scholarly journals Estimation of the HEC-HMS model parameters in data-scarce regions. Application to the Ouergha watershed (Sebou, Morocco)

2021 ◽  
Vol 314 ◽  
pp. 05002
Author(s):  
Hasna Moumni ◽  
Karima Sebari ◽  
Laila Stour ◽  
Abdellatif Ahbari
Keyword(s):  
Remote Sensing ◽  
Hydrological Model ◽  
Model Parameters ◽  
Flow Data ◽  
Random Parameters ◽  
Quality Of Data ◽  
Initial Values ◽  
Digital Elevation ◽  
Elevation Model

The availability, accessibility and quality of data are significant obstacles to hydrological modelling. Estimating the initial values of the hydrological model´’ ’s parameters is a laborious and determining task requiring much attention. Geographic information systems (GIS) and spatial remote sensing are prometting tools for processing and collecting data. In this work, we use an innovative approach to estimate the HEC-HMS hydrological model parameters from the soil map of Africa (250m), the land use map GLC30, the depth to bedrock map, the digital elevation model and observed flow data. The estimation approach is applied to the Ouergha basin (Sebou, Morocco). The proposed approach’s interest is to feed the HEC-HMS hydrological model with initial values of parameters close to the study area reality instead of using random parameters.

scholarly journals Hydrologic application comparison among typical open global DEM data based on remote sensing images

2018 ◽  
Author(s):  
Shangmin Zhao ◽  
Shifang Zhang ◽  
Weiming Cheng
Keyword(s):  
Remote Sensing ◽  
Similar Distribution ◽  
Remote Sensing Images ◽  
Topographic Analysis ◽  
Digital Elevation ◽  
Data Source ◽  
Elevation Model ◽  
Srtm Data ◽  
Better Than

As the data source in digital topographic analysis, digital elevation model (DEM) data plays an important role in many fields, and hydrologic application is an important one among them. The successive release of open global DEM datasets provides multi choices for these applications, but also brings puzzles in DEM data selection. Taking Fenhe River Basin of China as the study area, this research compared the hydrologic networks extracted by typical global DEM data using matching difference (MD), correctness (C) and figure of merit (FM) indexes. Firstly, four DEM-derived hydrologic networks (DHNs) were acquired through topographic analysis using four typical global DEM datasets, including Shuttle Radar Terrain Mission (SRTM) data with 1 arc second resolution (SRTM1), SRTM data with 3 arc second resolution (SRTM3), ASTER global DEM data in the second version (GDEM-v2) and ALOS world 3D-30m (AW3D30) data. Then, the reference hydrologic network (RHN) was interpreted based on remote sensing images. Finally, the DHNs were evaluated and compared by referencing the RHN using different indexes. Research results show: (1) four DHNs have similar distribution in mountain regions but much different performance in flat regions; (2) all the indexes (including MD, C and FM) indicate that about the quality of the DHNs, the best is the AW3D30 data, then the SRTM1 data, the next is the SRTM3 data, and the GDEM-v2 data has the worst quality; (3) through analyzing the MD distribution in different slope classes for the four global DEM datasets, the MD mainly distributes in flat region, and then sloping region, but seldom in steep region. Overall, AW3D30 has the best quality, a little better than SRTM1 and much better than SRTM3 and GDEM-v2; SRTM3 and GDEM-v2 data have much worse quality, and GDEM-v2 data is the worst in the four global DEM datasets. Considering that the AW3D30 data is originated from the DEM dataset with 5m resolution, it may exerts more effect in future digital topographic analysis.

scholarly journals Hydrologic application comparison among typical open global DEM data based on remote sensing images

2018 ◽  
Author(s):  
Shangmin Zhao ◽  
Shifang Zhang ◽  
Weiming Cheng
Keyword(s):  
Remote Sensing ◽  
Similar Distribution ◽  
Remote Sensing Images ◽  
Topographic Analysis ◽  
Digital Elevation ◽  
Data Source ◽  
Elevation Model ◽  
Srtm Data ◽  
Better Than

As the data source in digital topographic analysis, digital elevation model (DEM) data plays an important role in many fields, and hydrologic application is an important one among them. The successive release of open global DEM datasets provides multi choices for these applications, but also brings puzzles in DEM data selection. Taking Fenhe River Basin of China as the study area, this research compared the hydrologic networks extracted by typical global DEM data using matching difference (MD), correctness (C) and figure of merit (FM) indexes. Firstly, four DEM-derived hydrologic networks (DHNs) were acquired through topographic analysis using four typical global DEM datasets, including Shuttle Radar Terrain Mission (SRTM) data with 1 arc second resolution (SRTM1), SRTM data with 3 arc second resolution (SRTM3), ASTER global DEM data in the second version (GDEM-v2) and ALOS world 3D-30m (AW3D30) data. Then, the reference hydrologic network (RHN) was interpreted based on remote sensing images. Finally, the DHNs were evaluated and compared by referencing the RHN using different indexes. Research results show: (1) four DHNs have similar distribution in mountain regions but much different performance in flat regions; (2) all the indexes (including MD, C and FM) indicate that about the quality of the DHNs, the best is the AW3D30 data, then the SRTM1 data, the next is the SRTM3 data, and the GDEM-v2 data has the worst quality; (3) through analyzing the MD distribution in different slope classes for the four global DEM datasets, the MD mainly distributes in flat region, and then sloping region, but seldom in steep region. Overall, AW3D30 has the best quality, a little better than SRTM1 and much better than SRTM3 and GDEM-v2; SRTM3 and GDEM-v2 data have much worse quality, and GDEM-v2 data is the worst in the four global DEM datasets. Considering that the AW3D30 data is originated from the DEM dataset with 5m resolution, it may exerts more effect in future digital topographic analysis.

Improving bioclimatic envelop modeling for Lichens through remote sensing based substratum correction: A study over Indian Himalaya

2016 ◽  
Vol 1 (2) ◽  
Author(s):  
C. P. Singh ◽  
R. Bajpai ◽  
R. P. Singh ◽  
D. K. Upreti
Keyword(s):  
Remote Sensing ◽  
Predictive Accuracy ◽  
Geographic Area ◽  
Jammu And Kashmir ◽  
Indian Himalaya ◽  
Novel Approach ◽  
Digital Elevation ◽  
Average Probability ◽  
Niche Area ◽  
Elevation Model

In alpine Himalaya, the niche map of lichens and its characteristics is a gap area. A novel approach of improving the bioclimatic envelop through use of remote sensing inputs was employed. The 19 bioclimatic indices and digital elevation model were used for training niche models through occurrence records of 33 lichen species across Indian Himalaya. Substratum correction was carried out using LU/LC data. About 45% of the total geographic area studied is found to be very conducive (with niche probability > 70%) for the growth of lichens with predictive accuracy of 91% ascertained through cross-validation. Jammu and Kashmir is having highest niche area (36.02%); however, average probability niche score is highest in Uttarakhand (81.08). Area between 27o - 28o N latitude is having highest area however average probability score is highest in 30o - 31o N. Overall maximum niche area (35.50 %) is found in the regions dominated by alpine meadow, alpine grasslands and parts of cold deserts. The potential use lies in reporting yet to be explored lichens in the Indian Himalaya.

Unsupervised labelling of remote sensing images based on force field clustering

2021 ◽  
pp. 1-14
Author(s):  
Zhenggang Wang ◽  
Jin Jin
Keyword(s):  
Remote Sensing ◽  
Force Field ◽  
Image Data ◽  
Model Parameters ◽  
Remote Sensing Images ◽  
Initial Cluster ◽  
Data Points ◽  
Global Optimal ◽  
Density Force

Remote sensing image segmentation provides technical support for decision making in many areas of environmental resource management. But, the quality of the remote sensing images obtained from different channels can vary considerably, and manually labeling a mass amount of image data is too expensive and Inefficiently. In this paper, we propose a point density force field clustering (PDFC) process. According to the spectral information from different ground objects, remote sensing superpixel points are divided into core and edge data points. The differences in the densities of core data points are used to form the local peak. The center of the initial cluster can be determined by the weighted density and position of the local peak. An iterative nebular clustering process is used to obtain the result, and a proposed new objective function is used to optimize the model parameters automatically to obtain the global optimal clustering solution. The proposed algorithm can cluster the area of different ground objects in remote sensing images automatically, and these categories are then labeled by humans simply.

scholarly journals Paleovalleys mapping using remote sensing

2014 ◽  
Vol XL-5 ◽  
pp. 83-86
Author(s):  
A.B. Baibatsha
Keyword(s):  
Remote Sensing ◽  
Groundwater Resources ◽  
Alluvial Deposits ◽  
North East ◽  
Digital Elevation ◽  
Landsat 7 ◽  
Tectonic Zones ◽  
Materials Used ◽  
Elevation Model ◽  
Digital Elevation Model Data

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.

scholarly journals A Probabilistic Assessment of Soil Erosion Susceptibility in a Head Catchment of the Jemma Basin, Ethiopian Highlands

Geosciences ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 248 ◽  
Author(s):  
Mariaelena Cama ◽  
Calogero Schillaci ◽  
Jan Kropáček ◽  
Volker Hochschild ◽  
Alberto Bosino ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Remote Sensing Data ◽  
Gully Erosion ◽  
Entropy Model ◽  
Global Issues ◽  
Susceptibility Maps ◽  
Digital Elevation ◽  
Elevation Model ◽  
Color Composite

Soil erosion represents one of the most important global issues with serious effects on agriculture and water quality, especially in developing countries, such as Ethiopia, where rapid population growth and climatic changes affect widely mountainous areas. The Meskay catchment is a head catchment of the Jemma Basin draining into the Blue Nile (Central Ethiopia) and is characterized by high relief energy. Thus, it is exposed to high degradation dynamics, especially in the lower parts of the catchment. In this study, we aim at the geomorphological assessment of soil erosion susceptibilities. First, a geomorphological map was generated based on remote sensing observations. In particular, we mapped three categories of landforms related to (i) sheet erosion, (ii) gully erosion, and (iii) badlands using a high-resolution digital elevation model (DEM). The map was validated by a detailed field survey. Subsequently, we used the three categories as dependent variables in a probabilistic modelling approach to derive the spatial distribution of the specific process susceptibilities. In this study we applied the maximum entropy model (MaxEnt). The independent variables were derived from a set of spatial attributes describing the lithology, terrain, and land cover based on remote sensing data and DEMs. As a result, we produced three separate susceptibility maps for sheet and gully erosion as well as badlands. The resulting susceptibility maps showed good to excellent prediction performance. Moreover, to explore the mutual overlap of the three susceptibility maps, we generated a combined map as a color composite where each color represents one component of water erosion. The latter map yields useful information for land-use managers and planning purposes.

scholarly journals Distinguishing Glaciers between Surging and Advancing by Remote Sensing: A Case Study in the Eastern Karakoram

2020 ◽  
Vol 12 (14) ◽  
pp. 2297 ◽  
Author(s):  
Mingyang Lv ◽  
Huadong Guo ◽  
Jin Yan ◽  
Kunpeng Wu ◽  
Guang Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Google Earth ◽  
High Mountain ◽  
Glacier Mass Balance ◽  
Visual Interpretation ◽  
Stable Mode ◽  
Optical Images ◽  
Digital Elevation ◽  
Glacier Surges ◽  
Elevation Model

The Karakoram has had an overall slight positive glacier mass balance since the end of 20th century, which is anomalous given that most other regions in High Mountain Asia have had negative changes. A large number of advancing, retreating, and surging glaciers are heterogeneously mixed in the Karakoram increasing the difficulties and inaccuracies to identify glacier surges. We found two adjacent glaciers in the eastern Karakoram behaving differently from 1995 to 2019: one was surging and the other was advancing. In order to figure out the differences existing between them and the potential controls on surges in this region, we collected satellite images from Landsat series, ASTER, and Google Earth, along with two sets of digital elevation model. Utilizing visual interpretation, feature tracking of optical images, and differencing between digital elevation models, three major differences were observed: (1) the evolution profiles of the terminus positions occupied different change patterns; (2) the surging glacier experienced a dramatic fluctuation in the surface velocities during and after the event, while the advancing glacier flowed in a stable mode; and (3) surface elevation of the surging glacier decreased in the reservoir and increased in the receiving zone. However, the advancing glacier only had an obvious elevation increase over its terminus part. These differences can be regarded as standards for surge identification in mountain ranges. After combining the differences with regional meteorological conditions, we suggested that changes of thermal and hydrological conditions could play a role in the surge occurrence, in addition, geomorphological characteristics and increasing warming climate might also be part of it. This research strongly contributes to the literatures of glacial motion and glacier mass change in the eastern Karakoram through remote sensing.

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