scholarly journals Spectral and Growth Characteristics of Willows and Maize in Soil Contaminated with a Layer of Crude or Refined Oil

2021 ◽  
Vol 13 (17) ◽  
pp. 3376
Author(s):  
Raquel Serrano-Calvo ◽  
Mark E. J. Cutler ◽  
Anthony Glyn Bengough
Keyword(s):  
Remote Sensing ◽  
Chlorophyll Concentration ◽  
Absorption Feature ◽  
Refined Oil ◽  
Hydrocarbon Concentration ◽  
Band Area ◽  
Loam Soil ◽  
High Concentrations ◽  
Band Depth ◽  
Absorption Features

Remote sensing holds great potential for detecting stress in vegetation caused by hydrocarbons, but we need to better understand the effects of hydrocarbons on plant growth and specific spectral expression. Willow (Salix viminalis var. Tora) cuttings and maize (Zea mays var. Lapriora) seedlings were grown in pots of loam soil containing a hydrocarbon-contaminated layer at the base of the pot (crude or refined oil) at concentrations of 0.5, 5, or 50 g·kg−1. Chlorophyll concentration, biomass, and growth of plants were determined through destructive and nondestructive sampling, whilst reflectance measurements were made using portable hyperspectral spectrometers. All biophysical (chlorophyll concentration and growth) variables decreased in the presence of high concentrations of hydrocarbons, but at lower concentrations an increase in growth and chlorophyll were often observed with respect to nonpolluted plants, suggesting a biphasic response to hydrocarbon presence. Absorption features were identified that related strongly to pigment concentration and biomass. Variations in absorption feature characteristics (band depth, band area, and band width) were dependent upon the hydrocarbon concentration and type, and showed the same biphasic pattern noted in the biophysical measurements. This study demonstrates that the response of plants to hydrocarbon pollution varies according to hydrocarbon concentration and that remote sensing has the potential to both detect and monitor the variable impacts of pollution in the landscape.

scholarly journals Observation of Oceanic Eddy in the Northeastern Arabian Sea Using Multisensor Remote Sensing Data

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
R. K. Sarangi
Keyword(s):  
Remote Sensing ◽  
Arabian Sea ◽  
Chlorophyll Concentration ◽  
Climatic Conditions ◽  
Late Winter ◽  
Surrounding Water ◽  
Noaa Avhrr ◽  
Oceanic Eddy ◽  
Remote Sensing Satellite ◽  
Cold Core

An oceanic eddy of size about 150 kilometer diameter observed in the northeastern Arabian Sea using remote sensing satellite sensors; IRS-P4 OCM, NOAA-AVHRR and NASA Quickscat Scatterometer data. The eddy was detected in the 2nd week of February in Indian Remote Sensing satellite (IRS-P4) Ocean Color Monitor (OCM) sensor retrieved chlorophyll image on 10th February 2002, between latitude 16°90′–18°50′N and longitude 66°05′–67°60′E. The chlorophyll concentration was higher in the central part of eddy (~1.5 mg/m3) than the peripheral water (~0.8 mg/m3). The eddy lasted till 10th March 2002. NOAA-AVHRR sea surface temperature (SST) images generated during 15th February-15th March 2002. The SST in the eddy’s center (~23°C) was lesser than the surrounding water (~24.5°C). The eddy was of cold core type with the warmer water in periphery. Quickscat Scatterometer retrieved wind speed was 8–10 m/sec. The eddy movement observed southeast to southwest direction and might helped in churning. The eddy seemed evident due to convective processes in water column. The processes like detrainment and entrainment play role in bringing up the cooler water and the bottom nutrient to surface and hence the algal blooming. This type of cold core/anti-cyclonic eddy is likely to occur during late winter/spring as a result of the prevailing climatic conditions.

scholarly journals Mapping Seasonal High-Resolution PM2.5 Concentrations with Spatiotemporal Bagged-Tree Model across China

2021 ◽  
Vol 10 (10) ◽  
pp. 676
Author(s):  
Junchen He ◽  
Zhili Jin ◽  
Wei Wang ◽  
Yixiao Zhang
Keyword(s):  
Remote Sensing ◽  
Mean Squared Error ◽  
Fine Particulate Matter ◽  
Absolute Error ◽  
Superior Performance ◽  
Tree Model ◽  
Mixed Effect ◽  
Proposed Model ◽  
High Concentrations ◽  
Pm2.5 Concentration

High concentrations of fine particulate matter (PM2.5) are well known to reduce environmental quality, visibility, atmospheric radiation, and damage the human respiratory system. Satellite-based aerosol retrievals are widely used to estimate surface PM2.5 levels because satellite remote sensing can break through the spatial limitations caused by sparse observation stations. In this work, a spatiotemporal weighted bagged-tree remote sensing (STBT) model that simultaneously considers the effects of aerosol optical depth, meteorological parameters, and topographic factors was proposed to map PM2.5 concentrations across China that occurred in 2018. The proposed model shows superior performance with the determination coefficient (R2) of 0.84, mean-absolute error (MAE) of 8.77 μg/m3 and root-mean-squared error (RMSE) of 15.14 μg/m3 when compared with the traditional multiple linear regression (R2 = 0.38, MAE = 18.15 μg/m3, RMSE = 29.06 μg/m3) and linear mixed-effect (R2 = 0.52, MAE = 15.43 μg/m3, RMSE = 25.41 μg/m3) models by the 10-fold cross-validation method. The results collectively demonstrate the superiority of the STBT model to other models for PM2.5 concentration monitoring. Thus, this method may provide important data support for atmospheric environmental monitoring and epidemiological research.

Intercomparison of Phytoplankton functional types dynamics from satellite observations

2021 ◽  
Author(s):  
Marine Bretagnon ◽  
Séverine Alvain ◽  
Astrid Bracher ◽  
Philippe Garnesson ◽  
Svetlana losa ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Marine Environment ◽  
Model Simulation ◽  
Chlorophyll Concentration ◽  
Satellite Observations ◽  
Global Ocean ◽  
Ocean Colour ◽  
Marginal Seas ◽  
Functional Types ◽  
Wide Range

<p>Copernicus marine environment monitoring service (CMEMS) gives users access to a wide range of ocean descriptors. Both physics and biogeochemistry of the marine environment can be studied with complementary source of data, such as in situ data, modelling output and satellite observations at global scale and/or for European marginal seas. Among the ocean descriptors supplied as part of CMEMS, phytoplankton functional types (PFTs) describe the phytoplanktonic composition at global level or over European marginal seas. Studied phytoplankton assemblage is particularly important as it is the basis of the marine food-web. Composition of the first trophic level is a valuable indicator to infer the structure of the ecosystem and its health. Over the last decades, ocean colour remote sensing has been used to estimate the phytoplanktonic composition. The algorithms developed to estimate PFTs composition based on ocean colour observation can be classified in three categories: the spectral approaches, the abundance-based approaches (derived from the chlorophyll concentration) and the ecological approaches. The three approaches can lead to differences or, conversely, to similar patterns. Difference and similarity in PFTs estimation from remote sensing is a useful information for data assimilation or model simulation, as it provides indications on the uncertainties/variability associated to the PFT estimates. Indeed, PFT estimates from satellite observations are increasingly assimilated into ecological models to improve biogeochemical simulations, what highlights the importance to get an index or at least information describing the validity range of such PFTs estimates.</p><p>In this study, four algorithms (two abundance-based, and two spectral approaches) are compared. The aim of this study is to compare the related PFT products spatially and temporally, and to study the agreement of their derived PFT phenology. This study proposes also to compare PFT algorithms developed for the global ocean with those developed for specific regions in order to assess the potential strength and weakness of the different approaches. Once similarities and discrepancies between the different approaches are assessed, this information could be used by model to give an interval of confidence in model simulation.</p>

scholarly journals In situ effective snow grain size mapping using a compact hyperspectral imager

2020 ◽  
pp. 1-9
Author(s):  
Christopher Donahue ◽  
S. McKenzie Skiles ◽  
Kevin Hammonds
Keyword(s):  
Spatial Variability ◽  
Near Infrared ◽  
Absorption Feature ◽  
Micro Ct ◽  
Band Area ◽  
Snow Metamorphism ◽  
Wet Snow ◽  
Before And After ◽  
Computed Microtomography ◽  
Snow Samples

Abstract Effective snow grain radius (re) is mapped at high resolution using near-infrared hyperspectral imaging (NIR-HSI). The NIR-HSI method can be used to quantify re spatial variability, change in re due to metamorphism, and visualize water percolation in the snowpack. Results are presented for three different laboratory-prepared snow samples (homogeneous, ice lens, fine grains over coarse grains), the sidewalls of which were imaged before and after melt induced by a solar lamp. The spectral reflectance in each ~3 mm pixel was inverted for re using the scaled band area of the ice absorption feature centered at 1030 nm, producing re maps consisting of 54 740 pixels. All snow samples exhibited grain coarsening post-melt as the result of wet snow metamorphism, which is quantified by the change in re distributions from pre- and post-melt images. The NIR-HSI method was compared to re retrievals from a field spectrometer and X-ray computed microtomography (micro-CT), resulting in the spectrometer having the same mean re and micro-CT having 23.9% higher mean re than the hyperspectral imager. As compact hyperspectral imagers become more widely available, this method may be a valuable tool for assessing re spatial variability and snow metamorphism in field and laboratory settings.

Ammonium abundance and short-wave infrared absorption spectra of altered rocks

2020 ◽  
Vol 20 (4) ◽  
pp. 451-460
Author(s):  
Keiko Hattori ◽  
Anna Fonseca ◽  
Tabetha Sheppard
Keyword(s):  
Absorption Spectra ◽  
Nitrogen Isotope ◽  
Short Wave ◽  
Absorption Feature ◽  
Rock Composition ◽  
Content Type ◽  
Fine Grained ◽  
Supplementary Material ◽  
Short Wave Infrared ◽  
Absorption Features

Rhyolitic rocks hosting the El Zapote epithermal Ag deposit are pervasively altered and contain ammonium ranging from 290 to 1750 ppm. High ammonium values are found in samples containing abundant fine-grained illite. This fine-grained illite shows overall low ratios of K/(Al + Fe), likely due to ammonium substituting K+. Samples containing high ammonium, greater than 1000 ppm in the proximity of Ag-bearing veins, show distinct absorption features of ammonium in short-wave infrared (SWIR) absorption spectra. Samples containing ammonium ranging from 500 to 1000 ppm show mixed absorption signatures; some show prominent absorption features related to ammonium, whereas others have no recognizable features. There is no discernible absorption feature related to ammonium for samples containing less than 500 ppm NH4. The data suggest that SWIR spectroscopy is useful in locating the proximal areas to mineralization, but the extent of ammonium alteration is much larger than that identified by SWIR spectroscopy. Nitrogen isotope compositions of ammonium are similar to those of sedimentary rocks, suggesting that the source of ammonium in altered rhyolite is sedimentary basement rocks in the area.Supplementary material: bulk rock composition is available at https://doi.org/10.6084/m9.figshare.c.5015663

scholarly journals Dynamics of Vibrio cholerae in a Typical Tropical Lake and Estuarine System: Potential of Remote Sensing for Risk Mapping

2021 ◽  
Vol 13 (5) ◽  
pp. 1034
Author(s):  
Abdulaziz Anas ◽  
Kiran Krishna ◽  
Syamkumar Vijayakumar ◽  
Grinson George ◽  
Nandini Menon ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Vibrio Cholerae ◽  
Chlorophyll Concentration ◽  
Zooplankton Community ◽  
Human Consumption ◽  
Spatial And Temporal Variability ◽  
Estuarine System ◽  
High Association ◽  
Water And Sanitation

Vibrio cholerae, the bacterium responsible for the disease cholera, is a naturally-occurring bacterium, commonly found in many natural tropical water bodies. In the context of the U.N. Sustainable Development Goals (SDG) targets on health (Goal 3), water quality (Goal 6), life under water (Goal 14), and clean water and sanitation (Goal 6), which aim to “ensure availability and sustainable management of water and sanitation for all”, we investigated the environmental reservoirs of V. cholerae in Vembanad Lake, the largest lake in Kerala (India), where cholera is endemic. The response of environmental reservoirs of V. cholerae to variability in essential climate variables may play a pivotal role in determining the quality of natural water resources, and whether they might be safe for human consumption or not. The hydrodynamics of Vembanad Lake, and the man-made barrier that divides the lake, resulted in spatial and temporal variability in salinity (1–32 psu) and temperature (23 to 36 °C). The higher ends of this salinity and temperature ranges fall outside the preferred growth conditions for V. cholerae reported in the literature. The bacteria were associated with filtered water as well as with phyto- and zooplankton in the lake. Their association with benthic organisms and sediments was poor to nil. The prevalence of high laminarinase and chitinase enzyme expression (more than 50 µgmL−1 min−1) among V. cholerae could underlie their high association with phyto- and zooplankton. Furthermore, the diversity in the phytoplankton community in the lake, with dominance of genera such as Skeletonema sp., Microcystis sp., Aulacoseira sp., and Anabaena sp., which changed with location and season, and associated changes in the zooplankton community, could also have affected the dynamics of the bacteria in the lake. The probability of presence or absence of V. cholerae could be expressed as a function of chlorophyll concentration in the water, which suggests that risk maps for the entire lake can be generated using satellite-derived chlorophyll data. In situ observations and satellite-based extrapolations suggest that the risks from environmental V. cholerae in the lake can be quite high (with probability in the range of 0.5 to 1) everywhere in the lake, but higher values are encountered more frequently in the southern part of the lake. Remote sensing has an important role to play in meeting SDG goals related to health, water quality and life under water, as demonstrated in this example related to cholera.

Challenges in searching for hydrocarbons in CRISM-IR data

2020 ◽  
Author(s):  
Paola Manzari ◽  
Cosimo Marzo ◽  
Eleonora Ammannito
Keyword(s):  
Standard Deviation ◽  
Spatial Resolution ◽  
Methane Concentration ◽  
High Spatial Resolution ◽  
Depth Map ◽  
Mars Atmosphere ◽  
High Concentrations ◽  
Band Depth

<p>After having observed  some absorptions around 3.3 μm band in some CRISM spectra, we begun a study in the range between 3.2 and 3.4 μm to exploit the high spatial resolution of CRISM spectrometer (~18 m/pixel) to look for methane or other C-H absorptions on Mars surface. Concerning methane, we were searching for high concentrations, comparable to the “methane spikes” concentrations detected by Curiosity on Mars surface and the methane plumes detected in Mars atmosphere from ground telescopes. The search for absorptions around 3.3 μm was carried out fitting the spectra of selected CRISM datasets with the MGM function in the 3.2-3.4 μm range.  From the MGM fit we obtained a map of the absorption depths. By this depth map, aside rare, suspected, absorptions, a spectral artifact was highlighted.  Therefore, we chose to consider spectra with absorptions around 3.3 μm not clearly related to known and unknown artifacts, and band depth values greater than 4*standard deviation of the depth map. We used the Planetary Spectrum Generator tool to find the relation between the absorption depths at 3.3 μm and methane concentration. We finally discuss the rare interesting spectra both as potentially true absorptions and as a still unknown artifact.</p>

STANDOFF SENSING AND IMAGING OF EXPLOSIVE RELATED CHEMICAL AND BIO-CHEMICAL MATERIALS USING THz-TDS

2007 ◽  
Vol 17 (02) ◽  
pp. 239-249 ◽  
Author(s):  
Hua Zhong ◽  
Albert Redo-Sanchez ◽  
Xi-Cheng Zhang
Keyword(s):  
Remote Sensing ◽  
Glutamic Acid ◽  
Time Domain ◽  
Large Scale ◽  
Imaging System ◽  
Terahertz Time Domain Spectroscopy ◽  
Multiple Absorption ◽  
Thz Absorption ◽  
Absorption Features ◽  
Chemical Materials

We report the sensing and imaging of explosive related chemical and bio-chemical materials by using terahertz time domain spectroscopy (THz-TDS) at standoff distance. The 0.82 THz absorption peak of RDX is observed at a distance up to 30 m away from the emitter and receiver. Multiple absorption features of RDX, 2,4-DNT and Glutamic Acid are identified by using a large scale 2-D imaging system. These results support the feasibility of using THz-TDS technique in remote sensing and detection of chemical materials.

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