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By selecting one of the four series options shown below, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively, the user will be taken to that map.
The task of accurately mapping species-specific vegetation cover in remote and topographically complex regions like those found in Hawaiʻi presents unique challenges. This study leverages a machine learning approach to accurately classify vegetation into fine species-specific classes across the island of Lāna‘i, Hawaii, offering a novel methodology for tackling such challenges. Utilizing high-resolution WordView-2 satellite imagery, a neural network classifier and a custom lidar-based geometric correction, we introduced two new approaches to refine our high-resolution land cover classifications. This included the implementation of prior-based adjustments to class posterior probabilities to enhance land cover classification accuracy. Moreover, we developed mixed hierarchical classification maps that use class posterior probabilities to identify, at the pixel level, the finest land cover class that meets a user-defined confidence threshold. The resulting high-resolution land cover map for Lāna‘i captures the rich diversity and distribution of native and invasive plant species with high overall accuracy, generally exceeding 95%, based on independent ground control data. The capacity to produce wall-to-wall species-level vegetation maps provides a new window into monitoring vegetation dynamics on Lāna‘i and similarly remote and topographically complex regions, and contributes to our broader understanding of ecosystem responses to invasive species, climatic changes, and land management practices such as erosion and sediment control planning. Our approach offers a blueprint for similar efforts in other complex and remote ecosystems.
By selecting one of the four series options shown below, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively, the user will be taken to that map.
By selecting one of the four series options shown below, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively, the user will be taken to that map.
By selecting one of the four series options shown below, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively, the user will be taken to that map.
By selecting one of the four series options shown below, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively, the user will be taken to that map.
By selecting one of the four series options shown below, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively, the user will be taken to that map.
By selecting one of the four series options shown below, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively, the user will be taken to that map.
By selecting one of the four series options shown below, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively, the user will be taken to that map.
Flood‐inundation data are most useful for decision makers when presented in the context of maps of affected communities and (or) areas. But because the data are scarce and rarely cover the full extent of the flooding, interpolation and extrapolation of the information are needed. Many geographic information systems provide various interpolation tools, but these tools often ignore the effects of the topographic and hydraulic features that influence flooding. A barrier mapping method was developed to improve maps of storm tide produced by Hurricane Rita. Maps were developed for the maximum storm tide and at 3‐h intervals from midnight (00:00 hours) through noon (12:00 hours) on 24 September 2005. The improved maps depict storm‐tide elevations and the extent of flooding. The extent of storm‐tide inundation from the improved maximum storm‐tide map was compared with the extent of flood inundation from a map prepared by the Federal Emergency Management Agency (FEMA). The boundaries from these two maps generally compared quite well especially along the Calcasieu River. Also a cross‐section profile that parallels the Louisiana coast was developed from the maximum storm‐tide map and included FEMA high‐water marks.
Differential interferometric synthetic aperture radar (SAR) (DInSAR) has proven to be very useful in mapping and monitoring land subsidence in many regions of the world. Shanghai, China's largest city, is one of such areas suffering from land subsidence as a result of severe withdrawal of groundwater for different usages. DInSAR application in Shanghai with the C-band European Remote Sensing 1 & 2 (ERS-1/2) SAR data has been difficult mainly due to the problem of decorrelation of InSAR pairs with temporal baselines larger than 10 months. To overcome the coherence loss of C-band InSAR data, we used eight L-band Japanese Earth Resource Satellite (JERS-1) SAR data acquired during 2 October 1992 to 15 July 1998 to study land subsidence phenomenon in Shanghai. Three of the images were used to produce two separate digital elevation models (DEMs) of the study area to remove topographic fringes from the interferograms used for subsidence mapping. Six interferograms were used to generate 2 different time series of deformation maps over Shanghai. The cumulative subsidence map generated from each of the time series is in agreement with the land subsidence measurements of Shanghai city from 1990-1998, produced from other survey methods. ?? 2007 IEEE.
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The U.S. Geological Survey has generated a comprehensive data clearinghouse of digital vector cliff edges and associated rates of cliff retreat along the open-ocean California coast. These data, which are presented herein, were compiled as part of the U.S. Geological Survey's National Assessment of Shoreline Change Project. Cliff erosion is a chronic problem along many coastlines of the United States. As coastal populations continue to grow and community infrastructures are threatened by erosion, there is increased demand for accurate information including rates and trends of coastal cliff retreat. There is also a critical need for these data to be consistent from one region to another. One objective of this work is to a develop standard, repeatable methodology for mapping and analyzing cliff edge retreat so that periodic, systematic, and internally consistent updates of cliff edge position and associated rates of erosion can be made at a national scale. This data compilation for open-ocean cliff edges for the California coast is a separate, yet related study to Hapke and others, 2006 documenting shoreline change along sandy shorelines of the California coast, which is itself one in a series that includes the Gulf of Mexico and the Southeast Atlantic coast (Morton and others, 2004; Morton and Miller, 2005). Future reports and data compilations will include coverage of the Northeast U.S., the Great Lakes, Hawaii and Alaska. Cliff edge change is determined by comparing the positions of one historical cliff edge digitized from maps with a modern cliff edge derived from topographic LIDAR (light detection and ranging) surveys. Historical cliff edges for the California coast represent the 1920s-1930s time-period; the most recent cliff edge was delineated using data collected between 1998 and 2002. End-point rate calculations were used to evaluate rates of erosion between the two cliff edges. Please refer to our full report on cliff edge erosion along the California coastline at http://pubs.usgs.gov/of/2007/1133/ for additional information regarding methods and results (Hapke and others, 2007). Data in this report are organized into downloadable layers by region (Northern, Central and Southern California) and are provided as vector datasets with accompanying metadata. Vector cliff edges may represent a compilation of data from one or more sources and the sources used are included in the dataset metadata. This project employs the Environmental Systems Research Institute's (ESRI) ArcGIS as it's Geographic Information System (GIS) mapping tool and contains several data layers (shapefiles) that are used to create a geographic view of the California coast. The vector data form a basemap comprising polygon and line themes that include a U.S. coastline (1:80,000), U.S. cities, and state boundaries.
The U.S. Geological Survey, in cooperation with the Rockdale County Department of Water Resources, conducted a bathymetric and topographic survey of Randy Poynter Lake in northern Georgia in 2012. The Randy Poynter Lake watershed drains surface area from Rockdale, Gwinnett, and Walton Counties. The reservoir serves as the water supply for the Conyers-Rockdale Big Haynes Impoundment Authority. The Randy Poynter reservoir was surveyed to prepare a current bathymetric map and determine storage capacities at specified water-surface elevations. Topographic and bathymetric data were collected using a marine-based mobile mapping unit to estimate storage capacity. The marine-based mobile mapping unit operates with several components: multibeam echosounder, singlebeam echosounder, light detection and ranging system, navigation and motion-sensing system, and data acquisition computer. All data were processed and combined to develop a triangulated irregular network, a reservoir capacity table, and a bathymetric contour map.
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We use laser altimetry from the Ice, Cloud, and land Elevation Satellite (ICESat) to map the grounding zone (GZ) of the Ross Ice Shelf, Antarctica, at 491 locations where ICESat tracks cross the grounding line (GL). Ice flexure in the GZ occurs as the ice shelf responds to short-term sea-level changes due primarily to tides. ICESat repeat-track analysis can be used to detect this region of flexure since each repeated pass is acquired at a different tidal phase; the technique provides estimates for both the landward limit of flexure and the point where the ice becomes hydrostatically balanced. We find that the ICESat-derived landward limits of tidal flexure are, in many places, offset by several km (and up to ∼60 km) from the GL mapped previously using other satellite methods. We discuss the reasons why different mapping methods lead to different GL estimates, including: instrument limitations; variability in the surface topographic structure of the GZ; and the presence of ice plains. We conclude that reliable and accurate mapping of the GL is most likely to be achieved when based on synthesis of several satellite datasets
In order to highlight this project to the extraterrestrial mapping community, we repeat here our earlier abstract [1], with a corrected Figure 2. A report describing the Unified Lunar Control Network 2005 and the files associated with that network is now available as an on-line USGS Open-File Report [2] at the location http://pubs.usgs.gov/of/2006/1367/. A “Readme” file describes the available files, including the report text, the original photogrammetric solution input and output files, derived files such as information on all the control point positions, the expected vertical precision (EVP) of the points and the solution residuals, and a directory containing global DEMs derived from the point positions. While a paper providing further details about the solution is in preparation, we provide some useful additional information about the solution and possible uses for it here.
By selecting one of the four series options shown below, namely, -A, -B, -C, and -D for the geologic, topographic, Landsat natural-color, and Landsat false-color maps, respectively, the user will be taken to that map.