Urban Flood Mapping

2017 ◽  
Author(s):  
Indra Riyanto ◽  
Lestari Margatama

The recent degradation of environment quality becomes the prime cause of the recent occurrence of natural disasters. It also contributes in the increase of the area that is prone to natural disasters. Flood history data in Jakarta shows that flood occurred mainly during rainy season around January – February each year, but the flood area varies each year. This research is intended to map the flood potential area in DKI Jakarta by segmenting the Digital Elevation Model data. The data used in this research is contour data obtained from DPP–DKI with the resolution of 1 m. The data processing involved in this research is extracting the surface elevation data from the DEM, overlaying the river map of Jakarta with the elevation data. Subsequently, the data is then segmented using watershed segmentation method. The concept of watersheds is based on visualizing an image in three dimensions: two spatial coordinates versus gray levels, in which there are two specific points; that are points belonging to a regional minimum and points at which a drop of water, if placed at the location of any of those points, would fall with certainty to a single minimum. For a particular regional minimum, the set of points satisfying the latter condition is called the catchments basin or watershed of that minimum, while the points satisfying condition form more than one minima are termed divide lines or watershed lines. The objective of this segmentation is to find the watershed lines of the DEM image. The expected result of the research is the flood potential area information, especially along the Ciliwung river in DKI Jakarta.

2017 ◽  
Author(s):  
Indra Riyanto ◽  
Lestari Margatama

The recent degradation of environment quality becomes the prime cause of the recent occurrence of natural disasters. It also contributes in the increase of the area that is prone to natural disasters. Flood history data in Jakarta shows that flood occurred mainly during rainy season around January – February each year, but the flood area varies each year. This research is intended to map the flood potential area in DKI Jakarta by segmenting the Digital Elevation Model data. The data used in this research is contour data obtained from DPP–DKI with the resolution of 1 m. The data processing involved in this research is extracting the surface elevation data from the DEM, overlaying the river map of Jakarta with the elevation data. Subsequently, the data is then segmented using watershed segmentation method. The concept of watersheds is based on visualizing an image in three dimensions: two spatial coordinates versus gray levels, in which there are two specific points; that are points belonging to a regional minimum and points at which a drop of water, if placed at the location of any of those points, would fall with certainty to a single minimum. For a particular regional minimum, the set of points satisfying the latter condition is called the catchments basin or watershed of that minimum, while the points satisfying condition form more than one minima are termed divide lines or watershed lines. The objective of this segmentation is to find the watershed lines of the DEM image. The expected result of the research is the flood potential area information, especially along the Ciliwung river in DKI Jakarta.


Author(s):  
Indra Riyanto ◽  
Lestari Margatama ◽  
S. Samsinar ◽  
Babag Purbantoro ◽  
Luhur Bayuaji ◽  
...  

Degradation of environment quality is currently the prime cause of the recent occurrence of natural disasters; it also contributes in the increase of the area that is prone to natural disasters. This research is aimed to map the potential of areas around Pesanggrahan river in DKI Jakarta by segmenting the Digital Elevation Model derived from LIDAR data. The objective of this segmentation is to find the watershed lines of the DEM image. Data processing in this research is using LIDAR data which take the ground surface data, which is overlaid with Jakarta river map and subsequently, the data is then segmented the image. The expected result of the research is the flood potential area information, especially along the Pesanggrahan river in South Jakarta.


2021 ◽  
Vol 13 (14) ◽  
pp. 2810
Author(s):  
Joanna Gudowicz ◽  
Renata Paluszkiewicz

The rapid development of remote sensing technology for obtaining high-resolution digital elevation models (DEMs) in recent years has made them more and more widely available and has allowed them to be used for morphometric assessment of concave landforms, such as valleys, gullies, glacial cirques, sinkholes, craters, and others. The aim of this study was to develop a geographic information systems (GIS) toolbox for the automatic extraction of 26 morphometric characteristics, which include the geometry, hypsometry, and volume of concave landforms. The Morphometry Assessment Tools (MAT) toolbox in the ArcGIS software was developed. The required input data are a digital elevation model and the form boundary as a vector layer. The method was successfully tested on an example of 21 erosion-denudation valleys located in the young glacial area of northwest Poland. Calculations were based on elevation data collected in the field and LiDAR data. The results obtained with the tool showed differences in the assessment of the volume parameter at the average level of 12%, when comparing the field data and LiDAR data. The algorithm can also be applied to other types of concave forms, as well as being based on other DEM data sources, which makes it a universal tool for morphometric evaluation.


2011 ◽  
Vol 8 (5) ◽  
pp. 8865-8901
Author(s):  
P. Noel ◽  
A. N. Rousseau ◽  
C. Paniconi

Abstract. Subdivision of catchment into appropriate hydrological units is essential to represent rainfall-runoff processes in hydrological modelling. The commonest units used for this purpose are hillslopes (e.g. Fan and Bras, 1998; Troch et al., 2003). Hillslope width functions can therefore be utilised as one-dimensional representation of three-dimensional landscapes by introducing profile curvatures and plan shapes. An algorithm was developed to delineate and extract hillslopes and hillslope width functions by introducing a new approach to calculate an average profile curvature and plan shape. This allows the algorithm to be independent of digital elevation model resolution and to associate hillslopes to nine elementary landscapes according to Dikau (1989). This algortihm was tested on two flat and steep catchments of the province of Quebec, Canada. Results showed great area coverage for hillslope width function over individual hillslopes and entire watershed.


Author(s):  
Guizhi Wang

National administration of surveying, mapping and geoinformation started to launch the project of national fundamental geographic information database dynamic update in 2012. Among them, the 1:50000 database was updated once a year, furthermore the 1:250000 database was downsized and linkage-updated on the basis. In 2014, using the latest achievements of 1:250000 database, comprehensively update the 1:1000000 digital line graph database. At the same time, generate cartographic data of topographic map and digital elevation model data. This article mainly introduce national 1:1000000 cartographic data of topographic map, include feature content, database structure, Database-driven Mapping technology, workflow and so on.


Author(s):  
Ivan Kruhlov

Boundaries of 43 administrative units (raions and oblast towns) were digitized and manually rectified using official schemes and satellite images. SRTM digital elevation data were used to calculate mean relative elevation and its standard deviation for each unit, as well as to delineate altitudinal bioclimatic belts and their portions within the units. These parameters were used to classify the units via agglomerative cluster analysis into nine environmental classes. Key words: cluster analysis, digital elevation model, geoecosystem, geo-spatial analysis.


Author(s):  
A.B. Baibatsha

For work materials used multispectral satellite imagery Landsat (7 channels), medium spatial resolution (14,25–90 m) and a digital elevation model (data SRTM). For interpretation of satellite images and especially their infrared and thermal channels allocated buried paleovalleys pre-paleogene age. Their total length is 228 km. By manifestation of the content of remote sensing paleovalleys distinctly divided into two types, long ribbon-like read in materials and space survey highlights a network of small lakes. By the nature of the relationship established that the second type of river paleovalleys flogs first. On this basis, proposed to allocate two uneven river paleosystem. The most ancient paleovalleys first type can presumably be attributed to karst erosion, blurry chalk and carbon deposits foundation. Paleovalleys may include significant groundwater resources as drinking and industrial purposes. Also we can control the position paleovalleys zinc and bauxite mineralization area and alluvial deposits include uranium mineralization valleys infiltration type and placer gold. Direction paleovalleys choppy, but in general they have a north-east orientation, which is controlled by tectonic zones of the foundation. These zones are defined as the burial place themselves paleovalleys and position of karst cavities in areas interfacing with other structures orientation. The association of mineralization to the caverns in the beds paleovalleys could generally present conditions of formation of mineralization and carry it to the "Niagara" type. The term is obviously best reflects the mechanism of formation of these ores.


2021 ◽  
Author(s):  
Shizhou Ma ◽  
Karen Beazley ◽  
Patrick Nussey ◽  
Chris Greene

Abstract The Active River Area (ARA) is a spatial approach for identifying the extent of functional riparian area. Given known limitations in terms of input elevation data quality and methodology, ARA studies to date have not achieved effective computer-based ARA-component delineation, limiting the efficacy of the ARA framework in terms of informing riparian conservation and management. To achieve framework refinement and determine the optimal input elevation data for future ARA studies, this study tested a novel Digital Elevation Model (DEM) smoothing algorithm and assessed ARA outputs derived from a range of DEMs for accuracy and efficiency. It was found that the tested DEM smoothing algorithm allows the ARA framework to take advantage of high-resolution LiDAR DEM and considerably improves the accuracy of high-resolution LiDAR DEM derived ARA results; smoothed LiDAR DEM in 5-meter spatial resolution best balanced ARA accuracy and data processing efficiency and is ultimately recommended for future ARA delineations across large regions.


Author(s):  
M. Hubacek ◽  
V. Kovarik ◽  
V. Kratochvil

Digital elevation models are today a common part of geographic information systems and derived applications. The way of their creation is varied. It depends on the extent of area, required accuracy, delivery time, financial resources and technologies available. The first model covering the whole territory of the Czech Republic was created already in the early 1980's. Currently, the 5th DEM generation is being finished. Data collection for this model was realized using the airborne laser scanning which allowed creating the DEM of a new generation having the precision up to a decimetre. Model of such a precision expands the possibilities of employing the DEM and it also offers new opportunities for the use of elevation data especially in a domain of modelling the phenomena dependent on highly accurate data. The examples are precise modelling of hydrological phenomena, studying micro-relief objects, modelling the vehicle movement, detecting and describing historical changes of a landscape, designing constructions etc. <br><br> Due to a nature of the technology used for collecting data and generating DEM, it is assumed that the resulting model achieves lower accuracy in areas covered by vegetation and in built-up areas. Therefore the verification of model accuracy was carried out in five selected areas in Moravia. The network of check points was established using a total station in each area. To determine the reference heights of check points, the known geodetic points whose heights were defined using levelling were used. Up to several thousands of points were surveyed in each area. Individual points were selected according to a different configuration of relief, different surface types, and different vegetation coverage. The sets of deviations were obtained by comparing the DEM 5G heights with reference heights which was followed by verification of tested elevation model. Results of the analysis showed that the model reaches generally higher precision than the declared one in majority of areas. This applies in particular to areas covered by vegetation. By contrast, the larger deviations occurred in relation to the slope of the terrain, in particular in the micro-relief objects. The results are presented in this article.


2020 ◽  
Vol 9 (5) ◽  
pp. 334
Author(s):  
Timofey E. Samsonov

Combining misaligned spatial data from different sources complicates spatial analysis and creation of maps. Conflation is a process that solves the misalignment problem through spatial adjustment or attribute transfer between similar features in two datasets. Even though a combination of digital elevation model (DEM) and vector hydrographic lines is a common practice in spatial analysis and mapping, no method for automated conflation between these spatial data types has been developed so far. The problem of DEM and hydrography misalignment arises not only in map compilation, but also during the production of generalized datasets. There is a lack of automated solutions which can ensure that the drainage network represented in the surface of generalized DEM is spatially adjusted with independently generalized vector hydrography. We propose a new method that performs the conflation of DEM with linear hydrographic data and is embeddable into DEM generalization process. Given a set of reference hydrographic lines, our method automatically recognizes the most similar paths on DEM surface called counterpart streams. The elevation data extracted from DEM is then rubbersheeted locally using the links between counterpart streams and reference lines, and the conflated DEM is reconstructed from the rubbersheeted elevation data. The algorithm developed for extraction of counterpart streams ensures that the resulting set of lines comprises the network similar to the network of ordered reference lines. We also show how our approach can be seamlessly integrated into a TIN-based structural DEM generalization process with spatial adjustment to pre-generalized hydrographic lines as additional requirement. The combination of the GEBCO_2019 DEM and the Natural Earth 10M vector dataset is used to illustrate the effectiveness of DEM conflation both in map compilation and map generalization workflows. Resulting maps are geographically correct and are aesthetically more pleasing in comparison to a straightforward combination of misaligned DEM and hydrographic lines without conflation.


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