USGS ScienceSearch

Geology topics

Michael P. Stier

Publications and source records attributed to Michael P. Stier.

7 recordsLinked to original sources

Land-use and land-cover change in the Lower Rio Grande Ecoregions, Texas, 2001–2011

Urban growth and other land-use changes were examined in the Lower Rio Grande Valley and Alluvial Floodplain ecoregions in Texas, along the U.S.-Mexico border. The analysis focused on understanding the types and causes of land change as well as the recovery of natural land-cover types between years 2001 and 2011. The purpose was to develop improved capabilities for understanding land change dynamics in urbanizing ecoregions and to provide data for further analyses. The spatial data, including metadata, allows further exploration and characterization of changes affecting this dynamic region.

Texas

Causes of land change in the U.S. Interior Highlands, 2001–2011

The causes of land change from 2001 through 2011 for the Interior Highlands region of the south-central United States were assessed using satellite imagery, historical land-use and land-cover data, and digital orthophotos. The study was designed to develop improved regional land-use and land-cover change information, including identification of the proximate causes of change. The four leading causes of land change involved various stages of forest change: harvest (376,497 hectares), reforestation (105,150 hectares), stand loss to fire (98,875 hectares), and thinning (54,029 hectares). The study provides baseline spatial data for understanding human and ecological dynamics in the region. The spatial data, including metadata, are available in the data release associated with this report at https://doi.org/10.5066/P9W4SF05.

Missouri, Arkansas, Oklahoma, Kansas

Historical land use and land cover for assessing the northern Colorado Front Range urban landscape

We describe historical land-use and land-cover (LULC) maps for the northern Colorado urban Front Range. The Front Range urban landscape is diverse and interspersed with highly productive agriculture as well as natural land cover types including evergreen forest in the Rocky Mountain foothills and Great Plains grassland. To understand the dynamics of urban growth, raster maps were created at a 1 meter resolution for each of four time steps, nominally 1937, 1957, 1977, and 1997. In total, 38 detailed LULC classes were identified using manual interpretation techniques, aerial photographs, historical maps, and other available information. The maps provide high resolution spatial data for understanding the historical progression of urbanization and will allow further analysis of the effects of urban growth on social and ecological systems.

Colorado

Understanding recurrent land use processes and long-term transitions in the dynamic south-central United States, c. 1800 to 2006

Forests have historically been under significant land use pressures that cause periods of degradation, clearance, and recovery. To understand these changes, studies are needed that place trends in a historical landscape context and also examine recent dynamics. Here, we use historical investigation (c. 1800) and an examination of land use and land cover change between 1973 and 2006 to establish a baseline trajectory of the forested system of the south-central United States (US) plains. The study culminates in a highly detailed accounting of the processes and causes of land change between 2001 and 2006. In the study region, the forest transitioned from early low-intensity use, to clearance for farming and timber, to widespread recovery from degradation beginning in the 1930s. By 1970, the region was transitioning from recovered woodlands to an intensive regime of recurrent timber harvest and replanting. The recurring cycle inherent in intensive silviculture has been the main cause of land change for the past several decades, accounting for more than 95% of the total extent of change between 2001 and 2006. The transition to forest recovery in the south-central US was an important historical occurrence. However, the dynamic post-transition landscape needs to be better understood.

Arkansas, Louisiana, Oklahoma, Texas

Assessing landscape change and processes of recurrence, replacement, and recovery in the Southeastern Coastal Plains, USA

The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8 % of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15 % of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83 %. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3 % of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.

Alabama, Georgia, Florida, Lousianna, Mississippi,

Land-cover change in the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative, 1973 to 2000

This report summarizes baseline land-cover change information for four time intervals from between 1973 and 2000 for the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (LCC). The study used sample data from the USGS Land Cover Trends dataset to develop estimates of change for 10 land-cover classes in the LCC. The results show that an estimated 17.7 percent of the LCC land cover had a change during the 27-year period. Cyclic forest dynamics—of timber harvest and regrowth—are the most extensive types of land conversion. Agricultural land had an estimated net decline of 3.5 percent as cropland and pasture were urbanized and developed and converted to forest use. Urban and other developed land covers expanded from 2.0 percent of the LCC in 1973 to 3.1 percent in 2000. The report also highlights causes and challenges of land-cover change.

Gulf Coastal Plains, Ozarks

Land cover trends dataset, 1973-2000

The U.S. Geological Survey Land Cover Trends Project is releasing a 1973–2000 time-series land-use/land-cover dataset for the conterminous United States. The dataset contains 5 dates of land-use/land-cover data for 2,688 sample blocks randomly selected within 84 ecological regions. The nominal dates of the land-use/land-cover maps are 1973, 1980, 1986, 1992, and 2000. The land-use/land-cover maps were classified manually from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery using a modified Anderson Level I classification scheme. The resulting land-use/land-cover data has a 60-meter resolution and the projection is set to Albers Equal-Area Conic, North American Datum of 1983. The files are labeled using a standard file naming convention that contains the number of the ecoregion, sample block, and Landsat year. The downloadable files are organized by ecoregion, and are available in the ERDAS IMAGINE TM (.img) raster file format.

Data Series