Pub Date : 2024-02-27DOI: 10.1134/s001095252370065x
R. Kh. Tembotov
Abstract
Based on the information obtained on organic carbon content in soils and remote sensing data, a mapping model reflecting the spatial variation of organic carbon content in the upper horizons (0–20 cm) of soils in Central Caucasus was created using digital soil modelling and mapping technology. For modelling we applied a multifunctional approach involving a combination of actual data on the organic carbon content (training set) with data derived from external sources of information (remote sensing data) that was processed using a stepwise discriminant analysis. The necessity of creating a model of organic carbon distribution in soils separately for artificial (agrocenoses) and natural biogeocenoses was established using statistical methods of analysis. As a result of combining two hypothetical models, a verified model reflecting the real picture of changes in the organic carbon content in soils of Central Caucasus was obtained. The reliability of the model was 68%. It contains actual data on organic carbon content in natural and agrogenic soils of Central Caucasus. This model is a necessary tool for making decisions to maintain or increase current soil carbon stocks under conditions of climate change and increasing anthropogenic impact.
{"title":"Using a Multifunctional Approach for Cartographic Modeling of Organic Carbon Content in Natural and Arable Soils of the Central Caucasus","authors":"R. Kh. Tembotov","doi":"10.1134/s001095252370065x","DOIUrl":"https://doi.org/10.1134/s001095252370065x","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Based on the information obtained on organic carbon content in soils and remote sensing data, a mapping model reflecting the spatial variation of organic carbon content in the upper horizons (0–20 cm) of soils in Central Caucasus was created using digital soil modelling and mapping technology. For modelling we applied a multifunctional approach involving a combination of actual data on the organic carbon content (training set) with data derived from external sources of information (remote sensing data) that was processed using a stepwise discriminant analysis. The necessity of creating a model of organic carbon distribution in soils separately for artificial (agrocenoses) and natural biogeocenoses was established using statistical methods of analysis. As a result of combining two hypothetical models, a verified model reflecting the real picture of changes in the organic carbon content in soils of Central Caucasus was obtained. The reliability of the model was 68%. It contains actual data on organic carbon content in natural and agrogenic soils of Central Caucasus. This model is a necessary tool for making decisions to maintain or increase current soil carbon stocks under conditions of climate change and increasing anthropogenic impact.</p>","PeriodicalId":56319,"journal":{"name":"Cosmic Research","volume":"20 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140889911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1134/s0010952523700569
A. I. Kanev, A. V. Tarasov, A. N. Shikhov, N. S. Podoprigorova, F. A. Safonov
Abstract
The results of detection (segmentation) of forest disturbances (logged and windthrow areas) based on Sentinel-2 satellite images with convolutional neural networks of U-net architecture in different regions of the European territory of Russia and the Urals are presented. The volume of the training sample was over 17 thousand objects. Overall, both logged and windthrow areas are detected with satisfactory accuracy (the average F-measure is over 0.5). At the same time, substantial differences in detection accuracy were found depending on the characteristics of both disturbances themselves and the affected forest cover. Thus, the maximum accuracy was achieved for tornado-induced windthrow areas, due to their geometric features. The dependence of windthrow detection accuracy on the species composition of damaged forests is not obvious and requires clarification; at the same time, the average area of damaged forest sites has a substantial effect on it. The maximum F-measure calculated for logged areas detected on test pairs of Sentinel-2 images reaches 0.80, which is substantially higher than in previously published studies with the U-net model. The maximum accuracy is typical for large clear-cuts in mixed and dark coniferous forests, while selective logged areas in deciduous forests are characterized by lowest one. The accuracy for wintertime and summertime pairs of images is substantially higher than for multiseasonal pairs. Also, the accuracy strongly varies for different types of logged areas. Thus, forest roads on summertime images are detected with the lowest producer’s accuracy, while logged areas on wintertime images are detected with highest one.
摘要 介绍了基于哨兵-2 卫星图像的 U 型卷积神经网络在俄罗斯欧洲领土和乌拉尔不同地区对森林干扰（伐木区和风刮区）的检测（分割）结果。训练样本的数量超过 1.7 万个。总体而言，伐木区和风蚀区的检测精度令人满意（平均 F 值超过 0.5）。同时，由于干扰本身和受影响森林植被的特征不同，检测精度也存在很大差异。因此，龙卷风引起的风切变区域由于其几何特征而达到了最高精度。风切变检测精度与受损森林物种组成的关系并不明显，需要加以澄清；同时，受损森林地点的平均面积对其也有很大影响。对哨兵-2 图像测试对中检测到的伐木区计算出的最大 F 测量值达到 0.80，大大高于之前发表的使用 U 网模型的研究结果。针阔混交林和暗针叶林中的大面积伐木区的准确度最高，而落叶林中的选择性伐木区的准确度最低。冬季和夏季图像对的准确率远远高于多季节图像对。此外，不同类型采伐区的准确度也有很大差异。因此，夏季图像上的森林道路检测精度最低，而冬季图像上的伐木区检测精度最高。
{"title":"Identification of Logged and Windthrow Areas from Sentinel-2 Satellite Images Using the U-Net Convolutional Neural Network and Factors Affecting Its Accuracy","authors":"A. I. Kanev, A. V. Tarasov, A. N. Shikhov, N. S. Podoprigorova, F. A. Safonov","doi":"10.1134/s0010952523700569","DOIUrl":"https://doi.org/10.1134/s0010952523700569","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The results of detection (segmentation) of forest disturbances (logged and windthrow areas) based on <i>Sentinel-2</i> satellite images with convolutional neural networks of U-net architecture in different regions of the European territory of Russia and the Urals are presented. The volume of the training sample was over 17 thousand objects. Overall, both logged and windthrow areas are detected with satisfactory accuracy (the average F-measure is over 0.5). At the same time, substantial differences in detection accuracy were found depending on the characteristics of both disturbances themselves and the affected forest cover. Thus, the maximum accuracy was achieved for tornado-induced windthrow areas, due to their geometric features. The dependence of windthrow detection accuracy on the species composition of damaged forests is not obvious and requires clarification; at the same time, the average area of damaged forest sites has a substantial effect on it. The maximum F-measure calculated for logged areas detected on test pairs of <i>Sentinel-2</i> images reaches 0.80, which is substantially higher than in previously published studies with the U-net model. The maximum accuracy is typical for large clear-cuts in mixed and dark coniferous forests, while selective logged areas in deciduous forests are characterized by lowest one. The accuracy for wintertime and summertime pairs of images is substantially higher than for multiseasonal pairs. Also, the accuracy strongly varies for different types of logged areas. Thus, forest roads on summertime images are detected with the lowest producer’s accuracy, while logged areas on wintertime images are detected with highest one.</p>","PeriodicalId":56319,"journal":{"name":"Cosmic Research","volume":"3 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1134/s0010952523700570
A. G. Kostianoy, O. Yu. Lavrova, A. A. Polukhin, A. V. Kostyleva, P. V. Khlebopashev, D. M. Soloviev, P. D. Zhadanova
Abstract
From 1995 to the present, the level of the Caspian Sea decreased by almost 3 m, which significantly affects the morphometry and the ecological state of shallow water areas. First of all, this concerns the shallow Northern Caspian and, especially, the Volga Delta, which over the years has moved 10–20 km forward and grown by about 3000 km2 in area. Changes in the morphometric characteristics of the Volga Delta inevitably affect the hydrodynamic, hydrophysical, hydrochemical, and hydrobiological characteristics of river water in the foredelta. From May 18 to 20, 2021, complex hydrophysical, hydrochemical, and hydrobiological studies of river water were carried out in the southwestern part of the Volga Delta. A total of 32 stations were completed, at which water surface temperature, electrical conductivity, turbidity, and chlorophyll a and oxygen concentrations were measured and samples were taken for further analysis in the laboratory. They showed a complex picture of the distribution of the studied parameters, both along the watercourses and across them. Only high spatial resolution optical and infrared Landsat-8 OLI/TIRS satellite images, obtained on May 20, 2021, almost simultaneously with the ongoing studies in the Volga Delta, helped the spatial distribution of these parameters to be understood. As a result of the analysis of the images, it was possible for the first time to identify a horizontal fine structure of watercourses, which is an alternation of clear immiscible narrow jets with significantly different characteristics of temperature, suspended matter, turbidity, and chlorophyll a.
{"title":"Horizontal Fine Structure of River Water Flow in the Volga Delta According to Satellite Data of High Spatial Resolution","authors":"A. G. Kostianoy, O. Yu. Lavrova, A. A. Polukhin, A. V. Kostyleva, P. V. Khlebopashev, D. M. Soloviev, P. D. Zhadanova","doi":"10.1134/s0010952523700570","DOIUrl":"https://doi.org/10.1134/s0010952523700570","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>From 1995 to the present, the level of the Caspian Sea decreased by almost 3 m, which significantly affects the morphometry and the ecological state of shallow water areas. First of all, this concerns the shallow Northern Caspian and, especially, the Volga Delta, which over the years has moved 10–20 km forward and grown by about 3000 km<sup>2</sup> in area. Changes in the morphometric characteristics of the Volga Delta inevitably affect the hydrodynamic, hydrophysical, hydrochemical, and hydrobiological characteristics of river water in the foredelta. From May 18 to 20, 2021, complex hydrophysical, hydrochemical, and hydrobiological studies of river water were carried out in the southwestern part of the Volga Delta. A total of 32 stations were completed, at which water surface temperature, electrical conductivity, turbidity, and chlorophyll <i>a</i> and oxygen concentrations were measured and samples were taken for further analysis in the laboratory. They showed a complex picture of the distribution of the studied parameters, both along the watercourses and across them. Only high spatial resolution optical and infrared <i>Landsat-8</i> OLI/TIRS satellite images, obtained on May 20, 2021, almost simultaneously with the ongoing studies in the Volga Delta, helped the spatial distribution of these parameters to be understood. As a result of the analysis of the images, it was possible for the first time to identify a horizontal fine structure of watercourses, which is an alternation of clear immiscible narrow jets with significantly different characteristics of temperature, suspended matter, turbidity, and chlorophyll <i>a</i>.</p>","PeriodicalId":56319,"journal":{"name":"Cosmic Research","volume":"40 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139980003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1134/s0010952523700612
L. M. Mitnik, V. P. Kuleshov, M. L. Mitnik, A. V. Baranyuk
Abstract
The results of sensing of East Antarctica and the adjoining areas of the Southern Ocean by MTVZA-GYа microwave satellite radiometers at frequency ν = 10–190 GHz and AMSR2 at ν = 6–89 GHz in conditions of warm and humid air (an atmospheric river (AR)) invasion from the area of Tasmania area in March 2022 are presented. The surface air warming caused by AR was recorded by the Automatic Weather Station at the coast and at the Vostok, Concordia, and Dome CII stations in East Antarctica. The variability of atmospheric characteristics above Antarctica was studied using readings of radiosondes launched from the Casey station at the coast and Concordia station at a height of 3230 m and time series of brightness temperatures averaged over a circular area 200 km in diameter with the center at a distance of ~200 km from the Concordia station. The influence of air and surface temperature and atmospheric water-vapor content variations on brightness temperature Tb(ν) variations was estimated from the results of modeling of microwave radiation transfer in the atmosphere–firn system using radiosonde profiles from the Concordia station. It was shown that the increase in Tb(ν) at frequencies of 89–92 GHz of a large part of East Antarctica was caused mainly by an increase in the firn temperature. The increase at frequencies of ∼176–190 GHz in the area of the water vapor absorption line was caused by an increase of both the firn temperature and air temperature and humidity. Based on measurements of brightness temperature Tb(ν) over the open ocean at frequencies in the atmospheric-transparency windows of ∼6–48 and 88–92 GHz, wind speed W, cloud liquid-water content Q, and atmospheric water-vapor content V were determined and the temporal variability of parameters in the AR area was studied.
{"title":"Satellite Microwave Radiometric Measurements of Extreme Temperature Rise in East Antarctica in March 2022","authors":"L. M. Mitnik, V. P. Kuleshov, M. L. Mitnik, A. V. Baranyuk","doi":"10.1134/s0010952523700612","DOIUrl":"https://doi.org/10.1134/s0010952523700612","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The results of sensing of East Antarctica and the adjoining areas of the Southern Ocean by MTVZA-GYа microwave satellite radiometers at frequency ν = 10–190 GHz and AMSR2 at ν = 6–89 GHz in conditions of warm and humid air (an atmospheric river (AR)) invasion from the area of Tasmania area in March 2022 are presented. The surface air warming caused by AR was recorded by the Automatic Weather Station at the coast and at the Vostok, Concordia, and Dome CII stations in East Antarctica. The variability of atmospheric characteristics above Antarctica was studied using readings of radiosondes launched from the Casey station at the coast and Concordia station at a height of 3230 m and time series of brightness temperatures averaged over a circular area 200 km in diameter with the center at a distance of ~200 km from the Concordia station. The influence of air and surface temperature and atmospheric water-vapor content variations on brightness temperature <i>T</i><sub>b</sub>(ν) variations was estimated from the results of modeling of microwave radiation transfer in the atmosphere–firn system using radiosonde profiles from the Concordia station. It was shown that the increase in <i>T</i><sub>b</sub>(ν) at frequencies of 89–92 GHz of a large part of East Antarctica was caused mainly by an increase in the firn temperature. The increase at frequencies of ∼176–190 GHz in the area of the water vapor absorption line was caused by an increase of both the firn temperature and air temperature and humidity. Based on measurements of brightness temperature <i>T</i><sub>b</sub>(ν) over the open ocean at frequencies in the atmospheric-transparency windows of ∼6–48 and 88–92 GHz, wind speed <i>W</i>, cloud liquid-water content <i>Q</i>, and atmospheric water-vapor content <i>V</i> were determined and the temporal variability of parameters in the AR area was studied.</p>","PeriodicalId":56319,"journal":{"name":"Cosmic Research","volume":"76 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139979932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1134/s0010952523700727
A. Yu. Trokhimovskiy, O. I. Korablev, Yu. S. Ivanov, A. S. Patrakeev, A. A. Fedorova, I. A. Dzyuban, V. V. Druzhin, M. A. Poluarshinov, Yu. V. Smirnov
Abstract
The concept of a high aperture near-infrared cross-dispersion echelle-spectrometer is presented for greenhouse gases remote measurements from space. This task is of a global nature, industrial and household emissions are anthropogenic sources of greenhouse-gas emissions. In recent years, average levels of carbon (CO2) and methane (CH4) have continued to increase, reaching levels of 410 ppm and 1877 ppb, respectively, to date. Obtaining objective information about the state of the carbon balance in the atmosphere is possible only with the use of space-based instruments. The Driada instrument consists of three channels. The main one is a high-resolution spectrometer for the 1.4- to 1.67-μm wavelength range and is designed to measure CO2 absorption lines at 1.58 and 1.6 μm, CH4 lines at 1.65 μm, and a number of H2O lines. Two additional channels are designed to measure the O2 band at 0.76 μm and aerosol characterization. The scientific tasks and key parameters of the main infrared channel are discussed.
{"title":"Infrared Channel of the Driada Spectrometer for Greenhouse-Gas Measurement from Space","authors":"A. Yu. Trokhimovskiy, O. I. Korablev, Yu. S. Ivanov, A. S. Patrakeev, A. A. Fedorova, I. A. Dzyuban, V. V. Druzhin, M. A. Poluarshinov, Yu. V. Smirnov","doi":"10.1134/s0010952523700727","DOIUrl":"https://doi.org/10.1134/s0010952523700727","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The concept of a high aperture near-infrared cross-dispersion echelle-spectrometer is presented for greenhouse gases remote measurements from space. This task is of a global nature, industrial and household emissions are anthropogenic sources of greenhouse-gas emissions. In recent years, average levels of carbon (CO<sub>2</sub>) and methane (CH<sub>4</sub>) have continued to increase, reaching levels of 410 ppm and 1877 ppb, respectively, to date. Obtaining objective information about the state of the carbon balance in the atmosphere is possible only with the use of space-based instruments. The Driada instrument consists of three channels. The main one is a high-resolution spectrometer for the 1.4- to 1.67-μm wavelength range and is designed to measure CO<sub>2</sub> absorption lines at 1.58 and 1.6 μm, CH<sub>4</sub> lines at 1.65 μm, and a number of H<sub>2</sub>O lines. Two additional channels are designed to measure the O<sub>2</sub> band at 0.76 μm and aerosol characterization. The scientific tasks and key parameters of the main infrared channel are discussed.</p>","PeriodicalId":56319,"journal":{"name":"Cosmic Research","volume":"52 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139980386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1134/s0010952523700715
S. S. Shinkarenko, S. A. Bartalev, M. A. Bogodukhov, V. O. Zharko
Abstract
This report presents an analysis of the potential of using the information product ATL08 derived from the ATLAS/ICESat-2 (Advanced Topographic Laser Altimeter System/Ice, Cloud, and land Elevation Satellite) satellite lidar to determine the height of protective forest stands. Height measurements, corresponding to vegetation based on lidar data from 2019 to 2022, were compared with the results of aerial photography processing conducted in Volgograd oblast in 2022. A significant strong correlation was found between the mean and maximum canopy heights determined from aerial survey and laser scanning data for 20 × 14-m segments with a woody and shrub vegetation cover exceeding 50%. For the mean canopy height, the root mean square error (RMSE) is ±0.7 m and coefficient of determination R2 = 0.85; for the maximum canopy height, RMSE = 2.2 m and R2 = 0.83. Comparison of projective cover using lidar data, calculated as the ratio of the number of photons above a certain threshold height to the total number of photons in the segment, with aerial photography data showed insufficient accuracy of this approach. The results suggest that ATL08 lidar data holds promise for evaluating the height of protective forest stands, although it may not be suitable for determining projective cover.
{"title":"Assessment of the Potential for Determining the Height and Projective Cover of Protective Forest Stands Using ICESat-2 Data","authors":"S. S. Shinkarenko, S. A. Bartalev, M. A. Bogodukhov, V. O. Zharko","doi":"10.1134/s0010952523700715","DOIUrl":"https://doi.org/10.1134/s0010952523700715","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>This report presents an analysis of the potential of using the information product ATL08 derived from the ATLAS/<i>ICESat-2</i> (Advanced Topographic Laser Altimeter System/Ice, Cloud, and land Elevation Satellite) satellite lidar to determine the height of protective forest stands. Height measurements, corresponding to vegetation based on lidar data from 2019 to 2022, were compared with the results of aerial photography processing conducted in Volgograd oblast in 2022. A significant strong correlation was found between the mean and maximum canopy heights determined from aerial survey and laser scanning data for 20 × 14-m segments with a woody and shrub vegetation cover exceeding 50%. For the mean canopy height, the root mean square error (RMSE) is ±0.7 m and coefficient of determination <i>R</i><sup>2</sup> = 0.85; for the maximum canopy height, RMSE = 2.2 m and <i>R</i><sup>2</sup> = 0.83. Comparison of projective cover using lidar data, calculated as the ratio of the number of photons above a certain threshold height to the total number of photons in the segment, with aerial photography data showed insufficient accuracy of this approach. The results suggest that ATL08 lidar data holds promise for evaluating the height of protective forest stands, although it may not be suitable for determining projective cover.</p>","PeriodicalId":56319,"journal":{"name":"Cosmic Research","volume":"63 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1134/s0010952523700636
I. M. Mikhailenko, V. N. Timoshin
Abstract
The purpose of this work is to present new results of using Earth remote sensing data in the problem of managing agricultural technology in real time. The main reason for the low efficiency of modern precision farming technologies is the lack of an adequate theory of agricultural technology management. At the same time, when creating such a theory, one should take into account the fact that the object of management, which is agricultural technology, includes agrocenoses, in which, in addition to sowing a crop, weeds are also included. Failure to take this factor into account leads to a deterioration in management efficiency, a decrease in sowing productivity and an over expenditure of mineral fertilizers and herbicides. In the presented work, for the first time, a complete theory of managing the state of agrocenoses is presented. This theory makes it possible to obtain a given yield with the required reliability. Such management is formed on the basis of estimates of the parameters of the state of sowing crops and weeds, formed according to remote sensing data in real time. The presented theory is based on new mathematical models of parameters of the state of agricultural crops, the soil environment, and weeds, as well as models of the relationship of these parameters with remote sensing data. Mineral fertilizers, herbicides, and irrigation are control factors in agricultural technology. Naturally, the parameters of technological operations are the doses of applied mineral fertilizers and herbicides, as well as irrigation rates. These operations are carried out at the onset of certain phenological phases of sowing crops. Remote sensing data are entered precisely at such moments of time, and the parameters of the state of crops and weeds are estimated on their basis. The presented theory is based on classical control principles used in modern dynamic systems. According to the proposed theory, a specialized software package was developed, with the help of which the control system was tested on the example of spring wheat sowing.
{"title":"Control of the State of Agrocenoses Based on Earth Remote Sensing Data","authors":"I. M. Mikhailenko, V. N. Timoshin","doi":"10.1134/s0010952523700636","DOIUrl":"https://doi.org/10.1134/s0010952523700636","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The purpose of this work is to present new results of using Earth remote sensing data in the problem of managing agricultural technology in real time. The main reason for the low efficiency of modern precision farming technologies is the lack of an adequate theory of agricultural technology management. At the same time, when creating such a theory, one should take into account the fact that the object of management, which is agricultural technology, includes agrocenoses, in which, in addition to sowing a crop, weeds are also included. Failure to take this factor into account leads to a deterioration in management efficiency, a decrease in sowing productivity and an over expenditure of mineral fertilizers and herbicides. In the presented work, for the first time, a complete theory of managing the state of agrocenoses is presented. This theory makes it possible to obtain a given yield with the required reliability. Such management is formed on the basis of estimates of the parameters of the state of sowing crops and weeds, formed according to remote sensing data in real time. The presented theory is based on new mathematical models of parameters of the state of agricultural crops, the soil environment, and weeds, as well as models of the relationship of these parameters with remote sensing data. Mineral fertilizers, herbicides, and irrigation are control factors in agricultural technology. Naturally, the parameters of technological operations are the doses of applied mineral fertilizers and herbicides, as well as irrigation rates. These operations are carried out at the onset of certain phenological phases of sowing crops. Remote sensing data are entered precisely at such moments of time, and the parameters of the state of crops and weeds are estimated on their basis. The presented theory is based on classical control principles used in modern dynamic systems. According to the proposed theory, a specialized software package was developed, with the help of which the control system was tested on the example of spring wheat sowing.</p>","PeriodicalId":56319,"journal":{"name":"Cosmic Research","volume":"49 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1134/s0010952523700673
G. E. Khazanov, S. A. Ermakov, V. A. Dobrokhotov, G. V. Leshchev, A. V. Kupaev, O. A. Danilicheva
Abstract
Sea ice in its initial formation stages in the nearshore zone can exist in various forms such as grease ice, snow sludge, and pancake ice. These initial ice forms (IIFs) lead to the attenuation of waves on the sea surface, consequently affecting the intensity of microwave scattering on the sea surface. This complicates the identification of areas covered by IIFs that are situated between consolidated ice and open water. This work aims to analyze wave propagation in the presence of IIFs to develop physical models of wave attenuation. The paper presents a description and results of special field experiments to investigate the attenuation of wind waves of various lengths in the presence of ice simulators. Results of numerical simulation of the attenuation of gravitational waves and a comparison with experimental results are also given. One of the significant findings in the studied dependence of the attenuation coefficient on the ice floe size-to-wave length ratio, observed in both field and numerical experiments, is the discovery of a local maximum for waves with lengths of the order of the “ice floe” size. A physical interpretation of the mechanism of gravitational wave attenuation in the presence of ice floes is proposed, taking into account their attached mass.
{"title":"A Study of Gravitational Wave Attenuation in Fragmented Ice","authors":"G. E. Khazanov, S. A. Ermakov, V. A. Dobrokhotov, G. V. Leshchev, A. V. Kupaev, O. A. Danilicheva","doi":"10.1134/s0010952523700673","DOIUrl":"https://doi.org/10.1134/s0010952523700673","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Sea ice in its initial formation stages in the nearshore zone can exist in various forms such as grease ice, snow sludge, and pancake ice. These initial ice forms (IIFs) lead to the attenuation of waves on the sea surface, consequently affecting the intensity of microwave scattering on the sea surface. This complicates the identification of areas covered by IIFs that are situated between consolidated ice and open water. This work aims to analyze wave propagation in the presence of IIFs to develop physical models of wave attenuation. The paper presents a description and results of special field experiments to investigate the attenuation of wind waves of various lengths in the presence of ice simulators. Results of numerical simulation of the attenuation of gravitational waves and a comparison with experimental results are also given. One of the significant findings in the studied dependence of the attenuation coefficient on the ice floe size-to-wave length ratio, observed in both field and numerical experiments, is the discovery of a local maximum for waves with lengths of the order of the “ice floe” size. A physical interpretation of the mechanism of gravitational wave attenuation in the presence of ice floes is proposed, taking into account their attached mass.</p>","PeriodicalId":56319,"journal":{"name":"Cosmic Research","volume":"25 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1134/s0010952523700533
O. A. Girina, E. A. Loupian, A. Horvath, D. V. Melnikov, A. G. Manevich, A. A. Nuzhdaev, A. A. Bril, A. Yu. Ozerov, L. S. Kramareva, A. A. Sorokin
Abstract
The Sheveluch volcano is the most active volcano in Kamchatka. The paroxysmal explosive eruption of the volcano that destroyed the lava dome in the volcanic crater continued on April 10–13, 2023. According to various satellite data, the height of the separate eruptive clouds probably exceeded 15 km above sea level. A powerful cyclone, which dominated the entire Kamchatka Peninsula, pulled the eruptive cloud to the west, turned it to the south, stretched it to the north, and directed it to the east from the volcano. The dynamics of the development of ash and aerosol clouds of this eruption is reflected in the animations made from a series of Himawari-9 satellite images in the VolSatView IS from 08:00 UTC on April 10 to 07:00 UTC on April 14 (http://d33.infospace.ru/jr_d33/materials/2023v20n2/283-291/1683110898.webm) and of the Arctica-M1 satellite from 16:00 to 21:30 UTC on April 10 (http://d33.infospace.ru/jr_d33/materials/2023v20n2/283-291/1683821166.webm). It was noted that the eruptive column was not vertical: for example, at the initial moment of the eruption on April 10 at 13:20 UTC, it deviated to the north–northeast; on April 11, at 12:00 UTC to the northwest; and, on April 12, at 7:00 UTC to the southwest. During the paroxysmal eruption, sulfur dioxide continuously entered the atmosphere, the maximum amount of which was released on April 10–11, as a result of the explosive destruction of the lava dome of the Sheveluch volcano. Ash clouds along with aerosol clouds on April 10–13 were stretched into a strip more than 3500 km long from west to northeast. On April 21–22, the Sheveluch aerosol cloud was observed in the region of the Scandinavian Peninsula. The total area of the territory of Kamchatka and the Pacific Ocean where ash and aerosol plumes and clouds were observed during the April 10–13 eruption was about 3 280 000 km2. The paroxysmal eruption of Sheveluch volcano belongs to the sub-Plinian type because it is characterized by a large height of the eruptive cloud and a long event duration. For this eruption, the Volcanic Explosivity Index is estimated to be 3–4. A detailed description of the paroxysmal explosive eruption of the Sheveluch volcano and the spread of the eruptive cloud was performed based on data from various satellite systems (Himawari-9, NOAA-18/19, GOES-18, Terra, Aqua, JPSS-1, Suomi NPP, Arctica-M1, etc.) in the information system “Remote Monitoring of Kamchatka and Kuril Islands Volcanic Activity” (VolSatView, http://kamchatka.volcanoes.smislab.ru).
{"title":"Analysis of the Development of the Paroxysmal Eruption of the Sheveluch Volcano on April 10–13, 2023, Based on Data from Various Satellite Systems","authors":"O. A. Girina, E. A. Loupian, A. Horvath, D. V. Melnikov, A. G. Manevich, A. A. Nuzhdaev, A. A. Bril, A. Yu. Ozerov, L. S. Kramareva, A. A. Sorokin","doi":"10.1134/s0010952523700533","DOIUrl":"https://doi.org/10.1134/s0010952523700533","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The Sheveluch volcano is the most active volcano in Kamchatka. The paroxysmal explosive eruption of the volcano that destroyed the lava dome in the volcanic crater continued on April 10–13, 2023. According to various satellite data, the height of the separate eruptive clouds probably exceeded 15 km above sea level. A powerful cyclone, which dominated the entire Kamchatka Peninsula, pulled the eruptive cloud to the west, turned it to the south, stretched it to the north, and directed it to the east from the volcano. The dynamics of the development of ash and aerosol clouds of this eruption is reflected in the animations made from a series of <i>Himawari-9</i> satellite images in the VolSatView IS from 08:00 UTC on April 10 to 07:00 UTC on April 14 (http://d33.infospace.ru/jr_d33/materials/2023v20n2/283-291/1683110898.webm) and of the Arctica-M1 satellite from 16:00 to 21:30 UTC on April 10 (http://d33.infospace.ru/jr_d33/materials/2023v20n2/283-291/1683821166.webm). It was noted that the eruptive column was not vertical: for example, at the initial moment of the eruption on April 10 at 13:20 UTC, it deviated to the north–northeast; on April 11, at 12:00 UTC to the northwest; and, on April 12, at 7:00 UTC to the southwest. During the paroxysmal eruption, sulfur dioxide continuously entered the atmosphere, the maximum amount of which was released on April 10–11, as a result of the explosive destruction of the lava dome of the Sheveluch volcano. Ash clouds along with aerosol clouds on April 10–13 were stretched into a strip more than 3500 km long from west to northeast. On April 21–22, the Sheveluch aerosol cloud was observed in the region of the Scandinavian Peninsula. The total area of the territory of Kamchatka and the Pacific Ocean where ash and aerosol plumes and clouds were observed during the April 10–13 eruption was about 3 280 000 km<sup>2</sup>. The paroxysmal eruption of Sheveluch volcano belongs to the sub-Plinian type because it is characterized by a large height of the eruptive cloud and a long event duration. For this eruption, the Volcanic Explosivity Index is estimated to be 3–4. A detailed description of the paroxysmal explosive eruption of the Sheveluch volcano and the spread of the eruptive cloud was performed based on data from various satellite systems (<i>Himawari-9</i>, <i>NOAA-18/19</i>, <i>GOES-18</i>, <i>Terra</i>, <i>Aqua</i>, <i>JPSS-1</i>, <i>Suomi NPP</i>, <i>Arctica-M1</i>, etc.) in the information system “Remote Monitoring of Kamchatka and Kuril Islands Volcanic Activity” (VolSatView, http://kamchatka.volcanoes.smislab.ru).</p>","PeriodicalId":56319,"journal":{"name":"Cosmic Research","volume":"35 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139980372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1134/s0010952523700703
S. S. Shinkarenko, S. A. Bartalev
Abstract
The intensification of pasture degradation in the southern part of European Russia, which is caused by unfavorable hydrothermal conditions and unregulated livestock numbers, requires the development of approaches to assess the capacity of forage lands using Earth remote sensing methods. The spectral reflectance properties of vegetation are determined by its taxonomic, structural, phenological, biophysical, and biochemical characteristics. However, the patterns of how these parameters affect the spectral response are region-specific and heavily influenced by soil cover. Therefore, it is essential to expand the regional scope of studies on the spectral reflectance properties of various vegetation types. This research is devoted to determining the spectral reflectance properties of natural zonal pastures in southern European Russia, based on geobotanical investigations and field spectrometry using the PSR-1100f instrument within the 320–1100 nm range. Groundwork was carried out in May (the period of maximum green mass of vegetation) 2020–2022 in the territories of natural zonal pastures in Astrakhan and Volgograd oblasts, Stavropol krai, and the Republics of Dagestan and Kalmykia. Significant differences were found between feather grasses, semishrubs, and annuals in the visible and near-ultraviolet spectral regions. Changes in the projective cover, under other equal conditions, have the most significant impact on spectral properties in the 660–670 nm range, which is consistent with the results of other researchers. Vegetation indices were identified that are best suited for determining projective cover and above-ground biomass of pastures with various dominant species. Further research will enable transitioning from point measurements of spectral reflectance and structural vegetation characteristics to satellite data with different spatial resolutions.
{"title":"Analysis of the Impact of Species Composition, Projective Cover, and Phytomass of Vegetation in Arid Pasture Landscapes on Their Spectral Reflectance Properties Based on Ground Measurements","authors":"S. S. Shinkarenko, S. A. Bartalev","doi":"10.1134/s0010952523700703","DOIUrl":"https://doi.org/10.1134/s0010952523700703","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The intensification of pasture degradation in the southern part of European Russia, which is caused by unfavorable hydrothermal conditions and unregulated livestock numbers, requires the development of approaches to assess the capacity of forage lands using Earth remote sensing methods. The spectral reflectance properties of vegetation are determined by its taxonomic, structural, phenological, biophysical, and biochemical characteristics. However, the patterns of how these parameters affect the spectral response are region-specific and heavily influenced by soil cover. Therefore, it is essential to expand the regional scope of studies on the spectral reflectance properties of various vegetation types. This research is devoted to determining the spectral reflectance properties of natural zonal pastures in southern European Russia, based on geobotanical investigations and field spectrometry using the PSR-1100f instrument within the 320–1100 nm range. Groundwork was carried out in May (the period of maximum green mass of vegetation) 2020–2022 in the territories of natural zonal pastures in Astrakhan and Volgograd oblasts, Stavropol krai, and the Republics of Dagestan and Kalmykia. Significant differences were found between feather grasses, semishrubs, and annuals in the visible and near-ultraviolet spectral regions. Changes in the projective cover, under other equal conditions, have the most significant impact on spectral properties in the 660–670 nm range, which is consistent with the results of other researchers. Vegetation indices were identified that are best suited for determining projective cover and above-ground biomass of pastures with various dominant species. Further research will enable transitioning from point measurements of spectral reflectance and structural vegetation characteristics to satellite data with different spatial resolutions.</p>","PeriodicalId":56319,"journal":{"name":"Cosmic Research","volume":"9 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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