Geology Reports⌕ Search

USGS · 70012022

Discrimination of a chestnut-oak forest unit for geologic mapping by means of a principal component enhancement of Landsat multispectral scanner data

Abstract

A principal component image enhancement has been effective in applying Landsat data to geologic mapping in a heavily forested area of eastern Virginia. A chestnut-oak forest unit, which occurs on metavolcanic rocks and some metaclastic rocks in the western Piedmont and on highly weathered upland gravel deposits in the eastern Piedmont, can be discerned on a digitally enhanced Landsat winter image. The image enhancement procedure consists of a principal component transformation, a histogram normalization, and the inverse principal component transformation. The enhancement preserves the independence of the principal components, yet produces a more readily interpretable image than does a single principal component transformation. To determine how the chestnut-oak forest unit was being enhanced, average Landsat multispectral scanner (MSS) values were extracted for four sample forest types and were calculated through the inverted principal component transformation. Slope and intercept values for the linear histogram normalization were chosen to keep the scale between the raw MSS bands and the inverted principal component (PC) bands constant. Plots of the inverted principal component data show that the most separation between forest types is in inverted PC band 5. The chestnut-oak forest unit is characterized by a high value for inverted PC band 5 as opposed to a low value for inverted PC band 4. In contrast, raw MSS band 4 is greater than MSS band 5 for the four forest types sampled in the winter image. Such observations cannot be readily deduced from analysis of only the principal component rotation matrix. They may ultimately provide a means to map the distribution of chestnut-oak forest from Landsat.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M. D. Krohn, N.M. Milton, D. Segal, A. Enland. 2012-12-07. Discrimination of a chestnut-oak forest unit for geologic mapping by means of a principal component enhancement of Landsat multispectral scanner data. https://doi.org/10.1029/gl008i002p00151

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Evolution of summit magma pressure during the 2018 caldera collapse at Kılauea volcano

We utilized geodetic data from the 16 May to 4 August 2018 caldera collapse sequence to refine the geometries and pressure evolution of two summit reservoirs at Kīlauea volcano: the shallower Halema‘uma‘u (HMM) and deeper South Caldera (SC) reservoirs. We modeled magma reservoirs as pressurized spheroidal cavities and constrained reservoir geometries with Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar displacements. Inverting high-rate GPS and borehole tilt time series recovered time-dependent reservoir pressure changes and caldera ring fault shear stress. During the collapse sequence, the HMM reservoir accommodated episodic, co-collapse pressure increases of 1.9 MPa (median) and a net 5.8 MPa (median) decrease. Simultaneously, the SC reservoir underwent monotonic depressurization of 6.7 MPa (median). Negligible co-collapse pressure changes in the SC reservoir imply it was not exclusively supplying magma to the eruption vent. These results provide a coherent view of magma reservoir pressure evolution during the 2018 eruption.

Hawaii↗

EMIT reveals elevated calcite signatures in shorelines of Lake Powell and Lake Mead exposed by drought and Colorado River management

Nearly half of Earth’s seasonal freshwater storage variability occurs in human-managed reservoirs, resulting in large areas of reservoir-bed that are episodically inundated or subaerially exposed. Here we use hyperspectral data from NASA’s Earth Surface Mineral Dust Source Investigation (EMIT) mission to map calcite mineral assemblages across exposed surfaces in two large U.S. reservoirs, Lake Mead and Lake Powell. Results show distinct patterns in the occurrence of carbonate, clay, and mica minerals. Reservoir-deposited sediments exhibited significantly higher calcite proportions than adjacent, lithologically similar, non-inundated terrestrial surfaces. These differences likely reflect hydrologically-driven calcite precipitation, wherein warm, clear, productive reservoir waters drive calcium carbonate out of solution. We also detect reductions in calcite proportions in areas of the shoreline disturbed by human recreation. EMIT's imaging capabilities enable rapid, high-resolution mineralogical inventories across vast areas where field sampling is infeasible. We find EMIT is a scalable tool for monitoring geochemical changes associated with large water level fluctuations.

Arizona, Nevada, Utah↗

First application of a coastal-dune model (AeoLiS) to simulate fluvial-aeolian morphodynamics

Quantifying aeolian processes is important to decision-making in river management and for optimizing strategies for ecosystem conservation, natural resource management, and recreation. We applied the AeoLiS aeolian transport model, originally developed for coastal environments, to a dryland river corridor to evaluate its ability to simulate sediment dynamics in a fluvial-aeolian system. The model reproduced spatial and temporal patterns of geomorphic change at a Grand Canyon sandbar, including aeolian dune formation, observed in field data. The model effectively captured trends in observed sediment movement in the spring and summer months. Thus, despite assuming a single grain-size, static vegetation, and not directly accounting for variable sediment supply from fluvial sources, the model performs well at capturing aeolian processes in a complex fluvial-aeolian system. AeoLiS demonstrates strong potential for dryland river applications and management, due to its flexibility and compatibility with coupled modeling frameworks.

Arizona↗