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USGS2022

Iowa and Landsat

Iowa is famous for plenty of reasons—its State Fair butter sculptures, its first-in-the-Nation presidential caucuses, and the Iowa Hawkeyes football team, whose mascot doubles as the State nickname—but “corn” might be the first word to cross the mind of a non-Iowan. Iowa consistently leads the United States in corn production and in the production of hogs, which in turn consume a sizable share of the corn grown there. Corn also drives Iowa’s ethanol industry, which put nearly 4.5 billion gallons of fuel into the supply chain in 2020—more than any other State. Iowa owes its agricultural dominance largely to its fertile soils, making land management decisions critical to its future. Changes to land cover, more intensive land use, unusual precipitation patterns, and temperature changes, coupled with an influx of extreme weather events—some of which can be tied to or exacerbated by climate change—have placed pressure on the productive farm ground of Iowa’s 99 counties. Landsat Program satellites can be especially useful in the monitoring and management of croplands across the United States. Backed by a 50-year record of Earth surface change, Landsat satellites can detect the details of vegetation health by peering into the infrared and near-infrared parts of the electromagnetic spectrum. Iowa has long served as a proving ground for Landsat-based agricultural research, and its residents and leaders have benefited from that work. Here are a few examples of how the Landsat Program benefits Iowa.

Iowa↗

USGS2001

Tampa Bay Integrated Science Pilot Study: Baseline mapping, land surface dynamics and predictive modeling, and hazards vulnerability studies

Tampa Bay and its environs have experienced phenomenal urban growth and significant changes in land cover and land-use practices over the past 50 years. This trend is expected to continue, with the impact of human activity broadening geographically and intensifying throughout the region. One of the immediate impacts of urban growth is the creation of additional impervious surfaces, which in turn, generate increased urban runoff that contributes to higher levels of nutrient loading in water bodies throughout the area. To better understand these and other anthropogenic affects on the ecology of the natural environment of the region, this component of the Tampa Bay Pilot Study took a broad basin-wide view. This regional view was intended to provide geographic and temporal context for the smaller intensely studied sample field site locations within the estuarine environment.

Open-File Report↗

USGS2014

Landbird trends in national parks of the North Coast and Cascades Network, 2005-12

National parks in the North Coast and Cascades Network (NCCN) can fulfill vital roles as refuges for bird species dependent on late-successional forest conditions and as reference sites for assessing the effects of land-use and land-cover changes on bird populations throughout the larger Pacific Northwest region. Additionally, long-term monitoring of landbirds throughout the NCCN provides information that can inform decisions about important management issues in the parks, including visitor impacts, fire management, and the effects of introduced species. In 2005, the NCCN began implementing a network-wide Landbird Monitoring Project as part of the NPS Inventory and Monitoring Program. In this report, we discuss 8-year trends (2005–12) of bird populations in the NCCN, based on a sampling framework of point counts established in three large wilderness parks (Mount Rainier, North Cascades, and Olympic National Parks), 7-year trends at Lewis and Clark National Historical Park (sampled in 2006, 2008, 2010, and 2012), and 5-year trends at San Juan Islands National Historical Park (sampled in 2007, 2009, and 2011). Our analysis encompasses a fairly short time span for this long-term monitoring program. The first 2 years of the time series (2005 and 2006) were implemented as part of a limited pilot study that included only a small subset of the transects. The subsequent 6 years (2007–12) represent just a single cycle through 5 years of alternating panels of transects in the large parks, with the first of five alternating panels revisited for the first time in 2012. Of 204 transects that comprise the six sampling panels in the large parks, only 68 (one-third) have thus been eligible for revisit surveys (34 during every year after 2005, and an additional 34 only in 2012) and can contribute to our current trend estimates. We therefore initiated the current analysis with a primary goal of testing our analytical procedures rather than detecting trends that might be strong enough to drive conservation or management decisions in the parks or elsewhere. We expect that aggregated trend detection results may change substantially over the next several years, as the number of transects with revisit histories triples and the spatial dispersion of transects contributing to trend estimates also improves greatly. In the meantime, caution should be exercised in interpreting the importance of trends, as individual years can have very large influences on the direction and magnitude of trends in a time series of such limited duration (and limited numbers of repeat visits at the small parks). Nevertheless, we estimated trends for 43 species at Mount Rainier National Park, 53 species at North Cascades National Park Complex, and 41 species at Olympic National Park. Of 137 park-species combinations (including combined-park analyses), we found 16 significant decreases (12 percent) and five significant increases (4 percent). We identify several limitations of the current analytical framework for trend assessment but suggest that the overall sampling design is strong and amenable to analysis by more recently developed model-based methods. These could provide a more flexible framework for examining trends and other population parameters of interest, as well as testing hypotheses that relate the distribution and abundance of species to environmental covariates. A model-based approach would allow for modeling various components of the detection process and analyzing observations (detection process), population state (occupancy, population size, density), and change (trend, local extinction and colonization rates turnover) simultaneously. Finally, we also evaluate operational aspects of NCCN Landbird Monitoring Project, and conclude that our robust, multi-party partnership is successfully implementing the project as it was envisioned.

British Columbia;Oregon;Washington↗

USGS2007

A Deep Percolation Model for Estimating Ground-Water Recharge: Documentation of Modules for the Modular Modeling System of the U.S. Geological Survey

A daily water-budget model for estimating ground-water recharge, the Deep Percolation Model, was modularized for inclusion into the U.S. Geological Survey's Modular Modeling System. The model was modularized in order to facilitate estimation of ground-water recharge under a large range in climatic, landscape, and land-use and land-cover conditions. The model can be applied to areas as large as regions or as small as a field plot. An overview of the Modular Modeling System and the Deep Percolation Model is presented. Data requirements, parameters, and variables for the model are described. The modules that compose the Deep Percolation Model are documented.

Scientific Investigations Report↗

USGS2007

Nutrient and biological conditions of selected small streams in the Edwards Plateau, central Texas, 2005-06, and implications for development of nutrient criteria

During the summers of 2005 and 2006 the U.S. Geological Survey, in cooperation with the Texas Commission on Environmental Quality, evaluated nutrient and biological conditions in small streams in parts of the Edwards Plateau of Central Texas. Land-cover analysis was used to select 15 small streams that represented a gradient of conditions with the potential to affect nutrient concentrations across the study area, which comprises two of four subregions of the Edwards Plateau ecoregion. All 15 streams were sampled for water properties, nutrients, algae, benthic invertebrates, and fish in summer 2005, and eight streams were resampled in summer 2006. Streams that did not receive wastewater effluent had relatively low nutrient concentrations and were classified as oligotrophic; streams receiving wastewater effluent had relatively high nutrient concentrations and were classified as eutrophic. Nutrient concentrations measured in the least-disturbed streams closely matched the U.S. Environmental Protection Agency nutrient criteria recommendations based on estimated reference concentrations. Nitrogen/phosphorus ratios indicated streams not affected by wastewater effluent might be limited by phosphorus concentrations. Algal indicators of nutrient condition were closely related to dissolved nitrogen concentrations and streamflow conditions. Ambient dissolved nitrogen concentrations (nitrite plus nitrate) were positively correlated with benthic algal chlorophyll-a concentrations. The correlation of benthic algal chlorophyll-a with instantaneous nitrite plus nitrate load was stronger than correlations with ambient nutrients. Increased nutrient concentrations were associated with increased macroalgae cover, wider diel dissolved oxygen ranges, and reduced diel dissolved oxygen minimums. Benthic invertebrate aquatic life use scores generally were classified as High to Exceptional in study streams despite the influence of urbanization or wastewater effluent. Reductions in aquatic life use scores appeared to be related to extremely low flow conditions and the loss of riffle habitats. Benthic invertebrate aquatic life use scores and several of the metrics used to compute composite aquatic life use scores tended to increase with increasing total nitrogen concentrations. Fish community aquatic life use scores generally were classified as High or Exceptional with the exception of a few samples collected from streams receiving wastewater effluent that were classified as Intermediate. Fish community aquatic life use scores and several fish community metrics were positively correlated with nutrient concentrations and macroalgae cover. The majority of the positive correlations among nutrient concentrations, macroalgae cover, and fish metrics were strongly influenced by relatively high nutrient concentrations. Both benthic and planktonic chlorophyll-a measures were related to nutrients, but this study indicates that benthic chlorophyll-a was the better choice for monitoring nutrient enrichment because (1) the relation between benthic chlorophyll-a and nutrients was stronger, and (2) a strong relation between benthic chlorophyll-a and nutrients persisted after removal of the sites influenced by wastewater effluent, which indicates superior ability of benthic chlorophyll-a to discriminate between conditions at lower nutrient concentrations. The transect-based algal abundance estimate technique is a useful tool for identifying eutrophic conditions, assessing nuisance algal growth, and making broad comparisons among sites, but it appears to lack the fine resolution to identify lesser degrees of nutrient enrichment. Several individual benthic invertebrate and fish metrics were correlated with nutrient conditions, but correlations were generally positive and the reverse of what would be expected when nutrient enrichment causes a proliferation of algal growth and stream degradation. However, the benthic invertebrate functional feeding group metrics showed some

Scientific Investigations Report↗

USGS2025

Statistical streamflow comparison of current and historical 30-year periods for selected streams in New Jersey

As the population of New Jersey increases, supplying adequate drinking water to meet demand remains a high priority. To better understand potential streamflow trends over time, the U.S. Geological Survey completed a study comparing low flows at continuous- and partial-record streamgages in New Jersey between a historical period (1950–79) and a current period (1990–2019). Fourteen statistics (one median for each of the twelve monthly minimum 1-day flows, minimum 7-day average streamflow with a 10-year recurrence interval, and median of the daily mean flows for the month of September) were calculated to evaluate how streamflow conditions may differ between the two time periods. Percent change was also calculated to better understand the magnitude of difference between the periods at individual streamgages. A Paired Wilcoxon Signed-Rank Test was implemented to test for a change in distribution between the two time periods for each statistic of interest. Results indicated that the median of the minimum 1-day flows for the months of January, February, June, September, and December and the median of the daily mean flows for the month of September had a statistically significant difference in distribution between the time periods for continuous-record streamgages. None of the statistics had a statistically significant difference in distribution for the partial-record streamgages. The largest percent changes between time periods occurred in the northern part of the state, above the Fall Line. Precipitation, land cover, and water use changes were assessed to contribute to the understanding of these differences between time periods. The median of the minimum 1-day flows for the months of January and December generally increased across the state, whereas the median of the minimum 1-day flows for the months of May and September generally decreased throughout the state.

New Jersey↗

USGS2014

Global land cover mapping: a review and uncertainty analysis

Given the advances in remotely sensed imagery and associated technologies, several global land cover maps have been produced in recent times including IGBP DISCover, UMD Land Cover, Global Land Cover 2000 and GlobCover 2009. However, the utility of these maps for specific applications has often been hampered due to considerable amounts of uncertainties and inconsistencies. A thorough review of these global land cover projects including evaluating the sources of error and uncertainty is prudent and enlightening. Therefore, this paper describes our work in which we compared, summarized and conducted an uncertainty analysis of the four global land cover mapping projects using an error budget approach. The results showed that the classification scheme and the validation methodology had the highest error contribution and implementation priority. A comparison of the classification schemes showed that there are many inconsistencies between the definitions of the map classes. This is especially true for the mixed type classes for which thresholds vary for the attributes/discriminators used in the classification process. Examination of these four global mapping projects provided quite a few important lessons for the future global mapping projects including the need for clear and uniform definitions of the classification scheme and an efficient, practical, and valid design of the accuracy assessment.

Remote Sensing↗

USGS2018

Grasslands

Key findings: Total grassland carbon stocks in the conterminous United States, estimated to be about 7.4 petagrams of carbon (Pg C) in 2005, are projected to increase to about 8.2 Pg C by 2050. Although U.S. grasslands are expected to remain carbon sinks over this period, the uptake rate is projected to decline by about half. In the U.S. Great Plains, land-use and land-cover changes are expected to cause much of the change in carbon cycling as grasslands are converted to agricultural lands or to woody biomes (medium confidence). Increasing temperatures and rising atmospheric carbon dioxide (CO2) concentrations interact to increase productivity in northern North American grasslands, but this productivity response will be mediated by variable precipitation, soil moisture, and nutrient availability (high confidence, very likely). Soil carbon in grasslands is likely to be moderately responsive to changes in climate over the next several decades. Field experiments in grasslands suggest that altered precipitation can increase soil carbon, while warming and elevated CO2 may have only minimal effects despite altered productivity (medium confidence, likely). Carbon stocks and net carbon uptake in grasslands can be maintained with appropriate land management including moderate levels of grazing. Fire suppression can lead to encroachment of woody vegetation and increasing carbon storage in mesic regions, at the expense of grassland vegetation (high confidence, likely).

Report↗

USGS1986

A coefficient of agreement as a measure of thematic classification accuracy.

The classification error matrix typically contains tabulated results of accuracy evaluation for a thematic classification, such as a land-use and land-cover map. Diagonal elements of the matrix represent counts correct. The usual designation of classification accuracy has been total percent correct. Nondiagonal elements of the matrix have usually been neglected. A coefficient of agreement is determined for the interpreted map as a whole, and individually for each interpreted category. These coefficients utilize all cell values in the matrix.-from Authors

Photogrammetric Engineering and Remote Sensing↗

USGS2011

Disaster risk assessment case study: Recent drought on the Navajo Nation, USA

The Navajo Nation is an ecologically sensitive semi-arid to arid section of the southern Colorado Plateau. In this remote part of the United States, located at the Four Corners (Arizona, New Mexico, Colorado, and Utah), traditional people live a subsistence lifestyle that is inextricably tied to, and dependent upon, landscape conditions and water supplies. Soft bedrock lithologies and sand dunes dominate the region, making it highly sensitive to fluctuations in precipitation intensity, percent vegetation cover, and local land use practices. However, this region has sparse and discontinuous meteorological monitoring records. As a complement to the scant long-term meteorological records and historical documentation, we conducted interviews with 50 Native American elders from the Navajo Nation and compiled their lifetime observations on the changes in water availability, weather, and sand or dust storms. We then used these observations to further refine our understanding of the historical trends and impacts of climate change and drought for the region. In addition to altered landscape conditions due to climatic change, drought, and varying land use practices over the last 130 years, the Navajo people have been affected by federal policies and harsh economic conditions which weaken their cultural fabric. We conclude that a long-term drying trend and decreasing snowpack, superimposed on regional drought cycles, will magnify drought impacts on the Navajo Nation and leave its people increasingly vulnerable.

Report↗

USGS2017

A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011

Monitoring and mapping land cover changes are important ways to support evaluation of the status and transition of ecosystems. The Alaska National Land Cover Database (NLCD) 2001 was the first 30-m resolution baseline land cover product of the entire state derived from circa 2001 Landsat imagery and geospatial ancillary data. We developed a comprehensive approach named AKUP11 to update Alaska NLCD from 2001 to 2011 and provide a 10-year cyclical update of the state's land cover and land cover changes. Our method is designed to characterize the main land cover changes associated with different drivers, including the conversion of forests to shrub and grassland primarily as a result of wildland fire and forest harvest, the vegetation successional processes after disturbance, and changes of surface water extent and glacier ice/snow associated with weather and climate changes. For natural vegetated areas, a component named AKUP11-VEG was developed for updating the land cover that involves four major steps: 1) identify the disturbed and successional areas using Landsat images and ancillary datasets; 2) update the land cover status for these areas using a SKILL model (System of Knowledge-based Integrated-trajectory Land cover Labeling); 3) perform decision tree classification; and 4) develop a final land cover and land cover change product through the postprocessing modeling. For water and ice/snow areas, another component named AKUP11-WIS was developed for initial land cover change detection, removal of the terrain shadow effects, and exclusion of ephemeral snow changes using a 3-year MODIS snow extent dataset from 2010 to 2012. The overall approach was tested in three pilot study areas in Alaska, with each area consisting of four Landsat image footprints. The results from the pilot study show that the overall accuracy in detecting change and no-change is 90% and the overall accuracy of the updated land cover label for 2011 is 86%. The method provided a robust, consistent, and efficient means for capturing major disturbance events and updating land cover for Alaska. The method has subsequently been applied to generate the land cover and land cover change products for the entire state of Alaska.

Alaska↗

USGS1986

Development of labd cover and terrain databases for the Innoko National Wildlife Refuge, Alaska, using LANDSAT and digital terrain data

Landsat-derived land cover maps and associated elevation, slope, and aspect class maps were produced for the Innoko National Wildlife Refuge (3,850,000 acres; 1,555,095 hectares) in northwestern Alaska. These maps and associated digital data products are being used by the U. S. Fish and Wildlife Service for wildlife management, research, and comprehensive conservation planning. Portions of two Landsat Multispectral Scanner (MSS) scenes and digital terrain data were used to produce 1:250,000 scale land cover and terrain maps. Prints of summer and winter Landsat MSS scenes were used to manually interpret broad physiographic strata. These strata were transferred to U. S. Geological Survey 1:250,000-scale topographic maps and digitized. Seven major land cover classes and 23 subclasses were identified. The major land cover classes include: forest, scrub, dwarf scrub and related types, herbaceous, scarcely vegetated areas, water, and shadow.

Conference Paper↗

USGS2015

Using Landsat imagery to detect, monitor, and project net landscape change

Detailed landscape information is a necessary component to bird habitat conservation planning. The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center has been providing information on the Earth’s surface for over 40 years via the continuous series of Landsat satellites. In addition to operating, processing, and disseminating satellite images, EROS is the home to nationwide and global landscape mapping, monitoring, and projection products, including: National Land Cover Database (NLCD) – the definitive land cover dataset for the U.S., with updates occurring at five-year intervals; Global Land Cover Monitoring – producing 30m resolution global land cover; LANDFIRE – Landscape Fire and Resource Management Planning Tools–EROS is a partner in this joint program between U.S. Department of Agriculture and Department of Interior that produces consistent, comprehensive, geospatial data and databases that describe vegetation, wildland fuel, and fire regimes across the U.S.; Land Cover Trends – a landscape monitoring and assessment effort to understand the rates, trends, causes, and consequences of contemporary U.S. land use and land cover change; and Land Use and Land Cover (LULC) Modeling – a project extending contemporary databases of landscape change forward and backward in time through moderate-resolution land cover projections.

All Bird Bulletin↗

USGS2010

A priori evaluation of two-stage cluster sampling for accuracy assessment of large-area land-cover maps

Two-stage cluster sampling reduces the cost of collecting accuracy assessment reference data by constraining sample elements to fall within a limited number of geographic domains (clusters). However, because classification error is typically positively spatially correlated, within-cluster correlation may reduce the precision of the accuracy estimates. The detailed population information to quantify a priori the effect of within-cluster correlation on precision is typically unavailable. Consequently, a convenient, practical approach to evaluate the likely performance of a two-stage cluster sample is needed. We describe such an a priori evaluation protocol focusing on the spatial distribution of the sample by land-cover class across different cluster sizes and costs of different sampling options, including options not imposing clustering. This protocol also assesses the two-stage design's adequacy for estimating the precision of accuracy estimates for rare land-cover classes. We illustrate the approach using two large-area, regional accuracy assessments from the National Land-Cover Data (NLCD), and describe how the a priori evaluation was used as a decision-making tool when implementing the NLCD design.

International Journal of Remote Sensing↗

USGS2011

Thematic accuracy of the National Land Cover Database (NLCD) 2001 land cover for Alaska

The National Land Cover Database (NLCD) 2001 Alaska land cover classification is the first 30-m resolution land cover product available covering the entire state of Alaska. The accuracy assessment of the NLCD 2001 Alaska land cover classification employed a geographically stratified three-stage sampling design to select the reference sample of pixels. Reference land cover class labels were determined via fixed wing aircraft , as the high resolution imagery used for determining the reference land cover classification in the conterminous U.S. was not available for most of Alaska. Overall thematic accuracy for the Alaska NLCD was 76.2% (s.e. 2.8%) at Level II (12 classes evaluated) and 83.9% (s.e. 2.1%) at Level I (6 classes evaluated) when agreement was defined as a match between the map class and either the primary or alternate reference class label. When agreement was defined as a match between the map class and primary reference label only, overall accuracy was 59.4% at Level II and 69.3% at Level I. The majority of classification errors occurred at Level I of the classification hierarchy (i.e., misclassifications were generally to a different Level I class, not to a Level II class within the same Level I class). Classification accuracy was higher for more abundant land cover classes and for pixels located in the interior of homogeneous land cover patches.

Alaska↗

USGS2013

Estimation of sediment inflows to Lake Tuscaloosa, Alabama, 2009-11

The U.S. Geological Survey, in cooperation with the City of Tuscaloosa, evaluated the concentrations, loads, and yields of suspended sediment in the tributaries to Lake Tuscaloosa in west-central Alabama, from October 1, 2008, to January 31, 2012. The collection and analysis of these data will facilitate the comparison with historical data, serve as a baseline for future sediment-collection efforts, and help to identify areas of concern. Lake Tuscaloosa, at the reservoir dam, receives runoff from a drainage area of 423 square miles (mi 2 ). Basinwide in 2006, forested land was the primary land cover (68 percent). Comparison of historical imagery with the National Land Cover Database (2001 and 2006) indicated that the greatest temporal land-use change was timber harvest. The land cover in 2006 was indicative of this change, with shrub/scrub land (12 percent) being the secondary land use in the basin. Agricultural land use (10 percent) was represented predominantly by hay and pasture or grasslands. Urban land use was minimal, accounting for 4 percent of the entire basin. The remaining 6 percent of the basin has a land use of open water or wetlands. Storm and monthly suspended-sediment samples were collected from seven tributaries to Lake Tuscaloosa: North River, Turkey Creek, Binion Creek, Pole Bridge Creek, Tierce Creek, Carroll Creek, and Brush Creek. Suspended-sediment concentrations and streamflow measurements were statistically analyzed to estimate annual suspended-sediment loads and yields from each of these contributing watersheds. Estimated annual suspended-sediment yields in 2009 were 360, 540, and 840 tons per square mile (tons/mi 2 ) at the North River, Turkey Creek, and Carroll Creek streamflow-gaging stations, respectively. Estimated annual suspended-sediment yields in 2010 were 120 and 86 tons/mi 2 at the Binion Creek and Pole Bridge Creek streamflow-gaging stations, respectively. Estimated annual suspended-sediment yields in 2011 were 190 and 300 tons/mi 2 at the Tierce Creek and Brush Creek streamflow-gaging stations, respectively. The North River watershed at the streamflow-gaging station contributes 53 percent of the drainage area for Lake Tuscaloosa. A previous study in the 1970s analyzed streamflow and historical suspended-sediment samples to estimate a long-term average suspended-sediment yield of 300 tons per year per square mile in the North River watershed. Analysis of data collected in the North River watershed during the 2009 water year (October 2008 to September 2009) estimated a sediment yield of 360 tons/mi 2 . The North River watershed, a major portion of the Lake Tuscaloosa drainage basin, has not experienced a substantial increase in sedimentation rates. During the 2009 water year, the Turkey Creek watershed (6.16 mi 2 ) and the Carroll Creek watershed (20.9 mi 2 ) produced greater suspended-sediment yields than the North River watershed but contribute a much smaller drainage area to Lake Tuscaloosa. Aerial photography and bathymetric surveys indicate that Carroll Creek has experienced increased sediment deposition in the upstream portions of the channel. Carroll Creek is also the only watershed in the current study that has a substantial percentage (11 percent) of urban

Alabama↗

USGS2022

Detection and characterization of coastal tidal wetland change in the northeastern US using Landsat time series

Coastal tidal wetlands are highly altered ecosystems exposed to substantial risk due to widespread and frequent land-use change coupled with sea-level rise, leading to disrupted hydrologic and ecologic functions and ultimately, significant reduction in climate resiliency. Knowing where and when the changes have occurred, and the nature of those changes, is important for coastal communities and natural resource management . Large-scale mapping of coastal tidal wetland changes is extremely difficult due to their inherent dynamic nature. To bridge this gap, we developed an automated algorithm for DEtection and Characterization of cOastal tiDal wEtlands change (DECODE) using dense Landsat time series. DECODE consists of three elements, including spectral break detection, land cover classification and change characterization. DECODE assembles all available Landsat observations and introduces a water level regressor for each pixel to flag the spectral breaks and estimate harmonic time-series models for the divided temporal segments. Each temporal segment is classified (e.g., vegetated wetlands, open water, and others – including unvegetated areas and uplands) based on the phenological characteristics and the synthetic surface reflectance values calculated from the harmonic model coefficients, as well as a generic rule-based classification system. This harmonic model-based approach has the advantage of not needing the acquisition of satellite images at optimal conditions (i.e., low tide status) to avoid underestimating coastal vegetation caused by the tidal fluctuation. At the same time, DECODE can also characterize different kinds of changes including land cover change and condition change (i.e., land cover modification without conversion). We used DECODE to track status of coastal tidal wetlands in the northeastern United States from 1986 to 2020. The overall accuracy of land cover classification and change detection is approximately 95.8% and 99.8%, respectively. The vegetated wetlands and open water were mapped with user's accuracy of 94.6% and 99.0%, and producer's accuracy of 98.1% and 93.5%, respectively. The cover change and condition change were mapped with user's accuracy of 68.0% and 80.0%, and producer's accuracy of 80.5% and 97.1%, respectively. Approximately 3283 km 2 of the coastal landscape within our study area in the northeastern United States changed at least once (12% of the study area), and condition changes were the dominant change type (84.3%). Vegetated coastal tidal wetland decreased consistently (~2.6 km 2 per year) in the past 35 years, largely due to conversion to open water in the context of sea-level rise.

Remote Sensing of Environment↗

USGS2018

Inventory of lowland-breeding birds on the Alaska Peninsula

We conducted the first systematic inventory of birds in the lowlands (areas ≤100 m above sea level) of the Alaska Peninsula during summers of 2004–2007 to determine their breeding distributions and habitat associations in this remote region. Using a stratified random survey design, we allocated sample plots by elevation and land cover with a preference for wetland cover types used by shorebirds, a group of particular interest to land managers. We surveyed birds during 10-min counts at 792 points across 52, 5 km × 5 km sample plots distributed from south of the Naknek River (58.70°N,157.00°W) to north of Port Moller (56.00°N,160.52°W). We detected 95 bird species including 19 species of shorebirds and 34 species (36% of total) considered at the time to be of conservation concern for the land managers in the region. The most numerous shorebirds on point counts were dunlin Calidris alpina, short-billed dowitcher Limnodromus griseus, and Wilson's snipe Gallinago delicata. We found the breeding-season endemic marbled godwit Limosa fedoa beringiae at 20 plots within a 3,000-km 2 area from north of Ugashik Bay to just north of Port Heiden and east to the headwaters of the Dog Salmon and Ugashik rivers. The most abundant passerines on point counts were American tree sparrow Spizelloides arborea, Lapland longspur Calcarius lapponicus, and savannah sparrow Passerculus sandwichensis. Sandhill crane Antigone canadensis, glaucous-winged gull Larus glaucescens, and greater scaup Aythya marila were also relatively abundant. We categorized habitat associations for 30 common species and found that lowland herbaceous vegetation supported wetland-focused species including sandhill crane, marbled godwit, short-billed dowitcher, and dunlin; whereas, dwarf shrub-ericaceous vegetation supported tundra-associated species such as willow ptarmigan Lagopus lagopus, rock sandpiper Calidris ptilocnemis, and American pipit Anthus rubescens . Tall shrub vegetation was important to several species of warblers and sparrows, as well as one species of shorebird (greater yellowlegs Tringa melanoleuca ). We found that point counts augmented with incidental observations provided an almost complete inventory of lowland-breeding species on the study area. These data form a baseline to monitor any future changes in bird distribution and abundance on the Alaska Peninsula.

Alaska↗