scholarly journals Geo-spatial Analysis of Farmland Affected by 2020 Flooding of River Rima, Northwestern Nigeria

2021 ◽  
pp. 20-27
Author(s):  
Abdullahi Muktar ◽  
Sadiq A. Yelwa ◽  
Muhammad Tayyib Bello ◽  
Wali Elekwachi
Keyword(s):  
Satellite Image ◽  
Shuttle Radar Topography Mission ◽  
Policy Makers ◽  
Professional Advice ◽  
Maximum Water Level ◽  
Digital Elevation ◽  
Farm Produce ◽  
Terra Modis ◽  
Elevation Model ◽  
The Impact

The flooding of River Rima is an annual issue affecting farmland located within the floodplains. This phenomena causes loss of farm produce and mass destruction of buildings, including roads and bridges in the area. Estimating the farmland affected by the flood will help the policy makers in decision making on how to mitigate the impact of flooding in the affected areas. The Terra/MODIS satellite image with 7-2-1 bands combination was used to classify the image into four landcover types. The area covered by flood was selected to calculate the flood area using Image Calculator module on QGIS software. The class of water was imposed on Digital Elevation Model that was obtained from Environmental Monitoring Satellite called The Shuttle Radar Topography Mission (SRTM). The result shows that River Rima flood occupies about 17,517 km2, equivalent to 1.7 million hectares of farmland that is below 230 meters (ASL). It was recommended that the local authorities and decision makers may use the flood map to showing flood risk zones so as to deter construction beyond the buffer. Farmers should adhere strictly to NiMet’s advice based on flood predictions. The civil engineers should also take note of the maximum water level during flooding so as to apply professional advice when constructing roads and bridges in the area.

Influence of DEM resolution on topographic correction models using spot satellite image

2018 ◽  
Author(s):  
Ting-Pin Chiu 1 ◽  
Su-Fen Wang 2
Keyword(s):  
Satellite Image ◽  
Image Data ◽  
Topographic Correction ◽  
Dem Resolution ◽  
Digital Elevation ◽  
Sensor Geometry ◽  
Spot Image ◽  
Terrain Representation ◽  
Elevation Model ◽  
The Impact

Topographic correction models (TCMs) are valid on satellite image data preprocessing steps. The illumination angle may be sensitive to different terrain slope and aspect conditions base on sun-terrain-sensor geometry. Although the topographic correction is influenced by the sun azimuth and zenith angle, the correction result can be equally in the same image status. By contrast, the terrain factors change with different digital elevation model (DEM) resolution in the topographic correction equations and cause a significant effect. Slope is sensitive in rugged terrain, and aspect is impressionable at flat surface at a coarse DEM resolution data. As the DEM resolution lead a distinct result on TCMs, this research is aimed to examine the impact of DEM resolution on the accuracy of terrain representation and of the gradient determined. In this study, five TCMs, including cosine correction, C correction, SCS correction, SCS+C correction and Minnaert correction models are compared by different resolutions using SPOT image data. The 5 meter DEM obtained from Ministry of the interior will be resampled to 10 to 500 meters to test those topographic models sustainability on Lienhuachih Research Center. The accuracy of five topographic correction models base on different DEM resolution will be evaluated by root-mean-square error (RMSE).

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 In-Season Mapping of Irrigated Crops Using Landsat 8 and Sentinel-1 Time Series

2019 ◽  
Vol 11 (2) ◽  
pp. 118 ◽  
Author(s):  
Valérie Demarez ◽  
Florian Helen ◽  
Claire Marais-Sicre ◽  
Frédéric Baup
Keyword(s):  
Time Series ◽  
Shuttle Radar Topography Mission ◽  
Irrigation Scheduling ◽  
Landsat 8 ◽  
Radar Images ◽  
Optical Images ◽  
Multi Temporal ◽  
Irrigated Crops ◽  
Elevation Model ◽  
The Impact

Numerous studies have reported the use of multi-spectral and multi-temporal remote sensing images to map irrigated crops. Such maps are useful for water management. The recent availability of optical and radar image time series such as the Sentinel data offers new opportunities to map land cover with high spatial and temporal resolutions. Early identification of irrigated crops is of major importance for irrigation scheduling, but the cloud coverage might significantly reduce the number of available optical images, making crop identification difficult. SAR image time series such as those provided by Sentinel-1 offer the possibility of improving early crop mapping. This paper studies the impact of the Sentinel-1 images when used jointly with optical imagery (Landsat8) and a digital elevation model of the Shuttle Radar Topography Mission (SRTM). The study site is located in a temperate zone (southwest France) with irrigated maize crops. The classifier used is the Random Forest. The combined use of the different data (radar, optical, and SRTM) improves the early classifications of the irrigated crops (k = 0.89) compared to classifications obtained using each type of data separately (k = 0.84). The use of the DEM is significant for the early stages but becomes useless once crops have reached their full development. In conclusion, compared to a “full optical” approach, the “combined” method is more robust over time as radar images permit cloudy conditions to be overcome.

scholarly journals Predicting Channel Conveyance and Characterizing Planform Using River Bathymetry via Satellite Image Compilation (RiBaSIC) Algorithm for DEM-Based Hydrodynamic Modeling

2020 ◽  
Vol 12 (17) ◽  
pp. 2799
Author(s):  
Md N M Bhuyian ◽  
Alfred Kalyanapu
Keyword(s):  
Mean Squared Error ◽  
Satellite Image ◽  
Shuttle Radar Topography Mission ◽  
Willamette River ◽  
Bathymetric Data ◽  
Digital Elevation ◽  
Channel Slope ◽  
Dem Accuracy ◽  
Landsat Satellite ◽  
Discharge Estimation

Digital Elevation Models (DEMs) are widely used as a proxy for bathymetric data and several studies have attempted to improve DEM accuracy for hydrodynamic (HD) modeling. Most of these studies attempted to quantitatively improve estimates of channel conveyance (assuming a non-braided morphology) rather than accounting for the actual channel planform. Accurate representation of river conveyance and planform in a DEM is critical to HD modeling and can be achieved with a combination of remote sensing (e.g., satellite image) and field data, such as water surface elevation (WSE). Therefore, the objectives of this study are (i) to develop an algorithm for predicting channel conveyance and characterizing planform via satellite images and in situ WSE and (ii) to estimate discharge using the predicted conveyance via an HD model. The algorithm is named River Bathymetry via Satellite Image Compilation (RiBaSIC) and uses Landsat satellite imagery, Shuttle Radar Topography Mission (SRTM) DEM, Multi-Error-Removed Improved-Terrain (MERIT) DEM, and observed WSE. The algorithm is tested on four study areas along the Willamette River, Kushiyara River, Jamuna River, and Solimoes River. Channel slope and predicted hydraulic radius are subsequently estimated for approximating Manning’s roughness factor. Two-dimensional HD models using DEMs modified by the RiBaSIC algorithm and corresponding Manning’s roughness factors are employed for discharge estimation. The proposed algorithm can represent river planform and conveyance in single-channeled, meandering, wandering, and braided river reaches. Additionally, the HD models estimated discharge within 14–19% relative root mean squared error (RRMSE) in simulation of five years period.

scholarly journals MORPHOMETRIC CHARACTERIZATION OF THE HYDROGRAPHIC BASIN OF JAUQUARA RIVER IN THE TRANSITION BETWEEN THE CERRADO AND AMAZON BIOMES IN MATO GROSSO-BRAZIL

FLORESTA ◽  
2019 ◽  
Vol 49 (2) ◽  
pp. 325
Author(s):  
Gabriel Americo Cassettari ◽  
Tadeu Miranda De Queiroz
Keyword(s):  
Shuttle Radar Topography Mission ◽  
Mato Grosso ◽  
Digital Elevation ◽  
Circularity Index ◽  
Elevation Model ◽  
Basin Area ◽  
Morphometric Characterization ◽  
Effective Water ◽  
Unpublished Information

This study aimed to perform the Jauquara river watershed morphometric characterization. To watershed delimitation was used SRTM 30 type Digital Elevation Model (Shuttle Radar Topography Mission, with spatial resolution of 30 m) provided by USGS Earth Explorer platform. The geographic information system used to watershed delimitation process and maps generation was ArcGIS 10.1 from ESRI®. The morphometric variables calculus was based on classic methodologies of Applied Hydrology. The watershed has an area of 1408,03 km2 and perimeter of 288,43 km with compactness coefficient and circularity index of Kc = 2.15 and Ic = 0.21, respectively, which show an elongated shape. The drainage was classified as 5th order, reinforcing the configuration of the drainage network with a wide hydric distribution. The predominant altitude range is between 368 and 552 m, which corresponds to an area of 478.10 km2. It was observed that there is a predominance of smooth-wavy and undulated reliefs (3-8%, 8-20% slope), which correspond to 38,05% and 23,04% of the total basin area respectively. The morphometric characterization of the basin made it possible to obtain unpublished information that contributes to the decision making regarding the effective water management in the studied area, being this a guiding study for other works

DEM Generation and Accuracy Assessment Using ZY-3 Stereo Image Pairs

2015 ◽  
Vol 738-739 ◽  
pp. 613-617 ◽  
Author(s):  
Guo Yin Cai ◽  
Jie Huan ◽  
Yang Liu ◽  
Ming Yi Du
Keyword(s):  
3D Visualization ◽  
Accuracy Assessment ◽  
Satellite Image ◽  
Stereo Image ◽  
Stereo Pair ◽  
Topographic Analysis ◽  
Digital Elevation ◽  
Data Source ◽  
Image Pairs ◽  
Elevation Model

Digital Elevation Model (DEM) is an important data source for topographic analysis, 3D visualization and satellite image ortho-rectification. This paper focused on the DEM extraction and accuracy assessment from ZY-3 satellite with 3 stereo images. DEM was extracted using three different stereo pair image groups composed of forward and nadir view images, nadir and backward view images as well as forward and backward view images. The accuracy of the DEM was indicated by root-mean-square error (RMSE) values. The results showed that the stereo pair of nadir and forward view images achieved the best accuracy, while the pair of forward and backward view images obtained the worst. This might be useful for the selection of the stereo pair images for extracting DEM using ZY-3 satellite images.

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.

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