Geology topics

P.L. Chapman

Publications and source records attributed to P.L. Chapman.

4 recordsLinked to original sources

USGS2010

AVHRR composite period selection for land cover classification

Multitemporal satellite image datasets provide valuable information on the phenological characteristics of vegetation, thereby significantly increasing the accuracy of cover type classifications compared to single date classifications. However, the processing of these datasets can become very complex when dealing with multitemporal data combined with multispectral data. Advanced Very High Resolution Radiometer (AVHRR) biweekly composite data are commonly used to classify land cover over large regions. Selecting a subset of these biweekly composite periods may be required to reduce the complexity and cost of land cover mapping. The objective of our research was to evaluate the effect of reducing the number of composite periods and altering the spacing of those composite periods on classification accuracy. Because inter-annual variability can have a major impact on classification results, 5 years of AVHRR data were evaluated. AVHRR biweekly composite images for spectral channels 1-4 (visible, near-infrared and two thermal bands) covering the entire growing season were used to classify 14 cover types over the entire state of Colorado for each of five different years. A supervised classification method was applied to maintain consistent procedures for each case tested. Results indicate that the number of composite periods can be halved-reduced from 14 composite dates to seven composite dates-without significantly reducing overall classification accuracy (80.4% Kappa accuracy for the 14-composite data-set as compared to 80.0% for a seven-composite dataset). At least seven composite periods were required to ensure the classification accuracy was not affected by inter-annual variability due to climate fluctuations. Concentrating more composites near the beginning and end of the growing season, as compared to using evenly spaced time periods, consistently produced slightly higher classification values over the 5 years tested (average Kappa) of 80.3% for the heavy early/late case as compared to 79.0% for the alternate dataset case).

International Journal of Remote Sensing↗

USGS2010

AVHRR channel selection for land cover classification

Mapping land cover of large regions often requires processing of satellite images collected from several time periods at many spectral wavelength channels. However, manipulating and processing large amounts of image data increases the complexity and time, and hence the cost, that it takes to produce a land cover map. Very few studies have evaluated the importance of individual Advanced Very High Resolution Radiometer (AVHRR) channels for discriminating cover types, especially the thermal channels (channels 3, 4 and 5). Studies rarely perform a multi-year analysis to determine the impact of inter-annual variability on the classification results. We evaluated 5 years of AVHRR data using combinations of the original AVHRR spectral channels (1-5) to determine which channels are most important for cover type discrimination, yet stabilize inter-annual variability. Particular attention was placed on the channels in the thermal portion of the spectrum. Fourteen cover types over the entire state of Colorado were evaluated using a supervised classification approach on all two-, three-, four- and five-channel combinations for seven AVHRR biweekly composite datasets covering the entire growing season for each of 5 years. Results show that all three of the major portions of the electromagnetic spectrum represented by the AVHRR sensor are required to discriminate cover types effectively and stabilize inter-annual variability. Of the two-channel combinations, channels 1 (red visible) and 2 (near-infrared) had, by far, the highest average overall accuracy (72.2%), yet the inter-annual classification accuracies were highly variable. Including a thermal channel (channel 4) significantly increased the average overall classification accuracy by 5.5% and stabilized interannual variability. Each of the thermal channels gave similar classification accuracies; however, because of the problems in consistently interpreting channel 3 data, either channel 4 or 5 was found to be a more appropriate choice. Substituting the thermal channel with a single elevation layer resulted in equivalent classification accuracies and inter-annual variability.

International Journal of Remote Sensing↗

USGS1998

Effects of metal mining and milling on boundary waters of Yellowstone National Park, USA

Aquatic resources in Soda Butte Creek within Yellowstone National Park, USA, continue to be threatened by heavy metals from historical mining and milling activities that occurred upstream of the park's boundary. This includes the residue of gold, silver, and copper ore mining and processing in the early 1900s near Cooke City, Montana, just downstream of the creek's headwaters. Toxicity tests, using surrogate test species, and analyses of metals in water, sediments, and macroinvertebrate tissue were conducted from 1993 to 1995. Chronic toxicity to test species was greater in the spring than the fall and metal concentrations were elevated in the spring with copper exceeding water quality criteria in 1995. Tests with amphipods using pore water and whole sediment from the creek and copper concentrations in the tissue of macroinvertebrates and fish also suggest that copper is the metal of concern in the watershed. In order to understand current conditions in Soda Butte Creek, heavy metals, especially copper, must be considered important factors in the aquatic and riparian ecosystems within and along the creek extending into Yellowstone National Park.

Environmental Management↗

USGS1997

Phytotoxicity of floodplain soils contaminated with trace metals along the clark fork river, Grant-Kohrs Ranch National Historic Site, Deer Lodge, Montana, United States

Concentrations of metals in sediments and soils deposited along the floodplain of the Clark Fork River, within the Grant-Kohrs Ranch National Historic Site, Deer Lodge, Montana, USA, have exceeded maximum background concentrations in the United States for most metals tested. As a result of mining and smelting activities, portions of the Deer Lodge Valley, including the Grant-Kohrs Ranch, have received National Priority List Designation under the Comprehensive Environmental Response, Compensation and Liability Act. Using a series of plant germination tests, pH measurements, and metal analyses, this study investigated the toxicity of soils from floodplain 'slicken' areas, bare spots devoid of vegetation, along the Clark Fork River. The slicken soils collected from the Grant-Kohrs Ranch were toxic to all four plant species tested. The most sensitive endpoint in the germination tests was root length and the least sensitive was emergence. Considering emergence, the most sensitive species was the resident grass species Agrostis gigantea. The sensitivities were reversed when root lengths were examined, with Echinochloa crusgalli showing the greatest sensitivity. Both elevated concentrations of metals and low pH were necessary to produce an acutely phytotoxic response in laboratory seed germination tests using slicken soils. Moreover, pH values on the Grant-Kohrs Ranch appear to be a better predictor of acutely phytotoxic conditions than total metal levels.

Environmental Toxicology and Chemistry↗