Geology topics

Jim Smith

Publications and source records attributed to Jim Smith.

3 recordsLinked to original sources

USGS2022

Contemporary (1984–2020) fire history metrics for the conterminous United States and ecoregional differences by land ownership

Background: Remotely sensed burned area products are critical to support fire modelling, policy, and management but often require further processing before use. Aim: We calculated fire history metrics from the Landsat Burned Area Product (1984–2020) across the conterminous U.S. (CONUS) including (1) fire frequency, (2) time since last burn (TSLB), (3) year of last burn, (4) longest fire-free interval, (5) average fire interval length, and (6) contemporary fire return interval (cFRI). Methods: Metrics were summarised by ecoregion and land ownership, and related to historical and cheatgrass datasets to demonstrate further applications of the products. Key results: The proportion burned ranged from 0.7% in the Northeast Mixed Woods to 74.1% in the Kansas Flint Hills. The Flint Hills and Temperate Prairies showed the highest burn frequency, while the Flint Hills and the Sierra Nevada and Klamath Mountains showed the shortest TSLB. Compared to private, public land had greater burned area (19 of 31 ecoregions) and shorter cFRI (25 of 31 ecoregions). Conclusions: Contemporary fire history metrics can help characterise recent fire regimes across CONUS. Implications: In regions with frequent fire, comparison of contemporary with target fire regimes or invasive species datasets enables the efficient incorporation of burned area data into decision-making.

International Journal of Wildland Fire↗

USGS2022

Integration of vegetation classification with land cover mapping: Lessons from regional mapping efforts in the Americas

Aims : Natural resource management and biodiversity conservation rely on inventories of vegetation that span multiple management or political jurisdictions. However, while remote sensing data and analytical tools have enabled production of maps at increasing spatial resolution and reliability, there are limited examples where national or continental-scaled maps are produced to represent vegetation at high thematic detail. We illustrate two examples that have bridged the gap between traditional land cover mapping and modern vegetation classification. Study area : Our two case studies include national ( USA ) and continental (North and South America) vegetation and land cover mapping. These studies span conditions from subpolar to tropical latitudes of the Americas. Methods : Both case studies used a supervised modeling approach with the International Vegetation Classification ( IVC ) to produce maps that provide for greater thematic detail. Georeferenced locations for these vegetation types are used by machine learning algorithms to train a predictive model and generate a distribution map. Results : The USA LANDFIRE (Landscape Fire and Resource Management Planning Tools Project) case study illustrates how a history of vegetation-based classification and availability of key inputs can come together to generate standard map products covering more than 9.8 million km 2 that are unsurpassed anywhere in the world in terms of spatial and thematic resolution. That being said, it also remains clear that mapping at the thematic resolution of the IVC Group and finer resolution require very large and spatially balanced inputs of georeferenced samples. Even with extensive prior data collection efforts, these remain a key limitation. The NatureServe effort for the Americas - encompassing 22% of the global land surface - demonstrates methods and outputs suitable for worldwide application at continental scales. Conclusions : Continued collection of input data used in the case studies could enable mapping at these spatial and thematic resolutions around the globe.

Vegetation Classification and Survey↗

USGS2016

A comparison of NLCD 2011 and LANDFIRE EVT 2010: Regional and national summaries.

In order to provide the land cover user community a summary of the similarity and differences between the 2011 National Land Cover Dataset (NLCD) and the Landscape Fire and Resource Management Planning Tools Program Existing Vegetation 2010 Data (LANDFIRE EVT), the two datasets were compared at a national (conterminous U.S.) and regional (Eastern, Midwestern, and Western) extents (Figure 1). The comparisons were done by generalizing the LANDFIRE data to be consistent with mapped land cover classes in the NLCD (i.e., crosswalked). Summaries of the comparisons were based on areal extent including 1) the total extent of each land cover class, and 2) land cover classes in corresponding 900-m2 areas. The results from the comparisons provide the user community information regarding the utility of both datasets relative to their intended uses.

Report↗