scholarly journals The Influence of Shadow Effects on the Spectral Characteristics of Glacial Meltwater

2020 ◽  
Vol 13 (1) ◽  
pp. 36
Author(s):  
Kornelia Anna Wójcik-Długoborska ◽  
Robert Józef Bialik
Keyword(s):  
Spectral Properties ◽  
Satellite Images ◽  
Near Infrared ◽  
Spectral Band ◽  
Spectral Characteristics ◽  
High Sensitivity ◽  
Surface Model ◽  
Landsat 8 ◽  
Pixel Resolution ◽  
Ice Phenomena

The phenomenon of shadows due to glaciers is investigated in Antarctica. The observed shadow effect disrupts analyses conducted by remote sensing and is a challenge in the assessment of sediment meltwater plumes in polar marine environments. A DJI Inspire 2 drone equipped with a Zenmuse x5s camera was used to generate a digital surface model (DSM) of 6 King George Island glaciers: Ecology, Dera, Zalewski, Ladies, Krak, and Vieville. On this basis, shaded areas of coves near glaciers were traced. For the first time, spectral characteristics of shaded meltwater were observed with the simultaneous use of a Sequoia+ spectral camera mounted on a Parrot Bluegrass drone and in Landsat 8 satellite images. In total, 44 drone flights were made, and 399 satellite images were analyzed. Among them, four drone spectral images and four satellite images were selected, meeting the condition of a visible shadow. For homogeneous waters (deep, low turbidity, without ice phenomena), the spectral properties tend to change during the approach to an obstacle casting a shadow especially during low shortwave downward radiation. In this case, in the shade, the amount of radiation reflected in the green spectral band decreases by 50% far from the obstacle and by 43% near the obstacle, while in near infrared (NIR), it decreases by 42% and 21%, respectively. With highly turbid, shallow water and ice phenomena, this tendency does not occur. It was found that the green spectral band had the highest contrast in the amount of reflected radiation between nonshaded and shaded areas, but due to its high sensitivity, the analysis could have been overestimated. The spectral properties of shaded meltwater differ depending on the distance from the glacier front, which is related to the saturation of the water with sediment particles. We discovered that the pixel aggregation of uniform areas caused the loss of detailed information, while pixel aggregation of nonuniform, shallow areas with ice phenomena caused changes and the loss of original information. During the aggregation of the original pixel resolution (15 cm) up to 30 m, the smallest error occurred in the area with a homogeneous water surface, while the greatest error (over 100%) was identified in the places where the water was strongly cloudy or there were ice phenomena.

scholarly journals Spatiotemporal Fusion of Formosat-2 and Landsat-8 Satellite Images: A Comparison of “Super Resolution-Then-Blend” and “Blend-Then-Super Resolution” Approaches

2021 ◽  
Vol 13 (4) ◽  
pp. 606
Author(s):  
Tee-Ann Teo ◽  
Yu-Ju Fu
Keyword(s):  
Satellite Images ◽  
Traditional Approach ◽  
Spectral Band ◽  
Super Resolution ◽  
High Temporal Resolution ◽  
Landsat 8 ◽  
Fusion Model ◽  
Image Blending ◽  
Fine Resolution

The spatiotemporal fusion technique has the advantages of generating time-series images with high-spatial and high-temporal resolution from coarse-resolution to fine-resolution images. A hybrid fusion method that integrates image blending (i.e., spatial and temporal adaptive reflectance fusion model, STARFM) and super-resolution (i.e., very deep super resolution, VDSR) techniques for the spatiotemporal fusion of 8 m Formosat-2 and 30 m Landsat-8 satellite images is proposed. Two different fusion approaches, namely Blend-then-Super-Resolution and Super-Resolution (SR)-then-Blend, were developed to improve the results of spatiotemporal fusion. The SR-then-Blend approach performs SR before image blending. The SR refines the image resampling stage on generating the same pixel-size of coarse- and fine-resolution images. The Blend-then-SR approach is aimed at refining the spatial details after image blending. Several quality indices were used to analyze the quality of the different fusion approaches. Experimental results showed that the performance of the hybrid method is slightly better than the traditional approach. Images obtained using SR-then-Blend are more similar to the real observed images compared with images acquired using Blend-then-SR. The overall mean bias of SR-then-Blend was 4% lower than Blend-then-SR, and nearly 3% improvement for overall standard deviation in SR-B. The VDSR technique reduces the systematic deviation in spectral band between Formosat-2 and Landsat-8 satellite images. The integration of STARFM and the VDSR model is useful for improving the quality of spatiotemporal fusion.

A phthalocyanine-based fluorescent sensor for Zn2+ ion

2013 ◽  
Vol 17 (01n02) ◽  
pp. 99-103 ◽  
Author(s):  
Hui He ◽  
Jian-Yong Liu ◽  
Dennis K.P. Ng
Keyword(s):  
Metal Ions ◽  
Spectral Properties ◽  
Fluorescence Spectra ◽  
Near Infrared ◽  
Fluorescent Sensor ◽  
High Sensitivity ◽  
Absorption And Fluorescence Spectra

This paper describes the preparation and spectral properties of a near-infrared fluorophore in which two bis(2-picolyl)amino moieties are axially linked to a silicon(IV) phthalocyanine core. The effects of various metal ions on its absorption and fluorescence spectra have been examined. The results indicate that this compound shows a high sensitivity and moderate selectivity toward Zn2+ ion.

scholarly journals An UAV and Satellite Multispectral Data Approach to Monitor Water Quality in Small Reservoirs

2020 ◽  
Vol 12 (9) ◽  
pp. 1514 ◽  
Author(s):  
Carmen Cillero Castro ◽  
Jose Antonio Domínguez Gómez ◽  
Jordi Delgado Martín ◽  
Boris Alejandro Hinojo Sánchez ◽  
Jose Luis Cereijo Arango ◽  
...  
Keyword(s):  
Near Infrared ◽  
Spectral Band ◽  
Water Reservoir ◽  
Cyanobacterial Blooms ◽  
Landsat 8 ◽  
Chl A ◽  
Multispectral Data ◽  
Small Reservoirs ◽  
In Situ Data ◽  
Drinking Water Reservoir

A multi-sensor and multi-scale monitoring tool for the spatially explicit and periodic monitoring of eutrophication in a small drinking water reservoir is presented. The tool was built with freely available satellite and in situ data combined with Unmanned Aerial Vehicle (UAV)-based technology. The goal is to evaluate the performance of a multi-platform approach for the trophic state monitoring with images obtained with MultiSpectral Sensors on board satellites Sentinel 2 (S2A and S2B), Landsat 8 (L8) and UAV. We assessed the performance of three different sensors (MultiSpectral Instrument (MSI), Operational Land Imager (OLI) and Rededge Micasense) for retrieving the pigment chlorophyll-a (chl-a), as a quantitative descriptor of phytoplankton biomass and trophic level. The study was conducted in a waterbody affected by cyanobacterial blooms, one of the most important eutrophication-derived risks for human health. Different empirical models and band indices were evaluated. Spectral band combinations using red and near-infrared (NIR) bands were the most suitable for retrieving chl-a concentration (especially 2 band algorithm (2BDA), the Surface Algal Bloom Index (SABI) and 3 band algorithm (3BDA)) even though blue and green bands were useful to classify UAV images into two chl-a ranges. The results show a moderately good agreement among the three sensors at different spatial resolutions (10 m., 30 m. and 8 cm.), indicating a high potential for the development of a multi-platform and multi-sensor approach for the eutrophication monitoring of small reservoirs.

scholarly journals Identification of Continental Wetlands Using Different Orbital Remote Sensors

Terr Plural ◽  
2021 ◽  
Vol 15 ◽  
pp. 1-25
Author(s):  
Isadora Taborda Silva ◽  
Jéssica Rabito Chaves ◽  
Helen Rezende Figueiredo ◽  
Bruno Silva Ferreira ◽  
César Claudio Cáceres Encina ◽  
...  
Keyword(s):  
Near Infrared ◽  
Spectral Band ◽  
Landsat 8 ◽  
Remote Sensors ◽  
False Color ◽  
False Color Composite ◽  
International Importance ◽  
Color Composite ◽  
Shortwave Infrared ◽  
Sentinel 2

This paper evaluates the potential of false-color composite images, from 3 different remote sensing satellites, for the identification of continental wetlands. Landsat 8, Sentinel-2 and CBERS-4 scenes from three different Ramsar sites (i.e., sites designated to be of international importance) two sites located within the Mato-Grossense Pantanal and one within the Sul-mato-grossense were used for analyses. For each site, images from both the dry and rainy seasons were analyzed using Near-Infrared (NIR), Shortwave Infrared (SWIR), and visible (VIS) bands. The results show that false-color composite images from both the Landsat 8 and the Sentinel-2 satellites, with both SWIR 2-NIR-BLUE and NIR-SWIR-RED spectral band combinations, allow the identification of wetlands.

scholarly journals Forest Fire Area Detection by Using Landsat-8 and Sentinel-2 Satellite Images: A Case Study in Mugla, Turkey

2020 ◽  
Author(s):  
Bahadir Kurnaz ◽  
Caglar Bayik ◽  
Saygin Abdikan
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Satellite Images ◽  
Near Infrared ◽  
Kappa Statistics ◽  
Landsat 8 ◽  
Important Place ◽  
Burn Scar ◽  
Object Based ◽  
Sentinel 2

Abstract Background: Forests have an extremely important place in the ecosystem in terms of ensuring social and environmental balance. The biggest danger for forests that have this importance is forest fires due to various reasons. It is extremely important to estimate the formation and behavior characteristics of fires in terms of combating forest fires. Using the satellite images obtained with the developing technology for this purpose provides great convenience in the detection of the fire areas and the severity of the fire affected. In this study, forest fire that occurred in the Zeytinköy region of Muğla province was investigated using remotely sensed images. According to the reference data provided by the General Directorate of Forestry (GDF), 425 hectares of area was destroyed by fire. In this study, it is aimed to extract burn scar by applying seven vegetation indexes on Sentinel-2 and Landsat-8 satellite images. Additionally, forest fire areas have been determined with the object-based classification technique. Results: As a result of the study, when the obtained results are compared with the values obtained from GDF, it is determined that object based analysis of Sentinel-2 provided the highest accuracy with 98.36% overall accuracy and 0.976 kappa statistics. Comparing the results of spectral indices of Sentinel-2 and Landsat-8, Sentinel-2 resulted better results in all indices. Among the indices RdNBR and dNDVI obtained better results than other indices with Sentinel-2 and Landsat-8, respectively. Conclusions: In general, it has been determined that Sentinel-2 data is more suitable than Landsat-8 satellite images for determining Turkish red pine forest fired areas. Red and near infrared based images can be used for rapid mapping of fired areas. The results also indicated that the indices provided by multi-temporal Sentinel-2 data can assist forest management for rapid monitoring of fire scars and also for evolution of reforestation after fire.

The urban areas classification methodology according to multi-zone images of Sentinel 2 and Landsat 8 (on the example of the city of Thanh Hoa, Vietnam)

2020 ◽  
Vol 956 (2) ◽  
pp. 40-49
Author(s):  
Le Hung Trinh ◽  
Dinh Sinh Mai ◽  
V.R. Zablotskii
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Satellite Images ◽  
Near Infrared ◽  
Landsat 8 ◽  
Land Use Classification ◽  
Infrared Band ◽  
The Status ◽  
The Impact ◽  
Sentinel 2

In recent years, land cover changes very quickly in urban areas due to the impact of population growth and socio-economic development. The authors present the method of land cover/land use classification based on the combination of Sentinel 2 and Landsat 8 multi-resolution satellite images. A middle infrared band (band 11), a near infrared (band 8) of Sentinel 2 image and a thermal infrared one (band 10) of Landsat 8 image were used to calculate EBBI (Enhanced Built-up and Barreness Index). The EBBI index and Sentinel 2 spectral bands with spatial resolution 10 m (band 2, 3, 4, 8) were used to classify the land cover. The obtained results showed that, the method of land cover classification based on combination of Sentinel 2 and Landsat 8 satellite images improves the overall accuracy by about 5 % compared with the one using only Sentinel 2 data. The results obtained at the study can be used for the management, assessment and monitoring the status and dynamics of land cover in urban areas.

scholarly journals GENERATING ARTIFICIAL NEAR INFRARED SPECTRAL BAND FROM RGB IMAGE USING CONDITIONAL GENERATIVE ADVERSARIAL NETWORK

2020 ◽  
Vol V-3-2020 ◽  
pp. 279-285
Author(s):  
X. Yuan ◽  
J. Tian ◽  
P. Reinartz
Keyword(s):  
Near Infrared ◽  
Spectral Band ◽  
Depth Estimation ◽  
Absolute Error ◽  
Physical Models ◽  
Generative Adversarial Networks ◽  
Surface Model ◽  
Generative Adversarial Network ◽  
Sensing Applications ◽  
Rgb Image

Abstract. Near infrared bands (NIR) provide rich information for many remote sensing applications. In addition to deriving useful indices to delineate water and vegetation, near infrared channels could also be used to facilitate image pre-processing. However, synthesizing bands from RGB spectrum is not an easy task. The inter-correlations between bands are not clearly identified in physical models. Generative adversarial networks (GAN) have been used in many tasks such as generating photorealistic images, monocular depth estimation and Digital Surface Model (DSM) refinement etc. Conditional GAN is different in that it observes some data as a condition. In this paper, we explore a cGAN network structure to generate a NIR spectral band that is conditioned on the input RGB image. We test different discriminators and loss functions, and evaluate results using various metrics. The best simulated NIR channel has a mean absolute error of around 5 percent in Sentinel-2 dataset. In addition, the simulated NIR image can correctly distinguish between various classes of landcover.

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 Morphotectonic Characteristics Of Cisadane Watersshed Based On Satellite Images Analysis

2019 ◽  
Vol 20 (3) ◽  
pp. 175
Author(s):  
Sonny Mawardi ◽  
Emi Sukiyah ◽  
Iyan Haryanto
Keyword(s):  
Satellite Images ◽  
Digital Terrain Model ◽  
Tectonic Deformation ◽  
Surface Model ◽  
Landsat 8 ◽  
Infrastructure Development ◽  
Economic Activities ◽  
Terrain Model ◽  
Digital Terrain ◽  
Geomorphological Units

Cisadane Watershed is one of the most rapidly growing areas and infrastructure development, and has developed as a residential, industrial, administrative centers and other economic activities. The purpose of this paper is to use remote sensing satellite imageries to identify the morphotectonic characteristics of the Cisadane watershed both qualitatively and quantitatively. Processing stereomodel, stereoplotting and stereocompilation on TerraSAR-X Digital Surface Model (DSM) and SPOT 6 imageries, produced the  Digital Terrain Model (DTM) image, which has not been affected by land cover. Fusion of the DTM  and Landsat 8 RGB 567+8 images  is used to interpret the distribution of lithology, geomorphological units, and lineaments, which are an indication of geological structures. The morphotectonic characteristics of sub-watersheds qualitatively was carried out a bifurcation ratio calculation (Rb) which indicates tectonic deformation. Based on the analysis of satellite images both qualitatively and quantitatively, the morphotectonic characteristics of the upstream, middle and downstream Cisadane Watershed have been deformed.Keywords : satellite images, morphotectonic, DSM, DTM, Cisadane Watershed.

scholarly journals The monitoring of southern chernozem soil humus content with using multispectral satellite images Landsat: spatial and temporal aspects

2016 ◽  
Vol 17 (1-2) ◽  
pp. 22-30
Author(s):  
S. G. Chornyy ◽  
D. A. Abramov
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Satellite Images ◽  
Humus Content ◽  
Spectral Characteristics ◽  
Landsat 8 ◽  
Erosion Processes ◽  
Landsat 7 ◽  
Spatio Temporal ◽  
Spectral Channels

For rational use of soils it is necessary to possess exact information on soil properties. The traditional methods of monitoring of soils and (or) their separate properties based on local, one-time supervision don’t give an adequate assessment of a current state of a soil cover it should be noted. Transition to spatio-temporal methods with use of modern geoinformation and space technologies is necessary. Remote satellite methods of soil monitoring gain fast distribution, owing to the efficiency, a certain objectivism and relative low cost now, and also because of unique opportunities of one-time coverage by the images received from big height, enough territories, big on the area. For the development of remote monitoring chernozems southern used materials of multispectral scanning multispectral camera ETM + ( «Enhanced Thematic Mapper Plus»), which is on board the satellite «Landsat-7» (data of 2006, 2010, 2012) and OLI («Operational Land Imager»), which is on board the satellite «Landsat-8»(data 2015). The information obtained from them is unified from the point of view of preservation of geometry, calibration, a covering, spectral characteristics, quality of the image and availability of data, despite various carriers of devices ETM+ and OLI. The composite image which has been received from three cloudless satellite images of spring of 2012 (three terms of shooting – 21.04, 30.04, 05.05) has allowed to make the correlation analysis of extent of influence of maintenance of organic matter in a layer of soil of 0–10 cm at a brightness with various spectral channels of the camera ETM+. Such analysis has shown that the closest connection exists between the content of soil organic matter and brightness of the second (green), the third (red) and the fourth (the neighbor infrared) spectral channels. From them three, the greatest value of correlation has dependence between the content of soil organic matter (humus) and brightness of the red spectral channel (r=-0,32). For the purpose of spatio-temporal interpretation of the equation of multiple regressions, 20 agro landscapes in different parts of the Right-bank steppe of Ukraine (The Mykolayiv district and Zhovtnevy district of the Mykolayiv oblast) have been selected. For each agro landscapes was defined content of soil organic matter in the soil using Landsat 7 satellite images taken in 2006 and in 2010 and Landsat images 8 for 2015. The made estimates of maintenance of soil organic matter have shown on processes of fast loss of humus in all layers of soil. Annual losses of soil organic matter in a layer of 0–10 cm from 2006 for 2015 have made 0,16 % in a year, in a layer of 0–50 cm of about 0,13 % in a year, and in a layer of 0–100 cm at 0,10 % in a year. The irrational structure of sown areas and distribution of wind and water erosion processes is the reason of this sad process.

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