scholarly journals The Impact of Spatiotemporal Changes in Land Development (1984–2019) on the Increase in the Runoff Coefficient in Erbil, Kurdistan Region of Iraq

2020 ◽  
Vol 12 (8) ◽  
pp. 1302 ◽  
Author(s):  
Andam Mustafa ◽  
Michał Szydłowski
Keyword(s):  
Agricultural Land ◽  
Land Development ◽  
Flash Floods ◽  
Kurdistan Region ◽  
Lulc Changes ◽  
Digital Elevation ◽  
Large Expansion ◽  
Spatiotemporal Changes ◽  
Elevation Model ◽  
The Impact

Nowadays, geospatial techniques are a popular approach for estimating urban flash floods by considering spatiotemporal changes in urban development. In this study, we investigated the impact of Land Use/Land Cover (LULC) changes on the hydrological response of the Erbil basin in the Kurdistan Region of Iraq (KRI). In the studied area, the LULC changes were calculated for 1984, 1994, 2004, 2014 and 2019 using the Digital Elevation Model (DEM) and satellite images. The analysis of LULC changes showed that the change between 1984 and 2004 was slower than that between 2004 and 2019. The LULC analysis revealed a 444.4% growth in built-up areas, with a 60.4% decrease in agricultural land between 1984 and 2019. The influence of LULC on urban floods caused by different urbanization scenarios was ascertained using the HEC-GeoHMS and HEC-HMS models. Over 35 years, there was a 15% increase in the peak discharge of outflow, from 392.2 m3/s in 1984 to 450 m3/s in 2014, as well as the runoff volume for a precipitation probability distribution of 10%, which increased from 27.4 mm in 1984 to 30.9 mm in 2014. Overall, the probability of flash floods increased in the center of the city due to the large expansion of built-up areas.

Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

2020 ◽  
Vol 3 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Abdulla Al Kafy ◽  
Abdullah Al-Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Md. Soumik Sikdar ◽  
Mohammad Hasib Hasan Khan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Agricultural Land ◽  
Global Climate ◽  
Urban Expansion ◽  
Water Bodies ◽  
Landsat 8 ◽  
Lulc Changes ◽  
The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

scholarly journals Effect of DEM Interpolation Neighbourhood on Terrain Factors

2019 ◽  
Vol 8 (1) ◽  
pp. 30 ◽  
Author(s):  
Ying Zhu ◽  
Xuejun Liu ◽  
Jing Zhao ◽  
Jianjun Cao ◽  
Xiaolei Wang ◽  
...  
Keyword(s):  
Interpolation Method ◽  
Simulated Data ◽  
Topographic Features ◽  
Structure And Morphology ◽  
Digital Elevation ◽  
Different Types ◽  
Slope Error ◽  
Elevation Model ◽  
The Impact ◽  
Mls Method

Topographic factors such as slope and aspect are essential parameters in depicting the structure and morphology of a terrain surface. We study the effect of the number of points in the neighbourhood of a digital elevation model (DEM) interpolation method on mean slope, mean aspect, and RMSEs of slope and aspect from the interpolated DEM. As the moving least squares (MLS) method can maintain the inherent properties and other characteristics of a surface, this method is chosen for DEM interpolation. Three areas containing different types of topographic features are selected for study. Simulated data from a Gauss surface is also used for comparison. First, the impact of the number of points on the DEM root mean square error (RMSE) is analysed. The DEM RMSE in the three study areas decreases gradually with the number of points in the neighbourhood. In addition, the effect of the number of points in the neighbourhood on mean slope and mean aspect was studied across varying topographies through regression analysis. The two variables respond differently to changes in terrain. However, the RMSEs of the slope and aspect in all study areas are logarithmically related to the number of points in the neighbourhood and the values decrease uniformly as the number of points in the neighbourhood increases. With more points in the neighbourhood, the RMSEs of the slope and aspect are not sensitive to topography differences and the same trends are observed for the three studied quantities. Results for the Gauss surface are similar. Finally, this study analyses the spatial distribution of slope and aspect errors. The slope error is concentrated in ridges, valleys, steep-slope areas, and ditch edges while the aspect error is concentrated in ridges, valleys, and flat regions. With more points in the neighbourhood, the number of grid cells in which the slope error is greater than 15° is gradually reduced. With similar terrain types and data sources, if the calculation efficiency is not a concern, sufficient points in the spatial autocorrelation range should be analysed in the neighbourhood to maximize the accuracy of the slope and aspect. However, selecting between 10 and 12 points in the neighbourhood is economical.

scholarly journals Scale-Optimized Surface Roughness for Topographic Analysis

Geosciences ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 322 ◽  
Author(s):  
John B. Lindsay ◽  
Daniel R. Newman ◽  
Anthony Francioni
Keyword(s):  
Surface Roughness ◽  
Forest Cover ◽  
Agricultural Land ◽  
Spatial Scales ◽  
Grid Cell ◽  
Topographic Analysis ◽  
Digital Elevation ◽  
Locally Adaptive ◽  
Elevation Model

Surface roughness is a terrain parameter that has been widely applied to the study of geomorphological processes. One of the main challenges in studying roughness is its highly scale-dependent nature. Determining appropriate mapping scales in topographically heterogenous landscapes can be difficult. A method is presented for estimating multiscale surface roughness based on the standard deviation of surface normals. This method utilizes scale partitioning and integral image processing to isolate scales of surface complexity. The computational efficiency of the method enables high scale sampling density and identification of maximum roughness for each grid cell in a digital elevation model (DEM). The approach was applied to a 0.5 m resolution LiDAR DEM of a 210 km2 area near Brantford, Canada. The case study demonstrated substantial heterogeneity in roughness properties. At shorter scales, tillage patterns and other micro-topography associated with ground beneath forest cover dominated roughness scale signatures. Extensive agricultural land-use resulted in 35.6% of the site exhibiting maximum roughness at micro-topographic scales. At larger spatial scales, rolling morainal topography and fluvial landforms, including incised channels and meander cut banks, were associated with maximum surface roughness. This method allowed for roughness mapping at spatial scales that are locally adapted to the topographic context of each individual grid cell within a DEM. Furthermore, the analysis revealed significant differences in roughness characteristics among soil texture categories, demonstrating the practical utility of locally adaptive, scale-optimized roughness.

scholarly journals Impact of Spatial Resolution of Digital Elevation Model on Landslide Susceptibility Mapping: A case Study in Kullu Valley, Himalayas

Geosciences ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 360 ◽  
Author(s):  
Sansar Raj ◽  
Thimmaiah
Keyword(s):  
Digital Elevation Model ◽  
Spatial Resolution ◽  
Landslide Susceptibility ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Mountainous Regions ◽  
Digital Elevation ◽  
Kullu Valley ◽  
Elevation Model ◽  
The Impact

Landslides are one of the most damaging geological hazards in mountainous regions such as the Himalayas. The Himalayan region is, tectonically, the most active region in the world that is highly vulnerable to landslides and associated hazards. Landslide susceptibility mapping (LSM) is a useful tool for understanding the probability of the spatial distribution of future landslide regions. In this research, the landslide inventory datasets were collected during the field study of the Kullu valley in July 2018, and 149 landslide locations were collected as global positioning system (GPS) points. The present study evaluates the LSM using three different spatial resolution of the digital elevation model (DEM) derived from three different sources. The data-driven traditional frequency ratio (FR) model was used for this study. The FR model was used for this research to assess the impact of the different spatial resolution of DEMs on the LSM. DEM data was derived from Advanced Land Observing Satellite-1 (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) ALOS-PALSAR for 12.5 m, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global for 30 m, and the Shuttle Radar Topography Mission (SRTM) for 90 m. As an input, we used eight landslide conditioning factors based on the study area and topographic features of the Kullu valley in the Himalayas. The ASTER-Global 30m DEM showed higher accuracy of 0.910 compared to 0.839 for 12.5 m and 0.824 for 90 m DEM resolution. This study shows that that 30 m resolution is better suited for LSM for the Kullu valley region in the Himalayas. The LSM can be used for mitigation and future planning for spatial planners and developmental authorities in the region.

scholarly journals Assessment of Changes in a Viewshed in the Western Carpathians Landscape as a Result of Reforestation

Land ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 430
Author(s):  
Michał Sobala ◽  
Urszula Myga-Piątek ◽  
Bartłomiej Szypuła
Keyword(s):  
Digital Elevation Model ◽  
Forest Succession ◽  
Western Carpathians ◽  
Surface Model ◽  
Digital Surface Model ◽  
Mountainous Areas ◽  
Viewshed Analysis ◽  
Digital Elevation ◽  
Elevation Model ◽  
The Impact

A viewshed analysis is of great importance in mountainous areas characterized by high landscape values. The aim of this research was to determine the impact of reforestation occurring on former pasturelands on changes in the viewshed, and to quantify changes in the surface of glades. We combine a horizontal and a vertical approach to landscape analysis. The changes in non-forest areas and the viewshed from viewpoints located in glades were calculated using historical cartographic materials and a more recent Digital Elevation Model and Digital Surface Model. An analysis was conducted using a Visibility tool in ArcGIS. The non-forest areas decreased in the period 1848–2015. The viewshed in the majority of viewpoints also decreased in the period 1848–2015. In the majority of cases, the maximal viewsheds were calculated in 1879/1885 and 1933 (43.8% of the analyzed cases), whereas the minimal ones were calculated in 2015 (almost 57.5% of analyzed cases). Changes in the viewshed range from 0.2 to 23.5 km2 with half the cases analyzed being no more than 1.4 km2. The results indicate that forest succession on abandoned glades does not always cause a decline in the viewshed. Deforestation in neighboring areas may be another factor that has an influence on the decline.

scholarly journals Sensitivity analysis of the DEM resolution and effective parameters of runoff yield in the SWAT model: a case study

2019 ◽  
Vol 69 (1) ◽  
pp. 39-54 ◽  
Author(s):  
Mohammad Nazari-Sharabian ◽  
Masoud Taheriyoun ◽  
Moses Karakouzian
Keyword(s):  
Sensitivity Analysis ◽  
Assessment Tool ◽  
Swat Model ◽  
Computation Time ◽  
Effective Parameters ◽  
Digital Elevation ◽  
Elevation Model ◽  
The Impact ◽  
Reduce Computation Time

Abstract This study investigates the impact of different digital elevation model (DEM) resolutions on the topological attributes and simulated runoff, as well as the sensitivity of runoff parameters in the Mahabad Dam watershed in Iran. The watershed and streamlines were delineated in ArcGIS, and the hydrologic analyses were performed using the Soil and Water Assessment Tool (SWAT). The sensitivity analysis on runoff parameters was performed, using the Sequential Uncertainties FItting Ver. 2 algorithm, in the SWAT Calibration and Uncertainty Procedures (SWAT-CUP) program. The results indicated that the sensitivity of runoff parameters, watershed surface area, and elevations changed under different DEM resolutions. As the distribution of slopes changed using different DEMs, surface parameters were most affected. Furthermore, higher amounts of runoff were generated when DEMs with finer resolutions were implemented. In comparison with the observed value of 8 m3/s at the watershed outlet, the 12.5 m DEM showed more realistic results (6.77 m3/s). Comparatively, the 12.5 m DEM generated 0.74% and 2.73% more runoff compared with the 30 and 90 m DEMs, respectively. The findings of this study indicate that in order to reduce computation time, researchers may use DEMs with coarser resolutions at the expense of minor decreases in accuracy.

scholarly journals Floods Risk Mapping and Assessing Vulnerability of Morang, Nepal

2021 ◽  
Author(s):  
Pawan Thapa ◽  
Narayan Thapa
Keyword(s):  
Drainage Density ◽  
Google Earth ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Digital Elevation ◽  
Two Factors ◽  
Flooding Risk ◽  
Elevation Model ◽  
The One ◽  
The Impact

Abstract Background: The impact of flooding rises due to unplanned settlements, especially in developing and underdeveloped countries. This study tries to address these issues by mapping flood risk places and assessing their impact on population and household.Methods: This study used the dataset available in Google Earth Engine (GEE), Food and Agriculture Organization (FAO), Central Bureau Statistics (CBS), Earth Data for preparing slope, drainage density, digital elevation model, rainfall, land use map, and soil map. These maps create using GEE and QGIS through overlay analysis that has two factors. The one is influence and other slopes, and it has provided high and low value according to its role on flooding.Results: The risk assessment shows around twenty-four percent population is at higher risk, whereas more than three thousand settlements are prone to flooding. It depicts a significant increasing trend of floods in the Morang district.Conclusion: This settlement risk map can help determine the flood safe and very high-risk areas in the Morang district. It will support residential places' planning by the local government, urban planners, and community people to reduce flooding risk.

scholarly journals Floods Risk Mapping and Assessing Vulnerability of Morang, Nepal

2021 ◽  
Author(s):  
Pawan Thapa ◽  
Narayan Thapa
Keyword(s):  
Drainage Density ◽  
Google Earth ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Digital Elevation ◽  
Two Factors ◽  
Flooding Risk ◽  
Elevation Model ◽  
The One ◽  
The Impact

Abstract Background: The impact of flooding rises due to unplanned settlements, especially in developing countries. This study tries to address these issues by mapping flood risk places and assessing their impact on population and household.Methods: This study used the dataset available in Google Earth Engine (GEE), Food and Agriculture Organization (FAO), Central Bureau Statistics (CBS), Earth Data for preparing slope, drainage density, digital elevation model, rainfall, land use map, and soil map. These maps create using GEE and QGIS through overlay analysis that has two factors. The one is influence and other slopes, and it has provided high and low value according to its role on flooding.Results: The risk assessment shows around twenty-four percent population is at higher risk, whereas more than three thousand settlements are prone to flooding. It depicts a significant increasing trend of floods in the Morang district.Conclusion: This settlement risk map can help determine the flood safe and very high-risk areas in the Morang district. It will support residential places' planning by the local government, urban planners, and community people to reduce flooding risk.

scholarly journals Studying the peculiarities of agricultural lands with the use of digital relief models

2020 ◽  
Vol 26 (3) ◽  
pp. 221-228
Author(s):  
Kirill Teslenok ◽  
Anton Mushtaykin ◽  
Sergey Teslenok
Keyword(s):  
Agricultural Land ◽  
Arable Land ◽  
Initial Step ◽  
Nature Management ◽  
Agricultural Lands ◽  
Digital Elevation ◽  
Arable Farming ◽  
The Impact ◽  
The Relationship ◽  
Terrain Characteristics

The article highlights the stages of work during which the impact of individual terrain properties on arable farming was identified. The possibility of using digital elevation models (DEM) to identify those characteristics that can have a significant impact on such lands was studied. Findings have been made about the relationship between these features and the sites, and their place among other arable land features has been determined. The initial step was to select the baseline data for the area under study and obtain it in the form we needed. Here, techniques for automated DEM acquisition are being developed. At the next stage, individual terrain characteristics, complexity of their acquisition and ranking by importance for this methodology were considered and analyzed. At the final stage the analysis of agricultural lands, their connection with the relief and its characteristics was carried out, practical conclusions were drawn and recommendations were made based on them. It should be noted that the study area — the Vindrei River basin — is very illustrative for showing the advantages of the technology being developed. Its territory is occupied both by extensive agricultural land and forest areas. During the development of the methodology it was important to demonstrate the possibilities of using the technology in the field of nature management and improving economic efficiency of the area.

scholarly journals Classification of the Tatra Mountain lakes in terms of the duration of their ice cover (Poland and Slovakia)

2019 ◽  
Vol 79 (1) ◽  
Author(s):  
Bogdan Gadek ◽  
Mirosław Szumny ◽  
Bartłomiej Szypuła
Keyword(s):  
Climate Change ◽  
Ice Cover ◽  
Individual Characteristics ◽  
Freezing And Thawing ◽  
Digital Elevation ◽  
Mountain Environment ◽  
Elevation Model ◽  
The Impact ◽  
The Relationship

This paper presents the results of a classification of the Tatra lakes based on the duration of their ice cover, altitude, volume, and potential incoming solar radiation (PISR). It is embedded in the context of the impact of current climate change on the mountain environment. A digital elevation model, morphometric data, satellite imagery from the winter seasons of 2015-2017 and the Wrocław taxonomy method were used in the study. It was found that the order of freezing and thawing of the lakes investigated may change from year to year. The relationship between ice cover duration and altitude is clearly weakened by variations in lake volumes, with insolation having a noticeably lesser effect. Determining the duration of ice cover of the lakes over several seasons facilitates identifying the similarities and dissimilarities between them. Five groups of lakes displaying similar characteristics were identified as well as 2 groups of lakes with highly individual characteristics. Based on the data obtained, it can be concluded that the duration of ice cover on the Tatra lakes has been shortening noticeably over the last 100 years. Small high-altitude lakes seem to be most vulnerable to climate change.

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