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At least 1,477 records · Page 82Linked to original sources

Estimating occupancy probability of moose using hunter survey data

Monitoring rare species can be difficult, especially across large spatial extents, making conventional methods of population monitoring costly and logistically challenging. Citizen science has the potential to produce observational data across large areas that can be used to monitor wildlife distributions using occupancy models. We used citizen science (i.e., hunter surveys) to facilitate monitoring of moose ( Alces alces ) populations, an especially important endeavor because of their recent apparent declines in the northeastern and upper midwestern regions of the United States. To better understand patterns of occurrence of moose in New York, we used data collected through an annual survey of approximately 11,000 hunters between 2012 and 2014 that recorded detection–non-detection data of moose and other species. We estimated patterns of occurrence of moose in relation to land cover characteristics, climate effects, and interspecific interactions using occupancy models to analyze spatially referenced moose observations. Coniferous and deciduous forest with low prevalence of white-tailed deer ( Odocoileus virginianus ) had the highest probability of moose occurrence. This study highlights the potential of data collected using citizen science for understanding the spatial distribution of low-density species across large spatial extents and providing key information regarding where and when future research and management activities should be focused.

New York↗

Fena Valley Reservoir watershed and water-balance model updates and expansion of watershed modeling to southern Guam

In 2014, the U.S. Geological Survey, in cooperation with the U.S. Department of Defense’s Strategic Environmental Research and Development Program, initiated a project to evaluate the potential impacts of projected climate-change on Department of Defense installations that rely on Guam’s water resources. A major task of that project was to develop a watershed model of southern Guam and a water-balance model for the Fena Valley Reservoir. The southern Guam watershed model provides a physically based tool to estimate surface-water availability in southern Guam. The U.S. Geological Survey’s Precipitation Runoff Modeling System, PRMS-IV, was used to construct the watershed model. The PRMS-IV code simulates different parts of the hydrologic cycle based on a set of user-defined modules. The southern Guam watershed model was constructed by updating a watershed model for the Fena Valley watersheds, and expanding the modeled area to include all of southern Guam. The Fena Valley watershed model was combined with a previously developed, but recently updated and recalibrated Fena Valley Reservoir water-balance model. Two important surface-water resources for the U.S. Navy and the citizens of Guam were modeled in this study; the extended model now includes the Ugum River watershed and improves upon the previous model of the Fena Valley watersheds. Surface water from the Ugum River watershed is diverted and treated for drinking water, and the Fena Valley watersheds feed the largest surface-water reservoir on Guam. The southern Guam watershed model performed “very good,” according to the criteria of Moriasi and others (2007), in the Ugum River watershed above Talofofo Falls with monthly Nash-Sutcliffe efficiency statistic values of 0.97 for the calibration period and 0.93 for the verification period (a value of 1.0 represents perfect model fit). In the Fena Valley watershed, monthly simulated streamflow volumes from the watershed model compared reasonably well with the measured values for the gaging stations on the Almagosa, Maulap, and Imong Rivers—tributaries to the Fena Valley Reservoir—with Nash-Sutcliffe efficiency values of 0.87 or higher. The southern Guam watershed model simulated the total volume of the critical dry season (January to May) streamflow for the entire simulation period within –0.54 percent at the Almagosa River, within 6.39 percent at the Maulap River, and within 6.06 percent at the Imong River. The recalibrated water-balance model of the Fena Valley Reservoir generally simulated monthly reservoir storage volume with reasonable accuracy. For the calibration and verification periods, errors in end-of-month reservoir-storage volume ranged from 6.04 percent (284.6 acre-feet or 92.7 million gallons) to –5.70 percent (–240.8 acre-feet or –78.5 million gallons). Monthly simulation bias ranged from –0.48 percent for the calibration period to 0.87 percent for the verification period; relative error ranged from –0.60 to 0.88 percent for the calibration and verification periods, respectively. The small bias indicated that the model did not consistently overestimate or underestimate reservoir storage volume. In the entirety of southern Guam, the watershed model has a “satisfactory” to “very good” rating when simulating monthly mean streamflow for all but one of the gaged watersheds during the verification period. The southern Guam watershed model uses a more sophisticated climate-distribution scheme than the older model to make use of the sparse climate data, as well as includes updated land-cover parameters and the capability to simulate closed depression areas. The new Fena Valley Reservoir water-balance model is useful as an updated tool to forecast short-term changes in the surface-water resources of Guam. Furthermore, the now spatially complete southern Guam watershed model can be used to evaluate changes in streamflow and recharge owing to climate or land-cover changes. These are substantial improvements to the previous models of the Fena Valley watershed and Reservoir. Datasets associated with this report are available as a U.S. Geological Survey data release (Rosa and Hay, 2017; DOI:10.5066/F7HH6HV4).

Scientific Investigations Report↗

Development of a land-cover characteristics database for the conterminous U.S.

Information regarding the characteristics and spatial distribution of the Earth's land cover is critical to global environmental research. A prototype land-cover database for the conterminous United States designed for use in a variety of global modelling, monitoring, mapping, and analytical endeavors has been created. The resultant database contains multiple layers, including the source AVHRR data, the ancillary data layers, the land-cover regions defined by the research, and translation tables linking the regions to other land classification schema (for example, UNESCO, USGS Anderson System). The land-cover characteristics database can be analyzed, transformed, or aggregated by users to meet a broad spectrum of requirements. -from Authors

Photogrammetric Engineering and Remote Sensing↗

Evaluation of the initial thematic output from a continuous change-detection algorithm for use in automated operational land-change mapping by the U.S. Geological Survey

The U.S. Geological Survey (USGS) has begun the development of operational, 30-m resolution annual thematic land cover data to meet the needs of a variety of land cover data users. The Continuous Change Detection and Classification (CCDC) algorithm is being evaluated as the likely methodology following early trials. Data for training and testing of CCDC thematic maps have been provided by the USGS Land Cover Trends (LC Trends) project, which offers sample-based, manually classified thematic land cover data at 2755 probabilistically located sample blocks across the conterminous United States. These samples represent a high quality, well distributed source of data to train the Random Forest classifier invoked by CCDC. We evaluated the suitability of LC Trends data to train the classifier by assessing the agreement of annual land cover maps output from CCDC with output from the LC Trends project within 14 Landsat path/row locations across the conterminous United States. We used a small subset of circa 2000 data from the LC Trends project to train the classifier, reserving the remaining Trends data from 2000, and incorporating LC Trends data from 1992, to evaluate measures of agreement across time, space, and thematic classes, and to characterize disagreement. Overall agreement ranged from 75% to 98% across the path/rows, and results were largely consistent across time. Land cover types that were well represented in the training data tended to have higher rates of agreement between LC Trends and CCDC outputs. Characteristics of disagreement are being used to improve the use of LC Trends data as a continued source of training information for operational production of annual land cover maps.

Remote Sensing↗

Recent and future declines of a historically widespread pollinator linked to climate, land cover, and pesticides

The acute decline in global biodiversity includes not only the loss of rare species, but also the rapid collapse of common species across many different taxa. The loss of pollinating insects is of particular concern because of the ecological and economic values these species provide. The western bumble bee ( Bombus occidentalis ) was once common in western North America, but this species has become increasingly rare through much of its range. To understand potential mechanisms driving these declines, we used Bayesian occupancy models to investigate the effects of climate and land cover from 1998 to 2020, pesticide use from 2008 to 2014, and projected expected occupancy under three future scenarios. Using 14,457 surveys across 2.8 million km 2 in the western United States, we found strong negative relationships between increasing temperature and drought on occupancy and identified neonicotinoids as the pesticides of greatest negative influence across our study region. The mean predicted occupancy declined by 57% from 1998 to 2020, ranging from 15 to 83% declines across 16 ecoregions. Even under the most optimistic scenario, we found continued declines in nearly half of the ecoregions by the 2050s and mean declines of 93% under the most severe scenario across all ecoregions. This assessment underscores the tenuous future of B. occidentalis and demonstrates the scale of stressors likely contributing to rapid loss of related pollinator species throughout the globe. Scaled-up, international species-monitoring schemes and improved integration of data from formal surveys and community science will substantively improve the understanding of stressors and bumble bee population trends.

Proceedings of the National Academy of Sciences↗

Reptiles under the conservation umbrella of the greater sage‐grouse

In conservation paradigms, management actions for umbrella species also benefit co‐occurring species because of overlapping ranges and similar habitat associations. The greater sage‐grouse ( Centrocercus urophasianus ) is an umbrella species because it occurs across vast sagebrush ecosystems of western North America and is the recipient of extensive habitat conservation and restoration efforts that might benefit sympatric species. Biologists' understanding of how non‐target species might benefit from sage‐grouse conservation is, however, limited. Reptiles, in particular, are of interest in this regard because of their relatively high diversity in shrublands and grasslands where sage‐grouse are found. Using spatial overlap of species distributions, land cover similarity statistics, and a literature review, we quantified which reptile species may benefit from the protection of intact sage‐grouse habitat and which may be affected by recent (since about 1990) habitat restoration actions targeting sage‐grouse. Of 190 reptile species in the United States and Canadian provinces where greater sage‐grouse occur, 70 (37%) occur within the range of the bird. Of these 70 species, about a third (11 snake and 11 lizard species) have >10% of their distribution area within the sage‐grouse range. Land cover similarity indices revealed that 14 of the 22 species (8 snake and 6 lizard species) had relatively similar land cover associations to those of sage‐grouse, suggesting greater potential to be protected under the sage‐grouse conservation umbrella and greater potential to be affected, either positively or negatively, by habitat management actions intended for sage‐grouse. Conversely, the remaining 8 species are less likely to be protected because of less overlap with sage‐grouse habitat and thus uncertain effects of sage‐grouse habitat management actions. Our analyses of treatment databases indicated that from 1990 to 2014 there were at least 6,400 treatments implemented on public land that covered approximately 4 million ha within the range of the sage‐grouse and, of that, >1.5 million ha were intended to at least partially benefit sage‐grouse. Whereas our results suggest that conservation of intact sagebrush vegetation communities could benefit ≥14 reptiles, a greater number than previously estimated, additional research on each species' response to habitat restoration actions is needed to assess broader claims of multi‐taxa benefits when it comes to manipulative sage‐grouse habitat management. Published 2020. This article is a U.S. Government work and is in the public domain in the USA.

Idaho, Montana↗

Riparian forest cover modulates phosphorus storage and nitrogen cycling in agricultural stream sediments

Watershed land cover affects in-stream water quality and sediment nutrient dynamics. The presence of natural land cover in the riparian zone can reduce the negative effects of agricultural land use on water quality; however, literature evaluating the effects of natural riparian land cover on stream sediment nutrient dynamics is scarce. The objective of this study was to assess if stream sediment phosphorus retention and nitrogen removal varies with riparian forest cover in agricultural watersheds. Stream sediment nutrient dynamics from 28 sites with mixed land cover were sampled three times during the growing season. Phosphorus dynamics and nitrification rates did not change considerably throughout the study period. Sediment total phosphorus concentrations and nitrification rates decreased as riparian forest cover increased likely due to a decline in fine, organic material. Denitrification rates were strongly correlated to surface water nitrate concentrations. Denitrification rate and denitrification enzyme activity decreased with an increase in forest cover during the first sampling period only. The first sampling period coincided with the greatest connectivity between the watershed and in-stream processing, indicating that riparian forest cover indirectly decreased denitrification rates by reducing the concentrations of dissolved nutrients entering the stream. This reduction in load may allow the sediment to maintain greater nitrogen removal efficiency, because bacteria are not saturated with nitrogen. Riparian forest cover also appeared to lessen the effect of agriculture in the watershed by decreasing the amount of fine material in the stream, resulting in reduced phosphorus storage in the stream sediment.

Wisconsin↗

Sediment discharges during storm flow from proximal urban and rural karst springs, central Kentucky, USA

Since the mid-1990s, various studies have addressed the timing of sediment transport to karst springs during storm flow or the composition and provenance of sediment discharged from springs. However, relatively few studies have focused on the flow thresholds at which sediment is mobilized or total sediment yields across various time scales. We examined each of these topics for a mainly urban spring (Blue Hole) and a rural spring (SP-2) in the Inner Bluegrass region of central Kentucky (USA). Suspended sediment consisted mostly of quartz silt and sand, with lesser amounts of calcite and organic matter. Total suspended sediment (TSS) values measured during storm flow were greater at SP-2 than at Blue Hole. By aggregating data from four storms during 2 years, we found that median suspended-sediment size jumped as Q exceeded ???0.5 m 3 /s for both springs. At Blue Hole, TSS tended to vary with Q and capacity approached 1 g/L, but no systematic relationship between TSS and Q was evident at SP-2. Sediment fluxes from the Blue Hole basin were ???2 orders of magnitude greater for storms in March (2002 and 2004) than September (2002 and 2003). In contrast, sediment fluxes from the SP-2 basin were of similar magnitude in September 2003 and March 2004. The overall range of area-normalized fluxes for both springs, 9.16 ?? 10 -3 -4.45 ?? 10 2 kg/(ha h), overlaps values reported for farm plots and a stream in the Inner Bluegrass region and for other spring basins in the eastern USA and western Europe. Sediment compositions, sizes, and responses to storms in the basins may differ because of land use (e.g., the extent of impervious cover in the Blue Hole basin), basin size (larger for Blue Hole), conduit architecture, which appears to be more complex in the Blue Hole basin, and the impoundment of SP-2, which may have promoted decadal-scale storage of sediment upgradient. ?? 2009 Elsevier B.V. All rights reserved.

Journal of Hydrology↗

Relating mesocarnivore relative abundance to anthropogenic land-use with a hierarchical spatial count model

There is growing need to develop models of spatial patterns in animal abundance, yet comparatively few examples of such models exist. This is especially true in situations where the abundance of one species may inhibit that of another, such as the intensively-farmed landscape of the Prairie Pothole Region (PPR) of the central United States, where waterfowl production is largely constrained by mesocarnivore nest predation. We used a hierarchical Bayesian approach to relate the distribution of various land-cover types to the relative abundances of four mesocarnivores in the PPR: coyote Canis latrans, raccoon Procyon lotor, red fox Vulpes vulpes, and striped skunk Mephitis mephitis. We developed models for each species at multiple spatial resolutions (41.4 km2, 10.4 km2, and 2.6 km2) to address different ecological and management-related questions. Model results for each species were similar irrespective of resolution. We found that the amount of row-crop agriculture was nearly ubiquitous in our best models, exhibiting a positive relationship with relative abundance for each species. The amount of native grassland land-cover was positively associated with coyote and raccoon relative abundance, but generally absent from models for red fox and skunk. Red fox and skunk were positively associated with each other, suggesting potential niche overlap. We found no evidence that coyote abundance limited that of other mesocarnivore species, as might be expected under a hypothesis of mesopredator release. The relationships between relative abundance and land-cover types were similar across spatial resolutions. Our results indicated that mesocarnivores in the PPR are most likely to occur in portions of the landscape with large amounts of agricultural land-cover. Further, our results indicated that track-survey data can be used in a hierarchical framework to gain inferences regarding spatial patterns in animal relative abundance.

Iowa, Minnesota↗

Migrating birds’ use of stopover habitat in the southwestern United States

In the arid Southwest, migratory birds are known to use riparian stopover habitats; we know less about how migrants use other habitat types during migratory stopover. Using radar data and satellite land-cover data, we determined the habitats with which birds are associated during migration stopover. Bird densities differed significantly by habitat type at all sites in at least one season. In parts of Arizona and New Mexico upland forest supported high densities of migrants, especially in fall. Developed habitat, in areas with little upland forest, also supported high densities of migrants. Scrub/shrub and grassland habitats supported low to intermediate densities, but because these habitat types dominate the Southwestern landscape, they may provide stopover habitat for larger numbers of migratory birds than previously recognized. These results are complicated by continuing challenges related to target identity (i.e., distinguishing among birds, arthropods and bats). Our results suggest that it is too simplistic to (1) consider the arid West as a largely inhospitable landscape in which there are only relatively small oases of habitat that provide the resources needed by all migrants, (2) think of western riparian and upland forests as supporting the majority of migrants in all cases, and (3) consider a particular habitat unimportant for stopover solely on the basis of low densities of migrants.

The Condor↗

Terrestrial Ecosystems of the Conterminous United States

The U.S. Geological Survey (USGS), with support from NatureServe, has modeled the potential distribution of 419 terrestrial ecosystems for the conterminous United States using a comprehensive biophysical stratification approach that identifies distinct biophysical environments and associates them with known vegetation distributions (Sayre and others, 2009). This standardized ecosystem mapping effort used an ecosystems classification developed by NatureServe (Comer and others, 2003). The ecosystem mapping methodology was developed for South America (Sayre and others, 2008) and is now being implemented globally (Sayre and others, 2007). The biophysical stratification approach is based on mapping the major structural components of ecosystems (land surface forms, topographic moisture potential, surficial lithology, isobioclimates and biogeographic regions) and then spatially combining them to produce a set of unique biophysical environments. These physically distinct areas are considered as the fundamental structural units ('building blocks') of ecosystems, and are subsequently aggregated and labeled using the NatureServe classification. The structural footprints were developed from the geospatial union of several base layers including biogeographic regions, isobioclimates (Cress and others, 2009a), land surface forms (Cress and others, 2009b), topographic moisture potential (Cress and others, 2009c), and surficial lithology (Cress and others, in press). Among the 49,168 unique structural footprint classes that resulted from the union, 13,482 classes met a minimum pixel count threshold (20,000 pixels) and were aggregated into 419 NatureServe ecosystems using a semiautomated labeling process based on rule-set formulations for attribution of each ecosystem. The resulting ecosystems are those that are expected to occur based on the combination of the bioclimate, biogeography, and geomorphology. Where land use by humans has not altered land cover, natural vegetation assemblages are expected to occur, and these are described in the ecosystems classification. The map does not show the distribution of urban and agricultural areas - these will be masked out in subsequent analyses to depict the current land cover in addition to the potential distribution of natural ecosystems. This map depicts the smoothed and generalized image of the terrestrial ecosystems dataset. Additional information about this map and any data developed for the ecosystems modeling of the conterminous United States is available online at: http://rmgsc.cr.usgs.gov/ecosystems/.

Scientific Investigations Map↗

Effects of urban land-use change on streamflow and water quality in Oakland County, Michigan, 1970-2003, as inferred from urban gradient and temporal analysis

Various adverse hydrologic effects on streams have been attributed to urban development and expanded impervious surface area, including increased high flows, decreased low flows, increased variability (commonly referred to as flashiness), nutrient enrichment, and increased dissolved solids concentrations. These effects are often observed through the use of urban-gradient studies, which compare hydrologic characteristics among watersheds with different levels of development. This technique is frequently applied when comparable prior data are not available for the watersheds of interest. During 1966 - 1970, and again during 2001 - 2003, the U.S. Geological Survey collected a series of low-flow water-chemistry samples. Streamflow-gaging stations were operated throughout the period from 1966- 2003 as part of ongoing monitoring operations. This study compares these two water-quality data sets; tests the streamflow data for trends in high flows, low flows, and flashiness; and correlates 2000 land use with water-quality and streamflow data collected during the 2001 - 2003 study. Despite substantial change in land use during 1980 - 2000, with urban land covers replacing open space, forest, and agriculture, little evidence is found in the time-series data of alteration of the daily streamflow characteristics or nutrient enrichment in the study watersheds. However, a distinct shift is observable in chloride concentrations. Strong positive correlations exist across the urban gradient between development and increased peak flows as well as between development and increased flashiness. Correlations of water-quality data to development metrics show strong positive correlations with increased dissolved solids and salt content, as well as increased concentrations of fecal indicator bacteria ( Eschericia coli ). This apparent contradiction may be caused by the differences in the changes measured in each analysis. The change-through-time approach describes change from a fixed starting point of approximately 1970; the gradient approach describes the cumulative effect of all change up to approximately 2000. These findings indicate that although urbanization in Oakland County results in most of the effects observed in the literature, as evidenced in the gradient approach, relatively few of the anticipated effects have been observed during the past three decades. This relative stability despite rapid land-cover change may be related to efforts to mitigate the effects of development and a general decrease in the density of new residential development. It may also be related to external factors such as climate variability and reduced atmospheric deposition of specific chemicals.

Michigan↗

Water-quality assessment of the Cook Inlet Basin, Alaska — Environmental setting

The Cook Inlet Basin in Alaska is one of 59 study units selected for study for water-quality assessment as part of the U.S. Geological Survey's National Water-Quality Assessment program. The Cook Inlet Basin study unit encompasses the fresh surface and ground waters in the 39,325 square-mile area that drains to Cook Inlet, but does not include the marine waters of Cook Inlet. This report describes the natural factors (climate, physiography, geology, soils, land cover) and the human factors (population, land use, water use) that affect water quality, which is the first step in designing and conducting a multidisciplinary regional water-quality assessment. The surface- and ground-water hydrology, and the aquatic ecosystems of the Cook Inlet Basin are described. The report provides an overview of existing water-quality conditions and summarizes the results of selected water-quality studies of the basin.

Alaska↗

Small reservoir distribution, rate of construction, and uses in the upper and middle Chattahoochee basins of the Georgia Piedmont, USA, 1950-2010

Construction of small reservoirs affects ecosystem processes in numerous ways including fragmenting stream habitat, altering hydrology, and modifying water chemistry. While the upper and middle Chattahoochee River basins within the Southeastern United States Piedmont contain few natural lakes, they have a high density of small reservoirs (more than 7500 small reservoirs in the nearly 12,000 km2 basin). Policymakers and water managers in the region have little information about small reservoir distribution, uses, or the cumulative inundation of land cover caused by small reservoir construction. Examination of aerial photography reveals the spatiotemporal patterns and extent of small reservoir construction from 1950 to 2010. Over that 60 year timeframe, the area inundated by water increased nearly six fold (from 19 reservoirs covering 0.16% of the study area in 1950 to 329 reservoirs covering 0.95% of the study area in 2010). While agricultural practices were associated with reservoir creation from 1950 to 1970, the highest rates of reservoir construction occurred during subsequent suburban development between 1980 and 1990. Land cover adjacent to individual reservoirs transitioned over time through agricultural abandonment, land reforestation, and conversion to development during suburban expansion. The prolific rate of ongoing small reservoir creation, particularly in newly urbanizing regions and developing counties, necessitates additional attention from watershed managers and continued scientific research into cumulative environmental impacts at the watershed scale.

Georgia↗

Land-cover mapping of Red Rock Canyon National Conservation Area and Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern, Clark County, Nevada

DigitalGlobe’s QuickBird satellite high-resolution multispectral imagery was classified by using Visual Learning Systems’ Feature Analyst feature extraction software to produce land-cover data sets for the Red Rock Canyon National Conservation Area and the Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern in Clark County, Nevada. Over 1,000 vegetation field samples were collected at the stand level. The field samples were classified to the National Vegetation Classification Standard, Version 2 hierarchy at the alliance level and above. Feature extraction models were developed for vegetation on the basis of the spectral and spatial characteristics of selected field samples by using the Feature Analyst hierarchical learning process. Individual model results were merged to create one data set for the Red Rock Canyon National Conservation Area and one for each of the Areas of Critical Environmental Concern. Field sample points and photographs were used to validate and update the data set after model results were merged. Non-vegetation data layers, such as roads and disturbed areas, were delineated from the imagery and added to the final data sets. The resulting land-cover data sets are significantly more detailed than previously were available, both in resolution and in vegetation classes.

Nevada↗

Thematic accuracy of the 1992 National Land-Cover Data for the western United States

The MultiResolution Land Characteristics (MRLC) consortium sponsored production of the National Land Cover Data (NLCD) for the conterminous United States, using Landsat imagery collected on a target year of 1992 (1992 NLCD). Here we report the thematic accuracy of the 1992 NLCD for the six western mapping regions. Reference data were collected in each region for a probability sample of pixels stratified by map land-cover class. Results are reported for each of the six mapping regions with agreement defined as a match between the primary or alternate reference land-cover label and a mode class of the mapped 3×3 block of pixels centered on the sample pixel. Overall accuracy at Anderson Level II was low and variable across the regions, ranging from 38% for the Midwest to 70% for the Southwest. Overall accuracy at Anderson Level I was higher and more consistent across the regions, ranging from 82% to 85% for five of the six regions, but only 74% for the South-central region.

Remote Sensing of Environment↗

Refining Landsat classification results using digital terrain data

Scientists at the U.S. Geological Survey's Earth Resources Observation systems (EROS) Data Center have recently completed two land-cover mapping projects in which digital terrain data were used to refine Landsat classification results. Digital ter rain data were incorporated into the Landsat classification process using two different procedures that required developing decision criteria either subjectively or quantitatively. The subjective procedure was used in a vegetation mapping project in Arizona, and the quantitative procedure was used in a forest-fuels mapping project in Montana. By incorporating digital terrain data into the Landsat classification process, more spatially accurate landcover maps were produced for both projects.

Journal of Applied Photographic Engineering↗

Generation of a U.S. national urban land use product

Characterization of urban land uses is essential for many applications. However, differentiating among thematically-detailed urban land uses (residential, commercial, industrial, institutional, recreational, etc.) over broad areas is challenging, in part because image-based solutions are not ideal for establishing the contextual basis for identifying economic function and use. At present no current United States national-scale mapping exists for urban land uses similar to the classical Anderson Level II classification. This paper describes a product that maps urban land uses, and is linked to and corresponds with the National Land Cover Database (NLCD) 2006. In this product, NLCD urban pixels, in addition to their current imperviousness intensity classification, are assigned one of nine urban use classes based on information drawn from multiple data sources. These sources include detailed infrastructure information, population characteristics, and historical land use. The result is a method for creating a 30 m national-scale grid providing thematically-detailed urban land use information which complements the NLCD. Initial results for 10 major metropolitan areas are provided as an on-line link. Accuracy assessment of initial products yielded an overall accuracy of 81.6 percent.

Photogrammetric Engineering and Remote Sensing↗