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Utilizing NASA Earth Observations to Evaluate Urban Tree Canopy and Land Surface Temperature for Green Infrastructure Development and Urban Heat Mitigation in Huntsville, AL

Huntsville, Alabama’s population has grown by 10.8% since 2010, due in part to the city’s advancing engineering industry. Rapid urban growth negatively impacts the environment by decreasing tree canopy cover and increasing impervious surface cover, which can intensify the urban heat island effect. To examine the impacts of this urban growth on the environment, the team partnered with the City of Huntsville to utilize Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the International Space Station’s Global Ecosystems Dynamic Investigation (GEDI) and ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). The team utilized these Earth observations in combination with ancillary datasets to create a suite of end products to assist in mitigating the effects of extreme heat due to urban expansion and tree canopy loss. Rasters of annual land surface temperature (LST) was calculated in Google Earth Engine from 2010 to 2019. The team derived land cover classes through supervised and threshold classification methods to distinguish trees, other vegetation types, impervious surfaces, and water. From 2010 to 2019, LST increased approximately 4 °F for all census tracts within the city and the total amount of tree cover increases less than 3%. The findings will aid the city in future decision-making processes by indicating areas that would benefit from increased green infrastructure.

Greta Paris↗

NASA NTRS2020

Huntsville Urban Development: Utilizing NASA Earth Observations to Evaluate Urban Tree Canopy and Land Surface Temperature for Green Infrastructure Development and Urban Heat Mitigation in Huntsville, AL

Huntsville, Alabama’s population has grown by approximately 11% since 2010, due in part to the city’s advancing engineering industry. Rapid urban growth negatively impacts the environment by decreasing tree canopy cover and increasing impervious surface cover, which can intensify the urban heat island effect. To examine the impacts of this urban growth on the environment, the team partnered with the City of Huntsville to utilize Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the International Space Station’s Global Ecosystems Dynamic Investigation (GEDI) and ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). The team utilized these Earth observations in combination with ancillary datasets to create a suite of end products to assist in mitigating the effects of extreme heat due to urban expansion and tree canopy loss. Annual land surface temperature (LST) was calculated and land cover classes were derived through supervised and threshold classification methods to distinguish trees, other vegetation types, impervious surfaces, and water. From 2010 to 2019, LST increased approximately 4 °F for all census tracts within the city and the total amount of tree cover increased by approximately 3%. The findings will aid the city in future decision-making processes by indicating areas that would benefit from increased green infrastructure.

Greta Paris↗

NASA NTRS2020

Huntsville Urban Development: Utilizing NASA Earth Observations to Evaluate Urban Tree Canopy and Land Surface Temperature for Green Infrastructure Development and Urban Heat Mitigation in Huntsville, Alabama

Greta Paris↗

NASA NTRS1994

SeaWiFS technical report series. Volume 21: The heritage of SeaWiFS. A retrospective on the CZCS NIMBUS Experiment Team (NET) program

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission is based on the scientific heritage of the Coastal Zone Color Scanner (CZCS), a proof-of-concept instrument carried on the National Aeronautics and Space Administration (NASA) NIMBUS-7 environmental satellite for the purpose of measuring upwelling radiance from the ocean surface. The CZCS mission provided the first observations of ocean color from space, and over the mission lifetime of 1978-1986, allowed oceanographers an initial opportunity to observe the variable patterns of global biological productivity. One of the key elements of the CZCS mission was the formation of the CZCS NIMBUS Experiment Team (NET), a group of optical physicists and biological oceanographers. The CZCS NET was designated to validate the accuracy of the CZCS radiometric measurements and to connect the instrument's measurements to standard measures of oceanic biological productivity and optical seawater clarity. In the period following the cessation of CZCS observations, some of the insight and experience gained by the CZCS NET activity has dissipated as several proposed follow-on sensors failed to achieve active status. The Sea WiFS mission will be the first dedicated orbital successor to CZCS it in turn precedes observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) of the Earth Observing System (EOS). Since the CZCS NET experience is an important model for Sea WiFS and MODIS surface truth efforts, this document is intended to provide a comprehensive review of the validation of oceanographic data for the first orbital ocean color sensor mission. This document also summarizes the history of the CZCS NET activities. The references listed in the Bibliography are a listing of published scientific research which relied upon the CZCS BET algorithms, or research which was conducted on the basis of CZCS mission elements.

Acker, James G.↗

DOE OSTI2023

Structural complexity biases vegetation greenness measures

Vegetation ‘greenness’ characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. In conclusion, our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1981

Upstream energetic ions and electrons - Bow shock-associated or magnetospheric origin

An analysis is made of 35 proton bursts observed with the Max-Planck-Institut/University of Maryland sensor system on ISEE 3 far upstream of the earth's bow shock. These upstream bursts are found to fall into two distinctive groups. The first is accompanied by energetic electrons (more than about 75 keV), and the proton spectrum extends up to energies greater than about 300 keV and higher and bends over toward lower energies (less than about 30 keV). The second group, which is unaccompanied by energetic electron bursts, exhibits spectra which can be represented extremely well by exponentials in energy with a mean e-folding energy of approximately 15 keV. The first group is thought to be of a magnetospheric origin, and the second to be bow-shock associated.

Scholer, M.↗

NASA NTRS1992

Radar sensitivity and antenna scan pattern study for a satellite-based Radar Wind Sounder (RAWS)

Modeling global atmospheric circulations and forecasting the weather would improve greatly if worldwide information on winds aloft were available. Recognition of this led to the inclusion of the LAser Wind Sounder (LAWS) system to measure Doppler shifts from aerosols in the planned for Earth Observation System (EOS). However, gaps will exist in LAWS coverage where heavy clouds are present. The RAdar Wind Sensor (RAWS) is an instrument that could fill these gaps by measuring Doppler shifts from clouds and rain. Previous studies conducted at the University of Kansas show RAWS as a feasible instrument. This thesis pertains to the signal-to-noise ratio (SNR) sensitivity, transmit waveform, and limitations to the antenna scan pattern of the RAWS system. A dop-size distribution model is selected and applied to the radar range equation for the sensitivity analysis. Six frequencies are used in computing the SNR for several cloud types to determine the optimal transmit frequency. the results show the use of two frequencies, one higher (94 GHz) to obtain sensitivity for thinner cloud, and a lower frequency (24 GHz) to obtain sensitivity for thinner cloud, and a lower frequency (24 GHz) for better penetration in rain, provide ample SNR. The waveform design supports covariance estimation processing. This estimator eliminates the Doppler ambiguities compounded by the selection of such high transmit frequencies, while providing an estimate of the mean frequency. the unambiguous range and velocity computation shows them to be within acceptable limits. The design goal for the RAWS system is to limit the wind-speed error to less than 1 ms(exp -1). Due to linear dependence between vectors for a three-vector scan pattern, a reasonable wind-speed error is unattainable. Only the two-vector scan pattern falls within the wind-error limits for azimuth angles between 16 deg to 70 deg. However, this scan only allows two components of the wind to be determined. As a result, a technique is then shown, based on the Z-R-V relationships, that permit the vertical component (i.e., rain) to be computed. Thus the horizontal wind components may be obtained form the covariance estimator and the vertical component from the reflectivity factor. Finally, a new candidate system is introduced which summarizes the parameters taken from previous RAWS studies, or those modified in this thesis.

Stuart, Michael A.↗

NASA NTRS1993

Rugged, no-moving-parts windspeed and static pressure probe designs for measurements in planetary atmospheres

Instruments developed for making meteorological observations under adverse conditions on Earth can be applied to systems designed for other planetary atmospheres. Specifically, a wind sensor developed for making measurements within tornados is capable of detecting induced pressure differences proportional to wind speed. Adding strain gauges to the sensor would provide wind direction. The device can be constructed in a rugged form for measuring high wind speeds in the presence of blowing dust that would clog bearings and plug passages of conventional wind speed sensors. Sensing static pressure in the lower boundary layer required development of an omnidirectional, tilt-insensitive static pressure probe. The probe provides pressure inputs to a sensor with minimum error and is inherently weather-protected. The wind sensor and static pressure probes have been used in a variety of field programs and can be adapted for use in different planetary atmospheres.

Bedard, A. J., Jr.↗

NASA NTRS1993

Feasibility study of an orbiting laboratory for testing CSI technology

A concept for an orbiting laboratory for testing Controls-Structures Integration (CSI) technology is described. The CSI-Star concept reflects a lower cost, higher risk approach. The concept supports demonstration and validation testing for critical CSI technologies at a cost of $20M to $26M with a 1-year reliability of approximately 0.9. The Ball Aerospace QuickStar bus is the carrier for the CSI test article. QuickStar is launched as a secondary payload on the McDonnell Douglas Delta 2. The QuickStar/Delta 2 approach is flight proven. The CSI test article is a 20 foot, 1 Hz, truss beam which is deployed from the QuickStar bus. The test article is well instrumented for quality system identification. The laboratory provides three layers of active control consisting of global vibration suppression along the truss beam, vibration isolation between the beam and instrument platforms, and vibration compensation through the use of gimbaled platforms which point lasers relative to optical sensor targets. The configuration simulates the dynamics of multi-instrument science platforms such as those of the Earth Observation System (EOS) while maintaining strong ties to astrophysics missions such as the Optical Interferometer. Uplink/downlink services and a reprogrammable computer provide flexibility for long-term investigations by members of the CSI community (NASA, DoD, academia, and industry). CSI-Star fills the gap between short-term experiments, which have been conducted primarily on the Shuttle, and future science missions which require the technology. The on-orbit maturity of CSI technology must be established to obtain acceptance by project managers and to promote injection of the technology into future science missions.

Bicos, Andrew S.↗

NASA NTRS1999

Mapping Northern Ecosystems with POLDER: Applications for Circumpolar Methane Exchange

This Joint Research Interchange was originally Proposed concurrent with the launch in the fall of 1996 of a revolutionary new satellite sensor which offered great promise to significantly advance atmospheric, oceanographic and land surface studies, i.e., ADEOS POLDER (Advanced Earth Observation Satellite / POLarization and Directionality of the Earth's Reflectance). Unfortunately, the ADEOS mission ended on June 30, 1997 due to a loss of power. As a consequence, this NASA-UVM collaboration was redirected to focus on analyses of airborne-POLDER data acquired in support of the joint U.S.-Canada Boreal Ecosystem Atmosphere Study (BOREAS) in the summer of 1994. We present here a brief summary of results of that effort; details are provided in the manuscripts referenced below.

Livingston, Gerald↗

NASA NTRS2000

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Emerson, Charles W.↗

NASA NTRS2001

Controlling Malaria and Other Diseases Using Remote Sensing

Remote sensing offers the vantage of monitoring a vast area of the Earth continuously. Once developed and launched, a satellite gives years of service in collecting data from the land, the oceans, and the atmosphere. Since the 1980s, attempts have been made to relate disease occurrence with remotely sensed environmental and geophysical parameters, using data from Landsat, SPOT, AVHRR, and other satellites. With higher spatial resolution, the recent satellite sensors provide a new outlook for disease control. At sub-meter to I 10m resolution, surface types associated with disease carriers can be identified more accurately. The Ikonos panchromatic sensor with I m resolution, and the Advanced Land Imager with 1 Om resolution on the newly launched Earth Observing-1, both have displayed remarkable mapping capabilities. In addition, an entire array of geophysical parameters can now be measured or inferred from various satellites. Airborne remote sensing, with less concerns on instrument weight, size, and power consumption, also offers a low-cost alternative for regional applications. NASA/GSFC began to collaborate with the Mahidol University on malaria and filariasis control using remote sensing in late 2000. The objectives are: (1) To map the breeding sites for the major vector species; (2) To identify the potential sites for larvicide and insecticide applications; (3) To explore the linkage of vector population and transmission intensity to environmental variables; (4) To monitor the impact of climate change and human activities on vector population and transmission; and (5) To develop a predictive model for disease distribution. Field studies are being conducted in several provinces in Thailand. Data analyses will soon begin. Malaria data in South Korea are being used as surrogates for developing classification techniques. GIS has been shown to be invaluable in making the voluminous remote sensing data more readily understandable. It will be used throughout this study to clearly demonstrate the spatial relationship between the disease intensities, geophysical variables, and socioeconomic parameters. Asides from malaria and filariasis, application of remote sensing to the control of other diseases have been vigorously pursued by NASA's Environment and Health Initiative. The current program includes projects on Rift Valley fever, St. Louis encephalitis, dengue fever, ebola, African dust and diseases, meningitis, asthma, bartonellosis, cholera, and urban health concerns. Results from these projects indicate that remote sensing will play an increasingly important role in disease control in the future.

Kiang, Richard K.↗

NASA NTRS2004

Assimilation of SBUV Version 8 Radiances into the GEOS Ozone DAS

In operational weather forecasting, the assimilation of brightness temperatures from satellite sounders, instead of assimilation of 1D-retrievals has become increasingly common practice over the last two decades. Compared to these systems, assimilation of trace gases is still at a relatively early stage of development, and efforts to directly assimilate radiances instead of retrieved products have just begun a few years ago, partially because it requires much more computation power due to the employment of a radiative transport forward model (FM). This paper will focus on a method to assimilate SBUV/2 radiances (albedos) into the Global Earth Observation System Ozone Data Assimilation Scheme (GEOS-03DAS). While SBUV-type instruments cannot compete with newer sensors in terms of spectral and horizontal resolution, they feature a continuous data record back to 1978, which makes them very valuable for trend studies. Assimilation can help spreading their ground coverage over the whole globe, as has been previously demonstrated with the GEOS-03DAS using SBUV Version 6 ozone profiles. Now, the DAS has been updated to use the newly released SBUV Version 8 data. We will compare pre]lmlnarv results of SBUV radiance assimilation with the assimilation of retrieved ozone profiles, discuss methods to deal with the increased computational load, and try to assess the error characteristics and future potential of the new approach.

Mueller, Martin D.↗

NASA NTRS2002

NASA's New Laser Risk Reduction Program For Future Space Lidar Missions

NASA has been performing ground, airborne, and space-based scientific measurements since it was formed in 1958. Initial ground and airborne measurements were made with in situ instruments. By necessity, initial earth observation space-based missions were accomplished with passive remote sensing. Active microwave radar was added to the sensor repertoire in the late 1970s. A few key measurements important to NASA remain unaccomplished, however, despite the passive and radar successes. These critical measurements include space-based altimetry; and high spatial resolution profiling of aerosol properties, wind velocity, clouds, and molecular concentrations. Fortunately, a new technology, active optical radar or laser radar or lidar, has matured to the point that the last decade has seen a growing consideration of lidar for space missions. Part of the surge in consideration of lidar has been the tremendous progress in solid-state lasers fueled by advances in crystal growth quality and pump laser diode technology.

Michael J. Kavaya↗

NASA NTRS2011

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

Platnick, Steven E.↗

NASA NTRS2011

Assessing the Lifetime Performance of the Lightning Imaging Sensor (LIS): Implications for the Geostationary Lightning Mapper (GLM)

The Lightning Imaging Sensor (LIS) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite has been providing observations of total lightning over the Earth s Tropics for 13 years. This study examines the performance of the LIS throughout its time in orbit. Application of the Deep Convective Cloud Technique (DCCT) (Doelling et al., 2004) was performed on the LIS background pixels to assess the stability of the LIS instrument. The DCCT analysis indicates that the maximum deviation of the monthly mean radiance is within 2% of the overall mean, indicating stable performance over the period. In addition, an examination of the number of flashes detected over time similarly shows no significant trend (after adjusting for the orbit boost that occurred in August 2001). These and other results indicate that there has been no discernible change in LIS performance throughout its lifetime. A similar approach will used for monitoring the performance of the Geostationary Lightning Mapper (GLM) onboard the next generation Geostationary Operational Environmental Satellite-R (GOES-R). Since GLM is based on LIS design heritage, the LIS results indicate that GLM may also experience stable performance over its lifetime.

Buechler, D. E.↗

NASA NTRS2022

Phoenix Climate: Employing NASA Earth Observations to Conduct Site Suitability Analyses on Residential Tree Planting Initiatives in Phoenix, AZ

Phoenix, Arizona is the hottest city in the United States, with daytime summer temperatures consistently reaching upwards of 100°F. As these daytime temperatures continue to climb, heat-related illnesses and morbidity also increase. The City of Phoenix hopes to secure funding to implement the American Rescue Plan Act (ARPA) residential tree equity accelerator program. This funding will be used for targeted investments in underserved neighborhoods to increase tree canopy cover, engaging 5,000 households across selected neighborhoods. By partnering with the City of Phoenix, the Arizona Office of Heat Mitigation, and Arizona State University’s Urban Climate Research Center, our team identified residential neighborhoods, block groups within qualified census tracts, and parcels to be prioritized in the ARPA program. We conducted an analysis using NASA Earth observations, movement and heat exposure data, sociodemographic data, and tree canopy data. For Earth observations, we acquired daytime land surface temperature from the Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) and land cover classification from the United States Geological Survey (USGS) National Land Cover Database (NLCD). The project will support the prioritization of city resources and tree plantings based on community vulnerability, as well as help initiate public engagement efforts and literacy with an interactive dashboard and GIS layers that contribute to the city’s property information portal.

Alison Bautista↗

NASA NTRS2022

Characterizing Aerosol From Space With the MODerate Resolution Imaging Spectroradiometer (Modis) on the Terra and Aqua Satellites

Aerosols, the small, suspended liquid and solid particles in the atmosphere, have myriad effects on climate, weather, and air quality. When the NASA Earth-Observing System’s (EOS) Terra and Aqua satellites launched in 1999 and 2002, they each included many advanced sensors that have been used for aerosol research. In particular, the MODerate-resolution Imaging Spectroradiometer (MODIS) deployed on both satellites, has provided key data relating to aerosol loading and relative aerosol type on the global scale. Three different algorithms, known as “Dark Target”, “Deep Blue” and “MAIAC”, use different subsets of MODIS measurements and different assumptions to create various products such as Aerosol Optical Depth (AOD), fine mode fraction (FMF) and single scattering albedo (SSA). Although all three derive AOD in cloud-free conditions, each algorithm has different strengths and weaknesses in different areas of the globe and under different conditions. Here, we provide a short summary of each algorithm, description of products, and basic information about downloading and using the products. We also provide some examples of how MODIS aerosol products are used. Finally, we add a quick discussion about how these algorithms and products will continue after MODIS leaves orbit.

MODIS↗