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Projected water deficits mean that land and water managers must be proactive in their management of rivers and shallow aquifers, if they want to maintain the ecosystems dependent upon them. To do this, managers and decision makers need easy access to the best techniques available for determining how much water ecosystems need. This project will result in a Desert LCC-wide database of environmental flow needs and responses (environmental water demands) to help water and land managers make management decisions. This project will identify critical data gaps in flow need and flow response data in the Desert LCC (especially related to baseflow dependent streams) and result in a user-friendly, one-stop-shop for managers...
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Decision Support, California, New Mexico, Baja California, Map, All tags...
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Understanding the physiological impacts of climate change on arid lands species is a critical step towards ensuring the resilience and persistence of such species under changing temperature and moisture regimes. Varying degrees of vulnerability among different species will largely determine their future distributions in the face of climate change. Studies have indicated that Northern Mexico and the Southwestern United States are likely to become climate change hotspots, experiencing significantly drier and warmer average conditions by the end of the 21st century. However, relatively few studies have examined specifically the physiological effects of climate change on species inhabiting this region. This manuscript...
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: California, New Mexico, plants, Baja California, adaptation, All tags...
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This study uses growth in vegetation during the monsoon season measured from LANDSAT imagery as a proxy for measured rainfall. NDVI values from 26 years of pre- and post-monsoon season Landsat imagery were derived across Yuma Proving Ground (YPG) in southwestern Arizona, USA. The LANDSAT imagery (1986-2011) was downloaded from USGS’s GlobeVis website (http://glovis.usgs.gov/). Change in NDVI was calculated within a set of 2,843 Riparian Area Polygons (RAPs) up to 1 km in length defined in ESRI ArcMap 10.2.
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In 2011 through 2013, when nests were found, notes were kept on whether it held eggs or hatchlings at the time of discovery, and how it was found. Ammodramus savannarum ammolegus (commonly referred to as the Arizona Grasshopper Sparrow) occurs in the desert and plains grasslands of southeastern Arizona, southwestern New Mexico, and northern Sonora, Mexico. Although a subspecies of conservation concern, this data was produced as part of the first intensive study of its life history and breeding ecology, providing baseline data and facilitating comparisons with other North American Grasshopper Sparrow subspecies. This study is described in the publication listed in the larger work citation of this metadata record.
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This location is part of the Arizona Mineral Industry Location System (AzMILS), an inventory of mineral occurences, prospects and mine locations in Arizona. LaPaz43 is located in T7N R13W Sec 11 SE in the Salome - 15 Min quad. This collection consists of various reports, maps, records and related materials acquired by the Arizona Department of Mines and Mineral Resources regarding mining properties in Arizona. Information was obtained by various means, including the property owners, exploration companies, consultants, verbal interviews, field visits, newspapers and publications. Some sections may be redacted for copyright. Please see the access statement.
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Vegetation and land-cover changes are not always directional but follow complex trajectories over space and time, driven by changing anthropogenic and abiotic conditions. We present a multi-observational approach to land-change analysis that addresses the complex geographic and temporal variability of vegetation changes related to climate and land use. Using land-ownership data as a proxy for land-use practices, multitemporal land-cover maps, and repeat photography dating to the late 19th century, we examine changing spatial and temporal distributions of two vegetation types with high conservation value in the southwestern United States: grasslands and riparian vegetation. In contrast to many reported vegetation...
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The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in dense time series of Landsat image stacks to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm makes use of predictors derived from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions. Outputs of the BAECV algorithm consist of pixel-level burn probabilities for each Landsat scene, and annual burn probability, burn classification, and burn date composites. These products were generated for the conterminous United States for 1984 through 2015. These data are also available for download at https://rmgsc.cr.usgs.gov/outgoing/baecv/BAECV_CONUS_v1.1_2017/...
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Field spikes were prepared at 207 stream and river sites as part of the U.S. Geological Survey (USGS) National Water Quality Assessment (NAWQA) project between December, 2012, and September, 2015. At the field site, a depth-and width-integrated environmental sample was collected, and one subsample of the environmental sample was spiked with a known amount of a spike mixture. Both the spiked subsample ("spike sample") and another subsample ("environmental sample") of the original water sample were analyzed for pesticides at the USGS National Water Quality Laboratory (NWQL) by direct injection liquid chromatography with tandem mass spectrometry (LC-MS/MS), and were used to calculate the spike recovery of each analyte....
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Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
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Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
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Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.


map background search result map search result map ADMMR mining collection file: Critic Mine Physiological Effects of Climate Change on Species within the Desert LCC Desert LCC Environmental Flows Database Historical and Contemporary Geographic Data Reveal Complex Spatial and Temporal Responses of Vegetation to Climate and Land Stewardship Chloride Project Geochemical Location Plan - Zinc Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 - 2015) Mean of the Top Ten Percent of NDVI Values in the Yuma Proving Ground during Monsoon Season, 1986-2011 USGS Small-scale Dataset - Congressional Districts of the United States - 110th Congress 200710 Shapefile USGS Small-scale Dataset - Congressional Districts of the United States - 112th Congress 201101 Shapefile ADMMR Photo Archive file: Rumico Millsite 173-73 ADMMR Photo Archive file: Golden Eagle 60-6 ADMMR Photo Archive file: Gladstone McCabe 60-66 ADMMR Photo Archive file: Pinto Valley Mine 150-45 How nests found Arizona 2011-2013 USGS Combined Vector for Engine Mountain, Arizona 20160914 7.5 x 7.5 minute FileGDB 10.1 USGS Combined Vector for Greasewood, Arizona 20160915 7.5 x 7.5 minute Shapefile USGS Combined Vector for Howard Mesa, Arizona 20160915 7.5 x 7.5 minute FileGDB 10.1 USGS Combined Vector for Kingman SW, Arizona 20160914 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 18694 Guadalupe Spring, New Mexico 20170421 for 7.5 x 7.5 minute FileGDB 10.1 ADMMR Photo Archive file: Gladstone McCabe 60-66 ADMMR Photo Archive file: Golden Eagle 60-6 ADMMR Photo Archive file: Pinto Valley Mine 150-45 ADMMR mining collection file: Critic Mine ADMMR Photo Archive file: Rumico Millsite 173-73 How nests found Arizona 2011-2013 USGS Combined Vector for Engine Mountain, Arizona 20160914 7.5 x 7.5 minute FileGDB 10.1 USGS Combined Vector for Greasewood, Arizona 20160915 7.5 x 7.5 minute Shapefile USGS Combined Vector for Howard Mesa, Arizona 20160915 7.5 x 7.5 minute FileGDB 10.1 USGS Combined Vector for Kingman SW, Arizona 20160914 7.5 x 7.5 minute FileGDB 10.1 USGS Topo Map Vector Data (Vector) 18694 Guadalupe Spring, New Mexico 20170421 for 7.5 x 7.5 minute FileGDB 10.1 Mean of the Top Ten Percent of NDVI Values in the Yuma Proving Ground during Monsoon Season, 1986-2011 Historical and Contemporary Geographic Data Reveal Complex Spatial and Temporal Responses of Vegetation to Climate and Land Stewardship Physiological Effects of Climate Change on Species within the Desert LCC Desert LCC Environmental Flows Database Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 - 2015) USGS Small-scale Dataset - Congressional Districts of the United States - 110th Congress 200710 Shapefile USGS Small-scale Dataset - Congressional Districts of the United States - 112th Congress 201101 Shapefile