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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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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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Major forest species of Russia, created from an amalgamation of all applicable IIASA data with the Forest State Account of 1993, produced at a scale of 1:1 million. It is p art of the Land Resources of Russia collection. More information on the forestry datasets can be found at: http://www.iiasa.ac.at/Research/FOR/russia_cd/forestry.htm .
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The Forest Health Technology Enterprise Team (FHTET) was created by the Deputy Chief for State and Private Forestry in February 1995 to develop and deliver forest health technology services to field personnel in public and private organizations in support of the Forest Service’s land ethic, to “promote the sustainability of ecosystems by ensuring their health, diversity, and productivity.” This dataset shows the total basal area of all tree species as square feet per acre.For more information: http://www.fs.fed.us/foresthealth/technology/nidrm2012.shtml
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Plot-level field data were collected in the summer of 2014 to estimate aboveground and belowground biomass in the Great Dismal Swamp National Wildlife Refuge and Dismal Swamp State Park in North Carolina and Virginia. Data were collected at 85 plots. The location of the center of each plot was recorded with a Trimble ProXH global positioning system (GPS) and differentially corrected. Data files included 1: GDS_plots.csv, 2. GDS_FWD.csv, 3. GDS_LWD.csv, 4. GDS_Shrubs.csv, 5. GDS_Trees.csv, and 6. GDS_plot_summaries.csv. The data contained in GDS_plot_summaries.csv were calculated from the GDS_plots.csv, GDS_FWD.csv, GDS_LWD.csv, GDS_Shrubs.csv, GDS_Trees.csv files using the R statistical software environment (R Core...
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Data represent presence/absence for cedar decline occurrence. Cedar decline refers to the dying or decline of yellow-cedar (Chamaecyparis nootkatensis) forests in Southeast Alaska and is characterized by red or yellow foliage in trees currently dying, or by white-gray snags of old mortality. Mapped snags can be standing dead as long as eighty years. The data were collected via aerial sketch mapping techniques and recorded on 1:250,000 USGS base maps from 500-3000 foot above ground level(AGL) observations. Survey coverage has been most intense for forests adjacent to shorelines and waterways. Data are collected, refined and updated on an annual basis. This data represent not one year's mortality but the cumulative...
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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...
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This dataset consists of the average residual errors for the rulesets developed to predict biomass: http://app.databasin.org/app/pages/datasetPage.jsp?id=b0817400a441487baf1409580acc6620 The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis Program and the USFS Remote Sensing Applications Center.
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This dataset consists of the average residual errors for the rulesets developed to predict biomass: http://app.databasin.org/app/pages/datasetPage.jsp?id=e44f9d6470de4df7a24cbc52ff665b47 The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis Program and the USFS Remote Sensing Applications Center.
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This dataset consists of the average residual errors for the rulesets developed to predict biomass: http://app.databasin.org/app/pages/datasetPage.jsp?id=503ca5e998f64443bc04c330d3a9fcc0 The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis Program and the USFS Remote Sensing Applications Center.
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Potential Whitebark Pine range as calculated by regression analysis (Keane 2000).
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Plot-level field data were collected in the summer of 2014 to estimate aboveground and belowground biomass in the Great Dismal Swamp National Wildlife Refuge and Dismal Swamp State Park in North Carolina and Virginia. Data were collected at 85 plots. The location of the center of each plot was recorded with a Trimble ProXH global positioning system (GPS) and differentially corrected. Data files included 1: GDS_plots.csv, 2. GDS_FWD.csv, 3. GDS_LWD.csv, 4. GDS_Shrubs.csv, 5. GDS_Trees.csv, and 6. GDS_plot_summaries.csv. The data contained in GDS_plot_summaries.csv were calculated from the GDS_plots.csv, GDS_FWD.csv, GDS_LWD.csv, GDS_Shrubs.csv, GDS_Trees.csv files using the R statistical software environment (R Core...


    map background search result map search result map Whitebark Pine Range, Keane 2000 for Wyoming, 1000 meters Tree species from the Vegetation Resource Inventory for the North Pacific Landscape Conservation Cooperative, British Columbia, Canada SE Alaska Cumulative Yellow-Cedar Decline Tree species from the Vegetation Resource Inventory for the North Pacific Landscape Conservation Cooperative, British Columbia, Canada Land resources of Russia - Major forest species Puerto Rico biomass error map Eastern contiguous USA biomass error map Western contiguous USA biomass error map Total Basal Area of All Tree Species 2012 Great Dismal Swamp field measurements for aboveground and belowground biomass Great Dismal Swamp field measurements for aboveground and belowground biomass Great Dismal Swamp field measurements for aboveground and belowground biomass Great Dismal Swamp field measurements for aboveground and belowground biomass Puerto Rico biomass error map SE Alaska Cumulative Yellow-Cedar Decline Whitebark Pine Range, Keane 2000 for Wyoming, 1000 meters Total Basal Area of All Tree Species 2012 Tree species from the Vegetation Resource Inventory for the North Pacific Landscape Conservation Cooperative, British Columbia, Canada Tree species from the Vegetation Resource Inventory for the North Pacific Landscape Conservation Cooperative, British Columbia, Canada Western contiguous USA biomass error map Eastern contiguous USA biomass error map Land resources of Russia - Major forest species