scholarly journals Sharpening of Worldview-3 Satellite Images by Generating Optimal High-Spatial-Resolution Images

2020 ◽  
Vol 10 (20) ◽  
pp. 7313
Author(s):  
Honglyun Park ◽  
Namkyung Kim ◽  
Sangwook Park ◽  
Jaewan Choi
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Near Infrared ◽  
Spectral Distortion ◽  
Swir Band ◽  
Sentinel 2A ◽  
Types Of Information ◽  
Shortwave Infrared ◽  
Distortion Reduction

Compared to using images in the visible and near-infrared (VNIR) wavelength range only, remotely sensed satellite imagery from the spectral wavelengths of both VNIR and shortwave infrared (SWIR), such as Sentinel-2A and Worldview-3, is more effective for analyzing various types of information for tasks such as land cover mapping, environmental monitoring and land use change detection. In this manuscript, a new sharpening technique to enhance the spatial resolution of Worldview-3 satellite imagery with various spatial and spectral resolutions is proposed. Selected and synthesized band schemes were used to produce optimal panchromatic images; then, sharpened images were generated by applying the Gram-Schmidt adaptive (GSA) and Gram-Schmidt 2 (GS2) techniques, which are component substitution (CS)- and multiresolution analysis (MRA)-based algorithms, respectively. In addition, to minimize the spectral distortion of the initial sharpened image, a postprocessing methodology for spectral distortion reduction was developed. Qualitative and quantitative evaluation of the sharpened images showed that the pansharpening performance using the GS2 technique based on the selected band scheme and spectral distortion reduction was the best. To confirm the usability of the SWIR band, supervised classification based on machine learning was performed on the pansharpened images obtained by applying the technique proposed in this study and on the pansharpened images obtained by the VNIR bands only. The classification accuracy of the results using SWIR bands was higher than that of VNIR bands only. In particular, it was confirmed that the accuracy of the classification of artificial facilities known to be effective for SWIR bands was greatly improved.

scholarly journals Mineral Detection Using Sharpened VNIR and SWIR Bands of Worldview-3 Satellite Imagery

2021 ◽  
Vol 13 (10) ◽  
pp. 5518
Author(s):  
Honglyun Park ◽  
Jaewan Choi
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Near Infrared ◽  
False Negative ◽  
Similarity Score ◽  
Majority Voting ◽  
Similarity Analysis ◽  
Spectral Angle Mapper ◽  
Mineral Detection ◽  
Shortwave Infrared

Worldview-3 satellite imagery provides panchromatic images with a high spatial resolution and visible near infrared (VNIR) and shortwave infrared (SWIR) bands with a low spatial resolution. These images can be used for various applications such as environmental analysis, urban monitoring and surveying for sustainability. In this study, mineral detection was performed using Worldview-3 satellite imagery. A pansharpening technique was applied to the spatial resolution of the panchromatic image to effectively utilize the VNIR and SWIR bands of Worldview-3 satellite imagery. The following representative similarity analysis techniques were implemented for the mineral detection: the spectral angle mapper (SAM), spectral information divergence (SID) and the normalized spectral similarity score (NS3). In addition, pixels that could be estimated to indicate minerals were calculated by applying an empirical threshold to each similarity analysis result. A majority voting technique was applied to the results of each similarity analysis and pixels estimated to indicate minerals were finally selected. The results of each similarity analysis were compared to evaluate the accuracy of the proposed methods. From that comparison, it could be confirmed that false negative and false positive rates decreased when the methods proposed in the present study were applied.

scholarly journals SHARPENDING OF THE VNIR AND SWIR BANDS OF THE WIDE BAND SPECTRAL IMAGER ONBOARD TIANGONG-II IMAGERY USING THE SELECTED BANDS

2018 ◽  
Vol XLII-3 ◽  
pp. 1085-1092 ◽  
Author(s):  
Q. Liu ◽  
X. Li ◽  
G. Liu ◽  
C. Huang ◽  
H. Li ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Near Infrared ◽  
Wide Band ◽  
Spectral Bands ◽  
Texture Information ◽  
Swir Band ◽  
Texture Characteristics ◽  
Spectral Imager ◽  
Shortwave Infrared ◽  
Band Image

The Tiangong-II space lab was launched at the Jiuquan Satellite Launch Center of China on September 15, 2016. The Wide Band Spectral Imager (WBSI) onboard the Tiangong-II has 14 visible and near-infrared (VNIR) spectral bands covering the range from 403–990 nm and two shortwave infrared (SWIR) bands covering the range from 1230–1250 nm and 1628–1652 nm respectively. In this paper the selected bands are proposed which aims at considering the closest spectral similarities between the VNIR with 100 m spatial resolution and SWIR bands with 200 m spatial resolution. The evaluation of Gram-Schmidt transform (GS) sharpening techniques embedded in ENVI software is presented based on four types of the different low resolution pan band. The experimental results indicated that the VNIR band with higher CC value with the raw SWIR Band was selected, more texture information was injected the corresponding sharpened SWIR band image, and at that time another sharpened SWIR band image preserve the similar spectral and texture characteristics to the raw SWIR band image.

scholarly journals EXTRACTION OF BUILT-UP AREA USING HIGH RESOLUTION SENTINEL-2A AND GOOGLE SATELLITE IMAGERY

2018 ◽  
Vol XLII-4/W9 ◽  
pp. 165-169 ◽  
Author(s):  
S. Vigneshwaran ◽  
S. Vasantha Kumar
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Near Infrared ◽  
Accurate Information ◽  
Open Source Data ◽  
Kappa Value ◽  
Moderate Resolution ◽  
Sentinel 2A ◽  
Index Value ◽  
Normalized Difference Index

<p><strong>Abstract.</strong> Accurate information about the built-up area in a city or town is essential for urban planners for proper planning of urban infrastructure facilities and other basic amenities. The normalized difference indices available in literature for built-up area extraction are mostly based on moderate resolution images such as Landsat Thematic Mapper (TM) and enhanced TM (ETM+) and may not be applicable for high resolution images such as Sentinel-2A. In the present study, an attempt has been made to extract the built-up area from Sentinel-2A satellite data of Chennai, India using normalized difference index (NDI) with different band combinations. It was found that the built-up area was clearly distinguishable when the index value ranges between &amp;minus;0.29 and &amp;minus;0.09 in blue and near-infrared (NIR) band combination. Post extraction editing using Google satellite imagery was also attempted to improve the extraction results. The results showed an overall accuracy of 90% and Kappa value of 0.785. Same approach when applied for another area also yields good results with overall accuracy of 92% and Kappa value of 0.83. As the proposed approach is simple to understand, yields accurate results and requires only open source data, the same can be used for extracting the built-up area using Sentinel-2A and Google satellite imagery.</p>

Detecting Cutleaf Teasel (Dipsacus laciniatus) along a Missouri Highway with Hyperspectral Imagery

2012 ◽  
Vol 5 (2) ◽  
pp. 155-163 ◽  
Author(s):  
Diego J. Bentivegna ◽  
Reid J. Smeda ◽  
Cuizhen Wang
Keyword(s):  
Spatial Resolution ◽  
Native Species ◽  
Near Infrared ◽  
Bare Soil ◽  
Flowering Plants ◽  
Hyperspectral Images ◽  
Accurate Assessment ◽  
Water Classification ◽  
Management Techniques

AbstractCutleaf teasel is an invasive, biennial plant that poses a significant threat to native species along roadsides in Missouri. Flowering plants, together with understory rosettes, often grow in dense patches. Detection of cutleaf teasel patches and accurate assessment of the infested area can enable targeted management along highways. Few studies have been conducted to identify specific species among a complex of vegetation composition along roadsides. In this study, hyperspectral images (63 bands in visible to near-infrared spectral region) with high spatial resolution (1 m) were analyzed to detect cutleaf teasel in two areas along a 6.44-km (4-mi) section of Interstate I-70 in mid Missouri. The identified classes included cutleaf teasel, bare soil, tree/shrub, grass/other broadleaf plants, and water. Classification of cutleaf teasel reached a user's accuracy of 82 to 84% and a producer's accuracy of 89% in the two sites. The conditional κ value was around 0.9 in both sites. The image-classified cutleaf teasel map provides a practical mechanism for identifying locations and extents of cutleaf teasel infestation so that specific cutleaf teasel management techniques can be implemented.Cutleaf teasel is an exotic weed that infests roadside environments in Missouri. As a growing biennial, the plant develops as a rosette during the first year and bolts during the second. Dense patches contain flowering plants with understory rosettes. The objective of this work was to develop approaches for detecting cutleaf teasel patches with accurate assessment in a complex of species along a roadside. Thus, management of cutleaf teasel could be located at specific sites. Two hyperspectral images (63 bands with 1-m spatial resolution) were analyzed to detect cutleaf teasel along the Interstate Highway I-70 in mid Missouri. Classification of cutleaf teasel reached a user's accuracy of 82 to 84% and a producer's accuracy of 89% at the two sites. The image-classified teasel map provides a practical mechanism for identifying the locations and extents of cutleaf teasel infestation so that specific management techniques can be implemented.

scholarly journals Urban thermal micro-mapping using satellite imagery and ground-truth measurements: Kyiv city area case study

2019 ◽  
pp. 40-48
Author(s):  
Iryna Piestova ◽  
Mykola Lubskyi ◽  
Mykhailo Svideniuk ◽  
Stanislav Golubov ◽  
Oleksandr Laptiev
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Thermal Conditions ◽  
Ground Truth ◽  
Bare Soil ◽  
Landsat 8 ◽  
Thermal Anomalies ◽  
City Area ◽  
Thermal Emissivity ◽  
Sentinel 2A

The aim of this research is to enhance approaches existing for the assessment of cities thermal conditions under climate change impact by using multispectral satellite data for Kyiv city area. This paper describes the method and results of the Earth’s surface temperature (LST) and thermal emissivity calculation. Particularly, the thermal distribution was estimated based on spectral densities according to Planck’s law for “grey bodies” by using the Landsat-8 TIRS and Sentinel-2 MSI satellite imagery. Furthermore, the result was calibrated by ground data collected during the ground-truth measurements of the typical city surfaces temperature and thermal emissivity. The spatial resolution of the LST images obtained was enhanced by using the approach of subpixel processing, that is the pairs of invariant images shifted with subpixel accuracy. As a result, such an approach allowed to enhance the spatial resolution of the image up 46%, which is much higher than the potential performance of the thermal imaging sensors existing. The interrelation between the Earth’s surface type and the temperature was revealed by the results of the Sentinel-2A MSI image of 21 August 2017 supervised classification. Thus, the image was divided into the six major classes of the urban environment: building’s rooftops, roads surface, bare soil, grass, wood, and water. As a result, surfaces with vegetation much more cool next to artificial ones. The time-series analysis of 18 thermal images (Landsat TM and Landsat-8 TIRS) of Kyiv for the period from 6 Jun 1985 till 1 June 2018 was done for spatiotemporal changes investigation. Therefore, the sites of the LST thermal anomalies caused by landscape changes were developed. Among them are the sites of increased LST where thw “Olimpiyskiy” national sport center and adjacent parking was built and the site of decreased LST where the tram depot was liquidated and the territory was flooded.

scholarly journals A development of the Enhanced Built-up and Bareness Index (EBBI) based on combination of multi-resolution Landsat 8 and Sentinel 2 MSI images

2021 ◽  
Vol 62 (1) ◽  
pp. 1-9
Author(s):  
Hung Le Trinh ◽  
Ha Thu Thi Le ◽  
Loc Duc Le ◽  
Long Thanh Nguyen ◽  
Keyword(s):  
Land Cover ◽  
Satellite Imagery ◽  
Near Infrared ◽  
Urban Land ◽  
Urban Land Use ◽  
Landsat 8 ◽  
Infrared Band ◽  
Bare Land ◽  
Sentinel 2

Classification of built-up land and bare land on remote sensing images is a very difficult problem due to the complexity of the urban land cover. Several urban indices have been proposed to improve the accuracy in classifying urban land use/land cover from optical satellite imagery. This paper presents an development of the EBBI (Enhanced Built-up and Bareness Index) index based on the combination of Landsat 8 and Sentinel 2 multi-resolution satellite imagery. Near infrared band (band 8a), short wave infrared band (band 11) of Sentinel 2 MSI image and thermal infrared band (band 10) Landsat 8 image were used to calculate EBBI index. The results obtained show that the combination of Landsat 8 and Sentinel 2 satellite images improves the spatial resolution of EBBI index image, thereby improving the accuracy of classification of bare land and built-up land by about 5% compared with the case using only Landsat 8 images.

scholarly journals Pre-launch calibration results of the TROPOMI payload on-board the Sentinel 5 Precursor satellite

2018 ◽  
Author(s):  
Quintus Kleipool ◽  
Antje Ludewig ◽  
Ljubiša Babic ◽  
Rolf Bartstra ◽  
Remco Braak ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Near Infrared ◽  
Imaging System ◽  
Spectral Band ◽  
High Sensitivity ◽  
Radiometric Calibration ◽  
Random Errors ◽  
Synchronous Orbit ◽  
Shortwave Infrared ◽  
Ground Calibration

Abstract. The Sentinel 5 precursor satellite was successfully launched on 13th October 2017, carrying the Tropospheric Monitoring Instrument TROPOMI as its single payload. TROPOMI is the next generation atmospheric sounding instrument, continuing the successes of GOME, SCIAMACHY, OMI and OMPs, with higher spatial resolution, improved sensitivity and extended wavelength range. The instrument contains four spectrometers, divided over two modules sharing a common telescope, measuring the ultraviolet, visible, near-infrared and shortwave infrared reflectance of the Earth. The imaging system enables daily global coverage using a push-broom configuration, with a spatial resolution as low as 7 × 3.5 km2 in nadir from a Sun-synchronous orbit at 824 km and an equator crossing time of 13:30 local solar time. This article reports the pre-launch calibration status of the TROPOMI payload as derived from the on-ground calibration effort. Stringent requirements are imposed on the quality of on-ground calibration in order to match the high sensitivity of the instrument. In case that the systematic errors that originate from the calibration exceed the random errors in the observations, the scientific products may be compromised. A new methodology has been employed during the analysis of the obtained calibration measurements to ensure the consistency and validity of the calibration. This was achieved by using the production grade Level 0 to 1b data processor in a closed-loop validation setup. Using this approach the consistency between the calibration and the L1b product could be established, as well as confidence in the obtained calibration result. This article introduces this novel calibration approach, and describes all relevant calibrated instrument properties as they were derived before launch of the mission. For most of the relevant properties compliancy with the requirements could be established, including the knowledge of the instrument spectral and spatial response functions, and the absolute radiometric calibration. Partial compliancy was established for the straylight correction; especially the out-of-spectral-band correction for the NIR channel needs further validation. Incompliance was reported for the relative radiometric calibration of the Sun port diffusers. These latter two subjects will be addressed during the in-flight commissioning phase in the first 6 months following launch.

scholarly journals Determination of the TROPOMI-SWIR instrument spectral response function

2018 ◽  
Vol 11 (7) ◽  
pp. 3917-3933 ◽  
Author(s):  
Richard M. van Hees ◽  
Paul J. J. Tol ◽  
Sidney Cadot ◽  
Matthijs Krijger ◽  
Stefan T. Persijn ◽  
...  
Keyword(s):  
Response Function ◽  
Near Infrared ◽  
Spectral Response ◽  
Monochromatic Light ◽  
Imaging Spectrometer ◽  
Swir Band ◽  
Shortwave Infrared ◽  
Single Instrument

Abstract. The Tropospheric Monitoring Instrument (TROPOMI) is the single instrument on board the ESA Copernicus Sentinel-5 Precursor satellite. TROPOMI is a nadir-viewing imaging spectrometer with bands in the ultraviolet and visible, the near infrared and the shortwave infrared (SWIR). An accurate instrument spectral response function (ISRF) is required in the SWIR band where absorption lines of CO, methane and water vapor overlap. In this paper, we report on the determination of the TROPOMI-SWIR ISRF during an extensive on-ground calibration campaign. Measurements are taken with a monochromatic light source scanning the whole detector, using the spectrometer itself to determine the light intensity and wavelength. The accuracy of the resulting ISRF calibration key data is well within the requirement for trace-gas retrievals. Long-term in-flight monitoring of SWIR ISRF is achieved using five on-board diode lasers.

scholarly journals Optimized Performance Parameters for Nighttime Multispectral Satellite Imagery to Analyze Lightings in Urban Areas

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3313 ◽  
Author(s):  
Jasper de Meester ◽  
Tobias Storch
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Near Infrared ◽  
Atmospheric Effects ◽  
Spectral Bands ◽  
Multispectral Satellite Imagery ◽  
Radiation Sources ◽  
Yellow Orange ◽  
Band Combinations

Contrary to its daytime counterpart, nighttime visible and near infrared (VIS/NIR) satellite imagery is limited in both spectral and spatial resolution. Nevertheless, the relevance of such systems is unquestioned with applications to, e.g., examine urban areas, derive light pollution, and estimate energy consumption. To determine optimal spectral bands together with required radiometric and spatial resolution, at-sensor radiances are simulated based on combinations of lamp spectra with typical luminances according to lighting standards, surface reflectances, and radiative transfers for the consideration of atmospheric effects. Various band combinations are evaluated for their ability to differentiate between lighting types and to estimate the important lighting parameters: efficacy to produce visible light, percentage of emissions attributable to the blue part of the spectrum, and assessment of the perceived color of radiation sources. The selected bands are located in the green, blue, yellow-orange, near infrared, and red parts of the spectrum and include one panchromatic band. However, these nighttime bands tailored to artificial light emissions differ significantly from the typical daytime bands focusing on surface reflectances. Compared to existing or proposed nighttime or daytime satellites, the recommended characteristics improve, e.g., classification of lighting types by >10%. The simulations illustrate the feasible improvements in nocturnal VIS/NIR remote sensing which will lead to advanced applications.

scholarly journals Radiometric Comparison of 1.6-μm CO2 Absorption Band of Greenhouse Gases Observing Satellite (GOSAT) TANSO-FTS with Suomi-NPP VIIRS SWIR Band

2016 ◽  
Vol 33 (7) ◽  
pp. 1443-1453
Author(s):  
Sirish Uprety ◽  
Changyong Cao
Keyword(s):  
Greenhouse Gases ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Co2 Absorption ◽  
New Methods ◽  
Swir Band ◽  
Long Term Trends ◽  
Global Concern ◽  
Shortwave Infrared

AbstractAn atmospheric CO2 increase has become a progressively important global concern in recent past decades. Since the 1950s, the Keeling curve has documented the atmospheric CO2 increase as well as seasonal variations, which also intrigued scientists to develop new methods for global CO2 measurements from satellites. One of the dedicated satellite missions is the CO2 measurement in the 1.6-μm shortwave infrared spectra by the Greenhouse Gases Observing Satellite (GOSAT) Thermal and Near Infrared Sensor for Carbon Observations–Fourier Transform Spectrometer (TANSO-FTS) instrument. While this spectral region has unique advantages in detecting lower-trophosphere CO2, there are many challenges because it relies on accurate measurements of reflected solar radiance from Earth’s surface. Therefore, the calibration of the TANSO-FTS CO2 has a direct impact on the CO2 retrievals and its long-term trends. Coincidently, the Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) 1.6-μm band spectrally overlaps with the TANSO-FTS CO2 band, and both satellites are in orbit with periodical simultaneous nadir overpass measurements. This study performs an intercomparison of VIIRS and the TANSO-FTS CO2 band in an effort to evaluate and improve the radiometric consistency. Understanding the differences provides feedback on how well the GOSAT TANSO-FTS is performing over time, which is critical to ensure a well-calibrated, stable, and bias-free CO2 product.

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