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At least 1,009 records · Page 56Linked to original sources
USGS2021

Sediment mobility and river corridor assessment for a 140-kilometer segment of the main-stem Klamath River below Iron Gate Dam, California

This river corridor assessment documents sediment mobility and river response to flood disturbance along a 140-kilometer segment of the main-stem Klamath River below Iron Gate Dam, California. Field and remote sensing methods were used to assess fundamental indicators of active sediment transport and river response to a combination of natural runoff events and reservoir releases during the study period from 2005 to 2019. Discharge measurements at two gaged sites and bed-material samples at two ungaged sites provided direct and indirect evidence of mobile bed conditions, scour and fill, and surface flushing of fine sediment. Available remote-sensing datasets collected in 2005, 2009, 2010, and 2016 were used to determine sediment storage, flood inundation boundaries, and provide indirect evidence of flood-induced scour. These datasets validate channel-maintenance flows defined by Shea and others (2016). During the study period, flows greater than or equal to 6,030 cubic feet per second mobilized the substrate, caused localized scour, and flushed fine sediment from bar surfaces. Flows greater than or equal to 10,400 cubic feet per second stripped vegetation from bars and floodplains and produced deeper scour. Flood disturbance within the study reach is produced by the combined effect of natural flows and reservoir releases, which resulted in mobile bed conditions during the study period. Periodic scour and substrate disturbance are considered by the U.S. Fish and Wildlife Service to be integral for managing disease-induced mortality of juvenile and adult salmonids. Substrate conditions conducive to parasites that host infectious diseases, particularly Ceratonova shasta, occur periodically. Additional studies are required to determine whether disease prevalence can be mitigated by well-timed reservoir releases. Study results are useful for interpreting linkages among physical and biological processes and for evaluating the effectiveness of flow management targeted to improve river bed conditions for endangered salmonid populations.

California↗
USGS2023

Assessment and characterization of ephemeral stream channel stability in the Grand Valley, Colorado, 2018-22

The purpose of this study is to provide information regarding the stability of ephemeral streams on the north side of the Grand Valley, Colorado. The ungaged ephemeral streams in this semiarid region are of particular interest because (1) the underlying bedrock geology, Mancos Shale, is a sedimentary rock deposit that has been identified as a major contributor of salinity to the Colorado River and (2) despite infrequent flows of short duration, monsoon derived floods in these ephemeral streams can carry substantial amounts of sediment downstream, affecting up and downstream banks and channel cross sections. The study area is of interest as salinity, or the total dissolved solids concentration, in the Colorado River causes an estimated $300 to $400 million per year in economic damages in the United States and it is estimated that 62% of Upper Colorado River Basin dissolved-solid loads originate from geologic sources. In an effort to minimize salt contributions to the Colorado River from public lands administered by the Bureau of Land Management (BLM) a comprehensive three-pronged salinity control approach is being used which incorporates (1) controlling point sources of salinity; (2) controlling nonpoint sources of salinity; and (3) preventing nonpoint sources of salinity from persisting. In 2018, the U.S. Geological Survey, in cooperation with BLM, began an assessment of ephemeral streams located in the north side of the Grand Valley, Colorado, to characterize stream channel stability. The USGS developed a method for automatically extracting channel cross-section geometry from existing remotely sensed terrain models. Based on estimated flood stage and surrogate streamflows, hydraulic characteristics were calculated. Furthermore, the channel geometries and hydraulic characteristics were used to estimate channel stability utilizing a statistical model. In this ongoing study, cross-section stabilities were determined from a stream channel stability assessment for a subset of 1,406 visited locations out of a desired 13,415 cross sections which were delineated from remotely sensed terrain models. The application of Manning’s resistance equation in combination with multiple Logistic Regression models demonstrated that channel stability can be estimated with an 0.85 goodness of fit for a validation dataset when using a combination of drainage area, width to depth ratio, sinuosity, and shear stress as the explanatory variables. Stream channel stability was extrapolated for the remaining 13,415 unvisited cross sections using the multiple Logistic Regression model and defined explanatory variables. Mapping the ephemeral streams and their associated stabilities could be used to prioritize areas for BLM remediation or changes in management strategies to reduce sediment and salinity loading to the Colorado River.

Colorado↗
USGS2008

Evaluation of candidate Landsat Data Gap Sensors

The capabilities of the currently operational Landsat satellites may be lost before the launch of the follow-on Landsat Data Continuity Mission (LDCM), thus producing a gap in the Landsat data record and the National Satellite Land Remote Sensing Data Archive (NSLRSDA). In anticipation of a gap, the Federal agencies responsible for Landsat program management, the National Aeronautics and Space Administration (NASA) and the Department of Interior (DOI) U. S. Geological Survey (USGS), convened a Landsat Data Gap Study Team (LDGST). The study team assessed the basic characteristics of multiple systems and identified sensors aboard the China-Brazil Earth Resources Satellite (CBERS-2) and the Indian Remote Sensing (IRS-P6) ResourceSat-1 satellite as the most promising sources of Landsat-like data. The sensors include the combination of CBERS-2 Infrared Multi-spectral Scanner (IRMSS) and High Resolution Charged Coupled Device (CCD), as well as the IRS-P6 Advanced Wide Field Sensor (AWiFS) and the IRS-P6 Linear Imaging Self Scanning Sensor (LISS-III). The study team concluded that more robust technical evaluations of data and sensor performance are required before gap mitigation strategies can be fully formulated. A technical report is made available that summarizes the results from those evaluations, including the initial data characterization and science utility evaluation. The report can be accessed at http://calval.cr.usgs.gov/LDGST.php.

Conference Paper↗
USGS2012

The footprint of Alaskan tundra fires during the past half-century: implications for surface properties and radiative forcing

Recent large and frequent fires above the Alaskan arctic circle have forced a reassessment of the ecological and climatological importance of fire in arctic tundra ecosystems. Here we provide a general overview of the occurrence, distribution, and ecological and climate implications of Alaskan tundra fires over the past half-century using spatially explicit climate, fire, vegetation and remote sensing datasets for Alaska. Our analyses highlight the importance of vegetation biomass and environmental conditions in regulating tundra burning, and demonstrate that most tundra ecosystems are susceptible to burn, providing the environmental conditions are right. Over the past two decades, fire perimeters above the arctic circle have increased in size and importance, especially on the North Slope, indicating that future wildfire projections should account for fire regime changes in these regions. Remote sensing data and a literature review of thaw depths indicate that tundra fires have both positive and negative implications for climatic feedbacks including a decadal increase in albedo radiative forcing immediately after a fire, a stimulation of surface greenness and a persistent long-term (>10 year) increase in thaw depth. In order to address the future impact of tundra fires on climate, a better understanding of the control of tundra fire occurrence as well as the long-term impacts on ecosystem carbon cycling will be required.

Alaska↗
USGS2025

Decoding the spatiotemporal complexities of the permafrost carbon feedback with multimodal ensemble learning

Complex nonlinear relationships exist between the permafrost thermal state, active layer thickness, and terrestrial carbon cycle dynamics. In Arctic and boreal Alaska, significant uncertainties characterize the spatiotemporal rate and magnitude of permafrost degradation and the permafrost carbon feedback, with increasing recognition of the importance of thawing mechanisms. The challenges of monitoring sub-surface phenomena with remote sensing technology further complicate the issue. There is an urgent need to understand how and to what extent thawing permafrost destabilizes the carbon balance in Alaska and to characterize the feedback involved. In this research, we use our artificial intelligence-driven model GeoCryoAI to quantify permafrost carbon dynamics in Alaska. The GeoCryoAI model uses a hybridized process-constrained ensemble learning framework to simultaneously ingest, scale, and analyze in situ measurements, remote sensing observations, and process-based modeling outputs with disparate spatiotemporal sampling and data densities. We evaluated prior naïve (a) persistence and (b) teacher forcing approaches relative to (c) time-delayed GeoCryoAI simulations, yielding the following error metrics (RMSE) for active layer thickness (ALT), methane (CH 4 ), and carbon dioxide (CO 2 ), respectively: 1.997, 1.327, 1.007 cm [1963–2022]; 0.884, 0.715, 0.694 nmol CH 4 km −2 month −1 [1994–2022]; 1.906, 0.697, 0.213 µmol CO 2 km −2 month −1 [1994–2022]. Our approach overcomes traditional model inefficiencies and resolves spatiotemporal disparities. GeoCryoAI captures abrupt and persistent changes while introducing a novel methodology for assimilating contemporaneous information at various scales. We describe GeoCryoAI, the methodology, our results, and plans for future applications.

Alaska↗
USGS2008

Airborne Hyperspectral Survey of Afghanistan 2007: Flight Line Planning and HyMap Data Collection

Hyperspectral remote sensing data were acquired over Afghanistan with the HyMap imaging spectrometer (Cocks and others, 1998) operating on the WB-57 high altitude NASA research aircraft (http://jsc-aircraft-ops.jsc.nasa.gov/wb57/index.html). These data were acquired during the interval of August 22, 2007 to October 2, 2007, as part of the United States Geological Survey (USGS) project 'Oil and Gas Resources Assessment of the Katawaz and Helmand Basins'. A total of 218 flight lines of hyperspectral remote sensing data were collected over the country. This report describes the planning of the airborne survey and the flight lines that were flown. Included with this report are digital files of the nadir tracks of the flight lines, including a map of the labeled flight lines and corresponding vector shape files for geographic information systems (GIS).

Open-File Report↗
USGS2023

Least cost path analysis as an objective and automatic method to define the main fault trace for probabilistic fault displacement hazard analyses

A main goal of probabilistic fault displacement hazard analysis (PFDHA) is to quantify displacement along and across an identified active fault that poses a hazard to nearby infrastructure such as roads, bridges, pipelines, and telecommunications. PFDHA relies on empirical models developed using data sets of displacement measurements and mapped surface rupture traces compiled from past global surface rupturing earthquakes by field surveys or remote sensing. However, current approaches to determine the location of the main rupture trace are subjective and lack repeatability due to different geological interpretations of the often complex network of mapped rupture traces. This subjectivity makes it difficult to compile and analyze displacement measurements and ruptures from multiple events in a consistent manner. This study provides an objective and repeatable approach to define a main rupture trace that can be applied to either field or remote sensing data. The new approach defined here can be used in developing rupture trace connectivity and geometry for use in displacement model developments and for use in objectively defining the input fault trace for assessing fault displacement hazard.

Earthquake Spectra↗
USGS2004

Intra-seasonal mapping of CO 2 flux in rangelands of northern Kazakhstan at one-kilometer resolution

Algorithms that establish relationships between variables obtained through remote sensing and geographic information system (GIS) technologies are needed to allow the scaling up of site-specific CO2 flux measurements to regional levels. We obtained Bowen ratio-energy balance (BREB) flux tower measurements during the growing seasons of 1998-2000 above a grassland steppe in Kazakhstan. These BREB data were analyzed using ecosystem light-curve equations to quantify 10-day CO2 fluxes associated with gross primary production (GPP) and total respiration (R). Remotely sensed, temporally smoothed normalized difference vegetation index (NDVIsm) and environmental variables were used to develop multiple regression models for the mapping of 10-day CO2 fluxes for the Kazakh steppe. Ten-day GPP was estimated (R 2 = 0.72) by day of year (DOY) and NDVIsm, and 10-day R was estimated (R2 = 0.48) with the estimated GPP and estimated 10-day photosynthetically active radiation (PAR). Regression tree analysis estimated 10-day PAR from latitude, NDVIsm, DOY, and precipitation (R2 = 0.81). Fivefold cross-validation indicated that these algorithms were reasonably robust. GPP, R, and resulting net ecosystem exchange (NEE) were mapped for the Kazakh steppe grassland every 10 days and summed to produce regional growing season estimates of GPP, R, and NEE. Estimates of 10-day NEE agreed well with BREB observations in 2000, showing a slight underestimation in the late summer. Growing season (May to October) mean NEE for Kazakh steppe grasslands was 1.27 Mg C/ha in 2000. Winter flux data were collected during the winter of 2001-2002 and are being analyzed to close the annual carbon budget for the Kazakh steppe. ?? 2004 Springer-Verlag New York, LLC.

Environmental Management↗
USGS2012

Use of ASTER and MODIS thermal infrared data to quantify heat flow and hydrothermal change at Yellowstone National Park

The overarching aim of this study was to use satellite thermal infrared (TIR) remote sensing to monitor geothermal activity within the Yellowstone geothermal area to meet the missions of both the U.S. Geological Survey and the Yellowstone National Park Geology Program. Specific goals were to: 1) address the challenges of monitoring the surface thermal characteristics of the > 10,000 spatially and temporally dynamic thermal features in the Park (including hot springs, pools, geysers, fumaroles, and mud pots) that are spread out over ~ 5000 km 2 , by using satellite TIR remote sensing tools (e.g., ASTER and MODIS), 2) to estimate the radiant geothermal heat flux (GHF) for Yellowstone's thermal areas, and 3) to identify normal, background thermal changes so that significant, abnormal changes can be recognized, should they ever occur (e.g., changes related to tectonic, hydrothermal, impending volcanic processes, or human activities, such as nearby geothermal development). ASTER TIR data (90-m pixels) were used to estimate the radiant GHF from all of Yellowstone's thermal features and update maps of thermal areas. MODIS TIR data (1-km pixels) were used to record background thermal radiance variations from March 2000 through December 2010 and establish thermal change detection limits. A lower limit for the radiant GHF estimated from ASTER TIR temperature data was established at ~ 2.0 GW, which is ~ 30–45% of the heat flux estimated through geochemical thermometry. Also, about 5 km 2 of thermal areas was added to the geodatabase of mapped thermal areas. A decade-long time-series of MODIS TIR radiance data was dominated by seasonal cycles. A background subtraction technique was used in an attempt to isolate variations due to geothermal changes. Several statistically significant perturbations were noted in the time-series from Norris Geyser Basin, however many of these did not correspond to documented thermal disturbances. This study provides concrete examples of the strengths and limitations of current satellite TIR monitoring of geothermal areas, highlighting some specific areas that can be improved. This work provides a framework for future satellite-based thermal monitoring at Yellowstone and other volcanic and geothermal systems.

Idaho, Montana, Oregon, Wyoming↗
USGS2001

Satellite images for land cover monitoring - Navigating through the maze

Policy makers, managers, scientists and the public can view the changing environment using satellite images. More than 60 Earth observing satellites are collecting images of the Earth's surface. Remote sensing satellite systems for land cover assessment are operated by a growing number of countries including India, the United States, Japan, France, Canada and Russia. The focus of this publication is satellite systems for land cover monitoring. On the reverse is a table that compares a selection of these systems, whose data are globally available in a form suitable for land cover analysis. We hope the information presented will help you assess the utility of remotely sensed image to meet your needs.

Report↗
USGS2003

Regional forest land cover characterisation using medium spatial resolution satellite data

Increasing demands on forest resources require comprehensive, consistent and up-to-date information on those resources at spatial scales appropriate for management decision-making and for scientific analysis. While such information can be derived using coarse spatial resolution satellite data (e.g. Tucker et al. 1984; Zhu and Evans 1994; Cihlar et al. 1996; Cihlar et al., Chapter 12), many regional applications require more spatial and thematic details than can be derived by using coarse resolution imagery. High spatial resolution satellite data such as IKONOS and Quick Bird images (Aplin et al. 1997), though usable for deriving detailed forest information (Culvenor, Chapter 9), are currently not feasible for wall-to-wall regional applications because of extremely high data cost, huge data volume, and lack of contiguous coverage over large areas. Forest studies over large areas have often been accomplished using data acquired by intermediate spatial resolution sensor systems, including the Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and the Enhanced Thematic Mapper Plus (ETM+) of Landsat, the High Resolution Visible (HRV) of the Systeme Pour l'Observation de la Terre (SPOT), and the Linear Image Self-Scanner (LISS) of the Indian Remote Sensing satellite. These sensor systems are more appropriate for regional applications because they can routinely produce spatially contiguous data over large areas at relatively low cost, and can be used to derive a host of forest attributes (e.g. Cohen et al. 1995; Kimes et al. 1999; Cohen et al. 2001; Huang et al. 2001; Sugumaran 2001). Of the above intermediate spatial resolution satellites, Landsat is perhaps the most widely used in various types of land remote sensing applications, in part because it has provided more extensive spatial and temporal coverage of the globe than any other intermediate resolution satellite. Spatially contiguous Landsat data have been developed for many regions of the globe (e.g. Lunetta and Sturdevant 1993; Fuller et al. 1994b; Skole et al. 1997), and a circa 1990 Landsat image data set covering the entire land area of the globe has also been developed recently (Jones and Smith 2001). An acquisition strategy aimed at acquiring at least one cloud free image per year for the entire land area of the globe has been initiated for Landsat-7 (Arvidson et al. 2001). This will probably ensure the continued dominance of Landsat in the near future.

Book chapter↗
USGS1981

Landsat 3 return beam vidicon response artifacts

The return beam vidicon (RBV) sensing systems employed aboard Landsats 1, 2, and 3 have all been similar in that they have utilized vidicon tube cameras. These are not mirror-sweep scanning devices such as the multispectral scanner (MSS) sensors that have also been carried aboard the Landsat satellites. The vidicons operate more like common television cameras, using an electron gun to read images from a photoconductive faceplate. In the case of Landsats 1 and 2, the RBV system consisted of three such vidicons which collected remote sensing data in three distinct spectral bands. Landsat 3, however, utilizes just two vidicon cameras, both of which sense data in a single broad band. The Landsat 3 RBV system additionally has a unique configuration. As arranged, the two cameras can be shuttered alternately, twice each, in the same time it takes for one MSS scene to be acquired. This shuttering sequence results in four RBV "subscenes" for every MSS scene acquired, similar to the four quadrants of a square. See Figure 1. Each subscene represents a ground area of approximately 98 by 98 km. The subscenes are designated A, B, C, and D, for the northwest, northeast, southwest, and southeast quarters of the full scene, respectively. RBV data products are normally ordered, reproduced, and sold on a subscene basis and are in general referred to in this way. Each exposure from the RBV camera system presents an image which is 98 km on a side. When these analog video data are subsequently converted to digital form, the picture element, or pixel, that results is 19 m on a side with an effective resolution element of 30 m. This pixel size is substantially smaller than that obtainable in MSS images (the MSS has an effective resolution element of 73.4 m), and, when RBV images are compared to equivalent MSS images, better resolution in the RBV data is clearly evident. It is for this reason that the RBV system can be a valuable tool for remote sensing of earth resources. Until recently, RBV imagery was processed directly from wideband video tape data onto 70-mm film. This changed in September 1980 when digital production of RBV data at the NASA Goddard Space Flight Center (GSFC) began. The wideband video tape data are now subjected to analog-to-digital preprocessing and corrected both radiometrically and geometrically to produce high-density digital tapes (HDT's). The HDT data are subsequently transmitted via satellite (Domsat) to the EROS Data Center (EDC) where they are used to generate 241-mm photographic images at a scale of 1:500,000. Computer-compatible tapes of the data are also generated as digital products. Of the RBV data acquired since September 1, 1980, approximately 2,800 subscenes per month have been processed at EDC.

Open-File Report↗
USGS2002

Grid-cell-based crop water accounting for the famine early warning system

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996–97 and 1997–98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996–97 season in Zimbabwe. Agreement at a useful level ( r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline.

Hydrological Processes↗
USGS2013

What is the economic value of satellite imagery?

Does remote-sensing information, such as that from Landsat and similar Earth-observing satellites, provide economic benefits to society, and can this value be estimated? Using satellite data for northeastern Iowa, U.S. Geological Survey scientists modeled the relations among land uses, agricultural production, and dynamic nitrate (NO3-) contamination of aquifers. They demonstrated that information from such modeling can allow more efficient management of agricultural production without sacrificing groundwater quality. Just for northeastern Iowa, the value of such remote-sensing information was shown to be as much as $858 million ± $197 million per year, which corresponds to a current value of $38.1 billion ± $8.8 billion for that flow of benefits into the foreseeable future.

Fact Sheet↗
USGS2022

Civil applications committee

The interagency Civil Applications Committee (CAC) facilitates the appropriate civil uses of overhead remote sensing technologies and data collected by military and intelligence capabilities, including from commercial sources. The CAC is operated and staffed by the U.S. Geological Survey on behalf of the U.S. Department of the Interior and its interagency partners. The director of the U.S. Geological Survey is the chair of the committee, and the vice-chair is a non-Department of the Interior senior official. The CAC ensures certain Federal civil agencies have access to these remotely sensed assets to meet their statutory missions in ways that do not threaten the civil rights, civil liberties, and personal privacy of U.S. citizens. To meet its mandate, the CAC hosts various working groups and communities of interest including those focused on thermal issues (wildland fires and volcanoes), environmental security, and historical satellite imagery.

Fact Sheet↗
USGS2005

The Zamama-Thor region of Io: Insights from a synthesis of mapping, topography, and Galileo spacecraft data

We have studied data from the Galileo spacecraft's three remote sensing instruments (Solid-State Imager (SSI), Near-Infrared Mapping Spectrometer (NIMS), and Photopolarimeter-Radiometer (PPR)) covering the Zamama–Thor region of Io's antijovian hemisphere, and produced a geomorphological map of this region. This is the third of three regional maps we are producing from the Galileo spacecraft data. Our goal is to assess the variety of volcanic and tectonic materials and their interrelationships on Io using planetary mapping techniques, supplemented with all available Galileo remote sensing data. Based on the Galileo data analysis and our mapping, we have determined that the most recent geologic activity in the Zamama–Thor region has been dominated by two sites of large-scale volcanic surface changes. The Zamama Eruptive Center is a site of both explosive and effusive eruptions, which emanate from two relatively steep edifices (Zamama Tholi A and B) that appear to be built by both silicate and sulfur volcanism. A ∼100-km long flow field formed sometime after the 1979 Voyager flybys, which appears to be a site of promethean-style compound flows, flow-front SO 2 plumes, and adjacent sulfur flows. Larger, possibly stealthy, plumes have on at least one occasion during the Galileo mission tapped a source that probably includes S and/or Cl to produce a red pyroclastic deposit from the same vent from which silicate lavas were erupted. The Thor Eruptive Center, which may have been active prior to Voyager , became active again during the Galileo mission between May and August 2001. A pillanian-style eruption at Thor included the tallest plume observed to date on Io (at least 500 km high) and new dark lava flows. The plume produced a central dark pyroclastic deposit (probably silicate-rich) and an outlying white diffuse ring that is SO 2 -rich. Mapping shows that several of the new dark lava flows around the plume vent have reoccupied sites of earlier flows. Unlike most of the other pillanian eruptions observed during the Galileo mission, the 2001 Thor eruption did not produce a large red ring deposit, indicating a relative lack of S and/or Cl gases interacting with the magma during that eruption. Between these two eruptive centers are two paterae, Thomagata and Reshef. Thomagata Patera is located on a large shield-like mesa and shows no signs of activity. In contrast, Reshef Patera is located on a large, irregular mesa that is apparently undergoing degradation through erosion (perhaps from SO 2 -sapping or chemical decomposition of sulfur-rich material) from multiple secondary volcanic centers.

Icarus↗
USGS1998

North American landscape characterization project: The production of a continental scale three-decade Landsat data set

The North American Landscape Characterization (NALC) project is a component of the National Aeronautics and Space Administration (NASA) Landsat Pathfinder program. Pathfinder projects are focused on the investigation of global change utilizing current remote sensing technologies. The NALC project is a cooperative effort between the U. S. Environmental Protection Agency (EPA), the U.S. Geological Survey (USGS), and NASA to make Landsat data available to the widest possible user community for scientific research and general public interest. The NALC project is principally funded by the EPA Office of Research and Development and the USGS's Earth Resources Observation Systems (EROS) Data Center (EDC). The objectives of the NALC project are to produce standardized remote sensing data sets, develop standardized analysis methods, and derive standardized land cover change products for a large portion of the North American continent (the conterminous United States and Mexico) (Lunetta and Sturdevant, 1993). The standard product is the NALC “triplicate”;, consisting of co‐registered Landsat multispectral scanner data for the years 1973, 1986, and 1991 (plus or minus one year), plus co‐registered 3 arcsecond digital terrain elevation data. Processing began with the 1986 scene, which was precision corrected (with full terrain correction) to a 60 meter Universal Transverse Mercator base. Automated cross‐correlation procedures were used to co‐register the 1970's and 1990's data to the 1980's base, and independent verifications of registration quality were performed on all triplicate components. The pertinent metadata were compiled in a relational database, which includes WRS2 path/rows, scene ID's, image dates, solar azimuth and elevation, verification RMSE's, and the number of verification control points. NALC triplicate data sets are being used for a number of applications, including the analysis of urbanization patterns, dynamics of climatic fluctuations, deforestation studies, and vegetation classification and mapping. These data are being distributed through the Earth Observing System Data and Information System (EOSDIS) Information Management System (IMS) at a cost of $15(U.S.) for each triplicate.

Geocarto International↗
USGS1993

Forest to agriculture conversion in southern Belize: Implications for migrant land birds

Central America offers a suite of neotropical habitats vital to overwintering migrant land birds. The recent decline of many forest dwelling avian migrants is believed to be related in part to neotropical deforestation and land use change. However, spatio-temporal trends in neotropical habitat availability and avian migrant habitat use are largely unknown. Such information is needed to assess the impact of agriculture conversion on migrant land birds. In response, the USDI Fish and Wildlife Service and the University of Maine began a cooperative study in 1988 which applies remote sensing and field surveys to determine current habitat availability and avian migrant habitat use. Study sites include areas in Belize, Costa Rica, Guatemala and southern Mexico. Visual assessment of Landsat TM imagery indicates southern Belize forests are fragmented by various agricultural systems. Shifting agriculture is predominant in some areas, while permanent agriculture (citrus and mixed animal crops) is the primary system in others. This poster focuses on efforts to monitor forest to agriculture conversion in southern Belize using remote sensing, field surveys and GIS techniques. Procedures and avian migrant use of habitat are summarized.

Book chapter↗