Airborne Spectrometry Research Articles

Determination of nitrogen and chlorophyll content in two varieties of winter wheat plants means of ground and airborne spectrometry

Nitrogen in plants is part of the green pigment chlorophyll, as well as proteins, nucleic acids, phytohormones and alkaloids that indicates the key role of this element in plant life. Chlorophyll is the most important pigment of the photosynthetic process determining the life of all heterotrophic organisms on the planet. The facts mentioned above presuppose close relationships between nitrogen and chlorophyll in plants. The nitrogen content in plants serves as a basis for adjusting their nitrogen nutrition and calculating fertilization rates for high yields. This causes comstant importance of studying the content of nitrogen and chlorophyll in plants, especially by means of novel techniques with involving remote sensing. This study was focused on relationship between 19 vegetation indices (VI) and biochemical characteristics of vegetation, in particular nitrogen and chlorophyll content. Study areas were located within production fields of two varieties of winter wheat grown for harvest in 2016 by the grain company Baryshivska. The test plots varied by phytopathological situation in the phase of milk ripeness. Fungal infection of Bogdana variety caused significant varietal differences in biochemical parameters that were calculated by Kjeldahl makro-method for total nitrogen and by aerial survey with UAV (drone) for chlorophyll content. Among 19 VIs calculated by ground spectrometry the major part (16 VIs) were consistent with changes in nitrogen and chlorophyll content in the cultivars. In particular, CI rededge , CI green , MTCI, RVI, D731 / D700 and D735 / D700 were more than doubled, and NDRE1 and D718 / D700 were almost 1.5 times higher in the Skagen variety compared to the Bogdan variety. Only 3 indices: NDVI, Green NDVI and NI had limits of fluctuations of the values within the same limits, as varietal differences of biochemical indicators.

THE USE OF DECONVOLUTION TECHNIQUE FOR THE ANALYSIS OF GAMMA SPECTROMETRY DATA FROM FIELD MONITORING USING UNMANNED AERIAL VEHICLES.

Airborne gamma spectrometry is an effective tool for prompt monitoring and mapping of large areas contaminated after NPP accident, radionuclides leakage cases, an impact of uranium ore mining and processing, etc. Airborne spectrometry data analysis using deconvolution technique enables to calculate air kerma rates and/or radionuclides concentrations as well as identification of radionuclides. Application of this technique on the airborne data (from manned as well as an unmanned survey using drones) is rather specific due to the requirements for short time of one scan data acquisition, a relatively long distance from the source and small detector size, due to the limited payload of the usually used drones. Application of deconvolution techniques for analysis of spectra with very poor statistics, methods and possibilities to improve the processing of such spectra are discussed.

Integrated image processing and GIS-based techniques using knowledge-driven approaches to produce potential radioactivity map for the uraniferous granite of Egypt

ABSTRACTInterpretation of remote sensing data for allocating of lithologic units and for mapping of radioactive zones, supplies a valuable utility to produce Potential Radioactivity Map for the uraniferous granite. The study applied a digital image processing technique including interpretation and manipulation of Geophysical Airborne gamma-ray spectrometry data and The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor image data of Terra satellite over a case study well-known radioactive area of El-Missikat, El-Eridya and Kab Amiri areas in the Central Eastern Desert, Egypt. The possible forms of digital image manipulation are categorised into the following procedures: Minimum Noise Fraction (MNF) rotation, colour composite, band ratios, Principle Component Analysis (PCA), decorrelation stretching and Iterative Self-Organising Data Analysis Technique Algorithm (Isodata) unsupervised classification. Matched Filter (MF) classification was performed on the data to map a chosen well- known alteration mineral association with the uranium occurrences from USGS library. Each of these constructed images with the surveyed Airborne spectrometry data (equivalent uranium) has been given a suitable weight to be integrated using Geographic Information System (GIS) tools to delineate the most promising potential radioactive zones. Moreover, the other comparatively and quantitatively goal of the study was to evaluate the performance of various knowledge-driven mineral probability modelling.

Soil organic carbon assessment by field and airborne spectrometry in bare croplands: accounting for soil surface roughness

Visible, Near and Short Wave Infrared (VNSWIR) diffuse reflectance spectroscopy (350nm to 2500nm) has been proven to be an efficient tool to determine the Soil Organic Carbon (SOC) content. SOC assessment (SOCa) is usually done by using calibration samples and multivariate models. However one of the major constraints of this technique, when used in field conditions is the spatial variation in surface soil properties (soil water content, roughness, vegetation residue) which induces a spectral variability not directly related to SOC and hence reduces the SOCa accuracy. This study focuses on the impact of soil roughness on SOCa by outdoor VIS-NIR-SWIR spectroscopy and is based on the assumption that soil roughness effect can be approximated by its related shadowing effect.A new method for identifying and correcting the effect of soil shadow on reflectance spectra measured with an Analytical Spectral Devices (ASD) spectroradiometer and an Airborne Hyperspectral Sensor (AHS-160) on freshly tilled fields in the Grand Duchy of Luxembourg was elaborated and tested. This method is based on the shooting of soil vertical photographs in the visible spectrum and the derivation of a shadow correction factor resulting from the comparison of “reflectance” of shadowed and illuminated soil areas.Moreover, the study of laboratory ASD reflectance of shadowed soil samples showed that the influence of shadow on reflectance varies according to wavelength. Consequently a correction factor in the entire [350–2500nm] spectral range was computed to translate this differential influence.Our results showed that SOCa was improved by 27% for field spectral data and by 25% for airborne spectral data by correcting the effect of soil relative shadow. However, compared to simple mathematical treatment of the spectra (first derivative, etc.) able to remove variation in soil albedo due to roughness, the proposed method, leads only to slightly more accurate SOCa.

Analysis of petrophysical properties of some granitoids in Sweden

Variations seen in the airborne magnetic, airborne spectrometry and ground gravity data are used as a base to study some granitoids with various outcrop distributions in two areas in Sweden. The ground gamma-ray spectrometry data as well as density and magnetic susceptibility of rock samples are then used to study the details of changes in the petrophysical properties of the granitoid suites. The variation of petrophysical properties is even studied within an individual suite. We have observed that in a given suite of granitoid, various rock types, namely mafic and felsic, can be discriminated using airborne and ground geophysical data. Airborne spectrometry and ground gravity data show that a more granitic composition has a higher concentration of K, U and Th and also a lower Bouguer anomaly signature. The measured concentrations on the outcrops and the densities of the rock samples support these results very well. The lower densities of the more felsic rocks with higher K concentrations are very well correlated. The geophysical data cover large areas and thus are also cost-effective to use.

Contribution of a germanium detector in mobile gamma-ray spectrometry. Spectral analysis and performance

The sensitivity of the germanium semi-conductor detector is 30 times lower than that of the sodium iodide (NaI) detectors frequently used in airborne spectrometry. Its energy resolution however, is 20 times better, giving more accurate identification of radionuclides, especially when complex spectra are involved. The use of the germanium detector in mobile gamma-ray spectrometry provides a large amount of qualitative and quantitative information. In post-accident situations a germanium detector will be sufficient, and should therefore be used in preference to a NaI detector.An algorithm for detecting the total absorption peaks by studying the variations in the spectral profile of germanium gamma-ray spectra has been developed at the CEA. The use of digital filters that take into account the characteristics of the absorption peaks reduces the statistical fluctuations, making possible detection based on the analysis of the first and second derivatives. The absorption peak is then estimated by subtracting the background noise modelled in the detection window. This method of analysis offers the advantage of not requiring prior knowledge of the number or nature of the radionuclides to be detected. A study has been carried out to assess the specific performances of this detection software in different situations: average background noise in France and detection of artificial sources with varying activity levels.This analysis showed that the performance of our detection algorithm is very close to the theoretical detection limits, for both natural and artificial radionuclides. This algorithm is therefore well suited to the germanium type of spectral profile and to low count rates.