Spectral Brightness Coefficients Research Articles

Features of growth of agricultural crops and factors negatively affecting their growth

This <span>article is about methods of analyzing aerial images. Images from Planet.com for crops in North Kazakhstan owned by the Center for Cereal Production and Research. A.I. Barayev. The main goal of the research work is to develop and implement algorithms that allow identifying and distinguishing factors in aerial photographs that adversely affect the growth of plants during the growing season. Spectral brightness coefficient (SBC), normalized difference vegetation index (NDVI), textural features, clustering, and integral transformations are used to solve the problem. Particular attention has been paid to the development of software tools for selecting features that describe textural differences to divide texture regions into subregions. That is weeds, and pests in aerial images. The application of a set of textural features and orthogonal transformations to the analysis of experimental data is explored to identify regions of potentially correlated features in the future. The analysis of the received data made it possible to determine the characteristics of changes in the reflective capacity of agricultural plants and weeds in certain stages of the growing season. The obtained information is of great importance for confirming the observations from space remote from the aerial images.</span>

Results of using geoinformation and statistical analysis methods to study spectral reflectance characteristics of agricultural crops of Belarus

The results of using geoinformation and statistical analysis methods to study spectral reflectance characteristics of the nine most typical agricultural crops of Belarus are presented. Spectral brightness coefficients and normalised difference vegetation index (NDVI) values were extracted from Landsat-8 multispectral satellite images in the software package ENVI (version 5.2) and analysed based on the methods of zonal statistics in the software complex ArcGIS (version 10.2) and mathematical and statistical analysis in the program Statistica (version 10). The verification of satellite data with the corresponding field measurements was carried out on the basis of correlation analysis, namely, a reliable strong positivelinear relationship between the measured in the field by a specialised GreenSeeker instrument NDVI values and the calculated by Landsat-8 satellite data NDVI values was established. The character of the distribution of spectral brightness coefficients and average NDVI values depending on the type of agricultural crop was assessed using a dispersion analysis, which allowed revealing patterns hidden in the spectral data. In particular, after applying the procedure of multiple comparisons using post hoc tests, it was established which types of crops significantly differ from each other and for which dates these differences were observed. The obtained scientific results were systematised and presented in the form of correspondingtables. The data contained in the tables made it possible to improve the methodology of automated recognition of the crops considered in the study.

Identification of factors that negatively affect the growth of agricultural crops by methods of orthogonal transformations

This paper focuses on aerospace image analysis methods. Aerospace images are considered for the study of agricultural crops of northern Kazakhstan belonging to the A. I. Barayev Research and Production Center for Grain Farming. The main goal of the research is the development and implementation of algorithms that make it possible to detect and highlight on aerospace images the factors that negatively affect the growth of crops over the growing seasons. To resolve the problem, the spectral brightness coefficient (SBC), NDVI, clustering, orthogonal transformations are used. Special attention was paid to the development of software tools for selecting characteristics that describe texture differences to segment texture regions into sub-regions. That is, the issue of the applicability of sets of textural features and orthogonal transformations for the analysis of experimental data to identify characteristic areas on aerospace images that can be associated with weeds, pests, etc. in the future was investigated. The questions of signal image processing remain the focus of attention of different specialists. The images act both as a result and as a research object in physics, astronautics, meteorology, forensic medicine and many other areas of science and technology. Furthermore, image processing systems are currently being used to resolve many applied problems. A program has been implemented in the MATLAB environment that allows performing spectral transformations of six types: 1) cosine; 2) Hadamard of order 2n; 3) Hadamard of order n=p+1, p≡3 (mod4); 4) Haar; 5) slant; 6) Daubechies 4. Analysis of the data obtained revealed the features of changes in the reflectivity of cultivated crops and weeds in certain periods of the growing season. The data obtained are of great importance for the validation of remote space observations using aerospace images

Segmentation of aerospace images by a non-standard approach using informative textural features

The article presents an analysis of a non-standard approach to the segmentation of textural areas in aerospace images. The question of the applicability of sets of textural features for the analysis of experimental data is being investigated to identify characteristic areas on aerospace images that in the future it will be possible to identify types of crops, weeds, diseases, and pests. The selection of suitable algorithms was carried out and appropriate software tools were created on Matlab 2021a and in the software package for statistical analysis Statistica 12. The main way to extract information is to decrypt images, which are the main carrier of information about the underlying surface. The main tasks of texture area analysis include selection and formation of features describing textural differences; selection and segmentation of textural areas; classification of textural areas; identification of an object by texture. To solve the tasks, spectral brightness coefficient (SBC), Normalized Difference Vegetation Index (NDVI), textural features of various crops and weeds. Much attention will be paid to the development of software tools that allow the selection of features describing textural differences for the segmentation of textural areas into subdomains. That is the question of the applicability of sets of textural features and other parameters for the analysis of experimental data to identify types of soils and soils, vegetation types, humidity, crop damage in aerospace images will be resolved. This approach is universal and has great potential for identifying objects using image clustering. To identify the boundaries of areas with different properties of the image under study, images of the same surface area taken at different times are considered.

Analysis of the spectral properties of wheat growth in different vegetation periods

The article presents a technique for studying space images based on the analysis of the spectral brightness coefficient (SBC) of space images of the earth's surface. Recognition of plant species, soils, and territories using satellite images is an applied task that allows to implement many processes in agriculture and automate the activities of farmers and large farms. The main tool for analyzing satellite imagery data is the clustering of data that uniquely identifies the desired objects and changes associated with various reasons. Based on the data obtained in the course of experiments on obtaining numerical SBC values, the patterns of behavior of the processes of reflection of vegetation, factors that impede the normal growth of plants, and the proposed clustering of the spectral ranges of wave propagation, which can be used to determine the type of objects under consideration, are revealed. Recognition of these causes through the analysis of SBC satellite images will create an information system for monitoring the state of plants and events to eliminate negative causes. SBC data is divided into non-overlapping ranges, i.e. they form clusters reflecting the normal development of plant species and deviations associated with negative causes. If there are deviations, then there is an algorithm that determines the cause of the deviation and proposes an action plan to eliminate the defect. It should be noted that the distribution of the brightness spectra depends on the climatic and geographical conditions of the plant species and is unique for each region. This study refers to the Akmola region, where grain crops are grown

Методика экспериментального исследования коэффициентов спектральной яркости материалов и природных фонов.

The article describes a technique for experimental study of spectral brightness coefficients in the wavelength range of 470 ... 940 nm of objects, natural and anthropogenic backgrounds using a multispectral camera. Examples of the results of measurements of the spectral brightness coefficients are given.

Spectral properties of soils and agricultural crops for analysis of satellite images of the Akmola region

This paper considers the spectral properties of soils and vegetation and their analysis for further application of the results of the article for processing satellite images. Basically, the soils and soils of the Akmola region and agricultural crops inherent in this region are considered. When analyzing the spectral brightness coefficient (SCR), there are differences in the SCR of soils of different types and vegetation. Based on the results of data analysis, the following conclusions were obtained: soil recognition is informative in the wavelength range from 700 nm to 1300 nm; crop recognition is informative in the wavelength range from 850 nm to 1100 nm. When developing an object recognition algorithm, two fixed points of 0.55 microns and a point of 0.66-0.68 microns will be considered for the presence of extremes to determine the type of object.

Procedures for in-flight calibration of satellite spectral equipment

The paper presents procedures developed for in-flight calibration of satellite spectral equipment (by solving direct and inverse problems in the theory of radiation transfer in the atmosphere) using quasi-synchronous sub-satellite point measurements. Also presented are the results of processing and analysis of several sessions of multi-level measurements conducted at the Zyabrovka test range (Republic of Belarus, Gomel region). Measurements taken from ground and air used spectral instrumentation developed at the Airspace Research department of Sevchenko IAPP of BSU to support satellite test ranges on the ground. Verification results are provided for measurements taken on the ground, in air and in space. Used for verification of the ground and space measurements were data from the multi-spectral spacecraft Sentinel-2. Key words: in-flight calibrations, sub-satellite test range, spectral brightness coefficients, field measurements.

Spectral characteristics of some agricultural crops in different phenological phases of vegetation

For deciphering crops from satellite images at different time periods, it is necessary to have information about the spectral reflectivity of plants during their passage through the phenological phases of vegetation. An attempt was made to evaluate the spectral reflectivity of the main fruit crops and grapes in different phenological phases of the growing season using Sentinel-2 satellite images and the ENVI software package. Field research methods, plots were selected on which peach, grapes, cherries, apple trees, plums, and apricots grow are used. It was established that planting crops was carried out by mixing cultivars in order to reduce the risk of additional costs as a result of possible adverse natural processes and phenomena. For each section, the maximum, minimum, and average values of the spectral brightness coefficient were obtained and analyzed within 13 bands of Sentinel-2 satellite images. Space images were selected for 04/07/2019, 04/27/2019 and 05/12/2019, as the most suitable for the periods of the beginning of flowering (04/07/2019), the end of flowering (04/27/2019) and the beginning of fruit ripening (12/05/2019), with minimal cloud overlap values. To eliminate the external influence of the soil within each pixel of the image, the linear spectral separation module of the ENVI software package was used, a reference soil fragment was selected and its spectral characteristics were obtained, which made it possible to depict graphs of the spectral curves of the crops under study within each section. It was not possible to obtain a distinction of the spectral brightness coefficient for all sections, which is associated with the presence of additional external elements.

Designing a methodological concept for the diagnosis of early development of the main wheat diseases pathogens

The studies presented in the article were carried out in 2018-2019 on the experimental field of the All-Russian Research Institute of Biological Plant Protection. The aim of the research was to assess the feasibility of diagnosing the early development of major diseases pathogens based on the results of ground-based spectrometry and the use of phytomonitoring technology, taking into account the genotypes of different winter wheat varieties. There were three options of the experimental plots for the research: the 1st – protected against diseases by fungicides, the 2nd – with an artificial infectious background, the 3rd – with the natural development of diseases. According to the results of data analysis, the most significant changes in the spectral characteristics of the studied plant backgrounds were noted at the time of the first signs of disease in the form of a decrease in the spectral brightness coefficient in the near infrared range. Using special tools in the experimental plots, the following pathogens were identified before the appearing of disease symptoms: Blumeria graminis (DC.) Speer f. sp. tritici Marchal , Puccinia striiformis West., Pyrenophora tritici-repentis Died., Puccinia triticina Erikss. Data on the diseases development, plant infestation by pathogens are compared with spectrometric measurements.

Landscape optical properties of land within iron ore deposits based on satellite data

In the area of the Krivoy Rog-Kremenchug suture zone, the optical characteristics of landscape elements were studied, both at iron ore deposits and above predicted morphostructures on iron ore deposits. Within the predicted morphostructures with a high magnetic field (iron ore rocks of the Krivoy Rog series), measurements were made of the spectral brightness coefficient (CMF) of vegetation cover. The Landsat-8 satellite image was used to perform spectrometry analysis using factor analysis (factor analysis 2 was most indicative) and elevated values of the optical characteristics of vegetation within the morphostructures above ferruginous rocks were revealed. This made it possible to predict deposits of iron ores within the predicted morphostructures with a high magnetic field intensity.

Method of constructing a space-time grid of variable size images and its application in image processing of landfills

The paper proposes a method of slicing space images into areas of varying sizes to automate the image processing, beginning from the receipt of raw data (download pictures) up to mapping of the underlying surface indices. Indices calculation are based on one image (the surface and the vegetation indices temperature, indices of objects detection on the ground and etc.) and their time series (conducting temporal processing). The downloading of the sources of satellite images algorithm from the sites archives of geodata from the initial data download (the observation area, stage, time period, etc.) is also represented. The procedure of cutting images into segments of varying sizes is described. It allows to use the ?contents? of image both in general and for each pixel of the earth's surface to have a whole time series of the spectral brightness coefficients. Examples of time series of geo-referenced source images and the individual indices of the underlying surface are automatically generated by the algorithm method, for specific problems of space debris monitoring (vegetation indices reaction, the degree of soil degradation, detection of indices).

Algorithm for Recovery of Integrated Water Vapor Content in the Atmosphere over Land Surfaces Based on Satellite Spectroradiometer Data

An algorithm is proposed for making charts of the distribution of water vapor in the atmosphere based on multispectral images of the earth by the Ocean and Land Color Instrument (OLCI) on board of the European research satellite Sentinel-3. The algorithm is based on multiple regression fits of the spectral brightness coefficients at the upper boundary of the atmosphere, the geometric parameters of the satellite location (solar and viewing angles), and the total water vapor content in the atmosphere. A regression equation is derived from experimental data on the variation in the optical characteristics of the atmosphere and underlying surface, together with Monte-Carlo calculations of the radiative transfer characteristics. The equation includes the brightness coefficients in the near IR channels of the OLCI for the absorption bands of water vapor and oxygen, as well as for the transparency windows of the atmosphere. Together these make it possible to eliminate the effect of the reflection spectrum of the underlying surface and air pressure on the accuracy of the measurements. The algorithm is tested using data from a prototype OLCI, the medium resolution imaging spectrometer (MERIS). A sample chart of the distribution of water vapor in the atmosphere over Eastern Europe is constructed without using subsatellite data and digital models of the surface relief. The water vapor contents in the atmosphere determined using MERIS images and data provided by earthbound measurements with the aerosol robotic network (AERONET) are compared with a mean square deviation of 1.24 kg/m2.

Assessing the trophic state of water bodies by high-resolution remote spectrometry in visible band

Analysis is presented of many-year spectrometric data in the visible band of electromagnetic spectrum collected for the Don R., including the Tsimlyansk Reservoir in 2010–2013 with a period of ~15 days. An algorithm has been proposed for separating spectral brightness coefficient of the rising radiation from water into six categories. A nomenclature scale of the trophic status of water bodies has been constructed. The obtained scale coincides with the nomenclature scales constructed by chlorophyll a concentration for water bodies under different physiographic conditions. The unquestioning advantage of remote sensing methods for assessing water body (WB) trophic status is emphasized, i.e., the possibility to carry out real-time studies within minutes at high representativeness of the results with respect to the examined aquatic ecosystem.

Analysis of Indicatrices of the Spectral Brightness Coefficient for Surfaces with Different Microgeometry

Analysis of Indicatrices of the Spectral Brightness Coefficient for Surfaces with Different Microgeometry

Информационные свойства спектральных коэффициентов яркости и вегетационных индексов для калибровки аэрокосмических снимков

Investigetion use limitation and error of normalized information properties of the colors response curves, indexes and coefficients used at thematic interpretation of the space remote information as well as in GIS problems analysis are carried out. Use conditions of synergic approach of G. Haken's informational entropy are rotined for development and simulation of information remote indication performances of an ecological process characteristics with forecast possibility of its critical state and informative trends of spreading.

A study of spectral-polarization characteristics of plant canopies using land-based remote sensing

The study addresses reflection and spectral-polarization characteristics of forest stands and farm crops obtained under field conditions. The study of the reflection properties of farm crops shows that during the summer plant growing season, the major factors influencing the plant canopy reflectance are morpho-physiological parameters, plant architectonics, solar elevation h0, and viewing angle. The crop reflectance minimum was recorded at viewing angles 25–30° with respect to the nadir. Coniferous and broadleaf forest stands had similar reflectance spectra of polarized light. The polarized component was smaller for all coniferous stands than for broadleaf ones. For broad-leaved farm crops (wheat and corn), the polarized component of the spectral brightness coefficients had a greater influence on the plant reflectance in the red and near-infrared spectral regions, λ>720nm.

Method of Principal Components and Fourier Analysis of Brightness-Coefficient Spectra for Diagnostics of Pine Needles

The spectral brightness coefficients of pine needles exposed to aqueous solutions of sulfuric acid have been analyzed by the method of principal components and fast Fourier transform. Wavelengths informative for control of changes in the needles have been selected.

SEASONAL CHANGES IN SPECTRAL BRIGHTNESS OF AGRICULTURAL CROPS AS A FUNCTION OF CHLOROPHYLL CONTENT AND PLANT CONDITIONS

The results of multiyear research on the condition of agricultural crops are analyzed on the basis of data on the reflectance of plants during their growing season. A universal method is proposed for assessing the physiological state and content of plant pigments on the basis of the chlorophyll potential S(t) in the red absorption band λ = 680 nm, as determined from spectral brightness coefficients.

The reflection and scattering of light by a plant leaf

The spectral polarization characteristics of the visible radiation reflected and scattered by a plant leaf were investigated. Measurements of the spectral brightness coefficient, the directed reflection coefficients, and the degree and azimuth of polarization of radiation reflected from a leaf were performed at different angles of incidence of radiation on the leaf and different angles of observation. More than 500 measurements were performed for 36 samples. Maple (Acer platanoides) leaves from different trees were used as objects of investigation. Peculiarities of the mechanism of formation of the flux of radiation reflected from a plant leaf have been revealed.