scholarly journals Influence of the Lineament Geological Features on the Hydrologic Flow Direction of Wadi Al Kuf Catchment Area, Cyrenaica, Northeastern Libya

2019 ◽  
Vol 34 (3) ◽  
pp. 153-164
Author(s):  
Ammar A Ammar
Keyword(s):  
Catchment Area ◽  
Flow Direction ◽  
Rock Fracture ◽  
Main Trend ◽  
Landsat 8 ◽  
Pixel Resolution ◽  
Radar Images ◽  
Set Systems ◽  
Geological Features ◽  
Al Jabal Al Akhdar

Wadi Al Kuf Catchment Area WKCA is one of the largest watershed basins on Al Jabal al Akhdar Cyrenaica anticlinorium, the area is more than 960Km2, and considers as a semi-wet basin. This basin highly affected with lineaments geological features just like morphometric and tectonics types including fissures, fault systems and joints set systems in the highly karst lime stones of Al Jabal al Akhdar group lithological formations. These lineaments phenomena were measured and extracted from the radar images of digital terrain model of 30 meters space grid, and the hyper spectral Landsat 8 of 15 meters pixel resolution, they were processed and interpreted by several geospatial geomatics and geological software. The direction orientation and the rock density of these fissures, fractures, joints set systems, faults and the morphometric dendritic drainage pattern had been measured and illustrated from the rose diagram analysis and the geological map. The mainstream of this catchment area WKCA is the 6th order and mainly parallel to the main trend direction with the first escarpment circular fault at the major orogeny tectonic fault of Al Jabal al Akhdar uplift, and these lineaments features is averaged 58.3o  with the azimuth degree along the mainstream. The drainage density,  lineaments density analysis and distribution of the WKCA have been classified as low lineaments rock fractures in the eastern boundary of the basin, moderate lineaments rock fissures in the middle of the basin and high density of rock fracture in the western and northern boundary of the basin, these had reflected the deep percolations and infiltrations to the ground water-bearing aquifer in the WKCA through the secondary and the tertiary porosity of the hydrological karst system.

scholarly journals Compiling a new glacier inventory for southeastern Qinghai–Tibet Plateau from Landsat and PALSAR data

2016 ◽  
Vol 62 (233) ◽  
pp. 579-592 ◽  
Author(s):  
LINGHONG KE ◽  
XIAOLI DING ◽  
LEI ZHANG ◽  
JUN HU ◽  
C. K. SHUM ◽  
...  
Keyword(s):  
Shuttle Radar Topography Mission ◽  
Tibet Plateau ◽  
Landsat 8 ◽  
Glacier Change ◽  
Glacier Area ◽  
Glacier Inventory ◽  
Radar Images ◽  
Water Classification ◽  
Multi Temporal ◽  
Classification Information

ABSTRACTGlacier change has been recognized as an important climate variable due to its sensitive response to climate change. Although there are a large number of glaciers distributed over the southeastern Qinghai–Tibetan Plateau, the region is poorly represented in glacier databases due to seasonal snow cover and frequent cloud cover. Here, we present an improved glacier inventory for this region by combining Landsat observations acquired over 2011–13 (Landsat 8/OLI and Landsat TM/ETM+), coherence images from Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar images and the Shuttle Radar Topography Mission (SRTM) DEM. We present a semi-automated scheme for integrating observations from multi-temporal Landsat scenes to mitigate cloud obscuration. Further, the clean-ice observations, together with coherence information, slope constraints, vegetation cover and water classification information extracted from the Landsat scenes, are integrated to determine the debris-covered glacier area. After manual editing, we derive a new glacier inventory containing 6892 glaciers >0.02 km2, covering a total area of 6566 ± 197 km2. This new glacier inventory indicates gross overestimation in glacier area (over 30%) in previously published glacier inventories, and reveals various spatial characteristics of glaciers in the region. Our inventory can be used as a baseline dataset for future studies including glacier change assessment.

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 Using RGISTools to Estimate Water Levels in Reservoirs and Lakes

2020 ◽  
Vol 12 (12) ◽  
pp. 1934 ◽  
Author(s):  
Ana F. Militino ◽  
Manuel Montesino-SanMartin ◽  
Unai Pérez-Goya ◽  
M. Dolores Ugarte
Keyword(s):  
Time Series ◽  
Mean Squared Error ◽  
Water Levels ◽  
Process Time ◽  
Landsat 8 ◽  
Northern Spain ◽  
Software Environment ◽  
Efficient Manner ◽  
Radar Images

The combination of freely accessible satellite imagery from multiple programs improves the spatio-temporal coverage of remote sensing data, but it exhibits barriers regarding the variety of web services, file formats, and data standards. Ris an open-source software environment with state-of-the-art statistical packages for the analysis of optical imagery. However, it lacks the tools for providing unified access to multi-program archives to customize and process the time series of images. This manuscript introduces RGISTools, a new software that solves these issues, and provides a working example on water mapping, which is a socially and environmentally relevant research field. The case study uses a digital elevation model and a rarely assessed combination of Landsat-8 and Sentinel-2 imagery to determine the water level of a reservoir in Northern Spain. The case study demonstrates how to acquire and process time series of surface reflectance data in an efficient manner. Our method achieves reasonably accurate results, with a root mean squared error of 0.90 m. Future improvements of the package involve the expansion of the workflow to cover the processing of radar images. This should counteract the limitation of the cloud coverage with multi-spectral images.

scholarly journals Possibilities of including surface runoff barriers in the slope-length factor calculation in the GIS environment and its integration in the user-friendly LS-RUSLE tool

2020 ◽  
Vol 15 (No. 4) ◽  
pp. 246-257
Author(s):  
Jiří Brychta ◽  
Martina Brychtová
Keyword(s):  
Surface Runoff ◽  
Flow Direction ◽  
Slope Angle ◽  
Pixel Resolution ◽  
Slope Length ◽  
Slope Length Factor ◽  
Ephemeral Gullies ◽  
Erosion Modelling ◽  
Gis Environment ◽  
User Friendly

The effect of the morphology is key aspect of erosion modelling. In Universal Soil Loss Equation (USLE) type methods, this effect is expressed by the topographic factor (LS). The LS calculation in GIS is performed by a unit contributing area (UCA) method and can mainly be influenced by the pixel resolution, by the flow direction algorithm and by the inclusion of a hydrologically closed unit (HCU) principle, the cutoff slope angle (CSA) principle and the ephemeral gullies extraction (EG) principle. This research presents a new LS-RUSLE tool created with the inclusion of these principles in the automatic user-friendly GIS tool. The HCU principle using a specific surface runoff interruption algorithm, based on pixels with NoData values at the interruption points (pixels), appears to be key. With this procedure, the occurrence of overestimation results by flow conversion was rapidly reduced. Additionally, the reduction of extreme L and LS values calculated in the GIS environment was reached by the application of the CSA and EG principles. The results of the LS-RUSLE model show the prospective use of this tool in practice.

Simulation of streamflow in two Mediterranean catchments using a process-based model and remote sensing products

2020 ◽  
Author(s):  
Tiago Ramos ◽  
Lucian Simionesei ◽  
Marta Basso ◽  
Vivien Stefan ◽  
Ana Oliveira ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Catchment Area ◽  
Vegetation Index ◽  
Crop Growth ◽  
Assessment Tools ◽  
Landsat 8 ◽  
Network Computing ◽  
Area Index ◽  
Model Simulations

<p>Watershed modelling is one of the most important assessment tools in watershed planning and management. Nonetheless, the classic calibration of watershed models, in which a few discharge gauges near the outlet of a catchment are used to compare measured and simulated streamflow, is often criticized by not assuring that relevant processes such as evapotranspiration, soil moisture, crop growth, and groundwater recharge are well represented in the catchment area. This study aimed to simulate streamflow in two Mediterranean catchments, Orba (778km<sup>2</sup>) in Italy and Segre (1286km<sup>2</sup>) in Spain, using the physically-based, fully distributed MOHID-Land model. Model calibration/validation of streamflow was first performed following a classical approach. Different products derived from remote sensing platforms were then used to evaluate the adequacy of model simulations of crop growth and soil moisture in the catchment area.</p><p>The MOHID-Land model considers four compartments or mediums (atmosphere, porous media, soil surface and river network), computing water dynamics through the different mediums using mass and momentum conservation equations. The model was implemented in the two simulated catchments with a resolution of 1 km. Data inputs included the Digital Elevation Model over Europe (EU-DEM) with a resolution of 30 m; the soil hydraulic properties map from EU-SoilHydroGrids ver1.0 with a resolution of 250 m; the CORINE land cover map from 2012 with a resolution of 100 m; the hourly weather data (precipitation, wind velocity, relative air humidity, solar radiation and surface air temperature) from local weather stations; and the reservoir discharge data from governmental and/or regional agencies. Simulations were run from 2006-2014 for Orba and from 2008-2018 for Segre, and included a model warm-up, a calibration, and a validation period. Comparison between simulated and measured flows were performed in 2 and 10 hydrometric stations located in the Orba and Segre catchments, respectively. Four statistical parameters (R<sup>2</sup>, RMSE, PBIAS and NSE) were used to evaluate model performance, confirming the good fitting of model simulations to measured data.</p><p>Model simulations of leaf area index (LAI) were then compared with LAI maps at 30 m resolution derived from ATCOR and Landsat 8 imagery data using the Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI). Furthermore, model simulation of soil moisture were also compared at the surface depth (0-5 cm) with soil moisture maps at 1 km resolution created with the DISaggregation based on a Physical And Theoretical scale CHange (DISPATCH) algorithm for the downscaling of the 40 km SMOS (Soil Moisture and Ocean Salinity) soil moisture data using land surface temperature (LST) and NDVI data. Results showed the fundamental differences between the MOHID-Land and remote sensing outputs, with major differences being analyzed by soil units and land use classes.</p>

scholarly journals ON THE ROLE OF MESOSCALE VORTICES IN THE OIL SPILL TRANSPORT IN THE SOUTH-EASTERN BALTIC SEA (SATELLITE INFORMATION)

2019 ◽  
Vol 47 (3) ◽  
pp. 8-19 ◽  
Author(s):  
A. I. Ginzburg ◽  
E. V. Krek ◽  
A. G. Kostianoy ◽  
D. M. Soloviev
Keyword(s):  
Vortex Dynamics ◽  
Vortex Motion ◽  
Landsat 8 ◽  
Radar Images ◽  
Optical Images ◽  
Total Transport ◽  
First Time ◽  
Vortex Movement ◽  
Eastern Baltic

In this paper, on the basis of an analysis of the successive satellite optical images (MODISAqua, TIRS Landsat-8, AVHRR NOAA-18) and radar images (SAR-C Sentinel-1A, SAR-C Radarsat-2) on June 8–11, 2015, the effect of the mesoscale vortex movement (anticyclone with diameter of 35 km and associated cyclone) on the transport of oil spots in the northern part of the Gdansk Bay was demonstrated for the first time. The velocities of this transport are estimated; the observed picture of the movement of the spots is compared with their transfer according to the Seatrack Web model. The largest (about 20 cm/s) drift velocity corresponded to the spot that appeared near the periphery of the anticyclonic vortex (the region of maximum velocities), the smallest one was at the spot near the center of the vortex. At a wind speed of not more than 5 m/s on June 10 and an assumed orbital velocity of the anticyclone of the order of 20 cm/s, the contribution of the vortex motion to the total transport of the spots under the influence of wind and vortex should be decisive. The observed drift of the spots did not correspond to the forecast of their movement by the Seatrack Web numerical model, which did not take into account the vortex dynamics of the waters.

scholarly journals High-frequency monitoring of anomalous methane point sources with multispectral Sentinel-2 satellite observations

2020 ◽  
Author(s):  
Daniel J. Varon ◽  
Dylan Jervis ◽  
Jason McKeever ◽  
Ian Spence ◽  
David Gains ◽  
...  
Keyword(s):  
Point Source ◽  
High Frequency ◽  
Point Sources ◽  
Oil Field ◽  
Satellite Observations ◽  
Landsat 8 ◽  
Pixel Resolution ◽  
Spectral Bands ◽  
Frequency Monitoring ◽  
Sentinel 2

Abstract. We demonstrate the capability of the Sentinel-2 MultiSpectral satellite Instrument (MSI) to detect and quantify large methane point sources with fine pixel resolution (20 m) and rapid revisit rates (2–5 days). We present three methane column retrieval methods that use shortwave infrared (SWIR) measurements from MSI spectral bands 11 (~1560–1660 nm) and 12 (~2090–2290 nm) to detect atmospheric methane plumes. The most successful is the multi-band/multi-pass (MBMP) method, which uses a combination of the two bands and a non-plume control observation to retrieve methane columns. The MBMP method can quantify point sources down to about 3 t h−1 with precision of ~30 %–90 % (1σ) over favourable (quasi-homogeneous) surfaces. We applied our methods to perform high-frequency monitoring of strong methane point source plumes from a well-pad device in the Hassi Messaoud oil field of Algeria (October 2019 to August 2020, observed every 2.5 days) and from a compressor station in the Korpezhe oil/gas field of Turkmenistan (August 2015 to November 2020, observed every 5 days). The Algerian source was detected in 93 % of cloud-free scenes, with source rates ranging from 2.6 to 51.9 t h−1 (averaging 9.3 t h−1) until it was shut down by a flare lit in August 2020. The Turkmen source was detected in 40 % of cloud-free scenes, with variable intermittency and a 9-month shutdown period in March-December 2019 before it resumed; source rates ranged from 3.5 to 92.9 t h−1 (averaging 20.5 t h−1). Our source rate retrievals for the Korpezhe point source are in close agreement with GHGSat-D satellite observations for February 2018 to January 2019, but provide much higher observation density. Our methods can be readily applied to other satellite instruments with coarse SWIR spectral bands, such as Landsat-7 and Landsat-8. High-frequency satellite-based detection of anomalous methane point sources as demonstrated here could enable prompt corrective action to help reduce global methane emissions.

ACFNet: A Feature Fusion Network for Glacial Lake Extraction Based on Optical and Synthetic Aperture Radar Images

2021 ◽  
Vol 13 (24) ◽  
pp. 5091
Author(s):  
Jinxiao Wang ◽  
Fang Chen ◽  
Meimei Zhang ◽  
Bo Yu
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Glacial Lake ◽  
Landsat 8 ◽  
Glacial Lakes ◽  
Sar Images ◽  
Radar Images ◽  
Optical Images ◽  
Sar Data ◽  
Aperture Radar

Glacial lake extraction is essential for studying the response of glacial lakes to climate change and assessing the risks of glacial lake outburst floods. Most methods for glacial lake extraction are based on either optical images or synthetic aperture radar (SAR) images. Although deep learning methods can extract features of optical and SAR images well, efficiently fusing two modality features for glacial lake extraction with high accuracy is challenging. In this study, to make full use of the spectral characteristics of optical images and the geometric characteristics of SAR images, we propose an atrous convolution fusion network (ACFNet) to extract glacial lakes based on Landsat 8 optical images and Sentinel-1 SAR images. ACFNet adequately fuses high-level features of optical and SAR data in different receptive fields using atrous convolution. Compared with four fusion models in which data fusion occurs at the input, encoder, decoder, and output stages, two classical semantic segmentation models (SegNet and DeepLabV3+), and a recently proposed model based on U-Net, our model achieves the best results with an intersection-over-union of 0.8278. The experiments show that fully extracting the characteristics of optical and SAR data and appropriately fusing them are vital steps in a network’s performance of glacial lake extraction.

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