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At least 1,045 records · Page 58

Precision Assessment of the HPLC Phytoplankton Pigment Dataset Analyzed by NASA to Quantify Global Variability in Support of Ocean Color Remote Sensing

The ability to generate chlorophyll a (Chl a) assessments from ocean color orbital sensors, such as VIIRS and MODIS, that satisfy the requirements to be climate-quality data record (CDR) quality is contingent in part on the quality of the in situ ground or sea truth observations that serve as datasets for vicarious calibration and algorithm validation activities. NASA has a mandate to collect, analyze, and distribute in situ data of the highest possible quality with documented uncertainties and in keeping with established performance metrics. Using a dataset of over 18,000 HPLC phytoplankton pigment samples representing water collected in all major ocean basins analyzed a central laboratory (Field Support Group (FSG) of the Ocean Ecology Laboratory (OEL) at NASA Goddard Space Flight Center (GSFC)), we performed an assessment of the global precision among sample replicates of Chl a as well as major accessory pigments. We investigated the impacts of filtration volume, water basin, collection technique, pigment concentration, and different filtration volumes for replicate filters on replicate filter precision, as well as investigating any pigment-specific differences. Our results quantify sample variability with the goal of understanding any systemic biases or biogeographic influences.

Thomas, Crystal S.↗

Models, In situ, and Remote Sensing of Aerosols (MIRA)

There is a natural partitioning of scientific interest amongst three specialties of aerosol re-search: modeling, in situ measurements, and remote sensing. The broader aerosol community benefits when these groups interact, and this strengthens overall scientific impact on climate and air quality research and predictions. The new MIRA working group establishes a forum for identifying collaborations and improving discussions amongst specialties and across regional boundaries. One area of keen interest is uniting satellite and ground-based lidar groups with other aerosol disciplines. Elastic backscatter lidars depend upon a priori knowledge of aerosol properties to convert measured lidar profiles into aerosol extinction profiles. Acquiring additional insight on aerosol properties and transport is highly valuable to these lidar groups to improve the data quality and aid in their scientific interpretation. Another area of interest is to facilitate the incorporation of measurements into global aerosol models. Modelers need aerosol optical look-up tables that enable quick conversions of hydrated (and dry) polydisperse size distributions into aerosol optical properties (extinction, scattering, etc.), but many of the existing tables are based upon outdated measurements. Thus, MIRA is building the Tables of Aerosol Optics (TAO), which is a community collection of aerosol optical calculations. This expands on the historical efforts of Shettle and Fenn, d’Almeida, GADS, OPAC, etc., except that TAO seeks continual input from the community. Thus, as aerosol measurement and computational techniques advance, so does the TAO collective. Since TAO is a community collective, it is expected that users will optionally upload computations for aerosol type as well as computations for all of the traditional aerosol species(like amm sulfate, amm nitrate, organics, etc.). The near-term purpose of the MIRA working group is to: *Characterize regional aerosol lidar ratios to support improvements of aerosol extinction profiles and understanding of aerosol typing. *Create TAO --a community cooperative of aerosol optical tables. *Facilitate international communications between aerosol measurement and modeling groups. *Encourage the use of regional knowledge to develop and improve remote sensing techniques for current and future backscatter lidars located in space. *Enable and foster communication between the scientists who run global aerosol models and scientists who analyze space-based lidar data. We will discuss how a collaborative aerosol working group will be organized on this topic. Those who are interested in MIRA can sign up for the MIRA email listserver at https://forms.gle/qdbCnngzNJc5YJi57.

Greg Schuster↗

Models, In situ, and Remote sensing of Aerosols (MIRA): Formation of an International Working Group

There is a natural partitioning of scientific interest amongst three specialties of aerosol re- search: modeling, in situ measurements, and remote sensing. The broader aerosol community benefits when these groups interact, and this strengthens overall scientific impact on climate and air quality research and predictions. The new MIRA working group establishes a forum for identifying collaborations and improving discussions amongst specialties and across regional boundaries. One area of keen interest is uniting satellite and ground-based lidar groups with other aerosol disciplines. Elastic backscatter lidars depend upon a priori knowledge of aerosol properties to convert measured lidar profiles into aerosol extinction profiles. Acquiring additional insight on aerosol properties and transport is highly valuable to these lidar groups to improve the data quality and aid in their scientific interpretation. Another area of interest is to facilitate the incorporation of measurements into global aerosol models. Modelers need aerosol optical look-up tables that enable quick conversions of hydrated (and dry) polydisperse size distributions into aerosol optical properties (extinction, scattering, etc.), but many of the existing tables are based upon outdated measurements. Thus, MIRA is building the Tables of Aerosol Optics (TAO), which is a community collection of aerosol optical calculations. This expands on the historical efforts of Shettle and Fenn, d’Almeida, GADS, OPAC, etc., except that TAO seeks continual input from the community. Thus, as aerosol measurement and computational techniques advance, so does the TAO collective. Since TAO is a community collective, it is expected that users will optionally upload computations for aerosol type as well as computations for all of the traditional aerosol species (like amm sulfate, amm nitrate, organics, etc.). The near-term purpose of the MIRA working group is to: * Characterize regional aerosol lidar ratios to support improvements of aerosol extinction profiles and understanding of aerosol typing. * Create TAO -- a community cooperative of aerosol optical tables. * Facilitate international communications between aerosol measurement and modeling groups. * Encourage the use of regional knowledge to develop and improve remote sensing techniques for current and future backscatter lidars located in space. * Enable and foster communication between the scientists who run global aerosol models and scientists who analyze space-based lidar data. We will discuss how a collaborative aerosol working group will be organized on this topic. Send email to calipso_v5alr-join@lists.nasa.gov with the word `subscribe' in the subject line to join MIRA.

Gregory Schuster↗

Contribution of space platforms to a ground and airborne remote-sensing programme over active Italian volcanoes

ERTS-1 imagery of the volcanic areas of southern Italy was used primarily for the evaluation of space platform capabilties in the domains of regional geology, soil and rock-type classification and, more generally, to study the environment of active volcanoes. The test sites were selected and equipped primarily to monitor thermal emission, but ground truth data was also collected in other domains (reflectance of rocks, soils and vegetation). The test areas were overflown with a two channel thermal scanner, while a thermo camera was used on the ground to monitor the hot spots. The primary goal of this survey was to plot the changes in thermal emission with time in the framework of a research program for the surveillance of active volcanoes. However, another task was an evaluation of emissivity changes by comparing the outputs of the two thermal channels. These results were compared with the reflectance changes observed on multispectral ERTS-1 imagery.

Cassinis, R.↗

A Synoptic System for Capturing Ecosystem Control Points Across Terrestrial‐Aquatic Interfaces

Interconnected landscape features such as terrestrial‐aquatic interfaces play an outsized role in biogeochemical cycles as ecosystem control points, but it is notoriously challenging to characterize these. Here, we document a synoptic sensor network design that is (a) flexible to accommodate diverse ecosystem interfaces and gradients, (b) adaptable to monitoring and modeling needs of small and large projects alike, (c) standardized for intercomparability across sites and field experiments, and (d) adequately replicated to capture heterogeneity of each parameter monitored. This real‐time monitoring of surface water, groundwater, soil, and vegetation supports configuration and evaluation of models that span upland, wetland, open water strata, and transitions between them. We established the network at seven sites along the Chesapeake Bay and Lake Erie coastlines, including large‐scale flood manipulation experiments in both regions. A central design element is “one data logger program to rule them all”—a collection of sensor‐specific modules deployed on 40 loggers controlling ∼2,000 sensors, with the goal of streamlining maintenance, debugging, and reproducible data processing. The network generates ∼6 M observations per month, capturing system dynamics at the broad spatial and fine temporal scales needed to initialize and benchmark models; measurement frequency can be modified remotely to capture events. This network design has also revealed behaviors not represented in Earth system models, such as transient groundwater oxygen pulses. Completely documented and open source, this standardized, flexible, and efficient sensor network design can reduce barriers to understanding environmental changes and ecosystem responses across systems and scales.

Ward, Nicholas D. [Pacific Northwest National Labo↗

Analysis of Cirrus Cloud Microphysical Data

The First International Satellite Cloud Climatology Regional Experiment (FIRE) program has the goal of improving our capabilities to understand, model and detect the properties of climatically-important clouds. This is being undertaken through a three-pronged effort of modeling, long-term observations and short-term intensive field studies. Through examination of satellite and other data it is apparent that stratus and cirrus cloud types have the greatest impact on climate due to their radiative effects and ubiquitous nature. As a result, the FIRE program has developed two paths of investigation, each having its own subset of research objectives and measurement programs. The work conducted under this grant was directed toward furthering our understanding of cirrus cloud systems. While it is known that cirrus are climatically important, the magnitude and even sign of the impact is unclear. Cirrus clouds affect the transfer of radiation according to their physical depth and location in the atmosphere and their microphysical composition. However, significant uncertainties still exist in how cirrus clouds form and how they are maintained, what their physical properties are and how they can be parameterized in numerical models. Better remote sensing techniques for monitoring cirrus cloud systems and improved modeling of radiative transfer through ice particles are also needed. A critical element in resolving these issues is a better understanding of cirrus cloud microphysical properties and how they vary. The focus of the research to be conducted under this grant was th data collected in situ by the University of North Dakota Citation aircraft. The goals of this research were to add to the body of knowledge of cirrus cloud microphysics, particularly at the small end of the size spectrum; and analyze the spatial variation of cirrus clouds.

Poellot, Michael R.↗

Evaluation of remote sensing-based evapotranspiration products at low-latitude eddy covariance sites

Remote sensing-based evapotranspiration (ET) products have been evaluated primarily using data from northern middle latitudes; therefore, little is known about their performance at low latitudes. To address this bias, an evaluation dataset was compiled using eddy covariance data from 40 sites between latitudes 30° S and 30° N. The flux data were obtained from the emerging network in Mexico (MexFlux) and from openly available databases of FLUXNET, AsiaFlux, and OzFlux. This unique reference dataset was then used to evaluate remote sensing-based ET products in environments that have been underrepresented in earlier studies. The evaluated products were: MODIS ET (MOD16, both the discontinued collection 5 (C5) and the latest collection (C6)), Global Land Evaporation Amsterdam Model (GLEAM) ET, and Atmosphere-Land Exchange Inverse (ALEXI) ET. Products were compared with unadjusted fluxes (ETorig) and with fluxes corrected for the lack of energy balance closure (ETebc). Three common statistical metrics were used: coefficient of determination (R2), root mean square error (RMSE), and percent bias (PBIAS). The effect of a vegetation mismatch between pixel and site on product evaluation results was investigated by examining the relationship between the statistical metrics and product-specific vegetation match indexes. Evaluation results of this study and those published in the literature were used to examine the performance of the products across latitudes. Differences between the MOD16 collection 5 and 6 datasets were generally smaller than differences with the other products. Performance and ranking of the evaluated products depended on whether ETorig or ETebc was used. When using ETorig, GLEAM generally had the highest R2, smallest PBIAS, and best RMSE values across the studied land cover types and climate zones. Neither MOD16 nor ALEXI performed consistently better than the other. When using ETebc, none of the products stood out in terms of both low bias and strong correlations. The use of ETebc instead of ETorig affected the biases more than the correlations. The product evaluation results showed no significant relationship with the degree of match between the vegetation at the pixel and site scale. The latitudinal comparison showed tendencies of lower R2 (all products) but better PBIAS and normalized RMSE values (MOD16 and GLEAM) for forests at low latitudes than for forests at northern middle latitudes. For non-forest vegetation, the products showed no clear latitudinal differences in performance.

Diego Salazar-Martínez↗

OSTA-1 - The Space Shuttle's first scientific payload

The capabilities of the first Space Shuttle scientific payload for remote sensing observations of the earth are evaluated, and the instruments used are from the Office of Space and Terrestrial Applications (OSTA-1). The payload gathered 10 million square kilometers of data over the earth's oceans, 6 million square kilometers of data over land masses, and global atmospheric data on carbon monoxide concentration. Shuttle imaging radar collected data over a 10,000 km sweep from Spain to Australia, a Shuttle multispectral infrared radiometer obtained 400,000 ten-channel spectra in clear weather conditions over four continents, and the Ocean Color Experiment detected water color for interpretation of major water constituents. The mission is considered to be a success based on the amount of data collected, and scientific and technical insight gained for the development of Shuttle flight instruments.

Moore, J. W.↗

CERES and the S'COOL Project

The first Clouds and the Earth's Radiant Energy System (CERES) instrument will be launched on the Tropical Rainfall Measuring Mission (TRMM) spacecraft from a Japanese launch site in November 1997. This instrument is a follow-on to the Earth Radiation Budget Experiment (ERBE) begun in the 1980's. The instrument will measure the radiation budget - incoming and outgoing radiant energy - of the Earth. It will establish a baseline and look for climatic trends. The major feature of interest is clouds, which play a very strong role in regulating our climate. CERES will identify clear and cloudy regions and determine cloud physical and microphysical properties using imager data from a companion instrument. Validation efforts for the remote sensing algorithms will be intensive. As one component of the validation, the S'COOL (Students' Cloud Observations On-Line) project will involve school children from around the globe in making ground truth measurements at the time of a CERES overpass. Their observations will be collected at the NASA Langley Distributed Active Archive Center (DAAC) and made available over the Internet for educational purposes as well as for use by the CERES Science Team in validation efforts. Pilot testing of the S'COOL project began in January 1997 with two local schools in Southeastern Virginia and one remote site in Montana. This experience is helping guide the development of the S'COOL project. National testing is planned for April 1997, international testing for July 1997, and global testing for October 1997. In 1998, when the CERES instrument is operational, a global observer network should be in place providing useful information to the scientists and learning opportunities to the students.

Chambers, Lin H.↗

Technical Report Series on the Boreal Ecosystem-Atmosphere Study (BOREAS) RSS-19 1994 CASI At-Sensor Radiance and Reflectance Images

The Remote Sensing Science (RSS)-19 team collected Compact Airborne Spectrographic Imager (CASI) images from the Chieftain Navaho aircraft in order to observe the seasonal change in the radiometric reflectance properties of the boreal forest landscape. CASI was deployed as a site-specific optical sensor during Boreal Ecosystem-Atmosphere Study (BOREAS) field campaigns. Image data were collected with CASI on 36 days during five field campaigns between February and September 1994, primarily at flux tower sites located at study sites near Thompson, Manitoba, and Prince Albert, Saskatchewan. A variety of CASI data collection strategies were used to meet the following scientific objectives: 1) canopy bidirectional reflectance, 2) canopy biochemistry, 3) spatial variability, and 4) estimates of up and downwelling Photosynthetically Active Radiation (PAR) and spectral albedo, as well as changes along transects across lakes and transects the Northern Study Area (NSA) and Southern Study Area (SSA). The images are stored as binary image files. A subset of the 1994 CASI acquisitions have been compressed and included on the BOREAS CD-ROM set. This subset includes three images for the NSA-OBS (Old Black Spruce) site on 06 Jun 94, 08 Aug 94, and 06 Sep 94, one image for the SSA-OBS site on 24 Jul 94; and one image for the NSA-Fen site on 08 Aug 94. The CASI imagery on the BOREAS CD-ROMs have been compressed using the Gzip program. The rest of the 1994 BOREAS CASI archive are not contained on the BOREAS CD-ROM set. Inventory listing files are supplied on the CD-ROM to inform users of the data that were collected. The RSS-19 1994 CASI images are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Miller, John↗

MONITORING ECO-HYDROLOGICAL SPRING ONSET OVER ALASKA AND NORTHERN CANADA WITH COMPLEMENTARY SATELLITE REMOTE SENSING DATA

More than half of the global land area undergoes seasonal freeze/thaw (FT) transitions in spring. Spatial patterns and timing of spring thawing influence eco-hydrological processes and landscape moisture availability over arctic and boreal ecosystems. The seasonal progression of spring thawing coincides with warmer temperatures, snowmelt, and a rapid increase in soil moisture, which initiates the growing season for ecosystem productivity. In this study, we utilize complementary satellite observations to determine the pattern and order of occurrence in landscape thawing, soil moisture increase, and ecosystem productivity that collectively define the eco-hydrological spring onset across Alaska and Northern Canada. Satellite data utilized include landscape FT status from SMAP and AMSR-2, OCO-2 derived solar-induced chlorophyll fluorescence (GOSIF), and gross primary production (GPP) and soil moisture from SMAP.

Youngwook Kim↗

Monitoring Eco-Hydrological Spring Onset Over Alaska and Northern Canada With Complementary Satellite Remote Sensing Data

More than half of the global land area undergoes seasonal freeze/thaw (FT) transitions in spring. Spatial patterns and timing of spring thawing influence eco-hydrological processes and landscape moisture availability over arctic and boreal ecosystems. The seasonal progression of spring thawing coincides with warmer temperatures, snowmelt, and a rapid increase in soil moisture, which initiates the growing season for ecosystem productivity. In this study, we utilize complementary satellite observations to determine the pattern and order of occurrence in landscape thawing, soil moisture increase, and ecosystem productivity that collectively define the eco-hydrological spring onset across Alaska and Northern Canada. Satellite data utilized include landscape FT status from SMAP and AMSR-2, OCO-2 derived solar-induced chlorophyll fluorescence (GOSIF), and gross primary production (GPP) and soil moisture from SMAP. The resulting spring onset maps showed spring thawing as the precursor to growing season onset, indicated by a rapid rise in available soil moisture and GPP. Our results indicated an average spring transition period of 3±2 (SD) weeks between initial landscape thawing and growing season onset. A rapid increase in soil moisture generally followed landscape thawing but occurred before the subsequent seasonal rise in GPP. Spring onset generally occurred earlier in boreal forest (DOY 102±14) than arctic tundra (DOY 124±22).

Derksen, Chris↗

Airborne gamma radiation measurements of soil moisture during FIFE: Activities and results

Soil moisture measurements were obtained during the summer of 1987 and 1989 near Manhattan, Kansas, using the National Weather Service (NWS) airborne gamma radiation system. A network of 24 flight lines were established over the research area. Airborne surveys were flown daily during two intensive field campaigns. The data collected was sufficient to modify the NWS standard operational method for estimating soil moisture for the Field Experiment (FIFE) flight lines. The average root mean square error of the soil moisture estimates for shorter FIFE flight lines was found to be 2.5 percent, compared with a reported value of 3.9 percent for NWS flight lines. Techniques were developed to compute soil moisture estimates for portions of the flight lines. Results of comparisons of the airborne gamma radiation soil moisture estimates with those obtained using the NASA Pushbroom Microwave Radiation (PBMR) system and hydrological model are presented. The airborne soil moisture measurements, and real averages computed using all remotely sensed and ground data, have been in support of the research of the many FIFE investigators whose overall goal was the upscale integration of models and the application of satellite remote sensing.

Peck, Eugene L.↗

Effects of vegetation on passive microwave estimates of soil moisture

Data collected over plots using a microwave radiometer with a wavelength of 21 cm were used to evaluate a theoretical model of the effect of vegetative cover on the emission of soils. The theoretical model was used as a basis of a simplified model which predicts the emissivity of a soil-vegetation complex with a full canopy cover. This model, when transformed to predict soil moisture, requires measurements of the microwave brightness temperature, surface temperature and vegetation biomass. Since surface temperature can be determined using thermal infrared measurements and vegetation biomass could be estimated with visible and near infrared measurements, the simplified model could be applied using only remotely sensed data.

Jackson, T. J.↗

Air Pollution Inputs to the Mojave Desert By Fusing Surface Mobile and Airborne in Situ and Airborne and Satellite Remote Sensing: A Case Study of Interbasin Transport With Numerical Model Validation

Deserts are fragile and highly sensitive ecosystems that increasingly are affected by upwind urban areas and industrial activities. The Los Angeles Basin (LAB) contributes to poor air quality in downwind deserts including the Mojave Desert. Few studies have investigated potential air pollution inputs to the Mojave, whose fragile ecosystem includes endangered plant and animal species. Data were collected on 19 August 2015 by a mobile air quality laboratory, AMOG (AutoMObile trace Gas) Surveyor, that observed inputs can arise from the LAB as well as the San Joaquin Valley (SJV), California. The campaign used a strong methane (CH4) plume as a tracer for the downwind fate of emissions from Bakersfield area petroleum production and also measured ozone (O3). Additional in situ concurrent airborne GHG and O3 data were collected by AJAX - Alpha Jet Atmospheric eXperiment. Both AMOG and AJAX measure winds. Mojave Desert air quality was very poor (visibility ~4 km). Based on the winds, an additional source was inferred beyond the LAB and SJV Basins. Numerical transport modeling and analysis of aerosol lidar data collected the same day by the Cloud Profiling LiDAR onboard the Earth Research-2 stratospheric airplane demonstrated that fires in Northern California were responsible, with prevailing winds transporting air southwards along the eastern Sierra Nevada Range (Bishop Valley) to the Mojave. Whereas the southern and eastern Mojave are impacted by SJV and LAB outflow, the north Mojave generally avoids these inputs. This study shows it can be affected by even distant wildfires, which likely will increase in occurrence and intensity from climate change. Thus, regulatory efforts to reduce air quality impacts on the endangered Mojave ecosystem must include wildfires and also account for the significant differences between different regions of the Mojave. Currently, there is a paucity of studies, highlighting the critical need for field research.

Ira Leifer↗

NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset

Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest near Crested Butte, CO with remotely sensed data including imaging spectroscopy. The flight box design encompassed the watersheds, and flight design targeted a minimum of 30% overlap between adjacent flight lines. The total area surveyed was 334 km2 across 72 lines. Flight lines were oriented north-south for consistency in solar illumination geometry. Seven days were required to cover the flight area. Some areas were flown additional times to improve data quality or temporal coincidence between airborne acquisitions and field sampling. In total, 102 lines were collected and can be downloaded here: https://portal.nersc.gov/wfsfa/doi-10-15485-1617204/. The instrument used for the acquisition was an Airborne Visible-Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG), which records radiance within 426 contiguous spectral bands in the wavelength range from 380 to 2510 nm. The instrument was flown at a target aboveground altitude of 1000 m for a processed data spatial resolution of 1 m. These data are non-orthorectified, radiance data that require further processing prior to use as a surface reflectance data set.

2018 NEON and 2025 CHESS Campaigns↗

Automatic Image Point Matching

Sparse Image Point Matching (SIPM) is a foundational technology for photo triangulation, structure from motion (SfM), Simultaneous Location and Mapping (SLAM), and data fusion. The goal of the matching is to automatically generate sets of image coordinates that identify the same feature across images. Ideally, the process should be robust to lighting, scale, perspective, and modality changes. The scope of the image matching topic in the field of remote sensing (RS) is enormous because of the variety of collection platforms, modalities, sensor types, applications, and subjects. In this work, we report the history of and assess the state of the art of visible-spectrum (panchromatic and color) image matching of the Earth’s surface. Work specific to large-format images (LFI) (e.g., metric aerial cameras and Earth-observing satellites) will be highlighted. However, the state of the art in this century will mostly be traced through machine vision research and benchmarks because research specific to LFI is rare.

97 MATHEMATICS AND COMPUTING↗

Results of the 1971 Corn Blight Watch experiment.

The objective of the experiment was to evaluate the use of advanced remote sensing techniques to detect the development and spread of southern corn leaf blight during the growing season across the Corn Belt region. The sampling plan involved the selection of the study area, the determination of the flightline, and the determination of a field sample design. Aspects of data acquisition are discussed, giving attention to ground data collection and aerial data collection. Details of data flow are considered along with data analysis procedures and corn blight records. The experiment results are examined, taking into account photointerpretation results, the machine analysis of multispectral scanner data results, the influence of blight on yields, and questions of crop identification.

Macdonald, R. B.↗