Search USGS⌕ Search

Geology topics

James Vogelmann

Publications and source records attributed to James Vogelmann.

28 records · Page 2Linked to original sources
USGS2003

Deriving annual integrated NDVI greenness at 30 m spatial resolution

Temporal greenness matrics have been found useful for characterizing vegetation phenology, and have been used to discriminate vegetation cover types and to estimate key vegetation attributes including percent cover and green biomass. So far, however, such matrics have been calculated only from coarse resolution satellite data. Intermediate spatial resolution satellites like Landsat cannot provide the temporal resolutions needed for directly calculating such greenness matrics. In this study, we developed a method to indirectly derive annual integrated NDVI at 30 m spatial resolution using 250 m MODIS data and 30 m Landsat ETM+ imagery. Results showed that more than 90% of the variance of the annual integrated NDVI calculated using one full year’s MODIS data could be explained using as few as 3 appropriately selected observations, demonstrating the feasibility of indirectly estimating the annual integrated NDVI at intermediate spatial resolutions, as normally only limited number of useful observations would be available within the life cycle of a typical project at such spatial resolutions. The developed method was applied to two ETM+ paths/rows, for each of which 3 ETM+ images were acquired in roughly spring, summer and fall/winter seasons around the year 2000. Of the total variance of the MODIS annual integrated NDVI, 81% was explained by the three ETM+ images for one path/row and 74% for the other.

Conference Paper↗
USGS2003

Predictive modeling of forest cover type and tree canopy height in the central Rocky Mountains of Utah

Maps of forest cover type and canopy height are needed for LANDFIRE, a multi-scale fire risk assessment project designed to generate intermediate-resolution data of vegetation and fire fuel characteristics for the U.S. Here we describe an evaluation study in the central Rockies of Utah, comparing tree-based methods, multivariate adaptive regression splines (MARS), and a hybrid method for mapping forest cover and canopy height on the basis of more than 2,000 forest inventory ground plots in the seven million ha mapping zone. The two forest attributes were modeled as functions of a variety of predictor variables, including: Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images acquired at three different seasons; Tasseled-cap brightness, greenness, and wetness; a forest type group map; and topographic variables derived from Digital Elevation Models (DEMs); and other ancillary variables. The hybrid modeling approach showed a marked increase in overall and within forest cover type accuracies, outperforming the tree-based and MARS approaches. Little difference was seen in global performance measures of forest canopy height models, but patterns in residual plots resulting from different modeling approaches raise questions about utility of height predictions in different applications.

Idaho, Utah, Wyoming↗
USGS2003

Deriving rangeland structural attributes using Landsat ETM+, ERS-1/ERS-2

The purpose of this study is to determine if Synthetic Aperture Radar (SAR) can be used independently, or in conjunction with Landsat Enhanced Thematic Mapper Plus (ETM+) to improve the classification accuracy of structural attributes of rangeland vegetation, particularly percent shrub cover and top shrub canopy height. Such information, if mapped accurately, can be used in models to better characterize fuel conditions and fire regimes, as well as to evaluate fire hazard status, called for by the U.S. National Fire Plan. The input datasets utilized in this investigation included eighteen bands of Landsat ETM+ path 38 / row 32 (three image dates, six bands each), backscattering and interferometic data derived from tandem ERS-1/2 SAR image pairs (C-band), and extensive field point data. The results showed the use of SAR data provided no significant improvement over the ETM+ data for estimating percent cover or shrub canopy height. The lack of improvement in classification accuracy is possibly due to the influence of topography on the radar backscattering signal. Additional results demonstrated improved model accuracies when a 3x3-averaging filter was applied to the eighteen bands of ETM+ imagery.

Conference Paper↗
USGS2003

Exploration of satellite-measured vegetation seasonality for Landfire land cover

The purpose of this study is to explore the use of satellite data and other sources of spatial data for large area classification in the western United States to support research on potential fire hazards. Extensive field information was made available to this project from two sources: Forest Inventory and Assessment (FIA) and Utah State University. Seasonal spectral patterns of reflectance generated for select vegetation communities indicated that substantial spectral changes occurred through the growing season for most land cover types. In many cases, pronounced spectral differences characterized different types of vegetation, indicating a high probability that classification will accurately separate these particular types of land cover. However, spectral similarities between other types of land cover, such as Douglas fir and white fir, indicate potential classification challenges. Results from this study also show that decision tree analysis is highly effective for assessing quality of input field data and for generating large area land cover classification data sets. It was found that a 5-7% improvement in classification results could be achieved simply by not using those field plots that appeared to be sub-optimal for classification purposes based on image interpretation.

Conference Paper↗
USGS2003

A strategy for mapping mid-scale existing vegetation in support of national fire fuel assessment

Geospatial distribution of natural vegetation is among the very important environmental parameters required for applications ranging from global climate change to monitoring of natural hazards, monitoring of ecosystem vitality, and fire management practices. Increasingly sophisticated applications require vegetation datasets to cover large areas at a suitable scale and provide sufficiently detailed information. In this paper, we describe a research effort to develop a remote sensing methodology capable of producing 30-meter resolution, wall-to-wall coverage of existing vegetation types and structure variables in support of a multi-agency fire fuels and fire risks assessment project. Success of this remote sensing research effort is dependent on improved sensor and data qualities, a thorough understanding of regional and local vegetation ecology, successful integration of remote sensing with a large amount of field plot data, and flexible mapping algorithms. Preliminary results produced in the Wasatch Range and Uinta Mountains of central Utah include 28 vegetation types with an overall accuracy of 60% (average by life forms), percent canopy density (sub-pixel density) of forest, shrub, and herbaceous cover (correlation coefficient of 89, 60, and 55% respectively), and average top canopy height of forest, shrub, and herbaceous cover (correlation coefficient of 73, 50, 20% respectively). Techniques to improve the first-round results are discussed, including refinements of mapping models and use of relevant environmental gradients and potential vegetation classification associated with actual vegetation types.

Conference Paper↗
USGS2000

Landsat 5/Landsat 7 underfly cross-calibration experiment

There was a one-time opportunity to obtain nearly coincident coverage from both Landsat 5 and Landsat 7 as Landsat 7 drifted to its final orbital position during the initialization and verification phase following launch. During the underfly period, Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data were collected using the U.S Landsat 7 ground station network and the solid-state recorder, while agreements were established with Space Imaging/EOSAT and various international ground stations to collect corresponding Landsat 5 Thematic Mapper (TM) data. Approximately 750 coincident scenes were collected during the underfly from 1-3 June 1999. Underfly data are intended to play a major role in developing cross-calibrations to bridge the results derived from historical Landsat 5 TM data with research performed with current Landsat 7 ETM+ data. The purpose of this paper is to provide an overview of the underfly experiment, and to provide some early comparative results between Landsat 5 and 7 data sets. Initial results indicate that products produced using TM and ETM+ data are very similar.

Conference Paper↗
USGS2000

National land-cover pattern data

Land cover and its spatial patterns are key ingredients in ecological studies that consider large regions and the impacts of human activities. Because land-cover maps show only cover types and their locations, further processing is needed to extract pattern information and to characterize its spatial variability. We are producing a nationally consistent spatial database of six land-cover pattern indices: forest area density, forest connectivity, the U index (a measure of general land-use pressure by humans), land-cover connectivity, land-cover diversity, and landscape pattern types. We use the land-cover maps produced by the Multi-resolution Land Characteristics Consortium for the conterminous United States at 30-m resolution. The goal of this paper is to encourage use of the pattern data as: contextual information and independent variables for studies involving a set of field sites; indicators of landscape conditions for ecological assessments; and dependent variables in biogeographic and socioeconomic models. The new maps will be most useful in studies that require consistent and comparable land-cover pattern measurements over large regions and can be combined with the original land-cover maps and other data.

Ecology↗
USGS2000

Implementation strategy for production of National Land-Cover Data (NLCD) from the Landsat 7 Thematic Mapper satellite

As environmental programs within and outside the federal government continue to move away from point-based studies to larger and larger spatial (not cartographic) scale, the need for land-cover and other geographic data have become ineluctable. The national land-cover mapping project of MRLC marks the first consistently classified conterminous land-cover data set, effectively replacing USGS' Land Use Data Analysis (LUDA) system derived from high altitidue aerial photography acquired in the early 1970's. Because of the continually changing nature of the earth's surface due to anthropogenic activities and other factors, a single point-in-time land-cover product is insufficient for many applications. Production of a second point-in-time land-cover product is proposed as a database. That proposed database design includes: (1) second, independently classified land-cover data set derived from Landsat 7 Thematic Mapper data; (2) the land-cover product being produced under the current effort, (3) selected spectral-based change estimates (e.g., temporal NDVI), (4) thirty-meter DEMS; and (5) selected landscape metrics. Development of the database for the conterminous United States will start after evaluation of the prototype.

Technical Report↗
USGS1996

Regional land cover characterization using multiple sources of intermediate-scale data

Many United States federal agencies need accurate, intermediate scaled, land cover information. While many techniques and approaches have been successfully used to classify land cover in relatively small regions, there are substantial problems in applying these techniques to large multi-scene regions. An evaluation was conducted of the multiple layer land characteristics data base approach for generating large area land cover information. Mosaicked leaves-on Landsat thematic mapper scenes were used in conjunction with leaves-off thematic mapper data, digital elevation (and derived slope, aspect and shaded relief) data, population census information, defense meteorological satellite program "city lights" data, land use and land cover data, digital line graph data, and national wetlands inventory data to derive land cover information. This approach was evaluated for Region III of the United States Environmental Protection Agency (middle Atlantic states).

Conference Paper↗