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Conifer health classification for Colorado, 2008

Colorado has undergone substantial changes in forests due to urbanization, wildfires, insect-caused tree mortality, and other human and environmental factors. The U.S. Geological Survey Rocky Mountain Geographic Science Center evaluated and developed a methodology for applying remotely-sensed imagery for assessing conifer health in Colorado. Two classes were identified for the purposes of this study: healthy and unhealthy (for example, an area the size of a 30- x 30-m pixel with 20 percent or greater visibly dead trees was defined as ?unhealthy?). Medium-resolution Landsat 5 Thematic Mapper imagery were collected. The normalized, reflectance-converted, cloud-filled Landsat scenes were merged to form a statewide image mosaic, and a Normalized Difference Vegetation Index (NDVI) and Renormalized Difference Infrared Index (RDII) were derived. A supervised maximum likelihood classification was done using the Landsat multispectral bands, the NDVI, the RDII, and 30-m U.S. Geological Survey National Elevation Dataset (NED). The classification was constrained to pixels identified in the updated landcover dataset as coniferous or mixed coniferous/deciduous vegetation. The statewide results were merged with a separate health assessment of Grand County, Colo., produced in late 2008. Sampling and validation was done by collecting field data and high-resolution imagery. The 86 percent overall classification accuracy attained in this study suggests that the data and methods used successfully characterized conifer conditions within Colorado. Although forest conditions for Lodgepole Pine (Pinus contorta) are easily characterized, classification uncertainty exists between healthy/unhealthy Ponderosa Pine (Pinus ponderosa), Pi?on (Pinus edulis), and Juniper (Juniperus sp.) vegetation. Some underestimation of conifer mortality in Summit County is likely, where recent (2008) cloud-free imagery was unavailable. These classification uncertainties are primarily due to the spatial and temporal resolution of Landsat, and of the NLCD derived from this sensor. It is believed that high- to moderate-resolution multispectral imagery, coupled with field data, could significantly reduce the uncertainty rates. The USGS produced a four-county follow-up conifer health assessment using high-resolution RapidEye remotely sensed imagery and field data collected in 2009.

Scientific Investigations Map

Relating nutrient and herbicide fate with landscape features and characteristics of 15 subwatersheds in the Choptank River watershed

Excess nutrients and agrochemicals from non-point sources contribute to water quality impairment in the Chesapeake Bay watershed and their loading rates are related to land use, agricultural practices, hydrology, and pollutant fate and transport processes. In this study, monthly baseflow stream samples from 15 agricultural subwatersheds of the Choptank River in Maryland USA (2005 to 2007) were characterized for nutrients, herbicides, and herbicide transformation products. High-resolution digital maps of land use and forested wetlands were derived from remote sensing imagery. Examination of landscape metrics and water quality data, partitioned according to hydrogeomorphic class, provided insight into the fate, delivery, and transport mechanisms associated with agricultural pollutants. Mean Nitrate-N concentrations (4.9 mg/L) were correlated positively with percent agriculture (R 2 = 0.56) and negatively with percent forest (R 2 = 0.60). Concentrations were greater ( p = 0.0001) in the well-drained upland (WDU) hydrogeomorphic region than in poorly drained upland (PDU), reflecting increased denitrification and reduced agricultural land use intensity in the PDU landscape due to the prevalence of hydric soils. Atrazine and metolachlor concentrations (mean 0.29 μg/L and 0.19 μg/L) were also greater ( p = 0.0001) in WDU subwatersheds than in PDU subwatersheds. Springtime herbicide concentrations exhibited a strong, positive correlation (R 2 = 0.90) with percent forest in the WDU subwatersheds but not in the PDU subwatersheds. In addition, forested riparian stream buffers in the WDU were more prevalent than in the PDU where forested patches are typically not located near streams, suggesting an alternative delivery mechanism whereby volatilized herbicides are captured by the riparian forest canopy and subsequently washed off during rainfall. Orthophosphate, CIAT (6-chloro- N -(1-methylethyl)-1,3,5-triazine-2,4-diamine), CEAT (6-chloro- N -ethyl-1,3,5-triazine-2,4-diamine), and MESA (2-[(2-ethyl-6-methylphenyl) (2-methoxy-1-methylethyl)amino]-2-oxoethanesulfonic acid) were also analyzed. These findings will assist efforts in targeting implementation of conservation practices to the most environmentally-critical areas within watersheds to achieve water quality improvements in a cost-effective manner.

Delaware, Maryland

Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams

In mountain headwater streams, the quality and resilience of summer cold-water habitat is generally regulated by stream discharge, longitudinal stream channel connectivity and groundwater exchange. These critical hydrologic processes are thought to be influenced by the stream corridor bedrock contact depth (sediment thickness), a parameter often inferred from sparse hillslope borehole information, piezometer refusal and remotely sensed data. To investigate how local bedrock depth might control summer stream temperature and channel disconnection (dewatering) patterns, we measured stream corridor bedrock depth by collecting and interpreting 191 passive seismic datasets along eight headwater streams in Shenandoah National Park (Virginia, USA). In addition, we used multi-year stream temperature and streamflow records to calculate several baseflow-related metrics along and among the study streams. Finally, comprehensive visual surveys of stream channel dewatering were conducted in 2016, 2019 and 2021 during summer low flow conditions (124 total km of stream length). We found that measured bedrock depths along the study streams were not well-characterized by soils maps or an existing global-scale geologic dataset where the latter overpredicted measured depths by 12.2 m (mean) or approximately four times the average bedrock depth of 2.9 m. Half of the eight study stream corridors had an average bedrock depth of less than 2 m. Of the eight study streams, Staunton River had the deepest average bedrock depth (3.4 m), the coldest summer temperature profiles and substantially higher summer baseflow indices compared to the other study steams. Staunton River also exhibited paired air and water annual temperature signals suggesting deeper groundwater influence, and the stream channel did not dewater in lower sections during any baseflow survey. In contrast, Paine Run and Piney River did show pronounced, patchy channel dewatering, with Paine Run having dozens of discrete dry channel sections ranging from 1 to greater than 300 m in length. Stream dewatering patterns were apparently influenced by a combination of discrete deep bedrock (20+ m) features and more subtle sediment thickness variation (1–4 m) depending on local stream valley hydrogeology. In combination, these unique datasets show the first large-scale empirical support for existing conceptual models of headwater stream disconnection based on spatially variable underflow capacity and shallow groundwater supply.

Virginia

Barkley Canyon gas hydrates: A synthesis based on two decades of seafloor observation and remote sensing

Barkley Canyon is one of the few known sites worldwide with the occurrence of thermogenic gas seepage and formation of structure-II and structure-H gas hydrate mounds on the seafloor. This site is the location of continuous seafloor monitoring as part of the Ocean Networks Canada (ONC) cabled observatory off the west coast off Vancouver Island, British Columbia, Canada. We combine repeat remotely operated vehicle (ROV) seafloor video observations, mapping with an autonomous underwater vehicle (AUV), ship-, ROV-, and AUV-based identification of gas flares, as well as seismic and Chirp data to investigate the distribution of fluid migration pathways. Geologically, the site with the prominent gas hydrate mounds and associated fluid seepage is covering an area of ∼0.15 km 2 and is situated on a remnant of a rotated fault block that had slipped off the steep flanks of the north-east facing canyon wall. The gas hydrate mounds, nearly constant in dimension over the entire observation period, are associated with gas and oil seepage and surrounded by debris of chemosynthetic communities and authigenic carbonate. The formation of gas hydrate at and near the seafloor requires additional accommodation space created by forming blisters at the seafloor that displace the regular sediments. An additional zone located centrally on the rotated fault block with more diffuse seepage (∼0.02 km 2 in extent) has been identified with no visible mounds, but with bacterial mats, small carbonate concretions, and clam beds. Gas venting is seen acoustically in the water column up to a depth of ∼300 m. However, acoustic water-column imaging during coring and ROV dives showed rising gas bubbles to much shallower depth, even <50 m, likely a result of degassing of rising oil droplets, which themselves cannot be seen acoustically. Combining all observations, the location of the gas hydrate mounds is controlled by a combination of fault-focused fluid migration from a deeper reservoir and fluid seepage along more permeable strata within the rotated slope block. Fluids must be provided continuously to allow the sustained presence of the gas hydrate mounds at the seafloor.

Barkley Canyon

Towards monitoring land-cover and land-use changes at a global scale: the global land survey 2005

Land cover is a critical component of the Earth system, infl uencing land-atmosphere interactions, greenhouse gas fl uxes, ecosystem health, and availability of food, fi ber, and energy for human populations. The recent Integrated Global Observations of Land (IGOL) report calls for the generation of maps documenting global land cover at resolutions between 10m and 30m at least every fi ve years (Townshend et al., in press). Moreover, despite 35 years of Landsat observations, there has not been a unifi ed global analysis of land-cover trends nor has there been a global assessment of land-cover change at Landsat-like resolution. Since the 1990s, the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) have supported development of data sets based on global Landsat observations (Tucker et al., 2004). These land survey data sets, usually referred to as GeoCover &trade;, provide global, orthorectifi ed, typically cloud-free Landsat imagery centered on the years 1975, 1990, and 2000, with a preference for leaf-on conditions. Collectively, these data sets provided a consistent set of observations to assess land-cover changes at a decadal scale. These data are freely available via the Internet from the USGS Center for Earth Resources Observation and Science (EROS) (see http://earthexplorer.usgs.gov or http://glovis.usgs.gov). This has resulted in unprecedented downloads of data, which are widely used in scientifi c studies of land-cover change (e.g., Boone et al., 2007; Harris et al., 2005; Hilbert, 2006; Huang et al. 2007; Jantz et al., 2005, Kim et al., 2007; Leimgruber, 2005; Masek et al., 2006). NASA and USGS are continuing to support land-cover change research through the development of GLS2005 - an additional global Landsat assessment circa 20051 . Going beyond the earlier initiatives, this data set will establish a baseline for monitoring changes on a 5-year interval and will pave the way toward continuous global land-cover monitoring at Landsat-like resolution in the next decade.

Photogrammetric Engineering and Remote Sensing

The global Landsat archive: Status, consolidation, and direction

New and previously unimaginable Landsat applications have been fostered by a policy change in 2008 that made analysis-ready Landsat data free and open access. Since 1972, Landsat has been collecting images of the Earth, with the early years of the program constrained by onboard satellite and ground systems, as well as limitations across the range of required computing, networking, and storage capabilities. Rather than robust on-satellite storage for transmission via high bandwidth downlink to a centralized storage and distribution facility as with Landsat-8, a network of receiving stations, one operated by the U.S. government, the other operated by a community of International Cooperators (ICs), were utilized. ICs paid a fee for the right to receive and distribute Landsat data and over time, more Landsat data was held outside the archive of the United State Geological Survey (USGS) than was held inside, much of it unique. Recognizing the critical value of these data, the USGS began a Landsat Global Archive Consolidation (LGAC) initiative in 2010 to bring these data into a single, universally accessible, centralized global archive, housed at the Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. The primary LGAC goals are to inventory the data held by ICs, acquire the data, and ingest and apply standard ground station processing to generate an L1T analysis-ready product. As of January 1, 2015 there were 5,532,454 images in the USGS archive. LGAC has contributed approximately 3.2 million of those images, more than doubling the original USGS archive holdings. Moreover, an additional 2.3 million images have been identified to date through the LGAC initiative and are in the process of being added to the archive. The impact of LGAC is significant and, in terms of images in the collection, analogous to that of having had two additional Landsat-5 missions. As a result of LGAC, there are regions of the globe that now have markedly improved Landsat data coverage, resulting in an enhanced capacity for mapping, monitoring change, and capturing historic conditions. Although future missions can be planned and implemented, the past cannot be revisited, underscoring the value and enhanced significance of historical Landsat data and the LGAC initiative. The aim of this paper is to report the current status of the global USGS Landsat archive, document the existing and anticipated contributions of LGAC to the archive, and characterize the current acquisitions of Landsat-7 and Landsat-8. Landsat-8 is adding data to the archive at an unprecedented rate as nearly all terrestrial images are now collected. We also offer key lessons learned so far from the LGAC initiative, plus insights regarding other critical elements of the Landsat program looking forward, such as acquisition, continuity, temporal revisit, and the importance of continuing to operationalize the Landsat program.

Remote Sensing of Environment

On-orbit calibration and performance of the EMIT imaging spectrometer

The Earth surface Mineral dust source InvesTigation (EMIT) is a remote visible to shortwave infrared (VSWIR) imaging spectrometer that has been operating onboard the International Space Station since July 2022. This article describes EMIT's on-orbit spectroradiometric calibration and validation. Accurate spectroscopy is vital to achieve consistent mapping results with orbital imaging spectrometers. EMIT takes a unique approach to this challenge, with just six optical elements, no shutter, and no onboard calibration systems. Its simple design focuses on uniformity and stability to enable vicarious spectroradiometric calibration. Our experiments demonstrate that this approach is successful, approaching the fidelity of manual field spectroscopy in some cases, and enabling new and more accurate products across diverse Earth science disciplines. EMIT achieves several notable firsts for an instrument of its class. It demonstrates successful on-orbit adjustments of Focal Plane Array (FPA) alignment with sub-micron precision. It offers spectral uniformity better than 98%. Optical artifacts in the measurement channels are at least three orders of magnitude below the primary solar-reflected surface signals. Its noise performance enables percent-level discrimination in the depths of mineral absorption features. In these aspects, EMIT satisfies the stringent performance needs for the next generation of VSWIR imaging spectrometers to observe the Earth's ecosystems, geology , and water resources.

Remote Sensing of Environment

Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)

Forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30 m spatial resolution using Web-Enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) (http://landsat.usgs.gov/WELD.php). The approach related multi-temporal WELD metrics and expert-derived training data for forest cover loss and bare ground gain through a decision tree classification algorithm. Forest cover loss was reported at state and ecoregional scales, and the identification of core forests' absent of change was made and verified using LiDAR data from the GLAS (Geoscience Laser Altimetry System) instrument. Bare ground gain correlated with population change for large metropolitan statistical areas (MSAs) outside of desert or semi-desert environments. GoogleEarth™ time-series images were used to validate the products. Mapped forest cover loss totaled 53,084 km2 and was found to be depicted conservatively, with a user's accuracy of 78% and a producer's accuracy of 68%. Excluding errors of adjacency, user's and producer's accuracies rose to 93% and 89%, respectively. Mapped bare ground gain equaled 5974 km2 and nearly matched the estimated area from the reference (GoogleEarth™) classification; however, user's (42%) and producer's (49%) accuracies were much less than those of the forest cover loss product. Excluding errors of adjacency, user's and producer's accuracies rose to 62% and 75%, respectively. Compared to recent 2001–2006 USGS National Land Cover Database validation data for forest loss (82% and 30% for respective user's and producer's accuracies) and urban gain (72% and 18% for respective user's and producer's accuracies), results using a single CONUS-scale model with WELD data are promising and point to the potential for national-scale operational mapping of key land cover transitions. However, validation results highlighted limitations, some of which can be addressed by improving training data, creating a more robust image feature space, adding contemporaneous Landsat 5 data to the inputs, and modifying definition sets to account for differences in temporal and spatial observational scales. The presented land cover extent and change data are available via the official WELD website (ftp://weldftp.cr.usgs.gov/CONUS_5Y_LandCover/ftp://weldftp.cr.usgs.gov/CONUS_5Y_LandCover/).

Remote Sensing of Environment

Predicting sea-level rise vulnerability of terrestrial habitat and wildlife of the Northwestern Hawaiian Islands

If current climate change trends continue, rising sea levels may inundate low-lying islands across the globe, placing island biodiversity at risk. Recent models predict a rise of approximately one meter (1 m) in global sea level by 2100, with larger increases possible in areas of the Pacific Ocean. Pacific Islands are unique ecosystems home to many endangered endemic plant and animal species. The Northwestern Hawaiian Islands (NWHI), which extend 1,930 kilometers (km) beyond the main Hawaiian Islands, are a World Heritage Site and part of the Papahanaumokuakea Marine National Monument. These NWHI support the largest tropical seabird rookery in the world, providing breeding habitat for 21 species of seabirds, 4 endemic land bird species and essential foraging, breeding, or haul-out habitat for other resident and migratory wildlife. In recent years, concern has grown about the increasing vulnerability of the NWHI and their wildlife populations to changing climatic patterns, particularly the uncertainty associated with potential impacts from global sea-level rise (SLR) and storms. In response to the need by managers to adapt future resource protection strategies to climate change variability and dynamic island ecosystems, we have synthesized and down scaled analyses for this important region. This report describes a 2-year study of a remote northwestern Pacific atoll ecosystem and identifies wildlife and habitat vulnerable to rising sea levels and changing climate conditions. A lack of high-resolution topographic data for low-lying islands of the NWHI had previously precluded an extensive quantitative model of the potential impacts of SLR on wildlife habitat. The first chapter (chapter 1) describes the vegetation and topography of 20 islands of Papahanaumokuakea Marine National Monument, the distribution and status of wildlife populations, and the predicted impacts for a range of SLR scenarios. Furthermore, this chapter explores the potential effects of SLR on wildlife breeding habitats for each island. The subsequent chapter (chapter 2) details a study of the Laysan Island ecosystem, describing a quantitative model that incorporates SLR, storm wave, and rising groundwater inundation. Wildlife, storm, and oceanographic data allowed for an assessment of the phenological and spatial vulnerability of Laysan Island's breeding bird species to SLR and storms. Using remote sensing and geospatial techniques, we estimated topography, classified vegetation, modeled SLR, and evaluated a range of climate change scenarios. On the basis of high-resolution airborne data collected during 2010-11 (root-mean-squared error = 0.05-0.18 m), we estimated the maximum elevation of 20 individual islands extending from Kure Atoll to French Frigate Shoals (range: 1.8-39.7 m) and computed the mean elevation (1.7 m, standard deviation 1.1 m) across all low-lying islands. We also analyzed general climate models to describe rainfall and temperature scenarios expected to influence adaptation of some plants and animals for this region. Outcomes for the NWHI predicted an increase in temperature of 1.8-2.6 degrees Celsius (&deg;C) and an annual decrease in precipitation of 24.7-76.3 millimeters (mm) across the NWHI by 2100. Our models of passive SLR (excluding wave-driven effects, erosion, and accretion) showed that approximately 4 percent of the total land area in the NWHI will be lost with scenarios of +1.0 m of SLR and 26 percent will be lost with +2.0 m of SLR. Some atolls are especially vulnerable to SLR. For example, at Pearl and Hermes Atoll our analysis indicated substantial habitat losses with 43 percent of the land area inundated at +1.0 m SLR and 92 percent inundated at +2.0 m SLR. Across the NWHI, seven islands will be completely submerged with +2.0 m SLR. The limited global ranges of some tropical nesting birds make them particularly vulnerable to climate change impacts in the NWHI. Climate change scenarios and potential SLR impacts presented here emphasize the need for early climate change adaptation and mitigation planning, especially for species with limited breeding distributions and/or ranges restricted primarily to the low-lying NWHI: Cyperus pennatiformis var. bryanii , Black-footed Albatross ( Phoebastria nigripes ), Laysan Albatross ( P. immutabilis ), Bonin Petrel ( Pterodroma hypoleuca ), Gray-backed Tern ( Onychoprion lunatus ), Laysan Teal ( Anas laysanensis ), Laysan Finch ( Telespiza cantans ), and Hawaiian monk seal ( Monachus schauinslandi ). Furthermore, SLR scenarios that include the effects of wave dynamics and groundwater rise may indicate amplified vulnerability to climate change driven habitat loss on low-lying islands. In chapter 2, we incorporated the combined effects of SLR, dynamic wave-driven inundation, and rising groundwater in a quantitative study specifically for the Laysan Island ecosystem. This is the first hydrodynamic model to simulate the combined impacts of SLR and wave-driven inundation in the NWHI. We developed a high-resolution digital elevation model (mean vertical accuracy of 0.32 m) for the island. Then using recent satellite imagery, geospatial models, and historical oceanographic, storm, and biological data we estimated potential inundation extent, habitat loss, and wildlife population impacts for a range of potential SLR scenarios (0.00, +0.50, +1.00, +1.50, and +2.00 m) that may occur over the next century. Additionally, we estimated the carrying capacity of Laysan Island for five species based on the available population monitoring data and described how potential losses in nesting habitat could influence population dynamics for Black-footed Albatross, Laysan Albatross, Red-footed Booby (Sula sula), Laysan Teal, and Laysan Finch. For some other seabird populations (Masked Booby, S. dactylatra ; Brown Booby, S. leucogaster ; Great Frigatebird, Fregata minor ; and Sooty Tern, Onychoprion fuscata ), we used recent colony distribution data, land cover maps, and nesting behavior to estimate potential losses of nesting habitat from SLR and wave-driven inundation. We observed far greater potential impacts of SLR to wildlife with the dynamic wave-driven modeling approach than with the passive modeling approach. Depending on SLR scenario and coastal orientation, during storms under a +2.00 m SLR scenario, the wave-driven inundation model predicted three times more inundation than the passive model (17.2 percent of total terrestrial area versus 4.6 percent, respectively). Large-wave events generally added 1 m of water height to passive inundation surfaces, therefore our dynamic models (during storm events) forecasted comparable inundation extents earlier than passive models. Although wave-driven water levels were highest in the northwest quadrant of Laysan Island, the greatest extent of inundation occurred in the southeast where coastal dunes less than 3 m above mean sea level provide little protection from wave-driven inundation. When wave-driven inundation was included in the SLR model for Laysan Island greater nesting habitat loss and potential impacts on wildlife population dynamics were predicted. The consequences of habitat loss due to SLR may be worse for species with colonies in the wave-exposed coastal zones (for example, Black-footed Albatross) and for populations already near the island's carrying capacity (for example, Laysan Teal). Species whose peak incubation and chick-rearing periods coincide with seasonally high wave heights also will be increasingly vulnerable, especially those species nesting on the ground in areas vulnerable to inundation, such as Gray-backed Tern and Black-footed Albatross. Other species that have space for population growth, or are not restricted to a narrow range of habitat types on Laysan (for instance, Sooty Terns), may be less sensitive to habitat loss from SLR over the next century. Our assessments of inundation risk, habitat loss, and wildlife species vulnerability synthesize current knowledge about individual islands and contribute to a broader understanding of the impacts of inundation from SLR and storm-induced waves. Yet, most NWHI and their bird populations lack monitoring data to evaluate adaptations to and impacts of climate change. Exceptions include some data sets from long-term monitoring of wildlife populations, tides, or weather at French Frigate Shoals, Laysan Island, and Midway Atoll. These data sets are potentially valuable baselines, which could be informative for adaptive learning (integrating management and science) to predict, adapt, and mitigate the effects of climate change on NWHI wildlife in the future. This study provides the first quantitative vulnerability assessment for all of the low-lying NWHI, and results identify biological communities, locales, and resident endangered species of Papahanaumokuakea Marine National Monument expected to be at risk from SLR. This report is also intended as a reference for managers and conservation planners, a tool to identify and potentially reduce uncertainty, and a starting place for developing climate change monitoring priorities and future scientific studies.

Hawai'i