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At least 1,297 records · Page 72Linked to original sources
USGS2018

Research note: Mapping spatial patterns in sewer age, material, and proximity to surface waterways to infer sewer leakage hotspots

Identifying areas where deteriorating sewer infrastructure is in close proximity to surface waterways is needed to map likely connections between sewers and streams. We present a method to estimate sewer installation year and deterioration status using historical maps of the sewer network, parcel-scale property assessment data, and pipe material. Areas where streams were likely buried into the sewer system were mapped by intersecting the historical stream network derived from a 10-m resolution digital elevation model with sewer pipe locations. Potential sewer leakage hotspots were mapped by identifying where aging sewer pipes are in close proximity (50-m) to surface waterways. Results from Pittsburgh, Pennsylvania (USA), indicated 41% of the historical stream length was lost or buried and the potential interface between sewers and streams is great. The co-location of aging sewer infrastructure (>75 years old) near stream channels suggests that 42% of existing streams are located in areas with a high potential for sewer leakage if sewer infrastructure fails. Mapping the sewer-stream interface provides an approach to better understand areas were failing sewers may contribute a disproportional amount of nutrients and other pathogens to surface waterways.

Pennsylvania↗
USGS2007

Mapping an invasive plant, Phragmites australis, in coastal wetlands using the EO-1 Hyperion hyperspectral sensor

Mapping tools are needed to document the location and extent of Phragmites australis, a tall grass that invades coastal marshes throughout North America, displacing native plant species and degrading wetland habitat. Mapping Phragmites is particularly challenging in the freshwater Great Lakes coastal wetlands due to dynamic lake levels and vegetation diversity. We tested the applicability of Hyperion hyperspectral satellite imagery for mapping Phragmites in wetlands of the west coast of Green Bay in Wisconsin, U.S.A. A reference spectrum created using Hyperion data from several pure Phragmites stands within the image was used with a Spectral Correlation Mapper (SCM) algorithm to create a raster map with values ranging from 0 to 1, where 0 represented the greatest similarity between the reference spectrum and the image spectrum and 1 the least similarity. The final two-class thematic classification predicted monodominant Phragmites covering 3.4% of the study area. Most of this was concentrated in long linear features parallel to the Green Bay shoreline, particularly in areas that had been under water only six years earlier when lake levels were 66??cm higher. An error matrix using spring 2005 field validation points (n = 129) showed good overall accuracy-81.4%. The small size and linear arrangement of Phragmites stands was less than optimal relative to the sensor resolution, and Hyperion's 30??m resolution captured few if any pure pixels. Contemporary Phragmites maps prepared with Hyperion imagery would provide wetland managers with a tool that they currently lack, which could aid attempts to stem the spread of this invasive species. ?? 2006 Elsevier Inc. All rights reserved.

Remote Sensing of Environment↗
USGS2007

Mapping moderate-scale land-cover over very large geographic areas within a collaborative framework: A case study of the Southwest Regional Gap Analysis Project (SWReGAP)

Land-cover mapping efforts within the USGS Gap Analysis Program have traditionally been state-centered; each state having the responsibility of implementing a project design for the geographic area within their state boundaries. The Southwest Regional Gap Analysis Project (SWReGAP) was the first formal GAP project designed at a regional, multi-state scale. The project area comprises the southwestern states of Arizona, Colorado, Nevada, New Mexico, and Utah. The land-cover map/dataset was generated using regionally consistent geospatial data (Landsat ETM+ imagery (1999-2001) and DEM derivatives), similar field data collection protocols, a standardized land-cover legend, and a common modeling approach (decision tree classifier). Partitioning of mapping responsibilities amongst the five collaborating states was organized around ecoregion-based "mapping zones". Over the course of 21/2 field seasons approximately 93,000 reference samples were collected directly, or obtained from other contemporary projects, for the land-cover modeling effort. The final map was made public in 2004 and contains 125 land-cover classes. An internal validation of 85 of the classes, representing 91% of the land area was performed. Agreement between withheld samples and the validated dataset was 61% (KHAT = .60, n = 17,030). This paper presents an overview of the methodologies used to create the regional land-cover dataset and highlights issues associated with large-area mapping within a coordinated, multi-institutional management framework. ?? 2006 Elsevier Inc. All rights reserved.

Remote Sensing of Environment↗
USGS2014

Mapping irrigated areas in Afghanistan over the past decade using MODIS NDVI

Agricultural production capacity contributes to food security in Afghanistan and is largely dependent on irrigated farming, mostly utilizing surface water fed by snowmelt. Because of the high contribution of irrigated crops (> 80%) to total agricultural production, knowing the spatial distribution and year-to-year variability in irrigated areas is imperative to monitoring food security for the country. We used 16-day composites of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to create 23-point time series for each year from 2000 through 2013. Seasonal peak values and time series were used in a threshold-dependent decision tree algorithm to map irrigated areas in Afghanistan for the last 14 years. In the absence of ground reference irrigated area information, we evaluated these maps with the irrigated areas classified from multiple snapshots of the landscape during the growing season from Landsat 5 optical and thermal sensor images. We were able to identify irrigated areas using Landsat imagery by selecting as irrigated those areas with Landsat-derived NDVI greater than 0.30–0.45, depending on the date of the Landsat image and surface temperature less than or equal to 310 Kelvin (36.9 ° C). Due to the availability of Landsat images, we were able to compare with the MODIS-derived maps for four years: 2000, 2009, 2010, and 2011. The irrigated areas derived from Landsat agreed well r 2 = 0.91 with the irrigated areas derived from MODIS, providing confidence in the MODIS NDVI threshold approach. The maps portrayed a highly dynamic irrigated agriculture practice in Afghanistan, where the amount of irrigated area was largely determined by the availability of surface water, especially snowmelt, and varied by as much as 30% between water surplus and water deficit years. During the past 14 years, 2001, 2004, and 2008 showed the lowest levels of irrigated area (~ 1.5 million hectares), attesting to the severe drought conditions in those years, whereas 2009, 2012 and 2013 registered the largest irrigated area (~ 2.5 million hectares) due to record snowpack and snowmelt in the region. The model holds promise the ability to provide near-real-time (by the end of the growing seasons) estimates of irrigated area, which are beneficial for food security monitoring as well as subsequent decision making for the country. While the model is developed for Afghanistan, it can be adopted with appropriate adjustments in the derived threshold values to map irrigated areas elsewhere.

Remote Sensing of Environment↗
USGS2024

Mapping and classification of volcanic deposits using multi-sensor unoccupied aerial systems

The deposits from volcanic eruptions represent the record of activity at a volcano. Identification, classification, and interpretation of these deposits are crucial to the understanding of volcanic processes and assessing hazards. However, deposits often cover large areas and can be difficult or dangerous to access, making field mapping dangerous and time-consuming. Remote sensing techniques are often used to map and identify the deposits of volcanic eruptions, though these techniques present their own trade-offs in terms of image resolution, wavelength, and observation frequency. Here, we present a new approach for mapping and classifying volcanic deposits using a multi-sensor unoccupied aerial system (UAS), and demonstrate its application on lava and tephra deposits associated with the 2018 eruption of Sierra Negra volcano (Galápagos Archipelago, Ecuador). We surveyed the study area and collected visible and thermal infrared (TIR) images. We used structure-from-motion photogrammetry to create a digital elevation model (DEM) from the visual images and calculated the solar heating rate of the surface from temperature maps based on the TIR images. We find that the solar heating rate is highest for tephra deposits and lowest for ʻaʻā lava, with pāhoehoe lava having intermediate values. This is consistent with the solar heating rate correlating to the density and particle size of the surface. The solar heating rate for the lava flow also decreases with increasing distance from the vent, consistent with an increase in density as the lava degasses. We combined the surface roughness (calculated from the DEM) and the solar heating rate of the surface to remotely classify tephra deposits and different lava morphologies. We applied both supervised and unsupervised machine learning algorithms and demonstrate that supervised methods can replicate the manual classification while the unsupervised method can identify major surface units with no ground truth information. These methods allow for remote mapping and classification at high spatial resolution (< 1 meter) of a variety of volcanic deposits, with potential for application to deposits from other processes (e.g., fluvial, glacial) and deposits on other planetary bodies.

Galápagos Archipelago, Sierra Negra volcano↗
USGS2001

Soil amplification maps for estimating earthquake ground motions in the Central US

The State Geologists of the Central United States Earthquake Consortium (CUSEC) are developing maps to assist State and local emergency managers and community officials in evaluating the earthquake hazards for the CUSEC region. The state geological surveys have worked together to produce a series of maps that show seismic shaking potential for eleven 1 X 2 degree (scale 1:250 000 or 1 in. ??? 3.9 miles) quadrangles that cover the high-risk area of the New Madrid Seismic Zone in eight states. Shear wave velocity values for the surficial materials were gathered and used to classify the soils according to their potential to amplify earthquake ground motions. Geologic base maps of surficial materials or 3-D material maps, either existing or produced for this project, were used in conjunction with shear wave velocities to classify the soils for the upper 15-30 m. These maps are available in an electronic form suitable for inclusion in the federal emergency management agency's earthquake loss estimation program (HAZUS). ?? 2001 Elsevier Science B.V. All rights reserved.

Engineering Geology↗
USGS2002

Description and comparison of geologic maps with FRAGSTATS - A spatial statistics program

FRAGSTATS is a public-domain GIS implementation of a set of spatial statistics that address a fundamental problem in GIS applications, description and comparison of maps. The spatial statistics from the 1:2,500,000-scale United States geologic map of Nevada, the central United States, and the northeastern United States quantify the differences in complexity and variability between these three geologic terranes. Nevada is defined by a large number of patches of small size and low size variability, whereas the Central area has a small number of patches with smaller relative size variability. All three areas have similar map-unit shape complexity with Nevada having the lowest. Based on the density of edges, the areas can be ranked from highest to lowest, as Nevada, Central, and Northeast. The Shannon diversity index ranks the areas from highest to lowest, as Northeast, Nevada, and Central, but the Shannon evenness index ranks them from highest to lowest, as Northeast, Central, and Nevada. These rankings may reflect the influence of folding in the Northeast and Central areas as opposed to basin and range extension in Nevada. The core areas statistic ranks the areas for spatial accuracy from highest to lowest, as Central, Northeast, and Nevada, with Northeast and Nevada being similar. For a scale comparison, the FRAGSTATS statistics quantify the increased complexity and spatial accuracy that is inherent in going from small- to larger-scale maps. For example for 1:2,500,000-1:500,000-scale maps of Nevada, respectively, the area weighted fractal dimension increase from 1.1 to 1.18, and the total core areas index almost doubles from 39.09 to 63.38. In addition, the fractal dimensions discriminate gross lithology and tectonic terranes. ?? 2002 Elsevier Science Ltd. All rights reserved.

Computers & Geosciences↗
USGS1997

Mapping of the Moon by Clementine

The "faster, cheaper, better" Clementine spacecraft mission mapped the Moon from February 19 to May 3, 1994. Global coverage was acquired in 11 spectral bandpasses from 415 to 2792 nm and at resolutions of 80-330 m/pixel; a thermal-infrared camera sampled ???20% of the surface; a high-resolution camera sampled selected areas (especially the polar regions); and a lidar altimeter mapped the large-scale topography up to latitudes of ??75??. The spacecraft was in a polar, elliptical orbit, 400-450 km periselene altitude. Periselene latitude was -28.5?? for the first month of mapping, then moved to +28.5??. NASA is supporting the archiving, systematic processing, and analysis of the ???1.8 million lunar images and other datasets. A new global positional network has been constructed from 43,000 images and ???0.5 million match points; new digital maps will facilitate future lunar exploration. In-flight calibrations now enable photometry to a high level of precision for the uv-visible CCD camera. Early science results include: (1) global models of topography, gravity, and crustal thicknesses; (2) new information on the topography and structure of multiring impact basins; (3) evidence suggestive of water ice in large permanent shadows near the south pole; (4) global mapping of iron abundances; and (5) new constraints on the Phanerozoic cratering rate of the Earth. Many additional results are expected following completion of calibration and systematic processing efforts. ?? 1997 COSPAR. Published by Elsevier Science Ltd.

Advances in Space Research↗
USGS2002

Geostatistical mapping of effluent-affected sediment distribution on the Palos Verdes shelf

Geostatistical techniques were used to study the spatial continuity of the thickness of effluent-affected sediment in the offshore Palos Verdes Margin area. The thickness data were measured directly from cores and indirectly from high-frequency subbottom profiles collected over the Palos Verdes Margin. Strong spatial continuity of the sediment thickness data was identified, with a maximum range of correlation in excess of 1.4 km. The spatial correlation showed a marked anisotropy, and was more than twice as continuous in the alongshore direction as in the cross-shelf direction. Sequential indicator simulation employing models fit to the thickness data variograms was used to map the distribution of the sediment, and to quantify the uncertainty in those estimates. A strong correlation between sediment thickness data and measurements of the mass of the contaminant p,p???-DDE per unit area was identified. A calibration based on the bivariate distribution of the thickness and p,p???-DDE data was applied using Markov-Bayes indicator simulation to extend the geostatistical study and map the contamination levels in the sediment. Integrating the map grids produced by the geostatistical study of the two variables indicated that 7.8 million m3 of effluent-affected sediment exist in the map area, containing approximately 61-72 Mg (metric tons) of p,p???-DDE. Most of the contaminated sediment (about 85% of the sediment and 89% of the p,p???-DDE) occurs in water depths < 100 m. The geostatistical study also indicated that the samples available for mapping are well distributed and the uncertainty of the estimates of the thickness and contamination level of the sediments is lowest in areas where the contaminated sediment is most prevalent. ?? 2002 Elsevier Science Ltd. All rights reserved.

Continental Shelf Research↗
USGS2002

High-resolution aeromagnetic mapping of volcanic terrain, Yellowstone National Park

High-resolution aeromagnetic data acquired over Yellowstone National Park (YNP) show contrasting patterns reflecting differences in rock composition, types and degree of alteration, and crustal structures that mirror the variable geology of the Yellowstone Plateau. The older, Eocene, Absaroka Volcanic Supergroup, a series of mostly altered, andesitic volcanic and volcaniclastic rocks partially exposed in mountains on the eastern margin of YNP, produces high-amplitude, positive magnetic anomalies, strongly contrasting with the less magnetic, younger, latest Cenozoic, Yellowstone Plateau Group, primarily a series of fresh and variably altered rhyolitic rocks covering most of YNP. The Yellowstone caldera is the centerpiece of the Yellowstone Plateau; part of its boundary can be identified on the aeromagnetic map as a series of discontinuous, negative magnetic anomalies that reflect faults or zones along which extensive hydrothermal alteration is localized. The large-volume rhyolitic ignimbrite deposits of the 0.63-Ma Lava Creek Tuff and the 2.1-Ma Huckleberry Ridge Tuff, which are prominent lithologies peripheral to the Yellowstone caldera, produce insignificant magnetic signatures. A zone of moderate amplitude positive anomalies coincides with the mapped extent of several post-caldera rhyolitic lavas. Linear magnetic anomalies reflect the rectilinear fault systems characteristic of resurgent domes in the center of the caldera. Peripheral to the caldera, the high-resolution aeromagnetic map clearly delineates flow unit boundaries of pre- and post-caldera basalt flows, which occur stratigraphically below the post-caldera rhyolitic lavas and are not exposed extensively at the surface. All of the hot spring and geyser basins, such as Norris, Upper and Lower Geyser Basins, West Thumb, and Gibbon, are associated with negative magnetic anomalies, reflecting hydrothermal alteration that has destroyed the magnetic susceptibility of minerals in the volcanic rocks. Within Yellowstone Lake, which is mostly within the Yellowstone caldera, aeromagnetic lows also are associated with known hydrothermal activity in the lake. Many of the magnetic lows extend beyond the areas of alteration and hot springs, suggesting a more extensive currently active or fossil hydrothermal system than is currently mapped. Steep magnetic gradients, suggesting faults or fractures, bound the magnetic lows. This implies that fractures localize the hot springs. Magnetic gradient trends reflect the mapped Basin and Range structural trends of north and northwest, as well as northeasterly trends that parallel the regional trend of the Snake River Plain and the track of the Yellowstone hot spot which follow the Precambrian structural grain. These trends are found both at small scales such as in hydrothermal basins and at more regional fault scales, which suggests that the regional stress field and reactivated older structures may exert some control on localization of hydrothermal activity. ?? 2002 Elsevier Science B.V. All rights reserved.

Journal of Volcanology and Geothermal Research↗
USGS2000

Testing methods to produce landscape-scale presettlement vegetation maps from the U.S. public land survey records

The U.S. Public Land Survey (PLS) notebooks are one of the best records of the pre-European settlement landscape and are widely used to recreate presettlement vegetation maps. The purpose of this study was to evaluate the relative ability of several interpolation techniques to map this vegetation, as sampled by the PLS surveyors, at the landscape level. Field data from Sylvania Wilderness Area, MI (U.S.A.), sampled at the same scale as the PLS data, were used for this test. Sylvania is comprised of a forested landscape similar to that present during presettlement times. Data were analyzed using two Arc/Info interpolation processes and indicator kriging. The resulting maps were compared to a 'correct' map of Sylvania, which was classified from aerial photographs. We found that while the interpolation methods used accurately estimated the relative forest composition of the landscape and the order of dominance of different vegetation types, they were unable to accurately estimate the actual area occupied by each vegetation type. Nor were any of the methods we tested able to recreate the landscape patterns found in the natural landscape. The most likely cause for these inabilities is the scale at which the field data (and hence the PLS data) were recorded. Therefore, these interpolation methods should not be used with the PLS data to recreate pre-European settlement vegetation at small scales (e.g., less than several townships or areas < 104 ha). Recommendations are given for ways to increase the accuracy of these vegetation maps.

Landscape Ecology↗
USGS2003

Survey methods for assessing land cover map accuracy

The increasing availability of digital photographic materials has fueled efforts by agencies and organizations to generate land cover maps for states, regions, and the United States as a whole. Regardless of the information sources and classification methods used, land cover maps are subject to numerous sources of error. In order to understand the quality of the information contained in these maps, it is desirable to generate statistically valid estimates of accuracy rates describing misclassification errors. We explored a full sample survey framework for creating accuracy assessment study designs that balance statistical and operational considerations in relation to study objectives for a regional assessment of GAP land cover maps. We focused not only on appropriate sample designs and estimation approaches, but on aspects of the data collection process, such as gaining cooperation of land owners and using pixel clusters as an observation unit. The approach was tested in a pilot study to assess the accuracy of Iowa GAP land cover maps. A stratified two-stage cluster sampling design addressed sample size requirements for land covers and the need for geographic spread while minimizing operational effort. Recruitment methods used for private land owners yielded high response rates, minimizing a source of nonresponse error. Collecting data for a 9-pixel cluster centered on the sampled pixel was simple to implement, and provided better information on rarer vegetation classes as well as substantial gains in precision relative to observing data at a single-pixel.

Environmental and Ecological Statistics↗
USGS2001

Io in the near infrared: Near-Infrared Mapping Spectrometer (NIMS) results from the Galileo flybys in 1999 and 2000

Galileo's Near-Infrared Mapping Spectrometer (NIMS) observed Io during the spacecraft's three flybys in October 1999, November 1999, and February 2000. The observations, which are summarized here, were used to map the detailed thermal structure of active volcanic regions and the surface distribution of SO 2 and to investigate the origin of a yet unidentified compound showing an absorption feature at ∼1 μm. We present a summary of the observations and results, focusing on the distribution of thermal emission and of SO 2 deposits. We find high eruption temperatures, consistent with ultramafic volcanism, at Pele. Such temperatures may be present at other hot spots, but the hottest areas may be too small for those temperatures to be detected at the spatial resolution of our observations. Loki is the site of frequent eruptions, and the low thermal emission may represent lavas cooling on the caldera's surface or the cooling crust of a lava lake. High-resolution spectral observations of Emakong caldera show thermal emission and SO 2 within the same pixels, implying that patches of SO 2 frost and patches of cooling lavas or sulfur flows are present within a few kilometers from one another. Thermal maps of Prometheus and Amirani show that these two hot spots are characterized by long lava flows. The thermal profiles of flows at both locations are consistent with insulated flows, with the Amirani flow field having more breakouts of fresh lava along its length. Prometheus and Amirani each show a white ring at visible wavelengths, while SO 2 distribution maps show that the highest concentration of SO 2 in both ring deposits lies outside the white portion. Visible measurements at high phase angles show that the white deposit around Prometheus extends into the SO 2 ring. This suggests that the deposits are thin and that compositional or grain size variations may occur in the radial direction. SO 2 mapping of the Chaac region shows that the interior of a caldera adjacent to Chaac has almost pure SO 2 . The deposit appears to be topographically controlled, suggesting a possible origin by liquid flow.

Journal of Geophysical Research E: Planets↗
USGS2010

Movie‐maps of low‐latitude magnetic storm disturbance

We present 29 movie‐maps of low‐latitude horizontal‐intensity magnetic disturbance for the years 1999–2006: 28 recording magnetic storms and 1 magnetically quiescent period. The movie‐maps are derived from magnetic vector time series data collected at up to 25 ground‐based observatories. Using a technique similar to that used in the calculation of Dst , a quiet time baseline is subtracted from the time series from each observatory. The remaining disturbance time series are shown in a polar coordinate system that accommodates both Earth rotation and the universal time dependence of magnetospheric disturbance. Each magnetic storm recorded in the movie‐maps is different. While some standard interpretations about the storm time equatorial ring current appear to apply to certain moments and certain phases of some storms, the movie‐maps also show substantial variety in the local time distribution of low‐latitude magnetic disturbance, especially during storm commencements and storm main phases. All movie‐maps are available at the U.S. Geological Survey Geomagnetism Program Web site ( http://geomag.usgs.gov ).

Space Weather↗
USGS2010

Geohydrologic use of lithofacies maps in glaciated areas

Subsurface conditions may differ considerably from conditions indicated by surficial geologic maps, particularly in glaciated areas. Therefore, it is advantageous to use a series of lithofacies maps as a sequence of overlays plotted on transparent paper. Such maps permit direct visual determination of the lithology and areal extent of aquifers and indicate areas of possible stream losses or gains. They indicate areas and boundaries of confining layers and, in some places, they may be used to delineate areas of water-table and artesian conditions. They are especially useful in determining buried channels in glaciated areas. The porosity of rock units making up an aquifer may be plotted on a lithofacies map, and the product of the volume of each lithologic type and the porosity provides an estimate of the total water in storage. In addition, if the water-bearing properties are known, the quantity of water moving through an aquifer and the amount available to wells may be determined. Lithofacies maps also aid in the explanation of complex changes in water quality.

Water Resources Research↗
USGS2018

Enhancement and integration of airborne gamma-ray spectrometric and Landsat imagery for regolith mapping — Cape York Peninsula

Airborne gamma-ray spectrometric data (400-m line spacing), gathered for the National Geoscience Mapping Accord North Queensland Project, has proved invaluable for differentiating regolith types based on their potassium, thorium and uranium signatures. The ability of the gamma-ray signal to penetrate the vegetation cover and as much as 40 cm below the surface was a considerable advantage in North Queensland, where traditional mapping techniques are hindered by the thick vegetation cover and where deeply weathered sandy soils frequently mask underlying geology. Two image-processing techniques were used to enhance the gamma-ray data and integrate them with Landsat Thematic Mapper (TM) data. Firstly, a sun-angle illuminated high-pass filtered component (hillshade) of the gamma-ray image was added to a three-band false-colour composite image of the corrected gamma-ray data. The hillshade component highlighted local changes in the gamma-ray signal which related to changes in regolith materials and lithology, and sharpened boundaries associated with geomorphic features. Secondly, the gamma-ray image was integrated (pixel by pixel) with the high-frequency component of the corresponding TM band 5 scene. This allowed the imagery to be interpreted in a geomorphological and structural context. Broad lithological divisions and structural domains were identified in the imagery, but most of the variation within these groups relates to the regolith cover and to geomorphic features in the landscape. Subtle variations in lithology were effectively interpreted only when the responses of the regolith cover are known. The gamma-ray imagery provided an insight into the weathering and geomorphic history of the region. In addition, the imagery can also be interpreted as a ‘geomorphic activity map’, separating stable landforms with deep weathering from younger landforms with active erosion and stripping of the surficial cover. This allows past and present geomorphic processes to be interpreted from the imagery, which in turn provides more informed extrapolation of field results and prediction of regolith types. The imagery was highly useful for basement and regolith mapping. There is considerable potential for assisting with interpretation of both stream-sediment geochemical data and environmental studies, since the resulting imagery effectively maps the distribution of sediments in the landscape, and identifies areas of erosion and land degradation.

Queensland↗
USGS2024

Mapping eelgrass cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery

Two eelgrass ( Zostera marina ) maps of Izembek Lagoon, Alaska, were generated by first creating maps of spectrally unique classes from each of two Sentinel-2 satellite images collected on July 1, 2016, and August 14, 2020, then attributing the spectral classes with information about eelgrass conditions based on field data. Maps depicting various eelgrass metrics, such as percent cover and modeled biomass, were generated using summaries of the ground data that spatially intersected each spectral class. Comparisons between the 2016 and 2020 Sentinel-2 maps of eelgrass distributional extent, as well as a 2006 Landsat map, indicated that areas where eelgrass presence may have declined between 2006 and 2020 were most prevalent in the central part Izembek Lagoon, while areas of possible biomass decline were more prevalent in the southern part between 2016 and 2020. Monitoring eelgrass conditions at Izembek Lagoon with satellite imagery and concurrent ground data provides capabilities for making comparisons over time, but the influences of tide levels, growing season phenology, and spatiotemporal co-registration accuracy should be considered when designing and interpreting change detection analyses.

Alaska↗
USGS2005

Automated mapping of hammond's landforms

We automated a method for mapping Hammond's landforms over large landscapes using digital elevation data. We compared our results against Hammond's published landform maps, derived using manual interpretation procedures. We found general agreement in landform patterns mapped by the manual and the automated approaches, and very close agreement in characterization of local topographic relief. The two approaches produced different interpretations of intermediate landforms, which relied upon quantification of the proportion of landscape having gently sloping terrain. This type of computation is more efficiently and consistently applied by computer than human. Today's ready access to digital data and computerized geospatial technology provides a good foundation for mapping terrain features, but the mapping criteria guiding manual techniques in the past may not be appropriate for automated approaches. We suggest that future efforts center on the advantages offered by digital advancements in refining an approach to better characterize complex landforms.

IEEE Geoscience and Remote Sensing Letters↗