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At least 19 records

Prelaunch Spectral Characterization of the Operational Land Imager-2

The Landsat-9 satellite, launched in September 2021, carries the Operational Land Imager-2 (OLI-2) as one of its payloads. This instrument is a clone of the Landsat-8 OLI and its mission is to continue the operational land imaging of the Landsat program. The OLI-2 instrument is not significantly different from OLI though the instrument-level pre-launch spectral characterization process was much improved. The focal plane modules used on OLI-2 were manufactured as spares for OLI and much of the spectral characterization of the components was performed for OLI. However, while the spectral response of the fully assembled OLI was characterized by a double monochromator system, the OLI-2 spectral characterization made use of the Goddard Laser for Absolute Measurement of Radiance (GLAMR). GLAMR is a system of tunable lasers that cover 350–2500 nm which are fiber-coupled to a 30 in integrating sphere permanently monitored by NIST-traceable radiometers. GLAMR allowed the spectral characterization of every detector of the OLI-2 focal plane in nominal imaging conditions. The spectral performance of the OLI-2 was, in general, much better than requirements. The final relative spectral responses (RSRs) represent the best characterization any Landsat instrument spectral response. This paper will cover the results of the spectral characterization from the component-level to the instrument-level of the Landsat-9 OLI-2.

Landsat-9

The Landsat Data Continuity Mission Operational Land Imager: Radiometric Performance

The Operational Land Imager (OLI) is one of two instruments to fly on the Landsat Data Continuity Mission (LDCM), which is scheduled to launch in December 2012 to become the 8th in the series of Landsat satellites. The OLI images in the solar reflective part of the spectrum, with bands similar to bands 1-5, 7 and the panchromatic band on the Landsat-7 ETM+ instrument. In addition, it has a 20 nm bandpass spectral band at 443 nm for coastal and aerosol studies and a 30 nm band at 1375 nm to aid in cirrus cloud detection. Like ETM+, spatial resolution is 30 m in the all but the panchromatic band, which is 15 meters. OLI is a pushbroom radiometer with approximately 6000 detectors per 30 meter band as opposed to the 16 detectors per band on the whiskbroom ETM+. Data are quantized to 12 bits on OLI as opposed to 8 bits on ETM+ to take advantage of the improved signal to noise ratio provided by the pushbroom design. The saturation radiances are higher on OLI than ETM+ to effectively eliminate saturation issues over bright Earth targets. OLI includes dual solar diffusers for on-orbit absolute and relative (detector to detector) radiometric calibration. Additionally, OLI has 3 sets of on-board lamps that illuminate the OLI focal plane through the full optical system, providing additional checks on the OLI's response[l]. OLI has been designed and built by Ball Aerospace & Technology Corp. (BATC) and is currently undergoing testing and calibration in preparation for delivery in Spring 2011. Final pre-launch performance results should be available in time for presentation at the conference. Preliminary results will be presented below. These results are based on the performance of the Engineering Development Unit (EDU) that was radiometrically tested at the integrated instrument level in 2010 and assembly level measurements made on the flight unit. Signal-to-Noise (SNR) performance: One of the advantages of a pushbroom system is the increased dwell time of the detectors allowing for significantly higher SNR than equivalent aperture whiskbroom systems. OLI performance based on the EDU at the "typical" radiance level as specified in the OLI requirements document are about 10 times better than ETM+ performance and 2-3 times better than the requirements for OLI (Table 1).

Markham, Brian

Landsat Data Continuity Mission

The Landsat Data Continuity Mission (LDCM) is currently under development and is on schedule to launch the 8th satellite in the Landsat series in December of 2012. LDCM is a joint project between the National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS). NASA is responsible for developing and launching the flight hardware and on-orbit commissioning and USGS is responsible for developing the ground system and operating the system onorbit after commissioning. Key components of the flight hardware are the Operational Land Imager (OLI), nearing completion by Ball Aerospace & Technologies Corp in Boulder, CO, the Thermal Infrared Sensor (TIRS), being built by NASA's Goddard Space Flight Center and the spacecraft, undergoing integration at Orbital Sciences Corp in Gilbert, Arizona. The launch vehicle will be an Atlas-5 with launch services provided by NASA's Kennedy Space Center. Key ground systems elements are the Mission Operations Element, being developed by the Hammers Corporation, and the Collection Activity Planning Element, Ground Network Element, and Data Processing and Archive System, being developed internally by the USGS Earth Resources Observations and Science (EROS) Center. The primary measurement goal of LDCM is to continue the global coverage of moderate spatial resolution imagery providing continuity with the existing Landsat record. The science goal for this imagery is to monitor land use and land cover, particularly as it relates to global climate change. Together the OLI and TIRS instruments on LDCM replace the ETM+ instrument on Landsat-7 with significant enhancements. The OLI is a pushbroom design instrument where the scanning mechanism of the ETM+ is effectively replaced by a long line of detectors. The OLI has 9 spectral bands with similar spatial resolution to ETM+: 7 of them similar to the reflective spectral bands on ETM+ and two new bands. The two new bands cover (1) the shorter wavelength blue part of the spectrum to help with coastal studies and aerosol analyses/atmospheric correction and (2) an atmospheric water absorption band, where the Earth surface is generally not visible, but Cirrus clouds are, to aid in cloud detection and screening. The radiometry of OLI benefits from improved SNR, dynamic range and quantization. OLI is undergoing system testing with a delivery scheduled for Spring 2011. The TIRS is also a pushbroom design and used QWIPS detectors that require cooling to 43K using a cryocooler. It.has two spectral bands, effectively splitting the ETM+ band 6 in half, that can be used as a split window to aid in atmospheric correction. It has nominally 100 m spatial resolution as opposed to the 60 m of Landsat-7 ETM+: TIRS has commenced integration and test, with a delivery to the spacecraft vendor scheduled for Winter 2011-2012. The Orbital spacecraft currently being integrated for LDCM will have improved capabilities for pointing over previous missions. These capabilities will allow the OLI and TIRS instruments to point off-nadir the equivalent of one WRS-2 path to increase the chances of coverage for high priority targets, particularly in the event of natural disasters. Also, the pointing capability will allow the calibration of the OLI using the sun (roughly weekly), the moon (monthly), stars (during commissioning) and the Earth (at 90 deg from normal orientation, a.k.a., side slither) quarterly. The solar calibration will be used for OLI absolute and relative calibration, the moon for trending the stability of the OLI response, the stars will be used for Line of Sight determination and the side slither will be an alternate OLI and relative gain determination methodology. The spacecraft is scheduled to begin integration with the OLI instrument in Summer 2011. The LDCM data processing and archive system (DPAS), located at USGS EROS, generates the products for distribution to users. Like Landsat-7 this includes an image assessment system for characrizing instrument performance and updating calibration parameters. Products will be generated that include the spectral bands from both instruments, terrain corrected and registered to the geoid. Also, like Landsat-7, data products will be distributed at no charge to the user. The current status and plans of the space and ground segments of the LDCM project will be presented along with performance predictions as available. More detailed information on the two instruments is intended to be presented in separate papers.

Markham, Brian

On-Orbit Measurement of the Focal Length of the SNPP VIIRS Instrument

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is a whiskbroom system with 22 spectral bands split between 16 moderate resolution bands (M-bands), five imagery resolution bands (I-bands) and a panchromatic day-night band. Latitude and Longitude geolocation data are generated for each pixel at the M-band, I-band and day-night band spatial resolutions based upon various instrument parameters including focal length. In this study we measure the focal length of the VIIRS instrument from on-orbit data. This is achieved by simulating VIIRS band I2 using Landsat 8 OLI band 5 utilizing the VIIRS instrument system point spread function (PSF) and geolocation data generated with varying values of focal length. The focal length value that produces the highest spatial correlation between the original and simulated VIIRS data is taken to be the measured instrument focal length.

Image analysis

Landsat-8 Operational Land Imager On-Orbit Radiometric Calibration

The Operational Land Imager (OLI), the VIS/NIR/SWIR sensor on the Landsat-8 has been successfully acquiring Earth Imagery for more than four years. The OLI incorporates two on-board radiometric calibration systems, one diffuser based and one lamp based, each with multiple sources. For each system one source is treated as primary and used frequently and the other source(s) are used less frequently to assist in tracking any degradation in the primary sources. In addition, via a spacecraft maneuver, the OLI instrument views the moon once a lunar cycle (approx. 29 days). The integrated lunar irradiances from these acquisitions are compared to the output of a lunar irradiance model. The results from all these techniques, combined with cross calibrations with other sensors and ground based vicarious measurements are used to monitor the OLI's stability and correct for any changes observed. To date, the various techniques have other detected significant changes in the shortest wavelength OLI band centered at 443 nm and these are currently being adjusted in the operational processing.

radiometric calibratio

Landsat Data Continuity Mission Expected Instrument Performance

The Landsat Data Continuity Mission (LDCM) is scheduled for a December 2012 launch date. LDCM is being managed by an interagency partnership between NASA and the U.S. Geological Survey (USGS). In order to provide the necessary spectral coverage of the visible through shortwave-infrared (SWIR) and the thermal-infrared (TIR), the satellite will carry two sensors. The Operational Land Imager (OLI) will collect data for nine visible to shortwave spectral bands with a spatial resolution of 30 m (with a 15 m panchromatic band). The Thermal Infrared Sensor (TIRS) will collect coincident image data for two TIR bands with a spatial resolution of 100 m. The OLI is fully assembled and tested and has been shipped by it's manufacturer, Ball Aerospace and Technology Corporation, to the Orbital Sciences Corporation (Orbital) facility where it is being integrated onto the LDCM spacecraft. Pre-launch testing indicates that OLI will meet all performance specification with margin. TIRS is in development at the NASA Goddard Space F!ight Center (GSFC) and is in final testing before shipping to the Orbital facility in January, 2012. The presentation will describe the LDCM satellite instrument systems, present pre-launch performance data for OLI and TIRS, and present simulated images to highlight notable features and expected imaging performance.

Dabney, Philip W.

Fire Island Water Resources: Assessing Sediment Dynamics and Turbidity Changes Along Fire Island National Seashore Using Satellite Data

Fire Island National Seashore has experienced damaging effects as a result of coastal erosion. Erosion has become an increasingly damaging problem that has led to the destruction of park and community infrastructure, contributed to rising groundwater tables, and posed a serious threat to a globally rare holly maritime forest. Beach nourishment project efforts have been made to mitigate damage, but dredging is expensive and can be thwarted by high rates of erosion. The NASA DEVELOP team partnered with the National Park Service and Fire Island National Seashore and used imagery from Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), and Sentinel-2 MultiSpectral Instrument (MSI) to analyze turbidity and sediment dynamics through surface reflectance data from 2000-2021. Imagery was atmospherically corrected using Atmospheric Correction for OLI Lite (ACOLITE) and visualized in SeaWiFS Data Analysis Systems (SeaDAS). Additionally, shoreline change was analyzed using high-resolution imagery from WorldView-2 acquired from Maxar for pre-Hurricane Sandy on July 25th, 2010 and post-Hurricane Sandy on December 18th, 2019. The results of this analysis showed that turbidity is highest in the winter seasons. The shoreline analysis estimated total shoreline loss of about 62 acres on the ocean side, and 11 acres on the bay side of the island. These results will be used to better inform future partner-designed shoreline management projects in the face of further erosion and sea level rise.

Kelly Young

Landsat Derived Bathymetry of Lakes on the Arctic Coastal Plan of Northern Alaska

The Pleistocene sand sea on the Arctic Coastal Plain (ACP) of northern Alaska is underlain by anancient sand dune field, a geological feature that affects regional lake characteristics. Many of these lakes, whichcover approximately 20 % of the Pleistocene sand sea, are relatively deep (up to 25 m). In addition to the nat-ural importance of ACP sand sea lakes for water storage, energy balance, and ecological habitat, the need forwinter water for industrial development and exploration activities makes lakes in this region a valuable resource.However, ACP sand sea lakes have received little prior study. Here, we collect in situ bathymetric data to test12 model variants for predicting sand sea lake depth based on analysis of Landsat-8 Operational Land Imager(OLI) images. Lake depth gradients were measured at 17 lakes in midsummer 2017 using a Humminbird 798ciHD SI Combo automatic sonar system. The field-measured data points were compared to red–green–blue (RGB)bands of a Landsat-8 OLI image acquired on 8 August 2016 to select and calibrate the most accurate spectral-depth model for each study lake and map bathymetry. Exponential functions using a simple band ratio (withbands selected based on lake turbidity and bed substrate) yielded the most successful model variants. For eachlake, the most accurate model explained 81.8 % of the variation in depth, on average. Modeled lake bathymetrieswere integrated with remotely sensed lake surface area to quantify lake water storage volumes, which rangedfrom 1.056×10−3to 57.416×10−3km3. Due to variations in depth maxima, substrate, and turbidity betweenlakes, a regional model is currently infeasible, rendering necessary the acquisition of additional in situ datawith which to develop a regional model solution. Estimating lake water volumes using remote sensing will fa-cilitate better management of expanding development activities and serve as a baseline by which to evaluatefuture responses to ongoing and rapid climate change in the Arctic. All sonar depth data and modeled lakebathymetry rasters can be freely accessed at https://doi.org/10.18739/A2SN01440 (Simpson and Arp, 2018) andhttps://doi.org/10.18739/A2HT2GC6G (Simpson, 2019), respectively.

Claire E Simpson

Progress Towards a 2012 Landsat Launch

The Landsat Data Continuity Mission (LDCM) is on schedule for a December 2012 launch date. The mission is being managed by an interagency partnership between NASA and the U.S. Geological Survey (USGS). NASA leads the development and launch of the satellite observatory while leads ground system development. USGS will assume responsibility for operating the satellite and for collecting, archiving, and distributing the LDCM data following launch. When launched the satellite will carry two sensors into orbit. The Operational Land Imager (OLI) will collect data for nine shortwave spectral bands with a spatial resolution of 30 m (with a 15 m panchromatic band). The Thermal Infrared Sensor (TIRS) will coincidently collect data for two thermal infrared bands with a spatial resolution of 100 m. The OLI is fully assembled and tested and has been shipped by it?s manufacturer, Ball Aerospace and Technology Corporation, to the Orbital Sciences Corporation (Orbital) facility where it is being integrated onto the LDCM spacecraft. Pre-launch testing indicates that OLI will meet all performance specification with margin. TIRS is in development at the NASA Goddard Space Flight Center (GSFC) and is in final testing before shipping to the Orbital facility in January, 2012. The ground data processing system is in development at the USGS Earth Resources Observation and Science (EROS) Center. The presentation will describe the LDCM satellite system, provide the status of system development, and present prelaunch performance data for OLI and TIRS. The USGS has committed to renaming the satellite as Landsat 8 following launch.

Irons, Jim

Assessing the Needs of NASA's Near Real-Time Earth Observation Products

"The 2017-2027 Decadal Survey for Earth Science and Applications from Space stated that NASA's Earth Science with planned implementation of applications provides sustained earth observations for societal benefits [1]. The Decadal Survey indicated that data latency is invaluable for time-sensitive applications including disaster risk reduction, wildland fire carbon emissions quantification, real-time measurements of the state of the hydrologic systems and many more. Data latency refers to the time between earth observation and data products available to users. During the past 13 years, NASA's Land, Atmosphere Near Real-Time Capability for Earth Observing Systems (LANCE) continues to provide free access to earth observation products that are made available much quicker than routine processing allows. The latency of most LANCE data products is Near Real-time (NRT) which is defined as less than three hours from satellite observations [2]. LANCE is managed by the Earth Science Data and Information System (ESDIS) Project at NASA Goddard Space Flight Center [3], and a User Working Group (UWG) is responsible for providing guidance to LANCE. LANCE data are used by direct users and brokers who add value to the data [4]. NASA Earth Applied Sciences Program (ASP) is one of the primary users of LANCE, which collaborates with partner organizations and provides support to scientists to solve problems in applications of earth observations. ASP promotes the use of LANCE NRT data products to demonstrate applications in decision making, facilitates end-user feedback to the science team to improve data products, and provides information on future demands for research. LANCE supports applications that need a rapid response including detecting wildland fires and volcanic eruptions, tracking smoke, ash and dust plumes, monitoring air quality and tracking extreme weather events such as hurricanes, landslides, and floods. To gather feedback regarding the availability, accessibility and actionability of NASA's NRT data products for societal benefit, three surveys and a few discussions with experts involved in the topic within ASP were conducted from the perspective of users. Feedback has been collected from users who are interested in using low latency NASA data within application communities of agriculture, disasters, water resources, health and air quality, ecological conservation, wildland fires and capacity building. Analysis-ready NRT data products in a variety of formats have been mentioned many times in the collected feedback, especially for applied users with little to no experience using research-grade earth observation products. Users prefer to have products that can be easily integrated into their existing workflows and take their analysis to the data. HDF5 is a commonly used data format for research, but typically requires some conversion to a more friendly format for applications and regular use in decision-making. Users prefer the GeoTIFF data format that can be directly ingested into a GIS mapping software and platform for data analysis and visualization. For example, LANCE’s fire, flood, SO2 and Black Marble Nighttime Blue/Yellow Composite data products have been integrated into NASA Disasters Mapping Portal, which is an GIS-based open data portal, for users in the disaster management community. There are 291 LANCE NRT layers available through GIBS and Worldview, where users can download a snapshot in GeoTIFF format. Operational users expect data to be processed as close to the user as possible. The collected feedback indicates that LANCE fire products within 3 hours latency would meet the needs of the wildland fire community. The ideal latency for volcanic application is 10-15 minutes. Users in Volcanic Ash Advisory Centers (VAAC) reported that the first forecast volcanic product should be issued within 75 minutes from the volcano eruption [5]. Overall, for disaster applications, data latency within 3 hours is useful while latency greater than 12 hours is not timely enough for operational use. Capacity building and training are critical for users to be able to access, interpret and use data products and tools for their decision making, especially for applied users with limited experience using earth observation products. LANCE data products have been used in a number of capacity building projects domestically and internationally [6]. As LANCE continues to bring new products into the system, users request training to utilize LANCE new and upcoming data products and capabilities in their applications. Due to the limitation of bandwidth and downstream flow paths, users in some developing countries need tools to select and download data for a specific area of interest instead of bulk downloads. The collected feedback also shows the lack of available SAR satellite low latency data products. The advantages of SAR to monitor conditions and changes on the ground through darkness, clouds, volcanic ash, and other atmospheric conditions, are appealing to low latency users. For example, terabytes of low latency but cloudy optical images are not helpful in rapidly identifying the extent of flood or fire impacts. LANCE could be complemented with low latency measurements via the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission [7]. Requests for higher spatial resolution products are expressed. A user from the wildland fire management community reported that products with 30-m spatial resolution could be used to detect small fires. The 30-m Landsat OLI fire data is now part of NASA’s Fire Information for Resource Management System (FIRMS) US/Canada [8]. Within the open and free NASA resources, LANCE disseminates NRT data products in a manner that allows them to be accessible and understandable to both scientific and applied users. In many application areas, latency plays an important or even decisive role where low latency earth observations help people to observe areas of interest, detect and track changes in the environment and make timely decisions. NASA’s Earth Applied Sciences Program promotes the use of LANCE NRT products and builds a bridge between application users and research teams. The collected feedback indicates data latency within 3 hours is useful for most of the applications, and shows the needs of user-friendly, analysis-ready products, and requests training on LANCE’s new and upcoming data products. User feedback has been provided to LANCE UWG for guidance and recommendations, and for translating findings into something actionable.

Tian Yao

Ocean Color Measurements with the Operational Land Imager on Landsat-8: Implementation and Evaluation in SeaDAS

The Operational Land Imager (OLI) is a multispectral radiometer hosted on the recently launched Landsat8 satellite. OLI includes a suite of relatively narrow spectral bands at 30 m spatial resolution in the visible to shortwave infrared, which makes it a potential tool for ocean color radiometry: measurement of the reflected spectral radiance upwelling from beneath the ocean surface that carries information on the biogeochemical constituents of the upper ocean euphotic zone. To evaluate the potential of OLI to measure ocean color, processing support was implemented in Sea-viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System (SeaDAS), which is an open-source software package distributed by NASA for processing, analysis, and display of ocean remote sensing measurements from a variety of spaceborne multispectral radiometers. Here we describe the implementation of OLI processing capabilities within SeaDAS, including support for various methods of atmospheric correction to remove the effects of atmospheric scattering and absorption and retrieve the spectral remote sensing reflectance (Rrs; sr−1). The quality of the retrieved Rrs imagery will be assessed, as will the derived water column constituents, such as the concentration of the phytoplankton pigment chlorophyll a.

Measurements

Landsat-8 Thermal Infrared Sensor (TIRS) Vicarious Radiometric Calibration

Launched in February 2013, the Landsat-8 carries on-board the Thermal Infrared Sensor (TIRS), a two-band thermal pushbroom imager, to maintain the thermal imaging capability of the Landsat program. The TIRS bands are centered at roughly 10.9 and 12 micrometers (Bands 10 and 11 respectively). They have 100 m spatial resolution and image coincidently with the Operational Land Imager (OLI), also on-board Landsat-8. The TIRS instrument has an internal calibration system consisting of a variable temperature blackbody and a special viewport with which it can see deep space; a two point calibration can be performed twice an orbit. Immediately after launch, a rigorous vicarious calibration program was started to validate the absolute calibration of the system. The two vicarious calibration teams, NASA/Jet Propulsion Laboratory (JPL) and the Rochester Institute of Technology (RIT), both make use of buoys deployed on large water bodies as the primary monitoring technique. RIT took advantage of cross-calibration opportunity soon after launch when Landsat-8 and Landsat-7 were imaging the same targets within a few minutes of each other to perform a validation of the absolute calibration. Terra MODIS is also being used for regular monitoring of the TIRS absolute calibration. The buoy initial results showed a large error in both bands, 0.29 and 0.51 W/sq m·sr·micrometers or -2.1 K and -4.4 K at 300 K in Band 10 and 11 respectively, where TIRS data was too hot. A calibration update was recommended for both bands to correct for a bias error and was implemented on 3 February 2014 in the USGS/EROS processing system, but the residual variability is still larger than desired for both bands (0.12 and 0.2 W/sq m·sr·micrometers or 0.87 and 1.67 K at 300 K). Additional work has uncovered the source of the calibration error: out-of-field stray light. While analysis continues to characterize the stray light contribution, the vicarious calibration work proceeds. The additional data have not changed the statistical assessment but indicate that the correction (particularly in band 11) is probably only valid for a subset of data. While the stray light effect is small enough in Band 10 to make the data useful across a wide array of applications, the effect in Band 11 is larger and the vicarious results suggest that Band 11 data should not be used where absolute calibration is required.

TIIRS

An Overview of the Landsat Data Continuity Mission

The advent of the Landsat Data Continuity Mission (LDCM), currently with a launch readiness date of December, 2012, will see evolutionary changes in the Landsat data products available from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The USGS initiated a revolution in 2009 when EROS began distributing Landsat data products at no cost to requestors in contrast to the past practice of charging the cost of fulfilling a request; that is, charging $600 per Landsat scene. To implement this drastic change, EROS terminated data processing options for requestors and began to produce all data products using a consistent processing recipe. EROS plans to continue this practice for the LDCM and will required new algorithms to process data from the LDCM sensors. All previous Landsat satellites flew multispectral scanners to collect image data of the global land surface. Additionally, Landsats 4, 5, and 7 flew sensors that acquired imagery for both reflective spectral bands and a single thermal band. In contrast, the LDCM will carry two pushbroom sensors; the Operational Land Imager (OLI) for reflective spectral bands and the Thermal InfraRed Sensor (TIRS) for two thermal bands. EROS is developing the ground data processing system that will both calibrate and correct the data from the thousands of detectors employed by the pushbroom sensors and that will also combine the data from the two sensors to create a single data product with registered data for all of the OLI and TIRS bands.

Irons, James R.

The Next Landsat Satellite: The Landsat Data Continuity Mission

The Landsat program is one of the longest running satellite programs for Earth observations from space. The program was initiated by the launch of Landsat 1 in 1972. Since then a series of six more Landsat satellites were launched and at least one of those satellites has been in operations at all times to continuously collect images of the global land surface. The Department of Interior (DOI) U.S. Geological Survey (USGS) preserves data collected by all of the Landsat satellites at their Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. This 40-year data archive provides an unmatched record of the Earth's land surface that has undergone dramatic changes in recent decades due to the increasing pressure of a growing population and advancing technologies. EROS provides the ability for anyone to search the archive and order digital Landsat images over the internet for free. The Landsat data are a public resource for observing, characterizing, monitoring, trending, and predicting land use change over time providing an invaluable tool for those addressing the profound consequences of those changes to society. The most recent launch of a Landsat satellite occurred in 1999 when Landsat 7 was placed in orbit. While Landsat 7 remains in operation, the National Aeronautics and Space Administration (NASA) and the DOI/ USGS are building its successor satellite system currently called the Landsat Data Continuity Mission (LDCM). NASA has the lead for building and launching the satellite that will carry two Earth-viewing instruments, the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The OLI will take images that measure the amount of sunlight reflected by the land surface at nine wavelengths of light with three of those wavelengths beyond the range of human vision. T1RS will collect coincident images that measure light emitted by the land surface as a function of surface temperature at two longer wavelengths well beyond the range of human vision. The DOI/USGS is developing the ground system that will command and control the LDCM satellite in orbit and manage the OLI and TIRS data transmitted by the satellite. DOI/USGS will thus operate the satellite and collect, archive, and distribute the image data as part of the EROS archive. DOI/USGS has committed to renaming LDCM as Landsat 8 following launch. By either name the satellite and its sensors will extend the 40-year archive with images sufficiently consistent with data from earlier Landsat satellites to allow multi-decadal, broad-area studies of our dynamic landscapes. The next Landsat satellite and ground system are on schedule for a January, 2013 launch.

Rons, James R.

Bryce Canyon Water Resources: Monitoring Vegetation Health and Water Availability in Bryce Canyon National Park for Drought Stress Mitigation Planning

Bryce Canyon National Park is home to groundwater-dependent ecosystems (GDEs) that are threatened by a multidecadal drought and increased groundwater extraction due to a spike in tourism. These ecosystems contain unique species that are only found in areas where near-surface groundwater is present, such as aspen groves and fens. These species contribute to the high biodiversity found in Bryce Canyon, which boosts an ecosystem’s productivity and the services it provides to the park. Unfortunately, many of these GDEs are too small to identify with traditional Earth observation platforms and are difficult to physically reach for monitoring purposes. This project partnered with the National Park Service to identify springs and seeps as a proxy for GDEs within Bryce Canyon from 2013–2022. Furthermore, this project tested the feasibility of various methods to detect and monitor springs and seeps and therefore facilitate the partner’s efforts to conserve these ecologically valuable GDEs in Bryce Canyon. The team mapped groundwater discharge with high resolution National Agriculture Imagery Program (NAIP) and assessed park vegetation trends with Landsat 8 Operational Land Imager (OLI) and PlanetScope imagery. In-situ precipitation data and the Western Land Data Assimilation System (WLDAS) were used to produce time series of climatic variables. Seeps and spring locations were predicted using random forest classification and maximum entropy machine learning models.

Groundwater dependent ecosystems

Monitoring Vegetation Health and Water Availability in Bryce Canyon National Park for Drought Stress Mitigation Planning

Bryce Canyon National Park is home to groundwater-dependent ecosystems (GDEs) that are threatened by a multidecadal drought and increased groundwater extraction due to a spike in tourism. These ecosystems contain unique species that are only found in areas where near-surface groundwater is present, such as aspen groves and willows. GDEs contribute to the high biodiversity found in Bryce Canyon, which boosts an ecosystem’s productivity and increases the overall ecological health of the park. Unfortunately, many GDEs in this area are too small to identify with traditional Earth observation platforms and are difficult to physically reach for identification and monitoring. NASA DEVELOP partnered with the National Park Service to establish a framework that both identified and assessed the health of GDEs within Bryce Canyon from 2013–2022. The team used high-resolution PlanetScope and Landsat 8 Operational Land Imager (OLI) to map springs, seeps, and GDEs. Modeled data from the Western Land Data Assimilation System (WLDAS) and in situ precipitation data were used to produce time series of climatic variables for the National Park Service to gain an understanding of how the GDEs are changing with the ongoing drought. This study is essential to the goal of the National Park Service to conserve the health of these GDEs.

Aaron Carr

Vermont Wildland Fires: Investigating the Role of Antecedent Conditions and Recent Environmental Trends in Exacerbating Fire Risk and Potential in Vermont

Under a changing climate, increases in dry conditions and extreme heat events are projected to exacerbate wildfire risk in the northeastern U.S. In recent years, Vermont has observed higher annual temperatures, more frequent heatwaves, increased annual precipitation, extreme flood events, and decreased snowfall. The mechanisms through which environmental factors contribute to increased fire risk in humid environments, such as Vermont, are poorly understood. The team partnered with the National Weather Service, the Vermont Division of Forests, and the University of Vermont to investigate phenological trends and antecedent conditions influencing wildland fire risk. For the phenological analysis, from 2001 to 2023, vegetation data, phenological dates, and snow water equivalent (SWE) values were accessed from Landsat 5Thematic Mapper (TM), Landsat 7Enhanced Thematic Mapper Plus (ETM+), Landsat 8Operational Land Imager (OLI), Landsat 9OLI-2, the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Snow Data Assimilation System (SNODAS), respectively. For the antecedent condition analysis, from 2008 to 2023, soil moisture, Environmental Stress Index, wind speed, minimum relative humidity, and daily precipitation data were obtained from the Global Land Data Assimilation System (GLDAS), SERVIR, gridMET Wind, gridMET Humidity, and NClimGrid, respectively. The study found that green-up dates over the study period remain relatively stable, while snowmelt dates appear increasingly variable. Minimum relative humidity was the most significant environmental variable correlated with wildfire risk in Vermont. Results from this study will inform the National Weather Service's preparation of fire forecasts before prescribed burns and support community outreach by the Vermont Agency of Natural Resources.

Wildland Fire

Performance of Landsat-8 and Sentinel-2 Surface Reflectance Products for River Remote Sensing Retrievals of Chlorophyll-A and Turbidity

Rivers and other freshwater systems play a crucial role in ecosystems, industry, transportation and agriculture. Despite the more than 40 years of inland water observations made possible by optical remote sensing, a standardized reflectance product for inland waters is yet forthcoming. The aim of this work is to compare the standard USGS land surface reflectance product to two Landsat-8 and Sentinel-2 aquatic remote sensing reflectance products over the Amazon, Columbia and Mississippi rivers. Landsat-8 reflectance products from all three routines are then evaluated for their comparative performance in retrieving chlorophyll-a and turbidity in reference to shipborne, underway in situ validation measurements. The land surface product shows the best agreement (4 percent Mean Absolute Percent Difference) with field measurements of radiometry collected on the Amazon River and generates 36 percent higher reflectance values in the visible bands compared to aquatic methods (ACOLITE (Atmospheric Correction for OLI (Operational Land Imager) 'lite') and SeaDAS (Sea-viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System)) with larger differences between land and aquatic products observed in Sentinel-2 (0.01 per steraradian) compared to Landsat-8 (0.001 per steraradian). Choice of atmospheric correction routine can bias Landsat-8 retrievals of chlorophyll-a and turbidity by as much as 59 percent and 35 percent respectively. Using a more restrictive time window for matching in situ and satellite imagery can reduce differences by 5–31 percent depending on correction technique. This work highlights the challenges of satellite retrievals over rivers and underscores the need for future optical and biogeochemical research aimed at improving our understanding of the absorbing and scattering properties of river water and their relationships to remote sensing reflectance.

Landsat-8