scholarly journals Elevation-Dependent Removal of Cirrus Clouds in Satellite Imagery

2020 ◽  
Vol 12 (3) ◽  
pp. 494
Author(s):  
Daniel Schläpfer ◽  
Rudolf Richter ◽  
Peter Reinartz
Keyword(s):  
Satellite Imagery ◽  
Atmospheric Correction ◽  
Cirrus Clouds ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Detection Algorithms ◽  
Digital Elevation ◽  
Variable Nature ◽  
Critical Issues ◽  
Elevation Model

Masking of cirrus clouds in optical satellite imagery is an important step in automated processing chains. Firstly, it is a prerequisite to a subsequent removal of cirrus effects, and secondly, it affects the atmospheric correction, i.e., aerosol and surface reflectance retrievals. Cirrus clouds can be detected with a narrow bandwidth channel near 1.38 μ m and operational detection algorithms have been developed for Landsat-8 and Sentinel-2 images. However, concerning cirrus removal in the case of elevated surfaces, current methods do not separate the ground reflected signal from the cirrus signal in the 1.38 μ m channel when performing an atmospheric correction, often resulting in an overcorrection of the cirrus influence. We propose a new operational algorithm using a Digital Elevation Model (DEM) to estimate the surface and cirrus cloud contributions in the 1.38 μ m channel and to remove cirrus effects during the surface reflectance retrieval. Due to the highly variable nature of cirrus clouds and terrain conditions, no generic quantitative results could be derived. However, results for typical cases and the achieved improvement in cirrus removal are given for selected scenes and critical issues and limitations of the approach are discussed.

scholarly journals APPLICATION OF DSM IN OBSTACLE CLEARANCE SURVEYING OF AERODROME

2016 ◽  
Vol XLI-B2 ◽  
pp. 227-233 ◽  
Author(s):  
X. Qiao ◽  
S. H. Lv ◽  
L. L. Li ◽  
X. J. Zhou ◽  
H. Y. Wang ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Satellite Imagery ◽  
Primary Objective ◽  
Considerable Improvement ◽  
Surface Model ◽  
Digital Surface Model ◽  
Horizontal Position ◽  
Obstacle Clearance ◽  
Digital Elevation ◽  
Elevation Model

Compared to the wide use of digital elevation model (DEM), digital surface model (DSM) receives less attention because that it is composed by not only terrain surface, but also vegetations and man-made objects which are usually regarded as useless information. Nevertheless, these objects are useful for the identification of obstacles around an aerodrome. The primary objective of the study was to determine the applicability of DSM in obstacle clearance surveying of aerodrome. According to the requirements of obstacle clearance surveying at QT airport, aerial and satellite imagery were used to generate DSM, by means of photogrammetry, which was spatially analyzed with the hypothetical 3D obstacle limitation surfaces (OLS) to identify the potential obstacles. Field surveying was then carried out to retrieve the accurate horizontal position and height of the obstacles. The results proved that the application of DSM could make considerable improvement in the efficiency of obstacle clearance surveying of aerodrome.

scholarly journals Determination of the Normalized Difference Vegetation Index (NDVI) with Top-of-Canopy (TOC) Reflectance from a KOMPSAT-3A Image Using Orfeo ToolBox (OTB) Extension

2020 ◽  
Vol 9 (4) ◽  
pp. 257 ◽  
Author(s):  
Kiwon Lee ◽  
Kwangseob Kim ◽  
Sun-Gu Lee ◽  
Yongseung Kim
Keyword(s):  
Open Source ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spectral Response ◽  
Atmospheric Correction ◽  
Urban Forestry ◽  
Google Earth ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Reflectance Data

Surface reflectance data obtained by the absolute atmospheric correction of satellite images are useful for land use applications. For Landsat and Sentinel-2 images, many radiometric processing methods exist, and the images are supported by most types of commercial and open-source software. However, multispectral KOMPSAT-3A images with a resolution of 2.2 m are currently lacking tools or open-source resources for obtaining top-of-canopy (TOC) reflectance data. In this study, an atmospheric correction module for KOMPSAT-3A images was newly implemented into the optical calibration algorithm in the Orfeo Toolbox (OTB), with a sensor model and spectral response data for KOMPSAT-3A. Using this module, named OTB extension for KOMPSAT-3A, experiments on the normalized difference vegetation index (NDVI) were conducted based on TOC reflectance data with or without aerosol properties from AERONET. The NDVI results for these atmospherically corrected data were compared with those from the dark object subtraction (DOS) scheme, a relative atmospheric correction method. The NDVI results obtained using TOC reflectance with or without the AERONET data were considerably different from the results obtained from the DOS scheme and the Landsat-8 surface reflectance of the Google Earth Engine (GEE). It was found that the utilization of the aerosol parameter of the AERONET data affects the NDVI results for KOMPSAT-3A images. The TOC reflectance of high-resolution satellite imagery ensures further precise analysis and the detailed interpretation of urban forestry or complex vegetation features.

scholarly journals Soil Moisture Estimation Using Citizen Observatory Data, Microwave Satellite Imagery, and Environmental Covariates

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2160
Author(s):  
Daniel Kibirige ◽  
Endre Dobos
Keyword(s):  
Soil Moisture ◽  
Expert Knowledge ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Regression Kriging ◽  
Environmental Covariates ◽  
Observatory Data ◽  
Digital Elevation ◽  
Elevation Model

Soil moisture (SM) is a key variable in the climate system and a key parameter in earth surface processes. This study aimed to test the citizen observatory (CO) data to develop a method to estimate surface SM distribution using Sentinel-1B C-band Synthetic Aperture Radar (SAR) and Landsat 8 data; acquired between January 2019 and June 2019. An agricultural region of Tard in western Hungary was chosen as the study area. In situ soil moisture measurements in the uppermost 10 cm were carried out in 36 test fields simultaneously with SAR data acquisition. The effects of environmental covariates and the backscattering coefficient on SM were analyzed to perform SM estimation procedures. Three approaches were developed and compared for a continuous four-month period, using multiple regression analysis, regression-kriging and cokriging with the digital elevation model (DEM), and Sentinel-1B C-band and Landsat 8 images. CO data were evaluated over the landscape by expert knowledge and found to be representative of the major SM distribution processes but also presenting some indifferent short-range variability that was difficult to explain at this scale. The proposed models were evaluated using statistical metrics: The coefficient of determination (R2) and root mean square error (RMSE). Multiple linear regression provides more realistic spatial patterns over the landscape, even in a data-poor environment. Regression kriging was found to be a potential tool to refine the results, while ordinary cokriging was found to be less effective. The obtained results showed that CO data complemented with Sentinel-1B SAR, Landsat 8, and terrain data has the potential to estimate and map soil moisture content.

Landform classification from a digital elevation model and satellite imagery

Geomorphology ◽  
2008 ◽  
Vol 100 (3-4) ◽  
pp. 453-464 ◽  
Author(s):  
Hossein Saadat ◽  
Robert Bonnell ◽  
Forood Sharifi ◽  
Guy Mehuys ◽  
Mohammad Namdar ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Satellite Imagery ◽  
Landform Classification ◽  
Digital Elevation ◽  
Elevation Model

scholarly journals LANDSLIDE SUSCEPTIBILITY MODELLING IN SELECTED STATES ACROSS SE. NIGERIA

2020 ◽  
Vol 4 (1) ◽  
pp. 23-27
Author(s):  
R. O. E. Ulakpa ◽  
V.U.D. Okwu ◽  
K. E. Chukwu ◽  
M. O. Eyankware
Keyword(s):  
Landslide Susceptibility ◽  
Landsat Imagery ◽  
Control Measures ◽  
Landslide Risk ◽  
Susceptibility Map ◽  
Landsat 8 ◽  
Aerial Photos ◽  
Anambra State ◽  
Digital Elevation ◽  
Elevation Model

Identification and mapping of landslide is essential for landslide risk and hazard assessment. This paper gives information on the uses of landsat imagery for mapping landslide areas ranging in size from safe area to highly prone areas. Landslide mitigation largely depends on the understanding of the nature of the factors namely: slope, soil type, lineament, lineament density, elevation, rainfall and vegetation. These factors have direct bearing on the occurrence of landslide. Identification of these factors is of paramount importance in setting out appropriate and strategic landslides control measures. Images for this study was downloaded by using remote sensing with landsat 8 ETM and aerial photos using ArcGIS 10.7 and Surfer 8 software, while Digital Elevation Model (DEM) and Google EarthPro TM were used to produce slope, drainage, lineament and elevation. From the processed landsat 8 imagery, landslide susceptibility map was produced, and landslide was category into various class; low, medium and high. From the study, it was observed that Enugu and Anambra state ranges from high to medium in terms of landslide susceptibility, Imo state ranges from medium to low.

Geoinformation mapping of landscapes on the example of the Primorskiy Ridge (Baikal region)

2020 ◽  
Vol 954 (12) ◽  
pp. 20-30
Author(s):  
Yu.V. Vanteeva ◽  
Е.А. Rasputina ◽  
S.V. Solodyankina
Keyword(s):  
Digital Elevation Model ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Topographic Wetness Index ◽  
Space Images ◽  
Topographic Position Index ◽  
Digital Elevation ◽  
Different Seasons ◽  
Position Index ◽  
Elevation Model

The authors present the results of geoinformation mapping the Primorskiy Ridge landscapes using Landsat 8 satellite images, the digital elevation model SRTM and the factor-dynamic classification of geosystems. At the first stage, the remote sensing data for different seasons were classified using the ISODATA method. Then, using the digital elevation model, the landforms were classified basing upon the topographic position index. According to combining the classification parameters of one of the space images and digital elevation model, each polygon is automatically assigned to a certain preliminary type of landscapes using boolean expressions. Legend adjustments were made basing upon the fieldwork materials. As a result, a digital landscape map of the southern part of the Primorsky Ridge was created; it reflects the landscape structure at the level of facies groups and contains attributive information about the landform, altitude, slope and aspect, topographic wetness index. The analysis of the landscape pattern showed a high fragmentation of landscape polygons, formed due to overlay operations, which indicates the need for generalization of landscape contours.

The Maras Triple Junction (southern Turkey) based on digital elevation model and satellite imagery interpretation

1994 ◽  
Vol 99 (B10) ◽  
pp. 20225-20242 ◽  
Author(s):  
Jean Chorowicz ◽  
Pascal Luxey ◽  
Nikos Lyberis ◽  
José Carvalho ◽  
Jean-François Parrot ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Satellite Imagery ◽  
Triple Junction ◽  
Digital Elevation ◽  
Southern Turkey ◽  
Elevation Model

scholarly journals DEVELOPMENT OF SCHEME FOR THE ATMOSPHERIC CORRECTION OF LANDSAT-8 OLI DATA

2018 ◽  
Vol XLII-5 ◽  
pp. 671-674
Author(s):  
V. N. Pathak ◽  
M. R. Pandya ◽  
D. B. Shah ◽  
H. J. Trivedi
Keyword(s):  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Coefficient Of Determination ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Standard Data ◽  
Satellite Signal

<p><strong>Abstract.</strong> In the present study, a physics based method called Scheme for Atmospheric Correction of Landsat-8 (SACLS8) is developed for the Operational Land Imager (OLI) sensor of Landsat-8. The Second Simulation of the Satellite Signal in the Solar Spectrum Vector (6SV) radiative transfer model is used in the simulations to obtain the surface reflectance. The surface reflectance derived using the SACL8 scheme is validated with the <i>in-situ</i> measurements of surface reflectance carried out at the homogeneous desert site located in the Little Rann of Kutch, Gujarat, India. The results are also compared with Landsat-8 surface reflectance standard data product over the same site. The good agreement of results with high coefficient of determination (R<sup>2</sup><span class="thinspace"></span>><span class="thinspace"></span>0.94) and low root mean square error (of the order of 0.03) with <i>in-situ</i> measurement values as well as those obtained from the Landsat-8 surface reflectance data establishes a good performance of the SACLS8 scheme for the atmospheric correction of Landsat-8 dataset.</p>

Sentinel-1 InSAR data by LiCSAR system

2021 ◽  
Author(s):  
Milan Lazecky ◽  
Yasser Maghsoudi Mehrani ◽  
Scott Watson ◽  
Yu Morishita ◽  
John Elliott ◽  
...  
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Atmospheric Correction ◽  
East African ◽  
Digital Elevation ◽  
African Rift ◽  
Earth Observation Satellites ◽  
Elevation Model ◽  
Data Coherence ◽  
Standard Frame

&lt;p&gt;Looking Into the Continents from Space with Synthetic Aperture Radar (LiCSAR) is a system built for large-scale interferometric processing of Sentinel-1 data. LiCSAR automatically produces geocoded wrapped and unwrapped interferograms combining every acquisition epoch with four preceding epochs, and complementary data (coherence, amplitude, line-of-sight unit vectors, digital elevation model, metadata, and atmospheric phase screen estimates by the Generic Atmospheric Correction Online Service, GACOS).&lt;/p&gt;&lt;p&gt;The LiCSAR products are generated in frame units where a standard frame covers ~220x250 km, at 0.001&amp;#176; resolution (WGS-84 coordinate system). Frames are continuously updated for tectonic and volcanic priority areas. In 2020, the LiCSAR system covered about 1,500 global frames in which we have processed over 89,000 Sentinel-1 acquisitions and generated over 300,000 interferograms. Among these, 470 frames cover 1,024 global volcanoes. We aim to cover the global seismic mask defined by the Committee on Earth Observation Satellites (CEOS), but focus initially on the Alpine-Himalayan belt and East African Rift.&lt;/p&gt;&lt;p&gt;We serve the products as open and freely accessible through our web portal: https://comet.nerc.ac.uk/comet-lics-portal and aim to provide them to shared infrastructures as the European Plate Observing System (EPOS). We also generate rapid response coseismic interferograms for earthquakes with moment magnitude (Mw)&gt; 5.5&amp;#160; a few hours after the postseismic data become available, and we update frames covering active volcanoes twice per day.&lt;/p&gt;&lt;p&gt;Our products can be directly converted to displacement time series and velocities using&amp;#160; the LiCSBAS time series analysis software. We present solutions implemented in LiCSAR, and show several case studies that use LiCSAR and LiCSBAS products to measure tectonic and volcanic deformation.&lt;/p&gt;&lt;p&gt;&lt;img src=&quot;https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.1c122b867cff59390830161/sdaolpUECMynit/12UGE&amp;app=m&amp;a=0&amp;c=02895a62108de9393057db6a355e3b06&amp;ct=x&amp;pn=gnp.elif&amp;d=1&quot; alt=&quot;&quot;&gt;&lt;/p&gt;

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