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Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) processes maps of vertical-column abundances of water vapor in atmosphere with good precision and spatial resolution. Maps provide information for meteorology, climatology, and agriculture.
We present a study of the impact of seasonal effects on the spatial distribution of Titan’s atmospheric gases HNC, CH3CN, and HC3N over a timescale of less than a Titan month (9 Earth months). These molecules are synthesized primarily in the upper and middle atmosphere as a result of CH4 and N2 photochemistry, and are redistributed around Titan’s globe as a result of diffusion and zonal and meridional circulation. With observations from the Atacama Large Millimeter/submillimeter Array (ALMA) obtained in August 2016 [1] and May 2017 [2], we produced high-resolution, spectrally and spatially resolved maps of the emission from these gases. These observations are contemporaneous with the end of the Cassini mission (around the time of the northern summer solstice), allowing for studies of seasonal variations in Titan’s organic chemistry through analysis of the production, destruction, and transport of complex molecules. We observed a strong reduction of 41% ± 4% in the HC3N flux coming from the north pole, while CH3CN and HNC remained relatively stable (within errors) over the 9 month period of our observations. In the south pole, CH3CN presented a 31% ± 10% increase, while HNC saw a reduction of 20% ± 8%, and HC3N remained fairly stable (within errors). The HNC emission comes primarily from the highest (thermospheric) altitudes, and is distributed more uniformly about Titan’s limb than HC3N and CH3CN; the latter two molecules show strong polar enhancements due to meridional circulation. The steep decline in the HC3N north polar concentration is consistent its short photochemical lifetime (compared to HNC and CH3CN), combined with a reduction in meridional transport of gases produced at lower latitudes, towards the northern (summer) pole. The loss of emission of HC3N in the northern hemisphere is also consistent with the breakdown of Titan’s northern polar vortex during the onset of the northern summer, leading to a loss of confinement of these species [3].
Mapping the spatial extent of recently identified englacial hydrological features (i.e., ice slabs and perennial firn aquifers) formed by meters-thick water-saturated firn layers over the percolation facies of the Greenland Ice Sheet using L-band microwave radiometry has recently been demonstrated. However, these initial maps are binary, and do not provide a parameter to estimate the spatial variability in the thickness and volumetric fraction of meltwater stored within the firn pore space. Here, we exploit enhanced-resolution vertical-polarization L-band brightness temperature (T^(B)_(V)) imagery (2015–2019) generated using observations collected over Greenland by NASA’s Soil Moisture Active Passive (SMAP) satellite and a simple two-layer L-band brightness temperature model. We map water-saturated firn layers via a “firn saturation” parameter, and interpret our results together with ice slab and perennial firn aquifer spatial extents, estimates of snow accumulation simulated via the Regional Atmospheric Climate Model (RACMOp2.3), and airborne radar surveys collected via NASA’s Operation IceBridge (OIB) campaigns. We find that variable firn saturation parameter values are mapped in lower snow accumulation ice slab areas in western, northern, and northeastern Greenland, where firn is colder and water-saturated firn layers seasonally refreeze as solid-ice. Higher firn saturation parameter values are mapped in higher snow accumulation perennial firn aquifer areas in southeastern, southern, and northwestern Greenland, where firn is near the melting point, and meters-thick water-saturated firn layers exist. Our results have implications for identifying expansive englacial reservoirs that store significant volumes of meltwater in locations that are vulnerable to meltwater-induced hydrofracturing and accelerated outlet glacier flow year-round.
The increased number of carefully selected narrow spectral bands and the increased spatial resolution of thematic mapper data over previously available satellite data contribute greatly to geologic exploration, both by providing spectral information that permits lithologic differentiation and recognition of alteration and spatial information that reveals structure. As vegetation and soil cover increase, the value of spectral components of TM data decreases relative to the value of the spatial component of the data. However, even in vegetated areas, the greater spectral breadth and discrimination of TM data permits improved recognition and mapping of spatial elements of the terrain. As our understanding of the spectral manifestations of the responses of soils and vegetation to unusual chemical environments increases, the value of spectral components of TM data to exploration will greatly improve in covered areas.
The Ourika watershed is characterized by higher than average flood flows, a rugged topography, a sparse vegetation cover and a friable substrate that makes it vulnerable to soil erosion. Soil is an important non-renewable asset capital, providing several ecosystem services that sustain life through physical and biological regulation processes. The loss, or otherwise, redistribution of biota by soil erosion in the Ourika watershed has received little attention and thus constitutes a key knowledge gap that needs to be addressed. This study quantifies the level of erosion and maps its spatial distribution in the watershed using the Sediment Delivery Ratio (SDR) of the Integrated Valuation of Ecosystem Services and Tradeoffs model (InVEST3.6.0). The SDR maps the overland sediment generation and delivery to the stream at the watershed level using rainfall, soil properties, topography, cover management and cropping practices as predefined set of input variables. Recommended internal model calibration was used and results were compared to similar studies carried out in different parts of Morocco for validation. The results reveal that 93% of the watershed is subject to a strong rainfall aggressiveness greater than 50 MJ mm ha–1 h–1 yr1 under an average rainfall intensity of 541 mm/year, rainfall capacity to initiate the detachment and transport of soil particles by runoff, and only 11.5% of the watershed area is protected with vegetative cover. We find that overall, the Ourika watershed is losing its soil to erosion at an alarming average rate of 258.48 ton.ha–1.yr–1, a rate well above the tolerable threshold of 7ton.ha–1.yr–1. The spatial distribution of this loss shows areas that need to be urgently remedied. The primary factors for soil erosion in the Ourika watershed appear to be related to the aggressive nature of local rainfall and the inherent susceptibility of soils, which can be costly to this cash-crop region. Because rainfall intensity, soil properties, and topography are intrinsic characteristics of the watershed, we suggest that seasonally adapted cropping rotations that maintains conservative practices with a high cover management may reduce soil erosion in the Ourika watershed.
Photosynthetic capacity is often quantified by the Rubisco-limited photosynthetic capacity (i.e. maximum carboxylation rate, V(sub cmax)). It is a key plant functional trait that is widely used in Earth System Models for simulation of the global carbon and water cycles. Measuring V(sub cmax) is time-consuming and laborious; therefore, the spatiotemporal distribution of V(sub cmax) is still poorly understood due to limited measurements of V(sub cmax). In this study, we used a data assimilation approach to map the spatial variation of V(sub cmax) for global terrestrial ecosystems from a 11-year-long satellite-observed solar-induced chlorophyll fluorescence (SIF) record. In this SIF-derived V(sub cmax) map, the mean V(sub cmax) value for each plant function type (PFT) is found to be comparable to a widely used N-derived V(sub cmax) dataset by Kattge et al. (2009). The gradient of V(sub cmax) along PFTs is clearly revealed even without land cover information as an input. Large seasonal and spatial variations of V(sub cmax) are found within each PFT, especially for diverse crop rotation systems. The distribution of major crop belts, characterized with high V(sub cmax) values, is highlighted in this V(sub cmax) map. Legume plants are characterized with high V(sub cmax) values. This V(sub cmax) map also clearly illustrates the emerging soybean revolution in South America where V(sub cmax) is the highest among the world. The gradient of V(sub cmax) in Amazon is found to follow the transition of soil types with different soil N and P contents. This study suggests that satellite-observed SIF is powerful in deriving the important plant functional trait, i.e. V(sub cmax), for global climate change studies.
The major scientific objective of the Gamma-Ray Spectrometer (GRS) on the 2001 Mars Odyssey Mission is to determine the distribution of elements in the near-surface of Mars. Mars Odyssey has been in its mapping orbit since February, 2002, and the GRS boom, which removes the instrument from the gamma-ray background of the spacecraft, was erected in June, 2002. In the 580 days since boom erection, we have accumulated 453 days of mapping data. The difference is due mostly to two times when Odyssey went into safe mode and the instrument warmed up forcing us to anneal out radiation damage that manifests itself after warming. Other data losses are due to simple transmitter data gaps and to intense solar particle events. The data from the GRS is statistical in nature. We have a very low count rate and a very low signal-to-noise ratio. With the exception of K, the most easily mapped elements have a signal/noise ratio on the order of 0.1 (0.5 for K) and the counting rates are on the order of 0.3 to 0.7 counts/min (4 cpm for K). In order to map the distribution of an element, we have to divide the total signal from Mars up into many cells that define the map s spatial resolution (unless the statistics are good enough that the intrinsic spatial resolution of the instrument, about 550 km diameter, dominates). The data for several elements have now achieved a statistical precision that permits us to make meaningful maps.
A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.
The Urban Environment Initiative (UEI), has been established as part of a Cooperative Agreement with the National Aeronautics and Space Administration (NASA). The UEI is part of NASA's overall High Performance Computing and Communications (HPCC) and the Information Infrastructure Technology Applications (IITA) programs. The goal of the UEI is to provide public access to Earth Science information and promote its use with a focus on the environment of urban areas. This goal will be accomplished through collaborative efforts of the UEI team with both community-based and local/regional governmental organizations. The UEI team is comprised of four organizations representing private industry, NASA, and universities: Prime Technologies Service Corporation, NASA's Minority University Space Interdisciplinary Network (MU-SPIN) California State University, at Los Angeles, and Central State University (Wilberforce, OH). "Urban Environment" refers to the web of environmental, economic, and social factors that combine to create the urban world in which we live. Examples of these factors are population distribution, neighborhood demographic profiles, economic resources, business activities, location and concentration of environmental hazards and various pollutants, proximity and level of urban services, which form the basis of the urban environment and ultimately affect our lives and experiences. The use of Geographic Information Systems (GIS) and remote sensing allows data to be visualized in the forms of maps and spatial images. The use of these tools allow analysis of information about urban environments. Also included are descriptions of the four query types which will assist in understanding the maps.
Stochastic inversion for flexural loads and flexural rigidity of the continental elastic layer can be accomplished most effectively by using the coherence of gravity and topography. However, the spatial resolution of coherence analysis has been limited by use of two-dimensional periodogram spectra from very large (greater than 10(exp 5)sq km) windows that generally include multiple tectonic features. Using a two-dimensional spectral estimator based on the maximum entropy method, the spatial resolution of flexural proerties can be enhanced by a factor of 4 or more, enabling more detailed analysis at the scale of individual tectonic features. This new approach is used to map the spatial variation of flexural rigidity along the Basin and Range transition to the Colorado Plateau and Middle Rocky Mountains physiographic provinces. Large variations in flexural isostatic responses are found, with rigidities ranging from as low as 8.7 x 10(exp 20) N m (elastic thickness (T(sub e) = 4.6 km) in the Basin and Range to as high as 4.1 x 10(exp 24) N m T(sub e) = 77 km) in the Middle Rocky Mountains. These results compare favorably woith independent determinations of flexural rigidity in the region. Areas of low flexural rigidity correlate strongly with areas of high surface heat flow, as is expected from the contingence of flexural rigidity on a temperature-dependent flow law. Also, late Cenozoic normal faults with large displacements are found primarily in area of low flexural rigidity region. The highest flexural rigidity is found within the Archean Wyoming craton, where evidence suggests that deeply rooted cratonic lithosphere may play a role in determining the distribution of tectonism at the surface.
The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases-with time and also is a function of position on the detector. To complicate matters further, the satellite is "wobbled", possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT HRI from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.
The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases with time and also is a function of position on the detector. To complicate matters further, the satellite is 'wobbled', possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT High Resolution Imager (HRI) from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC (an x ray spectral fitting package) response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how, the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.
An improved method for global petrologic mapping of the moon is presented, which uses a color-coded ternary diagram whose apexes are assigned the average Fe and Th/Ti ratio (normalized to chondrites) compositions of KREEP/Mg-suite rocks, mare basalts, and ferroan anorthosites. The composition of each pixel within these Apollo orbital gamma ray data bases is used to determine its position within the ternary diagram. The color corresponding to this ternary position is then placed on a classification map at that pixel's position within the orbital data bases. The resultant classification map shows spatial transitions among petrologic units, allows direct determination of the relative proportions of each end-member composition in a pixel, and provides more geologic information than can be obtained by using only the elemental data. The map units correspond remarkably well to previously delineated geologic provinces.
A technique was developed for mapping the spatial extent of frozen soils from the spectral characteristics of the 10.7 to 37 GHz radiobrightness. Through computational models for the spectral radiobrightness of diurnally heated freesing soils, a distinctive radiobrightness signature was identified for frozen soils, and the signature was cast as a discriminant for unsupervised classification. In addition to large area images, local area spatial averages of radiobrightness were calculated for each radiobrightness channel at 7 meteorologic sites within the test region. Local area averages at the meteorologic sites were used to define the preliminary boundaries in the Freeze Indicator discriminate. Freeze Indicator images based upon Nimbus 7, Scanning Multichannel Microwave Radiometer (SMMR) data effectively map temporal variations in the freeze/thaw pattern for the northern Great Plains at the time scale of days. Diurnal thermal gradients have a small but measurable effect upon the SMMR spectral gradient. Scale-space filtering can be used to improve the spatial resolution of a freeze/thaw classified image.
Observations of Comet P/Stephan-Oterma were made with an Intensified Dissector Scanner spectrograph on the McDonald Observatory 2.7-m telescope during the period from July 1980 to February 1981. These spectra cover a range of heliocentric distances from 2.3 AU preperihelion to 1.8 AU postperihelion. A small aperture was used to map the spatial distributions of the gases in the coma. Column densities of the observed cometary emissions (CN, C3, CH, and C2) were calculated, and it is shown that Stephan-Oterma appeared nearly spherically symmetric. These date are used by Cochran (1985) to constrain chemical models of Stephan-Oterma.
Early telescopic observations corroborated hydration related absorptions on Mars in the infrared. Images from the Viking missions led to speculation of hydrothermal alteration and were followed by two missions which mapped the spatial variability of the ~ 3 μm hydration feature. Since then, the Compact Reconnaissance Imager for Mars (CRISM) has provided high spatial resolution (up to 18m) spectral identification of a suite of hydrothermal and diagenetic minerals which have illuminated a range of formation mechanisms. Presence/absence and spatial segregation or mixing of minerals like prehnite, epidote, chlorite amphiboles, and mixed-layer Fe/Mg smectite-chlorite provide valuable evidence for the geologic setting of deposits on Earth, and these phases are often used as temperature and aqueous chemistry indicators in terrestrial systems. Mapping the distribution of these phases will help to answer whether Mars had widespread conditions favorable for low-grade metamorphism and diagenesis, or only focused hydrothermal systems in areas of high heat flow. Further characterizing the chemistry and structure of these phases will then help to answer how most of the widespread Fe/Mg phyllosilicates formed, further defining early geochemical cycling and climate. A fully automated approach for accurate mapping of important hydrothermal mineral phases on Mars has been a challenge. Due to overlapping features in the M-OH region (~2.2-2.4 μm), the strongest absorption features of chlorite, prehnite, and epidote in the short-wave infrared are difficult to distinguish from one another and from the most commonly occurring hydrated silicates on Mars, Fe/Mg smectites. Weaker absorptions are present in both prehnite and epidote which help to distinguish them from chlorite and smectites, but their relative strength in the presence of noise and spatial mixing is often too low to confidently identify them without the noise suppression and feature enhancement methods described here. The spectral signatures of mixed-layer Fe/Mg smectite-chlorite and partially chloritized Fe/Mg smectites have not yet been adequately assessed. Here we evaluate the effectiveness of two empirical and statistical methods for identifying and differentiating these phases using CRISM data.
With the near-future launch of geostationary pollution monitoring satellite instruments over North America, East Asia, and Europe, the air quality community is preparing for an integrated global atmospheric composition observing system at unprecedented spatial and temporal resolutions. One of the ways that NASA has supported this community preparation is through demonstration of future space-borne capabilities using the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument. This paper integrates repeated high-resolution maps from GeoTASO, ground-based Pandora spectrometers, and low Earth orbit measurements from the Ozone Mapping and Profiler Suite (OMPS), for case studies over two metropolitan areas: Seoul, South Korea on June 9, 2016 and Los Angeles, California on June 27, 2017. This dataset provides a unique opportunity to illustrate how geostationary air quality monitoring platforms and ground-based remote sensing networks will close the current spatiotemporal observation gap. GeoTASO observes large differences in diurnal behavior between these urban areas, with NO2 accumulating within the Seoul Metropolitan Area through the day but NO2 peaking in the morning and decreasing throughout the afternoon in the Los Angeles Basin. In both areas, the earliest morning maps exhibit spatial patterns similar to emission source areas (e.g., urbanized valleys, roadways, major airports). These spatial patterns change later in the day due to boundary layer dynamics, horizontal transport, and chemistry. The nominal resolution of GeoTASO is finer than will be obtained from geostationary platforms, but when NO2 data over Los Angeles are up-scaled to the expected resolution of TEMPO, spatial features discussed are conserved. Pandora instruments installed in both metropolitan areas capture the diurnal patterns observed by GeoTASO, continuously and over longer time periods, and will play a critical role in validation of the next generation of satellite measurement. These case studies demonstrate that different regions can have diverse diurnal patterns and that day-to-day variability due to meteorology or anthropogenic patterns such as weekday/weekend variations in emissions is large. Low Earth orbit measurements, despite their inability to capture the diurnal patterns at fine spatial resolution, will be essential for intercalibrating the geostationary radiances and cross-validating the geostationary retrievals in an integrated global observing system.
Application of high spectral resolution, Earth-based Fabry-Perot spectroscopy to the study of planetary atmospheres, for which current topics are outer planet HD and H2 spectra (atmospheric structure, D/H ratio), Mars CO2, CO, O2, and H2O spectra (atomspheric photochemistry), Venus H2O and HDO, associated laboratory spectroscopy (especially H2 overtone bands, HDO) was accomplished. Monochromatic charge coupled device (CCD) imaging photometry of the Jovian nebula, with images taken in rapid sequence among the diagnostic spectral lines of ionized sulfur species, provided self-supporting snapshots of the Jupiter/Io plasma conditions (spatially resolved electron and ion densities and temperatures), covering the post-Voyager period from 1981 and leading up to the Galileo tour in the early 1990s. High spectral resolution Fabry-Perot/charge coupled device (CCD) imaging of comets (OI, CI, and H2O(+) velocity maps and spatial distriubtions), and Io's charge exchanged neutral jet was studied.