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This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
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This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
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A species has been applied to each hectare based on the 6 species fields in the raw data and the percentage of each species within a given polygon. For example a hectare which is 75% Pine and 25% Cedar has a 25% chance of being flagged as ''Cedar'' and 75% chance of being flagged as ''Pine''. A code describing the commercial species or brush species in the layer. Species must be above a specified diameter to be recognized in the species composition of the layer. Leading species are described in terms of Genus, Species and Subspecies. There are currently 27 commercial tree species and five genus values recognized in the Province. The code may also used to describe brush species in cases where the Non-Productive Descriptor...
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Pacific-slope Flycatcher station lifetime productivity (STAPI) (log transformed) ranged between -0.034 and +0.606 with a mean value of +0.286 and a median value of +0.247. ________________________________________ Model 1 (3 parameters) Pacific-slope Flycatcher station lifetime productivity (STAPI) (log transformed) was a function of: a) INTERCEPT (0.3022), b) NLCD06AF90P (+0.01874) - percent all forest cover, 90m-resolution(3x aggregation of 30m-resolution), ranged between -1.901 and +6.011 (95% CL) with a mean value of +2.055 and a median value of +2.494, c) NLCD06IM33P (-0.02730) - percent impervious cover, 990m-resolution (33x aggregation of 30m-resolution), ranged between -1.057 and +5.084 (95% CL) with...
Electric utilities in the US have initiated forestry projects to conserve energy and to o€set carbon dioxide (CO2) emissions. In 1995, 40 companies raised US$2.5 million to establish the non-pro®t UtiliTree Carbon Company which is now sponsoring eight projects representing a mix of rural tree planting, forest preservation, forest management and research e€orts at both domestic (Arkansas, Louisiana, Mississippi, and Oregon) and international sites (Belize and Malaysia). The projects include extensive external veri®cation. Such forestry projects Ð properly documented, monitored and veri®ed Ð should be a component of domestic and international strategies to address greenhouse gas (GHG) emissions, due to GHG bene®ts,...
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Tree species locations
Tags: 3pg, forest, model
The balance between economic needs and natural resource conservation will become more tenuous in the future as a result of a myriad of environmental stressors. We propose a methodology that can help guide forest management practices whenever adequate species locational data and quality forest or land use data exist. More specifically, the results of this study can be used to evaluate alternative land and silviculture management scenarios in terms of creating or maintaining high-quality forest habitat for a specific species. We used data collected on radiotelemetered black bears from 1988 to 2015 to develop a regional habitat model throughout Louisiana and Arkansas using Mahalanobis distance (D2) statistic. We created...
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This dataset contains all National Forest Inventoried Roadless Areas (IRAs) for the Alaska Region (R10). The IRA data was originally submitted to GSTC by all national forests through their Regional Offices for the Forest Service's Roadless Area Conservation Initiative. The data was consolidated at the GSTC and used in the Draft Environment Impact Statement. Between the draft and final stages of the Environmental Impact Statement, the data was updated by the forests to reflect any corrections to Inventoried Roadless Areas that were based on their existing forest plan. The data was also supplemented to include Special Designated Area information and to include Inventoried Roadless Areas within Special Designated...
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This dataset portrays percent tree canopy coverage for NLCD mapping superzone twelve (south), covering parts of Louisiana, Mississippi, Alabama, Florida, and Arkansas . Refer to http://www.mrlc.gov/nlcd_multizone_map.php for a map of the superzones. From NLCD: The National Land Cover Database 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS),...
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Forest Retention Index classes for the southeastern United States at 2040 were processed using the Forest Retention Decision Tree and rendered on a 30-meter by 30-meter grid. The Forest Retention Index is used only for current forestland, identified using National Land Cover Database 2011. Many datasets were used as inputs for the Forest Retention Decision Tree, and they can be grouped into five broad categories: Protected, Tier 1 Priority, Tier 2 Priority, Threats to Forest Retention, and Socio-Economic Value of Forests. Protected datasets include Protected Areas Database-United States, National Conservation Easement Database, state-maintained databases, and private datasets volunteered by conservation partners....
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This dataset represents presence of Jack Pine (Pinus banksiana) in Minnesota (USA) at year 50 (2045) from a single model run of LANDIS-II. The simulation assumed Intergovernmental Panel on Climate Change (IPCC) B2 emissions (moderate) and used the Hadley 3 global circulation model. Restoration harvest rates and intensities were simulated.
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This dataset represents presence of Sugar Maple (Acer saccharum) in Minnesota (USA) at year 0 (2145) from a single model run of LANDIS-II. The simulation assumed Intergovernmental Panel on Climate Change (IPCC) B2 emissions (moderate) and used the Hadley 3 global circulation model. Contemporary harvest rates and intensities were simulated.
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This map depicts the forested regions in the western United States. Data was obtained from the the Sagestitch map and other state-level GAP landcover maps and merged into 90m raster dataset.


map background search result map search result map Tree species from the Vegetation Resource Inventory for the North Pacific Landscape Conservation Cooperative, British Columbia, Canada United States Forest Service (USFS) Inventoried Roadless Areas for Alaska (USA) Tree species locations Draft Indicator: Upland Hardwood Forests - Index of Upland Hardwood Birds "Western" Flycatcher (Productivity) National Land Cover Database, percent tree canopy coverage- superzone twelve (south) Forested Areas in the Western United States Minnesota (USA) Climate Change Project: Jack Pine at Year 50 (2045), assuming emissions scenario B2, Hadley3 GCM, restoration harvest rates and intensity Minnesota (USA) Climate Change Project: Sugar Maple at Year 150 (2145), assuming emissions scenario B2, Hadley3 GCM, contemporary harvest rates and intensity FSA 10:1 NAIP Imagery m_4107937_se_17_1_20151011_20151201 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_4107938_nw_17_1_20150728_20151201 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_4508803_sw_16_1_20150701_20151109 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_4508819_ne_16_1_20150701_20151109 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_4508827_nw_16_1_20150701_20151109 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_4508828_se_16_1_20150914_20151109 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3109532_sw_15_1_20141017_20141201 3.75 x 3.75 minute JPEG2000 from The National Map USGS 1:24000-scale Quadrangle for Forest, VA 1965 Forest Retention Index for the South at year 2040 FSA 10:1 NAIP Imagery m_4107937_se_17_1_20151011_20151201 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_4107938_nw_17_1_20150728_20151201 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_4508803_sw_16_1_20150701_20151109 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_4508819_ne_16_1_20150701_20151109 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_4508827_nw_16_1_20150701_20151109 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_4508828_se_16_1_20150914_20151109 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3109532_sw_15_1_20141017_20141201 3.75 x 3.75 minute JPEG2000 from The National Map USGS 1:24000-scale Quadrangle for Forest, VA 1965 Minnesota (USA) Climate Change Project: Sugar Maple at Year 150 (2145), assuming emissions scenario B2, Hadley3 GCM, contemporary harvest rates and intensity Minnesota (USA) Climate Change Project: Jack Pine at Year 50 (2045), assuming emissions scenario B2, Hadley3 GCM, restoration harvest rates and intensity National Land Cover Database, percent tree canopy coverage- superzone twelve (south) Draft Indicator: Upland Hardwood Forests - Index of Upland Hardwood Birds United States Forest Service (USFS) Inventoried Roadless Areas for Alaska (USA) Forest Retention Index for the South at year 2040 Forested Areas in the Western United States Tree species from the Vegetation Resource Inventory for the North Pacific Landscape Conservation Cooperative, British Columbia, Canada Tree species locations "Western" Flycatcher (Productivity)