Introduction to surficial seafloor mapping and characterization
No abstract available.
GSA Special Papers↗
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A passive microwave snow depth algorithm with a proxy for snow metamorphism
Passive microwave brightness temperatures of snowpacks depend not only on the snow depth, but also on the internal snowpack properties, particularly the grain size, which changes through the winter. Algorithms that assume a constant grain size can yield erroneous estimates of snow depth or water equivalent. For snowpacks that are subject to temperatures well below freezing, the bulk temperature gradient through the snowpack controls the metamorphosis of the snow grains. This study used National Weather Service (NWS) station measurements of snow depth and air temperature from the Northern US Great Plains to determine temporal and spatial variability of the snow depth and bulk snowpack temperature gradient. This region is well suited for this study because it consists primarily of open farmland or prairie, has little relief, is subject to very cold temperatures, and has more than 280 reporting stations. A geostatistical technique called Kriging was used to grid the randomly spaced snow depth measurements. The resulting snow depth maps were then compared with the passive microwave observations from the Special Sensor Microwave Imager (SSM/I). Two snow seasons were examined: 1988-89, a typical snow year, and 1996-97, a record year for snow that was responsible for extensive flooding in the Red River Basin. Inspection of the time series of snow depth and microwave spectral gradient (the difference between the 19 and 37 GHz bands) showed that while the snowpack was constant, the spectral gradient continued to increase. However, there was a strong correlation (0.6 < R2 < 0.9) between the spectral gradient and the cumulative bulk temperature gradient through the snowpack (TGI). Hence, TGI is an index of grain size metamorphism that has occurred within the snowpack. TGI time series from 21 representative sites across the region and the corresponding SSM/I observations were used to develop an algorithm for snow depth that requires daily air temperatures. Copyright ?? 2002 John Wiley & Sons, Ltd.
Hydrological Processes↗
Albedo boundaries on Mars in 1972: Results from Mariner 9
A map of “albedo” boundaries (light and dark markings) on Mars was prepared from Mariner 9 images. After special digital processing, these pictures provide detailed locations of albedo boundaries, which is significant in interpreting recent eolian activity. Derivation of absolute albedo values from the spacecraft data was not attempted. The map correlates well with telescopic observations of Mars after the 1971 dust storm.
Icarus↗
Vegetation classification and distribution mapping report: Canyon de Chelly National Monument
Executive Summary: The classification and distribution mapping of the vegetation of Canyon de Chelly National Monument (CACH) and surrounding environment was accomplished through a multi-agency effort between 2003 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center and Fort Collins Science Center, Navajo Natural Heritage Program, Northern Arizona University, and NatureServe. The project team described 48 plant communities for CACH—35 of which were described from quantitative classification based on field-relevé data collected in 2004. Five additional plant communities were based on field relevés collected in a previous study. The team derived four additional plant communities from field observations during the photointerpretation phase of the project, and field documented them during accuracy assessment. The National Vegetation Classification Standard served as a conceptual framework for assigning these plant communities to the alliance and association level. Ten of the 48 plant communities were designated “park specials”, that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing CACH, with three different map-class schemas: base, group, and management map classes. The base map classes represented the finest level of spatial detail. Photointerpreters delineated initial polygons through manual interpretation of 2003/2004 1:12,000-scale true color aerial photography supplemented by occasional computer screen digitizing on a mosaic of digitized aerial photos. These polygons were labeled with base map classes during photointerpretation. Field visits verified interpretation concepts. The vegetation map database includes • ? 53 base map classes, which consist of associations and park specials classified with the quantitative analysis • ? additional associations noted during photointerpretation • ? non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 4,718 polygons in the project area. A field-based accuracy assessment of the base map classes showed the overall accuracy to be 50.8% The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, Version 2 (Federal Geographic Data Committee 2008). Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as a first approximation of the group level. The project team identified 16 group map classes in this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 79.9%. In consultation with park staff, the team developed management map classes that consisted of park-defined groupings of base map classes and were intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 28 management map classes have an overall accuracy of 77.1%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary geographic information system and digital database products were also produced that can be used independently, or to augment the main products. These products include shapefiles of the location of field-collected data and relational databases of field-collected data.
Report↗
Vegetation classification and distribution mapping report: Mesa Verde National Park
The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe. The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts. The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover. The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%. In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.
Mesa Verde National Park↗
Remote sensing studies of the geomorphology of Surtsey, 1987-1991
The volcanic island of Surtsey, formed by explosive submarine and effusive subaerial eruptions between November 1963 and June 1967, consists of a complex combination of primary and redeposited tephra and alkaline olivine basalt lava flows in a 2.5 km 2 area (Thorarinsson, 1967; Thorarinsson et al., 1964; Fridriksson, 1975). During the past 24 years, wave and wind erosion of this subaerial mid-ocean ridge (MOR) vent complex have modified Surtsey's coastal morphology, including the deposition of a 0.5 km-long northern peninsula ( ness ) composed of tephra and rounded lava fragments derived from the southern half of the island. Detailed geomorphologic and sedimentologic mapping of the various surface units now present on Surtsey has been accomplished throughout the history of the evolving island, most recently by Calles et al. (1980) and Ingolfsson (1980). On the basis of these studies, an effort to quantify the topographic characteristics of the primary geomorphic units on the island was initiated by the National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS) in 1987. The objective has been to directly measure the microtopographic properties of the widest range of surface types possible, with special emphasis on the pristine or dynamic types. While large-scale topographic maps of Surtsey were prepared in 1968 and 1975 (Norrman, 1980; Norrman and Erlingsson, 1991; Calles et al, 1980), and geodetic leveling surveys have been carried out (Moore, 1980), there have been no recent attempts to geodetically determine the local topography of the island. Because of the rapid rates of geomorphic processes, such as erosion and deposition, on a small, geologically isolated volcanic island such as Surtsey, it is desirable to determine the meter-scale topographic character of its surface units and landforms, and later a remeasurement of the same surfaces to further quantify volumetric change, subsidence, and process rates. In addition, precise measurements of sub-meter-scale topography of pristine geologic surfaces provides necessary data for the investigation of whether various geologic processes demonstrate fractal or self-affine behavior at a range of length-scales within the interval 0.1 in to 1 km. Thus Surtsey offers a unique opportunity to apply new remote sensing techniques to the measurement of the evolving surface "roughness" characteristics of pristine geologic surfaces within an historically well-monitored environment.
Surtsey Research Progress Report↗
Chemical composition of sedimentary rocks in California and Hawaii
A compilation of published chemical analyses of sedimentary rocks of the United States was undertaken by the U.S. Geological Survey in 1952 to make available scattered data that are needed for a wide range of economic and scientific uses. About 20,000-25,000 chemical analyses of sedimentary rocks in the United States have been published. This report brings together 2,312 of these analyses from California and Hawaii. The samples are arranged by general lithologic characteristics and locality. Indexes of stratigraphy, rock name, commercial uses, and minor elements are provided. The sedimentary rocks are classified into groups and into categories according to the chemical analyses. The groups (A through F2) are defined by a system similar to that proposed by Brian Mason in 1952, in which the main parameters are the three major components of sedimentary rocks: (1) uncombined silica, (2) clay (R203 ? 3Si02 ? nH20), and (3) calcium-magnesium carbonate. The categories are based on the degree of admixture of these three major components with other components, such as sulfate, phos- phate, and iron oxide. Common-rock, mixed-rock, and special-rock categories apply to rocks consisting of 85 percent or more, 50-84 percent, and less than 49 percent, respectively, of the three major components combined. Maps show distribution of sample localities by States; triangular diagrams show the lithologic characteristics and classification groups. Cumulative-frequency curves of each constituent in each classification group of the common-rock and mixed-rock categories are also included. The numerous analyses may not adequately represent the geochemical nature of the rock types and formations of the region because of sampling bias. Maps showing distribution of sample localities indicate that many of the localities are in areas where, for economic or other reasons, special problems attracted interest. Most of the analyzed rocks tended to be fairly simple in composition - mainly mixtures of just two of the three major components or a mixture of these and a fourth component such as phosphate, gypsum, or iron oxide.
Professional Paper↗
Quantifying the visual-sensory landscape qualities that contribute to cultural ecosystem services using social media and LiDAR
Landscapes are increasingly recognized for providing valuable cultural ecosystem services with numer- ous non-material benefits by serving as places of rest, relaxation, and inspiration that ultimately improve overall mental health and physical well-being. Maintaining and enhancing these valuable benefits through targeted management and conservation measures requires understanding the spatial and tem- poral determinants of perceived landscape values. Content contributed through mobile technologies and the web are emerging globally, providing a promising data source for localizing and assessing these land- scape benefits. These georeferenced data offer rich in situ qualitative information through photos and comments that capture valued and special locations across large geographic areas. We present a novel method for mapping and modeling landscape values and perceptions that leverages viewshed analysis of georeferenced social media data. Using a high resolution LiDAR (Light Detection and Ranging) derived digital surface model, we are able to evaluate landscape characteristics associated with the visual- sensory qualities of outdoor recreationalists. Our results show the importance of historical monuments and attractions in addition to specific environmental features which are appreciated by the public. Evaluation of photo-image content highlights the opportunity of including temporally and spatially vari- able visual-sensory qualities in cultural ecosystem services (CES) evaluation like the sights, sounds and smells of wildlife and weather phenomena.
North Carolina↗
Geologic map of Lake Mead and surrounding regions, southern Nevada, southwestern Utah, and northwestern Arizona
Regional stratigraphic units and structural features of the Lake Mead region are presented as a 1:250,000 scale map, and as a Geographic Information System database. The map, which was compiled from existing geologic maps of various scales, depicts geologic units, bedding and foliation attitudes, faults and folds. Units and structural features were generalized to highlight the regional stratigraphic and tectonic aspects of the geology of the Lake Mead region. This map was prepared in support of the papers presented in this volume, Special Paper 463, as well as to facilitate future investigations in the region. Stratigraphic units exposed within the area record 1800 million years of geologic history and include Proterozoic crystalline rocks, Paleozoic and Mesozoic sedimentary rocks, Mesozoic plutonic rocks, Cenozoic volcanic and intrusive rocks, sedimentary rocks and surficial deposits. Following passive margin sedimentation in the Paleozoic and Mesozoic, late Mesozoic (Sevier) thrusting and Late Cretaceous and early Tertiary compression produced major folding, reverse faulting, and thrust faulting in the Basin and Range, and resulted in regional uplift and monoclinal folding in the Colorado Plateau. Cenozoic extensional deformation, accompanied by sedimentation and volcanism, resulted in large-magnitude high- and low-angle normal faulting and strike-slip faulting in the Basin and Range; on the Colorado Plateau, extension produced north-trending high-angle normal faults. The latest history includes integration of the Colorado River system, dissection, development of alluvial fans, extensive pediment surfaces, and young faulting. Stratigraphic units exposed within the area record 1800 million years of geologic history and include Proterozoic crystalline rocks, Paleozoic and Mesozoic sedimentary rocks, Mesozoic plutonic rocks, Cenozoic volcanic and intrusive rocks, sedimentary rocks and surfi cial deposits. Following passive margin sedimentation in the Paleozoic and Mesozoic, late Mesozoic (Sevier) thrusting and Late Cretaceous and early Tertiary compression produced major folding, reverse faulting, and thrust faulting in the Basin and Range, and resulted in regional uplift and monoclinal folding in the Colorado Plateau. Cenozoic extensional deformation, accompanied by sedimentation and volcanism, resulted in large-magnitude high- and low-angle normal faulting and strike-slip faulting in the Basin and Range; on the Colorado Plateau, extension produced north-trending high-angle normal faults. The latest history includes integration of the Colorado River system, dissection, development of alluvial fans, extensive pediment surfaces, and young faulting.
Arizona, Nevada, Utah↗
Military geology unit of the U.S. Geological Survey during World War II
On June 24, 1942, the temporary Military Geology Unit of the U.S. Geological Survey was formalized after the U.S. Army Corps of Engineers requested them to prepare terrain intelligence studies to meet wartime priorities. The entire Military Geology Unit wartime roster was 114 professionals, including 88 geologists, 11 soil scientists, and 15 other specialists; 14 were women. Assisting staff (illustrators, typists, photographers, and others) totaled 43. The unit produced 313 studies, including 140 major terrain folios, 42 other major special reports, and 131 minor studies. These reports contain about 5,000 maps, 4,000 photographs and figures, 2,500 large tables, and 140 terrain diagrams. Most products were designed in the beginning for general strategic planning in Washington and later for detailed strategic planning overseas; they utilized graphics and nontechnical, telegraphic-style tabular texts. The Military Geology Unit's principal effort was the preparation of the terrain folios titled Strategic Engineering Studies. They varied somewhat in content and format, but the key components usually were introduction, terrain appreciation, rivers, road and airfield construction, construction materials, and water resources. The folios, produced at an average rate of about one per week and at an average cost of $2,500, were compiled from scientific journals, books, maps, and photographs available in the Washington area by a team of 3 to 8 scientists; 8 to 12 teams might be working concurrently. MGU personnel took great pride in never having missed a delivery deadline.
Book chapter↗
A cotangent ruler for simplifying the graphic solution of problems in structural geology
The cotangent ruler is a device for measuring directly the dip of contoured surfaces, or, conversely, for constructing contours that represent planes of known dip. It greatly simplifies the graphic solution of problems in structural geology, and has several specialized applications to problems commonly encountered in mining geology and areal geologic mapping.
Economic Geology↗
USGS maps
Discover a small sample of the millions of maps produced by the U.S. Geological Survey (USGS) in its mission to map the Nation and survey its resources. This booklet gives a brief overview of the types of maps sold and distributed by the USGS through its Earth Science Information Centers (ESIC) and also available from business partners located in most States. The USGS provides a wide variety of maps, from topographic maps showing the geographic relief and thematic maps displaying the geology and water resources of the United States, to special studies of the moon and planets.
General Information Product↗
Map data catalog
The National Cartographic Information Center (NCIC) is the information branch of the National Mapping Program, U.S. Geological Survey. NCIC's mission is to help users gain better, faster, low-cost access to the cartographic holdings of Federal, State, and private agencies. This catalog tells how to order a wide range of mapping byproducts that may help to fill one or more of your special needs. For each such product, the catalog: - Describes and illustrates the product offered. - Explains the scope of geographic coverage available. - Lists typical uses of the product. - Explains how to order the products you need. Only a few of the products listed in this catalog are stocked. Most of them must be custom-produced to meet your particular requirement. Prices for the variety of products, formats and sizes are contained in a separate and periodically updated list. The price list is available free upon request from any NCIC office.
Report↗
Natural resource inventory and monitoring for Ulaan Taiga Specially Protected Areas—An assessment of needs and opportunities in northern Mongolia
Between 1997 and 2011, Mongolia established three specially protected areas in the north-central part of the country to protect various high-value resources. These areas are jointly referred to as the Ulaan Taiga Specially Protected Areas. In accordance with the goals of the draft general management plan, this report identifies options for initiating an inventory and monitoring program for the three protected areas. Together, the three areas comprise over 1.5 million hectares of mountainous terrain west of Lake Hovsgol and bordering the Darkhad Valley. The area supports numerous rare ungulates, endangered fish, and over 40 species of threatened plants. Illegal mining, illegal logging, and poaching pose the most immediate threats to resources. As a first step, a review of published literature would inform natural resource management at the Ulaan Taiga Specially Protected Areas because it would inform other inventories. Vegetation classification and mapping also would inform other inventory efforts because the process incorporates geographic analysis to identify environmental gradients, fine-scale sampling that captures species composition and structure, and landscape-scale results that represent the variety and extent of habitats for various organisms. Mapping using satellite imagery reduces the cost per hectare. Following a determination of existing knowledge, field surveys of vertebrates and vascular plants would serve to build species lists and fill in gaps in existing knowledge. For abiotic resources, a focus on monitoring air quality, evaluating and monitoring water quality, and assembling and storing weather data would provide information for correlating resource response status with changing environmental conditions. Finally, we identify datasets that, if incorporated into a geographic information system, would inform resource management. They include political boundaries, infrastructure, topography, surficial geology, hydrology, fire history, and soils. In terms of tracking high-value resources, vegetation monitoring at the plot scale would provide a basis for detecting change in such characteristics as plant species composition, vegetation structure, and productivity that are associated with landscape-scale factors such as climate change or biotic interactions. Continued population monitoring of rare ungulates, particularly argali or wild sheep ( Ovis ammon ), would provide information on how populations are responding to natural and anthropogenic stressors. Siberian taimen ( Hucho taimen ) also is an important monitoring target given ongoing threats of poaching and climate change.
Ulaan Taiga Specially Protected Areas↗
Potential impacts of projected climate change on vegetation-management strategies in Hawai‘i Volcanoes National Park
Climate change is expected to alter the seasonal and annual patterns of rainfall and temperature in the Hawaiian Islands. Land managers and other responsible agencies will need to know how plant-species habitats will change over the next century in order to manage these resources effectively. This issue is a major concern for resource managers at Hawai‘i Volcanoes National Park (HAVO), where currently managed Special Ecological Areas (SEAs) for important plant species and communities may no longer provide suitable habitats in the future as the climate changes. Expanding invasive-species distributions also may pose a threat to areas where native plants currently predominate. The objective of this project was to combine recent climate-modeling efforts for the state of Hawai‘i with existing models of plant-species distribution in order to forecast suitable habitat ranges under future climate conditions derived from the Coupled Model Intercomparison Project, phase 3 (CMIP3) global circulation model that was dynamically downscaled for the Hawaiian Islands by using the Hawai‘i Regional Climate Model (HRCM). The HRCM uses the A1B emission scenario (a median future climate projection) from the Special Report on Emissions Scenarios (SRES). On the basis of this model, maps showing projected plant-species ranges were generated for four years as snapshots in time (2000, 2040, 2070, 2090) and for three different trajectories of climate change (gradual, linear, rapid) between the present and future. We mapped probabilistic surfaces of suitable habitat for 39 plant species (both native and alien [nonnative]) identified as being of interest to HAVO resource managers. We displayed these surfaces in terms of change relative to present conditions, whether the range of a given plant species was expected to contract, expand, or remain the same in the future. Within HAVO, approximately two-thirds (18 of 29) of the modeled native plant species were projected to contract in range, whereas one-third (11 of 29) were projected to increase. Most of the HAVO SEAs were projected to lose most of the native plant species modeled. Within HAVO, all alien plant species except Lantana camara were projected to contract in range within the park; this trend was observed in most SEAs, including those at low, middle, and high elevations. Congruence was good in the “current” (2000) distribution of plant-species richness and SEA configurations; however, the congruence between species-richness hotspots and SEAs diminished by the projected “end-of-century” (2090) distribution. Over time, the projected species-richness hotspots increasingly occurred outside of the currently configured SEA boundaries.
Hawai'i↗
Analysis and machine mapping of the distribution of band recoveries.
Explore the source record for details and available documents.
Special Scientific Report - Wildlife↗
Geologic map and borehole stratigraphy of Hinkley Valley and vicinity, San Bernardino County, California
Hinkley Valley, in the central to western Mojave Desert of southeastern California, has a long historical record owing to its position as a crossroads for rail and road traffic and its position adjacent to the Mojave River. Subflow in the Mojave River provided groundwater recharge that maintained water consumption and demand by way of shallow wells for local agriculture in the valley. Its crossroads position led to construction of several power-transmission lines, pipeline, and communications cable routes that transect Hinkley Valley. One of these, a natural gas pipeline and its associated compressor station, was the locus of hexavalent chromium, Cr(VI), released into, and consequent contamination of, groundwater. Understanding the movement and fate of the contaminants is a complex hydrologic and geochemical problem. Geologic mapping of the Hinkley Valley area provides framework elements for use in resolving this problem. This report provides new information on surface and subsurface geology to better constrain the origin and geometry of hydrologically important deposits in the Hinkley Valley area and describes youthful faults that may control sediment distribution and groundwater flow. The geologic map (sheet 1) presents substantial new information on surficial geology, including Pliocene deposits, but does not contain significant new work on bedrock. Bedrock investigations were specific to identifying youthful faults and representative outcrops for rocks that were penetrated by boreholes in the valley. Special attention was placed on locating and describing youthful faults. In addition, we analyzed gravity data to (1) map horizontal gradients that we interpret to reflect long-term fault traces and to (2) estimate the depth to bedrock, which is defined as Miocene and older intrusive and metamorphic rocks for the purposes of this report. The subsurface geology of Hinkley Valley was investigated by examining borehole sediment cores and rock encountered at the base of the sediment section. We analyzed the core to determine depositional environments, provenance, and age of the sediment that infilled the valley. Valleys, mountains, and basins in the Hinkley Valley area are topographically complex and incompletely named. The nearly flat floored Hinkley Valley slopes gently northward. It is framed by Mount General and the informally named “Hinkley hills” (southeast of Mount General) on the northeast and by Iron Mountain and Lynx Cat Mountain on the southwest, although breaks in the western mountains allow stream connections between Hinkley Valley and another valley to the west that is herein referred to as Hawes valley. At its south end, Hinkley Valley is traversed by the entrenched Mojave River, which passes east out of the valley past Barstow. North of Hinkley Valley, a few low hills (including Red Hill) separate the valley from a broad west-sloping piedmont that is part of the physiographic Harper Basin (of which the Harper Lake playa is the center). The lower part of this piedmont, however, is referred to as Water Valley, although it is not a distinct valley. The name derives from groundwater sourced from subflow in the Mojave River, which caused shallow water and even artesian flow in Water Valley but not in other parts of the Harper Basin. When water filled the Harper Basin to form Pleistocene Lake Harper it not only submerged Water Valley but also northern Hinkley Valley.
California↗
Mapping forest change using stacked generalization: An ensemble approach
The ever-increasing volume and accessibility of remote sensing data has spawned many alternative approaches for mapping important environmental features and processes. For example, there are several viable but highly varied strategies for using time series of Landsat imagery to detect changes in forest cover. Performance among algorithms varies across complex natural systems, and it is reasonable to ask if aggregating the strengths of an ensemble of classifiers might result in increased overall accuracy. Relatively simple rules have been used in the past to aggregate classifications among remotely sensed maps (e.g. using majority predictions), and in other fields, empirical models have been used to create situationally specific algorithm weights. The latter process, called “stacked generalization” (or “stacking”), typically uses a parametric model for the fusion of algorithm outputs. We tested the performance of several leading forest disturbance detection algorithms against ensembles of the outputs of those same algorithms based upon stacking using both parametric and Random Forests-based fusion rules. Stacking using a Random Forests model cut omission and commission error rates in half in many cases in relation to individual change detection algorithms, and cut error rates by one quarter compared to more conventional parametric stacking. Stacking also offers two auxiliary benefits: alignment of outputs to the precise definitions built into a particular set of empirical calibration data; and, outputs which may be adjusted such that map class totals match independent estimates of change in each year. In general, ensemble predictions improve when new inputs are added that are both informative and uncorrelated with existing ensemble components. As increased use of cloud-based computing makes ensemble mapping methods more accessible, the most useful new algorithms may be those that specialize in providing spectral, temporal, or thematic information not already available through members of existing ensembles.
Remote Sensing of Environment↗