) ◽  
pp. 17-26
Author(s):  
Faiza hassainia Bouzahar ◽  
Lahbaci Ouerdachi ◽  
Mahdi Keblouti ◽  
Akram Seddiki
Keyword(s):  
Remote Sensing ◽  
Spatial Analysis ◽  
Flood Risk ◽  
Digital Terrain Model ◽  
Risk Map ◽  
Terrain Model ◽  
Digital Terrain ◽  
Wetland Biodiversity ◽  
Adopted Model ◽  
Flood Risk Map

AbstractThe study of flood risk involves the knowledge of the spatial variability in the characteristics of the vegetation cover, terrain, climate and changes induced by the intervention of humans in watersheds. The increased needs of the actors in land management mean that static maps no longer meet the requirements of scientists and decision-makers. Access is needed to the data, methods and tools to produce complex maps in response to the different stages of risk evaluation and response. The availability of very high spatial resolution remote sensing data (VHSR) and digital terrain model (DTM) make it possible to detect objects close to human size and, therefore, is of interest for studying anthropogenic activities. The development of new methods and knowledge using detailed spatial data, coupled with the use of GIS, naturally becomes beneficial to the risks analysis. Indeed, the extraction of information from specific processes, such as vegetation indices, can be used as variables such as water heights, flow velocities, flow rates and submersion to predict the potential consequences of a flood. The functionalities of GIS for cartographic overlay and multi-criteria spatial analysis make it possible to identify the flood zones according to the level of risk from the flood, thus making it a useful decision-making tool.This study was carried out on the territory of watersheds in the Annaba region, East of Algeria. The choice was guided by the availability of data (satellites images, maps, hydrology, etc.) and hydrological specificities (proximity to an urban area). The adopted model is divided into two parts. The first part is to establish a methodology for the preservation of wetland biodiversity and the protection of urban areas against floods. Thanks to the multi-criteria spatial analysis and the functionalities of the GIS, we established a flood risk map for the watershed defined above. The result was satisfactory compared with the field reality. The second part of the model consisted of the integration of cadastral information with the flood risk map obtained in the first part of our research.The primary objective of this mapping is to contribute to the development of flood risk management plans (in the sense of risk reduction). The mapping stage also provides quantitative elements to more accurately assess the vulnerability of a territory.

scholarly journals The Petawawa Research Forest: Establishment of a remote sensing supersite

2019 ◽  
Vol 95 (03) ◽  
pp. 149-156 ◽  
Author(s):  
Joanne C. White ◽  
Hao Chen ◽  
Murray E. Woods ◽  
Brian Low ◽  
Sasha Nasonova
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
New Technologies ◽  
Open Data ◽  
Digital Terrain Model ◽  
Lessons Learned ◽  
Remotely Sensed Data ◽  
The Public ◽  
Terrain Model ◽  
Digital Terrain

The pace of technological change in forest inventory and monitoring over the past 50 years has been remarkable, largely asa result of the increased availability of various forms of remotely sensed data. Benchmarking sites, with the requisite refer-ence and baseline data for evaluating the capacities of new technologies, algorithms, and approaches, can be extremely valu-able for sparking innovation, as well as for enabling transparent and scientifically sound assessments of technologies, newdata streams, and associated information outcomes. Herein we describe the establishment of a remote sensing supersite atthe Petawawa Research Forest (PRF) in southern Ontario, Canada, and summarize the open access datasets that have beencompiled and made available to the public. The PRF is approximately 10 000 ha in size and represents a complex assemblageof tree species and forest structures. More than 1900 data records, including multiple airborne laser scanning datasets andassociated derivatives (i.e., digital terrain model, canopy height model), airborne imagery, satellite remote sensing timeseries, and ground plot data, among others, have been made openly available for download from Canada’s National ForestInformation System. We identify issues and present opportunities associated with the establishment of a remote sensingsupersite at the PRF, as well as share some of the lessons learned to foster the establishment and open data sharing for othernational and international remote sensing supersites. The PRF supersite can be accessed from the following link: https://opendata.nfis.org/mapserver/PRF.html .

scholarly journals USING REMOTE SENSING AND GIS TO CREATE GEOGRAPHICAL BASES FOR THEMATIC MAPS

2021 ◽  
Vol 26 (5) ◽  
pp. 119-125
Author(s):  
Oyunkhand Byamba ◽  
◽  
Elena L. Kasyanova ◽  
Keyword(s):  
Remote Sensing ◽  
Three Dimensional ◽  
Digital Terrain Model ◽  
Gis Technology ◽  
Gis And Remote Sensing ◽  
Terrain Model ◽  
Digital Terrain ◽  
Terrain Models ◽  
Triangulation Network ◽  
Eastern Mongolia

The development of science always depends on technological progress. Cartography is rapidly changing and developing with the introduction of new computer technologies, such as GIS and remote sensing of the Earth. Recently, there have been qualitatively new types of cartographic products, in particular 3D terrain models, which in cartography are becoming a universal, optimal and operational method for displaying terrain. The article discusses a method for creating a three-dimensional digital terrain model in the form of an irregular triangulation network based on SRTM data and GIS technology on the example of the Khenti aimag of Eastern Mongolia.

scholarly journals PLANNING HARVESTING OPERATIONS IN FOREST ENVIRONMENT: REMOTE SENSING FOR DECISION SUPPORT

2019 ◽  
Vol IV-3/W1 ◽  
pp. 33-40
Author(s):  
M. Piragnolo ◽  
S. Grigolato ◽  
F. Pirotti
Keyword(s):  
Remote Sensing ◽  
Laser Scanner ◽  
Ground Surface ◽  
Digital Terrain Model ◽  
Remote Sensing Data ◽  
Forest Environment ◽  
K Value ◽  
Terrain Model ◽  
Digital Terrain ◽  
Roughness Index

<p><strong>Abstract.</strong> The goal of this work is to assess a method for supporting decisions regarding identification of most suitable areas for two types of harvesting approaches in forestry: skyline vs. forwarder. The innovative aspect consists in simulating the choices done during the planning in forestry operations. To do so, remote sensing data from an aerial laser scanner were used to create a digital terrain model (DTM) of ground surface under vegetation cover. Features extracted from the DTM are used as input for several machine learning predictors. Features are slope, distance from nearest roadside, relative height from nearest roadside and roughness index. Training and validation is done using areas defined by experts in the study area. Results show a K value of almost 0.92 for the classifier with best results, random forest. Sensibility of each feature is assessed, showing that both distance and height difference from nearest road-side are more significant than overall DTM value.</p>

scholarly journals Mapping and Evaluation of Flood Risk Areas along Asa River using Remote Sensing and GIS Techniques

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Kamoru A Adeniran ◽  
Yinka A. Ottawale ◽  
Matthew S. Ogunshina
Keyword(s):  
Remote Sensing ◽  
Flood Risk ◽  
Phase 1 ◽  
Digital Terrain Model ◽  
Roughness Coefficient ◽  
Army Corps ◽  
Gis And Remote Sensing ◽  
Terrain Model ◽  
Geometric Data ◽  
Risk Areas

Flooding in Ilorin city has become a yearly occurrence. Mapping and evaluation of flood risk areas along Asa River in Ilorin metropolis was carried out using the Geographic Information System (GIS) and remote sensing. The technique used includes conversion of Digital Terrain Model (DTM) to Triangulated Irregular Network (TIN) format. The geometric data was obtained from TIN through the use of United States Army Corps of Engineers, Hydrologic Engineering Centre, Geo River Analysis System (USACE HEC-geoRAS) in GIS. The obtained geometric data, Manning’s roughness coefficient (n), Expansion and contraction coefficient values and steady flow data of the River were used in HEC-RAS. The n values of 0.035, 0.016 and 0.02 were used for the channel, 0.045, 0.016 and 0.03 were used for the overbank and 0.2 was used for the bridges. Contraction and expansion co efficient value of 0.1 and 0.3 were used for channel and 0.3 and 0.5 were used for the bridges. Gumbel equation was used to estimate the flow for return period of 10, 50 and 100 years and the values of 155.13, 213.44 and 221.43 m3/s were obtained respectively. Delineated map was then compared with TIN terrain model to generate inundation map. The map revealed that some areas in Ilorin such as Coca-Cola Road, Baba Ode, Unity road, Obo Road, Taiwo-Isale, Amilengbe, Isale Koko, Mubo Phase 1, Mubo Phase 11, Royal Valley and Akerebiata prone to flood disasters. Estimated maximum top width for inundated area along the river ranges from 900.74 to 2375.11m.Keywords:-GIS, River Asa, DEM, Flood risk, HEC-RAS, Ground slope

Automatic generation of a digital terrain model from «Resurs-P» stereo «fortuitous» image pair

2017 ◽  
Vol 928 (10) ◽  
pp. 50-57
Author(s):  
N.E. Zharova ◽  
A.V. Bekenov ◽  
Aleksandr Chibunichev
Keyword(s):  
Remote Sensing ◽  
Digital Terrain Model ◽  
Automatic Generation ◽  
Image Pair ◽  
Digital Terrain Models ◽  
Terrain Model ◽  
Digital Terrain ◽  
Terrain Models ◽  
Voronezh Region ◽  
Imagery Data

Since the end of 2016 the imagery data from the Russian remote sensing satellites including Resurs-P spacecrafts have become commercially available in Russia, the CIS and far abroad. In this article we consider the possibility of automatic generation of digital terrain models using a stereo “fortuitous” image pair derived from two different Resurs-P spacecrafts. For the analysis we used two different date panchromatic images of the same area of Voronezh region in Russia. The images were obtained by the Geoton-L1 sensor of two different spacecrafts

scholarly journals EMERGENCY RESCUE MANAGEMENT SUPPORTED BY UAV REMOTE SENSING DATA

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 563-567 ◽  
Author(s):  
B. Weintrit ◽  
K. Bakuła ◽  
M. Jędryka ◽  
W. Bijak ◽  
W. Ostrowski ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Emergency Services ◽  
Digital Terrain Model ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Emergency Rescue ◽  
Terrain Model ◽  
Digital Terrain ◽  
Short Time ◽  
Source Of Information

<p><strong>Abstract.</strong> In the proposed SAFEDAM system, aerial and satellite-based information is used for the monitoring of river bodies, flood monitoring during the event, and for post-disaster damage assessment. UAV constitute a valuable source of information about the current situation in the field during the operation of emergency services. Time is crucial, and the basic assumption to use UAV remote sensing data is to make them available immediately after landing. Therefore, the approach of automatic orthomosaics created based on the exterior orientation of the transmitted images using direct georeference was selected instead of sophisticated automatic on-the-fly image-matching and georeferencing. The article conveys the justification for selecting this option in order to process orthomosaics with lower localisation accuracy in a short time. The developed algorithm takes into account the elements of exterior and interior orientation of the camera as well as the digital terrain model. The evaluation of the orthomosaic was conducted based on theorthophoto created in post-processing. Thanks to the approach used, images from the platform are available in the near real time on the screen of the interventional mode of the SAFEDAM system and are an extremely valuable and informative source of data. The system also integrates tools, which support the management of the action and prepares site documentation.</p>

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