ADVANCES IN SPACE RESEARCH空间研究进展
ADVANCES IN SPACE RESEARCH(英文缩写 ADV SPACE RES),ISSN 0273-1177,eISSN 1879-1948,中文译名:空间研究进展 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-10-01 至 2026-09-30，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 2.611 | Q2 |
| 2022 | 2.600 | Q1 |
| 2023 | 2.800 | Q1 |
| 2024 | 2.800 | Q1 |
| 2025 | 3.200 | Q1 |
ADVANCES IN SPACE RESEARCH 最新收录文献
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1. Crop type discrimination using Geo-Stat Endmember Extraction and machine learning algorithms.
PMID:期刊:日期:2024-01The identification of crop diversity in today's world is very crucial to ensure adaptation of the crop with changing climate for better productivity as well as food security. Towards this, Hyperspectral Remote Sensing (HRS) is an efficient technique based on imaging spectroscopy that offers the opportunity to discriminate crop types based on morphological as well as physiological features due to availability of contiguous spectral bands. The current work utilized the benefits of Airborne Visible Infrared Imaging spectrometer- New Generation (AVIRIS-NG) data and explored the techniques for classification and identification of crop types. The endmembers were identified using the Geo-Stat Endmember Extraction (GSEE) algorithm for pure pixels identification and to generate the spectral library of the different crop types. Spectral feature comparison was done among AVIRIS-NG, Analytical Spectral Device (ASD)-Spectroradiometer and Continuum Removed (CR) spectra. The best-fit spectra obtained with the Reference ASD-Spectroradiometer and Pure Pixel spectral library were then used for crop discrimination using the ten supervised classifiers namely Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), Support Vector Machine (SVM), Minimum Distance Classifier (MDC), Binary Encoding, deep learning-based Convolution Neural Network (CNN) and different algorithms of Ensemble learning such as Tree Bag, AdaBoost (Adaptive Boosting), Discriminant and RUSBoost (Random Under Sampling). In total, nine crop types were identified, namely, wheat, maize, tobacco, sorghum, linseed, castor, pigeon pea, fennel and chickpea. The performance evaluation of the classifiers was made using various metrics like Overall Accuracy, Kappa Coefficient, Precision, Recall and F1 score. The classifier 2D-CNN was found to be the best with Overall Accuracy, Kappa Coefficient, Precision, Recall and F1 score values of 89.065 %, 0.871,87.565%, 89.541% and 88.678% respectively. The output of this work can be utilized for large scale mapping of crop types at the species level in a short interval of time of a large area with high accuracy.
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2. Investigating Patterns of Air Pollution in Metropolises Using Remote Sensing and Neural Networks During the COVID-19 Pandemic.
PMID:期刊:日期:2023-06-21The purpose of this study is to determine the amount of air pollution in Tehran, Isfahan, Semnan, Mashhad, Golestan, and Shiraz during the Corona era and before. For this purpose, Sentinel satellite images were used to investigate the concentration of Methane (CH), Carbon Monoxide (CO), Carbon Dioxide (CO), Nitrogen Dioxide (NO), Ozone (O), Sulfur Dioxide (SO), aerosol pollutants in In the era before and during Corona. Furthermore, greenhouse effect-prone areas were determined in this study. In the following, the state of air inversion in the studied area was determined by taking the temperature on the surface of the earth and in the upper atmosphere, as well as the wind speed into account. In this research, the prediction of air temperature for the year 2040 was conducted using the Markov and Cellular Automaton (CA)-Markov methods, considering the impact of air pollution on the air temperature of metropolises. Additionally, the Radial Basis Function (RBF) and Multilayer Perceptron (MLP) methods have been developed to determine the relationship between pollutants, areas prone to air inversions, and temperature values. According to the results, pollution caused by pollutants has decreased in the Corona era. According to the results, there is more pollution in Tehran and Isfahan metropolises. In addition, the results showed that air inversions in Tehran is the highest. Additionally, the results showed a high correlation between temperature and pollution levels (R=0.87). Thermal indices in the studied area indicate that Isfahan and Tehran, with high values of Surface Urban Heat Island (SUHI) and being in the 6th class of thermal comfort (Urban Thermal Field Variance Index (UTFVI)), are affected by thermal pollution. The results showed that parts of southern Tehran province, southern Semnan and northeastern Isfahan will have higher temperatures in 2040 (class 5 and 6). Finally, the results of the neural network method showed that the MLP method with R=0.90 is more accurate than the RBF method in predicting pollution amounts. This study significantly contributes by introducing innovative advancements through the application of RBF and MLP methods to assess air pollution levels during the COVID-19 and pre-pandemic periods, while also investigating the intricate relationships among greenhouse gases, air inversion, air temperature, and pollutant indices within the atmosphere. The utilization of these methods notably enhances the accuracy and reliability of pollution predictions, amplifying the originality and significance of this research.
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3. A Hansel & Gretel breadcrumb-style dynamically deployed communication network paradigm using mesh topology for planetary subsurface exploration.
3. Hansel&Gretel面包屑风格的动态部署通信网络范式，使用网格拓扑进行行星地下勘探PMID:期刊:日期:2023-02-11We introduce a dynamically deployed communication network (DDCN) paradigm using mesh topology in support of a distributed robotic multi-agent approach for the autonomous exploration of subsurface environments, i.e., caves, lava tube caves, lakes, and oceans, etc. The DDCN, comprising wireless communication beacons autonomously deployed via a rover or submersible in a Hansel & Gretel-inspired breadcrumb style, allows for the longest and most robust communication link between subterranean robotic agent(s) within, e.g., a lave tube cave or a subsurface ocean, and associated surface-borne robotic agent(s). Moreover, we briefly touch on the development of a robotic testbed and wired/wireless communication beacons in support of such astrobiological surface/subsurface exploration scenarios. Candidate lava tube caves have been identified on the Moon and Mars, raising possibilities for planetary exploration, astrobiology, habitat construction for future astronauts, and potential mining operations. Subterranean caverns, and in particular relatively deep lava tube caves, provide a possible refuge for life under otherwise challenging planetary surface conditions, and, as such, are of prime astrobiological relevance. Lava tube caves or other subsurface environments may also be suitable habitats for astronauts and subsequent human settlement but are yet to be explored in part due to difficulties ensuring continued communication with a robotic probe inside these environments. Moreover, the existence of subsurface oceans on ocean worlds, such as Europa, Enceladus, and Titan, has been backed by varying levels of evidence since the 1980s, though there has been no confirmation, i.e., direct observation, thus far. Such environments are also shielded from radiation, and, in combination with the hypothesized presence of water, are additional candidate environments for finding extant or fossilized life. The DDCN paradigm introduced herein directly addresses NASA's Space Technology Grand Challenges - "All Access Mobility" by enabling the most unconstrained exploration of subsurface environments through a dynamic communication network which ensures transmission of data from and possibly commands to the subsurface robotic probe. 2023 COSPAR. Published by Elsevier B.V. All rights reserved.
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4. Exploring the effect of COVID-19 pandemic lockdowns on urban cooling: A tale of three cities.
PMID:期刊:日期:2022-09-28COVID-19 pandemic has had a major impact on our society, environment and public health, in both positive and negative ways. The main aim of this study is to monitor the effect of COVID-19 pandemic lockdowns on urban cooling. To do so, satellite images of Landsat 8 for Milan and Rome in Italy, and Wuhan in China were used to look at pre-lockdown and during the lockdown. First, the surface biophysical characteristics for the pre-lockdown and within-lockdown dates of COVID-19 were calculated. Then, the land surface temperature (LST) retrieved from Landsat thermal data was normalized based on cold pixels LST and statistical parameters of normalized LST (NLST) were calculated. Thereafter, the correlation coefficient (r) between the NLST and index-based built-up index (IBI) was estimated. Finally, the surface urban heat island intensity (SUHII) of different cities on the lockdown and pre-lockdown periods was compared with each other. The mean NLST of built-up lands in Milan (from 7.71 °C to 2.32 °C), Rome (from 5.05 °C to 3.54 °C) and Wuhan (from 3.57 °C to 1.77 °C) decreased during the lockdown dates compared to pre-lockdown dates. The r (absolute value) between NLST and IBI for Milan, Rome and Wuhan decreased from 0.43, 0.41 and 0.16 in the pre-lockdown dates to 0.25, 0.24, and 0.12 during lockdown dates respectively, which shows a large decrease for all cities. Analysis of SUHI for these cities showed that SUHII during the lockdown dates compared to pre-lockdown dates decreased by 0.89 °C, 1.78 °C, and 1.07 °C respectively. The results indicated a high and substantial impact of anthropogenic activities and anthropogenic heat flux (AHF) on the SUHI due to the substantial reduction of huge anthropogenic pressure in cities. Our conclusions draw attention to the contribution of COVID-19 lockdowns (reducing the anthropogenic activities) to creating cooler cities.
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5. Using satellite images of nighttime lights to predict the economic impact of COVID-19 in India.
PMID:期刊:日期:2022-05-24The outbreak of COVID-19 in early 2020 heralded a deep global recession not seen since the Second World War. With entire nations in lockdown, burgeoning economies of countries like India plunged into a downward spiral. The conventional instruments of estimating the short-term economic impact of a pandemic is limited, and as a result, it is challenging to implement timely monetary policies to mitigate the financial impact of such unforeseen events. This study investigates the promise of using nighttime images of lights on Earth, also known as nightlight (NTL), captured by the Visible Infrared Imaging Radiometer Suite (VIIRS) instrumentation onboard the Suomi National Polar-Orbiting Partnership (Suomi NPP) satellite mission to measure the economic cost of the pandemic in India. First, a novel data processing framework was developed for a recently released radiance dataset known as VNP46A1, part of NASA's Black Marble suite of NTL products. Second, the elasticity of nightlight to India's National Gross Domestic Product (GDP) was estimated using panel regression followed by machine learning to predict the Year-over-Year (YoY) change in GDP during Fiscal Year (FY) 2020Q1 (Apr-Jun, 2020). Electricity consumption, known to closely track economic output and precipitation were included as additional features to improve model performance. A strong relationship between both electricity usage and nightlight to GDP was observed. The model predicted a YoY contraction of 24% in FY2020Q1, almost identical to the official GDP decline of 23.9% later announced by the Indian Government. Based on the findings, the study concludes that nightlight along with electricity usage can be invaluable proxies for estimating the cost of short-term supply-demand shocks such as COVID-19, and should be explored further.
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6. Impact of COVID-19 lockdown on the fine particulate matter concentration levels: Results from Bengaluru megacity, India.
PMID:期刊:日期:2021-01-20Leveraging the COVID-19 India-wide lockdown situation, the present study attempts to quantify the reduction in the ambient fine particulate matter concentrations during the lockdown (compared with that of the pre-lockdown period), owing to the highly reduced specific anthropogenic activities and thereby pollutant emissions. The study was conducted over Bengaluru (India), using PM (mass concentration of particulate matter having size less than or equal to 2.5 µm) and Black Carbon mass concentration (BC) data. Open-access datasets from pollution control board (PCB) were also utilised to understand the spatial variability and region-specific reduction in PM across the city. The highest percentage reduction was observed in BC (black carbon attributable to fossil fuel combustion), followed by total BC and PM. No decrease in BC (black carbon attributable to wood/biomass burning) was observed, suggesting unaltered wood-based cooking activities and biomass-burning (local/regional) throughout the study period. Results support the general understanding of multi-source (natural and anthropogenic) nature of PM in contrast to limited-source (combustion based) nature of BC. The diurnal amplitudes in BC and BC were reduced, while they remained almost the same for PM and BC. Analysis of PCB data reveal the highest reduction in PM in an industrial cluster area. The current lockdown situation acted as a natural model to understand the role of a few major anthropogenic activities (viz., traffic, construction, industries related to non-essential goods, etc.) in enhancing the background fine particulate matter levels. Contemporary studies reporting reduction in surface fine particulate matter and satellite retrieved columnar Aerosol Optical Depth (AOD) during COVID-19 lockdown period are discussed.
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8. Variations in the ionosphere-thermosphere system from tides, ultra-fast Kelvin waves, and their interactions.
PMID:期刊:日期:2019-08-23Large scale waves, such as the atmospheric tides and ultra-fast Kelvin waves (UFKW), have direct effects on the neutral wind and temperature fields of the ionosphere-thermosphere (I-T) system. In this study we examine the response of the I-T system to the atmospheric tides, one UFKW, and the secondary waves generated from their interactions using the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM). We find that forcing an UFKW at the lower boundary of the TIEGCM is all that is required for it to setup in the model. We see variations around 10% in the zonal winds that lead to similar variations in the total electron content (TEC) depending on the phase of the UFKW. From these simulations, we expect the Ionospheric Connection Explorer (ICON) mission will be able to fully capture these wave interactions by observing winds and temperatures at the mesopause and above.
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9. Planetary Protection and the astrobiological exploration of Mars: Proactive steps in moving forward.
PMID:期刊:日期:2019-03Future efforts towards Mars exploration should include a discussion about the effects that the strict application of Planetary Protection policies is having on the astrobiological exploration of Mars, which is resulting in a continued delay in the search for Martian life. As proactive steps in the path forward, here we propose advances in three areas. First, we suggest that a redefinition of Planetary Protection and Special Regions is required for the case of Mars. Particularly, we propose a definition for special places on Mars that we can get to in the next 10-20 years with rovers and landers, where try to address questions regarding whether there is present-day near-surface life on Mars or not, and crucially doing so before the arrival of manned missions. We propose to call those special places 'Astrobiology Priority Exploration" regions (APEX regions). Second, we stress the need for the development of robotic tools for the characterization of complex organic compounds as unequivocal signs of life, and particularly new generations of complex organic chemistry and biosignature detection instruments, including advances in DNA sequencing. And third, we advocate for a change from the present generation of SUV-sized landers and rovers to new robotic assets that are much easier to decontaminate such as microlanders: they would be very small with limited sensing capabilities, but there would be many of them available for launch and coordination from an orbiting platform. Implementing these changes will help to move forward with an exploration approach that is much less risky to the potential Mars biosphere, while also being much more scientifically rigorous about the exploration of the 'life on Mars" question - a question that needs to be answered both for astrobiological discovery and for learning more definitive lessons on Planetary Protection.
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10. Advanced Illumination Modeling for Data Analysis and Calibration. Application to the Moon.
PMID:期刊:日期:2018-08-25We present a new illumination modeling tool, called IllumNG, developed at NASA Goddard Space Flight Center (GSFC). We describe its capabilities to enhance the analysis and calibration of science data collected by planetary missions. We highlight these with examples making use of lunar data, particularly the topographic and radiometric measurements collected by the Lunar Orbiter Laser Altimeter (LOLA) instrument, with applications to radiometric measurements from other LRO instruments as well. The unique features of IllumNG are its accuracy and flexibility to handle multiple types of observers and light sources, and its ability to accurately model both singly- and doubly-scattered radiation to an observer.