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At least 1,063 records · Page 59Linked to original sources
USGS2016

MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA

Wheat stem sawfly ( Cephus cinctus Norton, Hymenoptera: Cephidae) has long been a significant insect pest of spring, and more recently, winter wheat in the northern Great Plains. Wheat stem sawfly was first observed infesting winter wheat in Colorado in 2010 and, subsequently, has spread rapidly throughout wheat production regions of the state. Here, we used maximum entropy modeling (MaxEnt) to generate habitat suitability maps in order to predict the risk of crop damage as this species spreads throughout the winter wheat-growing regions of Colorado. We identified environmental variables that influence the current distribution of wheat stem sawfly in the state and evaluated whether remotely sensed variables improved model performance. We used presence localities of C. cinctus and climatic, topographic, soils, and normalized difference vegetation index and enhanced vegetation index data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery as environmental variables. All models had high performance in that they were successful in predicting suitable habitat for C. cinctus in its current distribution in eastern Colorado. The enhanced vegetation index for the month of April improved model performance and was identified as a top contributor to MaxEnt model. Soil clay percent at 0–5 cm, temperature seasonality, and precipitation seasonality were also associated with C. cinctus distribution in Colorado. The improved model performance resulting from integrating vegetation indices in our study demonstrates the ability of remote sensing technologies to enhance species distribution modeling. These risk maps generated can assist managers in planning control measures for current infestations and assess the future risk of C. cinctus establishment in currently uninfested regions.

Colorado↗
USGS2021

Riverscape approaches in practice: Perspectives and applications

Landscape perspectives in riverine ecology have been undertaken increasingly in the last 30 years, leading aquatic ecologists to develop a diverse set of approaches for conceptualizing, mapping and understanding ‘riverscapes’. Spatiotemporally explicit perspectives of rivers and their biota nested within the socio-ecological landscape now provide guiding principles and approaches in inland fisheries and watershed management. During the last two decades, scientific literature on riverscapes has increased rapidly, indicating that the term and associated approaches are serving an important purpose in freshwater science and management. We trace the origins and theoretical foundations of riverscape perspectives and approaches and examine trends in the published literature to assess the state of the science and demonstrate how they are being applied to address recent challenges in the management of riverine ecosystems. We focus on approaches for studying and visualizing rivers and streams with remote sensing, modelling and sampling designs that enable pattern detection as seen from above (e.g. river channel, floodplain, and riparian areas) but also into the water itself (e.g. aquatic organisms and the aqueous environment). Key concepts from landscape ecology that are central to riverscape approaches are heterogeneity, scale (resolution, extent and scope) and connectivity (structural and functional), which underpin spatial and temporal aspects of study design, data collection and analysis. Mapping of physical and biological characteristics of rivers and floodplains with high-resolution, spatially intensive techniques improves understanding of the causes and ecological consequences of spatial patterns at multiple scales. This information is crucial for managing river ecosystems, especially for the successful implementation of conservation, restoration and monitoring programs. Recent advances in remote sensing, field-sampling approaches and geospatial technology are making it increasingly feasible to collect high-resolution data over larger scales in space and time. We highlight challenges and opportunities and discuss future avenues of research with emerging tools that can potentially help to overcome obstacles to collecting, analysing and displaying these data. This synthesis is intended to help researchers and resource managers understand and apply these concepts and approaches to address real-world problems in freshwater management.

Biological Reviews↗
USGS2001

Environmental studies of the World Trade Center area after the September 11, 2001 attack

This web site describes the results of an interdisciplinary environmental characterization of the World Trade Center (WTC) area after September 11, 2001. Information presented in this site was first made available to the World Trade Center emergency response teams on September 18, 2001 (Thermal hot spot information), and September 27, 2001 (maps and compositional results). The Airborne Visible / Infrared Imaging Spectrometer (AVIRIS), a hyperspectral remote sensing instrument, was flown by JPL/NASA over the World Trade Center (WTC) area on September 16, 18, 22, and 23, 2001 ( Link to the AVIRIS JPL data facility) . A 2-person USGS crew collected samples of dusts and airfall debris from more than 35 localities within a 1-km radius of the World trade Center site on the evenings of September 17 and 18, 2001. Two samples were collected of indoor locations that were presumably not affected by rainfall (there was a rainstorm on September 14). Two samples of material coating a steel beam in the WTC debris were also collected. The USGS ground crew also carried out on-the-ground reflectance spectroscopy measurements during daylight hours to field calibrate AVIRIS remote sensing data. Radiance calibration and rectification of the AVIRIS data were done at JPL/NASA. Surface reflectance calibration, spectral mapping, and interpretation were done at the USGS Imaging Spectroscopy Lab in Denver. The dust/debris and beam-insulation samples were analyzed for a variety of mineralogical and chemical parameters using Reflectance Spectroscopy (RS), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), chemical analysis, and chemical leach test techniques in U.S. Geological Survey laboratories in Denver, Colorado.

New York↗
USGS2020

A newly emerging thermal area in Yellowstone

Yellowstone is a large restless caldera that contains many dynamic thermal areas that are the surface expression of the deeper magmatic system. In 2018, using a Landsat 8 nighttime thermal infrared image, we discovered the emergence of a new thermal area located near Tern Lake on the northeast margin of the Sour Creek dome. A high-spatial-resolution airborne visible image from August 2017 revealed a large (~33,000 m2) area of recently fallen trees, mostly devoid of vegetation, with bright soil, similar to other nearby thermal areas. Field observations in August 2019 confirmed that this was a steam-heated acid-sulfate thermal area, with an arc-shaped zone of hydrothermally altered soil and heated ground, with surface temperatures of 60-80 °C, several steaming fumaroles, and boiling temperatures (93 °C) just beneath the surface. Fallen trees in contact with warm ground were being carbonized, yet there were some cooler areas with new trees growing. Observations of stressed or dying vegetation from archived satellite and airborne remote sensing data going back to 1994 indicated that this thermal area started emerging around 2000. It increased in size slowly until around 2005, when the radiative heat output started measurably increasing. From 2005 to 2012 it grew more rapidly; and from 2012 through 2019 the growth rate slowed and the heat output stabilized. We predict that this stabilizing trend will continue in the coming years. The initial formation of this new thermal area was not clearly linked to any distinct seismic or geodetic events, although the period of rapid growth partly coincided with a period of rapid local uplift, possibly suggesting a causative relationship. The identification of this emerging thermal area illustrates the importance of satellite thermal infrared imaging combined with high-spatial-resolution remote sensing data and field observations for mapping, measuring, and monitoring Yellowstone's thermal areas. It is also an example of the dynamics we expect to observe within large caldera systems like Yellowstone, where changes in the size and distribution of thermal areas are normal and do not indicate an impending eruption nor any significant changes in the broader magmatic system.

Wyoming↗
USGS2007

Geographic Research in the USGS Western Region

The two geography research programs of the U.S. Geological Survey (USGS), Land Remote Sensing and Geographic Analysis and Monitoring, have very strong relevance to the USGS mission and science strategy. In the western United States, the particular niche of these geography programs is in connecting USGS science to people and communities. Reports from the National Academy of Sciences and other organizations invariably encourage the U.S. Geological Survey (USGS) to ensure the quality of its science while finding ways to make it more relevant to important societal issues. Much of the geography research conducted in the USGS Western Region does exactly that. In Menlo Park, California, the geography research team is focused on developing tools and techniques to help people assess risk from natural hazards and environmental impacts. In Flagstaff and Tucson, Arizona, geography scientists explore new ways to use remote sensing to help communities deal with environmental issues.

Fact Sheet↗
USGS2012

Evaluation of NDVI to assess avian abundance and richness along the upper San Pedro River

Remote-sensing models have become increasingly popular for identifying, characterizing, monitoring, and predicting avian habitat but have largely focused on single bird species. The Normalized Difference Vegetation Index (NDVI) has been shown to positively correlate with avian abundance and richness and has been successfully applied to southwestern riparian systems which are uniquely composed of narrow bands of vegetation in an otherwise dry landscape. Desert riparian ecosystems are important breeding and stopover sites for many bird species but have been degraded due to altered hydrology and land management practices. Here we investigated the use of NDVI, coupled with vegetation, to model the avian community structure along the San Pedro River, Arizona. We also investigated how vegetation and physical features measured locally compared to those data that can be gathered through remote-sensing. We found that NDVI has statistically significant relationships with both avian abundance and species richness, although is better applied at the individual species level. However, the amount of variation explained by even our best models was quite low, suggesting that NDVI habitat models may not presently be an accurate tool for extensive modeling of avian communities. We suggest additional studies in other watersheds to increase our understanding of these bird/NDVI relationships.

Arizona↗
USGS2005

The detection and mapping of oil on a marshy area by a remote luminescent sensor

Airborne remote sensing can be a cost-effective method for monitoring pollutants in large areas such as occur in oil spills. An opportunity to test a particular method arose when a well ruptured and for 23 days spewed a 90-meter fountain of oil into the air, dispersing the oil over a wide area. The method tested was an airborne luminescence detector with a Fraunhofer Line Discriminator (FLD) which was flown over the affected area 41 days after the well was capped to obtain a map or the deposition pattern. To calibrate the system, samples of Spartina (wire grass) and Phragmites (common reed) were collected from the contaminated area and the oil residues were eluted in cyclohexane and quantitatively analyzed in a fluorescence photometer. Good correlation was observed between the remote sensor (FLD) and the laboratory analysis. Isopleths defining the deposition pattern of oil were drawn from the remote sensing information. A discussion will be presented on the feasibility of using this instrument for similar contamination incidents for cleanup and damage assessment.

Conference Paper↗
USGS2013

Effects of grazing on leaf area index, fractional cover and evapotranspiration by a desert phreatophyte community at a former uranium mill site on the Colorado Plateau

This study employed ground and remote sensing methods to monitor the effects of grazing on leaf area index (LAI), fractional cover (f c ) and evapotranspiration (ET) of a desert phreatophyte community over an 11 year period at a former uranium mill site on the Colorado Plateau, U.S. Nitrate, ammonium and sulfate are migrating away from the mill site in a shallow alluvial aquifer. The phreatophyte community, consisting of Atriplex canescens (ATCA) and Sarcobatus vermiculatus (SAVE) shrubs, intercepts groundwater and could potentially slow the movement of the contaminant plume through evapotranspiration (ET). However, the site has been heavily grazed by livestock, reducing plant cover and LAI. We used livestock exclosures and revegetation plots to determine the effects of grazing on LAI, f c and ET, then projected the findings over the whole site using multi-platform remote sensing methods. We show that ET is approximately equal to annual precipitation at the site, but when ATCA and SAVE are protected from grazing they can develop high f c and LAI values, and ET can exceed annual precipitation, with the excess coming from groundwater discharge. Therefore, control of grazing could be an effective method to slow migration of contaminants at this and similar sites in the western U.S.

Colorado Plateau↗
USGS2011

Where the wild things are: Predicting hotspots of seabird aggregations in the California Current System

Marine Protected Areas (MPAs) provide an important tool for conservation of marine ecosystems. To be most effective, these areas should be strategically located in a manner that supports ecosystem function. To inform marine spatial planning and support strategic establishment of MPAs within the California Current System, we identified areas predicted to support multispecies aggregations of seabirds (“hotspots”). We developed habitat‐association models for 16 species using information from at‐sea observations collected over an 11‐year period (1997–2008), bathymetric data, and remotely sensed oceanographic data for an area from north of Vancouver Island, Canada, to the USA/Mexico border and seaward 600 km from the coast. This approach enabled us to predict distribution and abundance of seabirds even in areas of few or no surveys. We developed single‐species predictive models using a machine‐learning algorithm: bagged decision trees. Single‐species predictions were then combined to identify potential hotspots of seabird aggregation, using three criteria: (1) overall abundance among species, (2) importance of specific areas (“core areas”) to individual species, and (3) predicted persistence of hotspots across years. Model predictions were applied to the entire California Current for four seasons (represented by February, May, July, and October) in each of 11 years. Overall, bathymetric variables were often important predictive variables, whereas oceanographic variables derived from remotely sensed data were generally less important. Predicted hotspots often aligned with currently protected areas (e.g., National Marine Sanctuaries), but we also identified potential hotspots in Northern California/Southern Oregon (from Cape Mendocino to Heceta Bank), Southern California (adjacent to the Channel Islands), and adjacent to Vancouver Island, British Columbia, that are not currently included in protected areas. Prioritization and identification of multispecies hotspots will depend on which group of species is of highest management priority. Modeling hotspots at a broad spatial scale can contribute to MPA site selection, particularly if complemented by fine‐scale information for focal areas.

California↗
USGS2023

A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management

Ecological condition continues to decline in arid and semi-arid river basins globally due to hydrological over-abstraction combined with changing climatic conditions. Whilst provision of water for the environment has been a primary approach to alleviate ecological decline, how to accurately monitor changes in riverine trees at fine spatial and temporal scales, remains a substantial challenge. This is further complicated by constantly changing water availability across expansive river basins with varying climatic zones. Within, we combine rare, fine-scale, high frequency temporal in-situ field collected data with machine learning and remote sensing, to provide a robust model that enables broadscale monitoring of physiological tree water stress response to environmental changes via actual evapotranspiration (ET). Physiological variation of Eucalyptus camaldulensis (River Red Gum) and E. largiflorens (Black Box) trees across 10 study locations in the southern Murray-Darling Basin, Australia, was captured instantaneously using sap flow sensors, substantially reducing tree response lags encountered by monitoring visual canopy changes. Actual ET measurement of both species was used to bias correct a national spatial ET product where a Random Forest model was trained using continuous timeseries of in-situ data of up to four years. Precise monthly AMLETT ( A ustralia-wide M achine L earning ET for T rees) ET outputs in 30 m pixel resolution from 2012 to 2021, were derived by incorporating additional remote sensing layers such as soil moisture, land surface temperature, radiation and EVI and NDVI in the Random Forest model. Landsat and Sentinal-2 correlation results between in-situ ET and AMLETT ET returned R 2 of 0.94 (RMSE 6.63 mm period −1 ) and 0.92 (RMSE 6.89 mm period −1 ), respectively. In comparison, correlation between in-situ ET and a national ET product returned R 2 of 0.44 (RMSE 34.08 mm period −1 ) highlighting the need for bias correction to generate accurate absolute ET values. The AMLETT method presented here, enhances environmental management in river basins worldwide. Such robust broadscale monitoring can inform water accounting and importantly, assist decisions on where to prioritize water for the environment to restore and protect key ecological assets and preserve floodplain and riparian ecological function.

The Journal of Environmental Management↗
USGS2020

Projecting spatiotemporally explicit effects of climate change on stream temperature: A model comparison and implications for coldwater fishes

Conservation planners and resource managers seek information about how the availability and locations of cold-water habitats will change in the future and how these predictions vary among models. We used a physical process-based model to demonstrate the implications of climate change for streamflow and water temperature in two watersheds with distinctive flow regimes: the Snoqualmie watershed (WA) and Siletz watershed (OR), USA. Our model incorporated a downscaled ensemble of global climate model outputs and was calibrated with in situ and remotely sensed water temperatures. We compared predictions from our processed-based model to those from a publicly available and widely used statistical model. The process-based model projected greater changes in summer maximum water temperatures for the mixed-rain-snow Snoqualmie watershed than for the rain-dominated Siletz watershed as a result of the near-complete loss of winter snowpack and significant reduction in summer flow in the Snoqualmie watershed expected by the 2080s. Both models projected generally similar future spatial patterns of maximum water temperature in the two rivers, with cool reaches distributed farther upstream and fewer in number. However, the process-based model projected higher spatial heterogeneity in water temperature due to our spatially explicit simulation of streamflow and because we calibrated the model with spatially continuous remotely sensed water temperature data. We used stream temperature projections to assess the vulnerability of Pacific salmon and trout to changes in the spatial distribution of cold-water habitats during August by the 2080s. Results suggest that salmonids may have fewer summertime cold-water habitats in both watersheds. Projected stream warming may further limit particular species and life stages, especially in the Snoqualmie watershed. Our comparison of models highlights the importance of considering what might be gained by using a process-based model for evaluating and prioritizing management actions that mitigate climate impacts on cold-water habitats for stream fishes.

Oregon, Washington↗
USGS1997

Sea-ice processes in the Laptev Sea and their importance for sediment export

Based on remote-sensing data and an expedition during August-September 1993, the importance of the Laptev Sea as a source area for sediment-laden sea ice was studied. Ice-core analysis demonstrated the importance of dynamic ice-growth mechanisms as compared to the multi-year cover of the Arctic Basin. Ice-rafted sediment (IRS) was mostly associated with congealed frazil ice, although evidence for other entrainment mechanisms (anchor ice, entrainment into freshwater ice) was also found. Concentrations of suspended particulate matter (SPM) in patches of dirty ice averaged at 156 g m-3 (standard deviation ?? = 140 g m-3), with a background concentration of 5 g m-3. The potential for sediment entrainment over the broad, shallow Laptev Sea shelf during fall freeze-up was studied through analysis of remote-sensing data and weather-station records for the period 1979-1994. Freeze-up commences on 26 September (?? = 7 d) and is completed after 19 days (?? = 6 d). Meteorological conditions as well as ice extent prior to and during freeze-up vary considerably, the open-water area ranging between 107 x 103 and 447 x 103 km2. Ice motion and transport of IRS were derived from satellite imagery and drifting buoys for the period during and after the expedition (mean ice velocities of 0.04 and 0.05 m s-1, respectively). With a best-estimate sediment load of 16 t km-2 (ranging between 9 and 46 t km-2), sediment export from the eastern Laptev Sea amounts to 4 x 10-6 t yr-1, with extremes of 2 x 10-6 and 11 x 106 t yr-1. Implications for the sediment budget of the Laptev shelf, in particular with respect to riverine input of SPM, which may be of the same order of magnitude, are discussed.

Continental Shelf Research↗
USGS2017

Effects of lateral confinement in natural and leveed reaches of a gravel-bed river: Snake River, Wyoming, USA

This study examined the effects of natural and anthropogenic changes in confining margin width by applying remote sensing techniques – fusing LiDAR topography with image-derived bathymetry – over a large spatial extent: 58 km of the Snake River, Wyoming, USA. Fused digital elevation models from 2007 and 2012 were differenced to quantify changes in the volume of stored sediment, develop morphological sediment budgets, and infer spatial gradients in bed material transport. Our study spanned two similar reaches that were subject to different controls on confining margin width: natural terraces versus artificial levees. Channel planform in reaches with similar slope and confining margin width differed depending on whether the margins were natural or anthropogenic. The effects of tributaries also differed between the two reaches. Generally, the natural reach featured greater confining margin widths and was depositional, whereas artificial lateral constriction in the leveed reach produced a sediment budget that was closer to balanced. Although our remote sensing methods provided topographic data over a large area, net volumetric changes were not statistically significant due to the uncertainty associated with bed elevation estimates. We therefore focused on along-channel spatial differences in bed material transport rather than absolute volumes of sediment. To complement indirect estimates of sediment transport derived by morphological sediment budgeting, we collected field data on bed mobility through a tracer study. Surface and subsurface grain size measurements were combined with bed mobility observations to calculate armoring and dimensionless sediment transport ratios, which indicated that sediment supply exceeded transport capacity in the natural reach and vice versa in the leveed reach. We hypothesize that constriction by levees induced an initial phase of incision and bed armoring. Because levees prevented bank erosion, the channel excavated sediment by migrating rapidly across the restricted braidplain and eroding bars and islands.

Wyoming↗
USGS2024

The influence of anthropogenic regulation and evaporite dissolution on earthquake-triggered ground failure

Remote sensing observations of Searles Lake following the 2019 moment magnitude 7.1 Ridgecrest, California, earthquake reveal an area where surface ejecta is arranged in a repeating hexagonal pattern that is collocated with a solution-mining operation. By analyzing geologic and geotechnical data, here we show that the hexagonal surface ejecta is likely not a result of liquefaction. Instead, we propose dissolution cavity collapse (DCC) as an alternative driving mechanism. We support this theory with pre-event Interferometric Synthetic Aperture Radar data, which reveals differential subsidence patterns and the creation of subsurface void space. We also find that DCC is likely triggered at a lower shaking threshold than classical liquefaction. This and other unknown mechanisms can masquerade as liquefaction, introducing bias into liquefaction prediction models that rely on liquefaction inventories. This paper also highlights the opportunities and drawbacks of using remote sensing data to disentangle the complex factors that influence earthquake-triggered ground failure.

California↗
USGS2007

Climate Change Research at USGS Center for Earth Resources Observation and Science (EROS)

Research and development projects at EROS apply unique resources to support the USGS mission of developing understanding, monitoring, and modeling of climate variability and change and their human, physical, and biological impacts. Remote sensing resources, both new and archived, form the core of our ability to determine changes in the state or condition of the Earth’s surface and its dynamic landscape and ecosystem processes. This rich resource provides powerful biophysical information for local to global areas. Archival data form the basis for assessing human and climate impacts on the land surface, trends of land use, and an understanding of climate and management impacts. Biophysical information from satellite data is assimilated into quantitative models that allow all disciplines of the USGS to understand impacts on ecosystem processes. Major processes and problems we address include: carbon fluxes, hydrological processes, albedo changes and regional climates, mangroves and wetland protection of coastal environments, natural and manmade hazards (e.g., fire and drought), ecosystem change and succession, land use and land cover change, and more. The integration of remote sensing, modeling, and multidisciplinary approaches fosters international scientific leadership across all disciplines for the USGS.

Fact Sheet↗
USGS2003

To the National Map and beyond

Scientific understanding, technology, and social, economic, and environmental conditions have driven a rapidly changing demand for geographic information, both digital and analog. For more than a decade, the U.S. Geological Survey (USGS) has been developing innovative partnerships with other government agencies and private industry to produce and distribute geographic information efficiently; increase activities in remote sensing to ensure ongoing monitoring of the land surface; and develop new understanding of the causes and consequences of land surface change. These activities are now contributing to a more robust set of geographic information called The National Map (TNM). The National Map is designed to provide an up-to-date, seamless, horizontally and vertically integrated set of basic digital geographic data, a frequent monitoring of changes on the land surface, and an understanding of the condition of the Earth's surface and many of the processes that shape it. The USGS has reorganized its National Mapping Program into three programs to address the continuum of scientific activities-describing (mapping), monitoring, understanding, modeling, and predicting. The Cooperative Topographic Mapping Program focuses primarily on the mapping and revision aspects of TNM. The National Map also includes results from the Land Remote Sensing and Geographic Analysis and Monitoring Programs that provide continual updates, new insights, and analytical tools. The National Map is valuable as a framework for current research, management, and operational activities. It also provides a critical framework for the development of distributed, spatially enabled decision support systems.

Cartography and Geographic Information Science↗
USGS2006

Preliminary Surficial Geologic Map of the Mesquite Lake 30' X 60' Quadrangle, California and Nevada

The Quaternary surficial geologic map of the Mesquite Lake, California-Nevada 30'X60' quadrangle depicts deposit age and geomorphic processes of erosion and deposition, as identified by a composite of remote sensing investigations, laboratory analyses, and field work, in the arid to semi-arid Mojave Desert area, straddling the California-Nevada border. Mapping was motivated by the need to address pressing scientific and social issues such as understanding and predicting the effects of climate and associated hydrologic changes, human impacts on landscapes, ecosystem function, and natural hazards at a regional scale. As the map area lies just to the south of Las Vegas, Nevada, a rapidly expanding urban center, land use pressures and the need for additional construction materials are forecasted for the region. The map contains information on the temporal and spatial patterns of surface processes and hazards that can be used to model specific landscape applications. Key features of the geologic map include: (1) spatially extensive Holocene alluvial deposits that compose the bulk of Quaternary units (~25%), (2) remote sensing and field studies that identified fault scarps or queried faults in the Kingston Wash area, Shadow Mountains, southern Pahrump Valley, Bird Spring Range, Lucy Gray Mountains and Piute Valley, (3) a lineament indicative of potential fault offset is located in Mesquite Valley, (4) active eolian dunes and sand ramps located on the east side of Mesquite, Ivanpah, and Hidden Valleys adjacent to playas, (4) groundwater discharge deposits in southern Pahrump Valley, Spring Mountains, and Lucy Gray Mountains and (5) debris-flow deposits spanning almost the entire Quaternary period in age.

Open-File Report↗
USGS1984

LANDSAT M. S. S. IMAGE MOSAIC OF TUNISIA.

The Landsat mosaic of Tunisia funded by USAID for the Remote Sensing Laboratory, Soils Division, Ministry of Agriculture, Tunisia, was completed by the USGS in September 1983. It is a mixed mosaic associating digital corrections and enhancements to manual mosaicking and corresponding to the Tunisian request for high resolution and the limited available funds. The scenes were processed by the Environmental Research Institute of Michigan, resampling the data geodesically corrected to fit the Universal Transverse Mercator projection using control points from topographic maps at 1:50,000 and 1:100,000 scales available in the U. S. The mosaicking was done in the Eastern Mapping Center under the supervision of the Graphic Arts System Section. The three black and white mosaics were made at the 1:1,000,000 scale and various products generated. They included color film positives at 1:2,000,000 and 1:4,000,000 scales reproducible in the Remote Sensing Laboratory in Tunis and corresponding color prints as well as tricolor prints at various scales from 1:500,000 to 1:2,000,000.

Conference Paper↗