The 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.

We 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.

The 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 (CH4), Carbon Monoxide (CO), Carbon Dioxide (CO2), Nitrogen Dioxide (NO2), Ozone (O3), Sulfur Dioxide (SO2), 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[2]=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[2]=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.

COVID-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.

The 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.

Leveraging 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 PM2.5 (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 PM2.5 across the city. The highest percentage reduction was observed in BCff (black carbon attributable to fossil fuel combustion), followed by total BC and PM2.5. No decrease in BCbb (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 PM2.5 in contrast to limited-source (combustion based) nature of BC. The diurnal amplitudes in BC and BCff were reduced, while they remained almost the same for PM2.5 and BCbb. Analysis of PCB data reveal the highest reduction in PM2.5 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.

Large 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.

We 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.

Future 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.

A conceptual design is presented for a low complexity, heritage-based flyby mission to Io, Jupiter's innermost Galilean satellite and the most volcanically active body in the Solar System. The design addresses the 2011 Decadal Surveys recommendation for a New Frontiers class mission to Io and is based upon the result of the June 2012 NASA-JPL Planetary Science Summer School. A science payload is proposed to investigate the link between the structure of Io's interior, it's volcanic activity, it's surface composition, and it's tectonics. A study of Io's atmospheric processes and Io's role in the Jovian magnetosphere is also planned. The instrument suite includes a visible/near IR imager, a magnetic field and plasma suite, a dust analyzer and a gimbaled high gain antenna to perform radio science investigations. Payload activity and spacecraft operations would be powered by three Advanced Stirling Radioisotope Generators (ASRG). The primary mission includes 10 flybys with close-encounter altitudes as low as 100 km. The mission risks are mitigated by ensuring that relevant components are radiation tolerant and by using redundancy and flight-proven parts in the design. The spacecraft would be launched on an Atlas V rocket with a delta-v of 1.3 km/s. Three gravity assists (Venus, Earth, Earth) would be used to reach the Jupiter system in a 6-year cruise. The resulting concept demonstrates the rich scientific return of a flyby mission to Io.

The Student Spaceflight Experiments Program (SSEP) is a United States national science, technology, engineering, and mathematics initiative that aims to increase student interest in science by offering opportunities to perform spaceflight experiments. The experiment detailed here was selected and flown aboard the third SSEP mission and the first SSEP mission to the International Space Station (ISS). Caenorhabditis elegans is a small, transparent, self-fertilizing hermaphroditic roundworm that is commonly used in biological experiments both on Earth and in Low Earth Orbit. Past experiments have found decreased expression of mRNA for several genes whose expression can be controlled by the FOXO transcription factor DAF-16. We flew a daf-16 mutant and control worms to determine if the effects of spaceflight on C. elegans are mediated by DAF-16. The experiment used a Type Two Fluids Mixing Enclosure (FME), developed by Nanoracks LLC, and was delivered to the ISS aboard the SpaceX Dragon and returned aboard the Russian Soyuz. The short time interval between experiment selection and the flight rendered preflight experiment verification tests impossible. In addition, published research regarding the viability of the FME in life science experiments was not available. The experiment was therefore structured in such a way as to gather the needed data. Here we report that C. elegans can survive relatively short storage and activation in the FME but cannot produce viable populations for post-flight analysis on extended missions. The FME appears to support short-duration life science experiments, potentially on supply or crew exchange missions, but not on longer ISS expeditions. Additionally, the flown FME was not properly activated, reportedly due to a flaw in training procedures. We suggest that a modified transparent FME could prevent similar failures in future flight experiments.

A major concern for bystander effects is the probability that normal healthy cells adjacent to the irradiated cells become genomically unstable and undergo further carcinogenesis after therapeutic irradiation or space mission where astronauts are exposed to low dose of heavy ions. Genomic instability is a hallmark of cancer cells. In the present study, two irradiation protocols were performed in order to ensure pure populations of bystander cells and the genomic instability in their progeny were investigated. After irradiation, chromosomal aberrations of cells were analyzed at designated time points using G2 phase premature chromosome condensation (G2-PCC) coupled with Giemsa staining and with multiplex fluorescent in situ hybridization (mFISH). Our Giemsa staining assay demonstrated that elevated yields of chromatid breaks were induced in the progeny of pure bystander primary fibroblasts up to 20 days after irradiation. MFISH assay showed no significant level of inheritable interchromosomal aberrations were induced in the progeny of the bystander cell groups, while the fractions of gross aberrations (chromatid breaks or chromosomal breaks) significantly increased in some bystander cell groups. These results suggest that genomic instability occurred in the progeny of the irradiation associated bystander normal fibroblasts exclude the inheritable interchromosomal aberration.

We differentiated mouse bone marrow cells in the presence of recombinant macrophage colony stimulating (rM-CSF) factor for 14 days during the flight of space shuttle Space Transportation System (STS)-126. We tested the hypothesis that the receptor expression for M-CSF, c-Fms was reduced. We used flow cytometry to assess molecules on cells that were preserved during flight to define the differentiation state of the developing bone marrow macrophages; including CD11b, CD31, CD44, Ly6C, Ly6G, F4/80, Mac2, c-Fos as well as c-Fms. In addition, RNA was preserved during the flight and was used to perform a gene microarray. We found that there were significant differences in the number of macrophages that developed in space compared to controls maintained on Earth. We found that there were significant changes in the distribution of cells that expressed CD11b, CD31, F4/80, Mac2, Ly6C and c-Fos. However, there were no changes in c-Fms expression and no consistent pattern of advanced or retarded differentiation during space flight. We also found a pattern of transcript levels that would be consistent with a relatively normal differentiation outcome but increased proliferation by the bone marrow macrophages that were assayed after 14 days of space flight. There also was a surprising pattern of space flight influence on genes of the coagulation pathway. These data confirm that a space flight can have an impact on the in vitro development of macrophages from mouse bone marrow cells.

Animal models are frequently used to assist in the determination of the long- and short-term effects of space flight. The space environment, including microgravity, can impact many physiological and immunological system parameters. It has been found that ground based models of microgravity produce changes in white blood cell counts, which negatively affects immunologic function. As part of the Center of Acute Radiation Research (CARR), we compared the acute effects on white blood cell parameters induced by the more traditionally used animal model of hindlimb unloading (HU) with a recently developed reduced weightbearing analog known as partial weight suspension (PWS). Female ICR mice were either hindlimb unloaded or placed in the PWS system at 16% quadrupedal weightbearing for 4 h, 1, 2, 7 or 10 days, at which point complete blood counts were obtained. Control animals (jacketed and non-jacketed) were exposed to identical conditions without reduced weightbearing. Results indicate that significant changes in total white blood cell (WBC), neutrophil, lymphocyte, monocyte and eosinophil counts were observed within the first 2 days of exposure to each system. These differences in blood cell counts normalized by day 7 in both systems. The results of these studies indicate that there are some statistically significant changes observed in the blood cell counts for animals exposed to both the PWS and HU simulated microgravity systems.