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9 results for “National Forest Inventory”
Dataset linking to the paper "Exploring characteristics of national forest inventories for integration with global space-based forest biomass data"
<p>The dataset links to the study titled “Exploring characteristics of national forest inventories for integration with global space-based forest biomass data”. This study is published in the journal “Science of the Total Environment” and the publication can be found at <a href="https://doi.org/10.1016/j.scitotenv.2022.157788">https://doi.org/10.1016/j.scitotenv.2022.157788</a>. The dataset contains four csv files that were used to produce the results and other figures in the paper. The description of the individual data files contained in the dataset is given below.</p> <p><strong>NFI availability and characteristics data: </strong>The data file “NFI_availability_characteristics.csv” contains data on the total number of NFIs, the NFI extent, and the year of the most recent NFI in countries with NFI as reported in FRA 2020 country reports. The respective data variables in the data file are termed as Number_of_NFI, Latest_NFI_extent_FRA2020, and Latest_NFI_year_FRA2020 (NFI years generally refer to the years of data collection). In addition, the data file contains data on the region and tropical domain per country. The tropical and subtropical countries were considered tropical in the analysis and interpretation of the results. These data were used to produce Figure 2 of the study. ArcMap 10.7.1 was used for this purpose. </p> <p><strong>National biomass intercomparison data: </strong>The data file “national_biomass_intercomparison.csv” contains national forest AGB data for the year 2018 from FRA 2020 and CCI Biomass product that were used in the national biomass intercomparison analysis. The total (tons) and average space-based AGB (tons/ha) are extracted directly from the CCI Biomass Map 2018 for each country included in the study. The processing is done in Python and R environments. The spatial resolution of the map is 100 m. The average FRA AGB data in tons per ha was compiled from FRA 2020 country reports. The total FRA AGB data (tons) was estimated by multiplying each country's average FRA AGB data with FRA forest area data (in ha).</p> <p>The data unit for total AGB was converted from tons to gigaton (Gt) in intercomparison analysis. The total CCI Map AGB estimates used in the analysis are termed as CCI_MAP_AGB_Gt in the data file and the average as CCI_Map_AGB_tons.ha. Similarly, the total FRA AGB data are termed as FRA_AGB_Gt and the average as FRA_AGB_ton.ha. The NFI availability and temporality were also used in intercomparison analysis and this data is termed as Latest_NFI_year_FRA2020 in the data file. The data were used to produce Figure 3 of the study in the R environment.</p> <p><strong>NFI plot design characteristics: </strong>The data file named “NFI_plot_design_characteristics.csv” contains data on variables that were used in the analysis of NFI plot designs in 46 tropical countries. This data file mainly contains the data that was used to produce Figure 4 and Figure 6 in the R environment. The value “uniform” in the sampling_stratification variable means no stratification was used in the sampling design. The variable name “psu” stands for primary sampling unit (both cluster and single plots), “psu_distance_km” for the distance between primary sampling units in km, “cluster_plotdis_m” for the distance between plots in meter in the cluster, “plotsize_ha” for plot (single and cluster plots ) size in ha, “plotshape” for plot shapes (single and cluster plots), “ILUA” for Integrated Land Use Assessment. The data were compiled from the latest NFI design manuals and NFI reports.</p> <p><strong>NFI years: </strong>The data file “NFI_years_tropical_countries_data.csv” contains data on NFI years of the latest NFI in 46 tropical countries that were used to produce Figure 1 using ArcMap 10.7.1. The years generally refer to the last years of data collection. Data were compiled from the latest country NFI design manual or NFI report. This included both ongoing and completed NFI.</p>
Willamette National Forest soil resource inventory (SRI 1992) clipped to the Andrews Experimental Forest
This layer contains the delineations of the soil landtype mapping units defined in the 1992 update to the SRI (Soil Resource Inventory) The mapping units are derived and defined on the basis of soil, landform, geology and vegetation characteristics. The average delineation size for each mapping unit is 50 to 600 acres. This data was originally mapped at the 1:24000 scale. Due to the reconnaissance nature of this survey, it lacks detail for use in high-intensity, small-area projects. These projects require additional on-site study by various technical specialists, including soil scientists. The dominant landtype of the mapping unit is described in the mapping unit description and identified by the same number as used for the mapping unit. Within the mapping unit, other landtypes occur. Those most commonly associated with the dominant landtype of the mapping unit are included in the descriptions as inclusions. These inclusions of other landtypes account for no more than 30 percent of the mapping unit. (for further descriptions of mapping unit symbology see SOIL RESOURCE INVENTORY" Willamette National Forest, Basic Soil Information and Interpretive Tables
Forest segmentation of multi-source national forest inventory biomass rasters and canopy height model from 2021
<p>The dataset is produced at Natural Resources Institute Finland (Luke) and the study is funded by the European Union's Horizon 2020 research and innovation programme (Holisoils, grant agreement No 101000289).</p> <p>Source data (multi-source National Forest Inventory, MS-NFI and peatland fertility map of Finland) of varying resolution (10m -16m) was reprojected to 10mx10m resolution from which stand polygons were formulated based on automatic segmentation and regional minimum size limit for a stand.</p> <p>The dataset is a file geodatabase with 5 regional layers, all including the polygons of stands with stand attributes based on MS-NFI 2021 information on the site type, fertility class, dominant height, basal area, diameter, age, volume as total and per tree species, total and aboveground biomass as total and per tree species.</p> <p>Coordinate system: ETRS-TM35FIN (EPSG:3067)</p>
High-Resolution Pan-European Forest Structure Maps: An Integration of Earth Observation and National Forest Inventory Data
<p>We developed Pan-European maps of timber volume (V), above-ground biomass (AGB), and deciduous-coniferous proportion (DCP) with a pixel size of 10 x 10 m<sup>2</sup> for the reference year 2020 using a combination of a Sentinel 2 mosaic, Copernicus layers, and National Forest Inventory (NFI) data.</p> <p>For mapping, we used the k-Nearest Neighbor (kNN, k=7) approach with a harmonized database of species-specific V and AGB from 14 NFIs across Europe. This database encompasses approximately 151,000 sample plots, which were intersected with the above-mentioned Earth observation data. The maps cover 40<a> European countries, </a>forming a continuous coverage of the western part of the European continent.</p> <p>A sample of 1/3 of NFI plots was left out for validation, whereas 2/3 of the plots were used for mapping. Maps were created independently for 13 multi-country processing areas. Root-mean-squared-errors (RMSEs) for AGB ranged from 53 % in the Nordic processing area to <a>73 % </a>the South-Eastern area.</p> <p>The created maps are the first of their kind as they are utilizing a huge amount of harmonized NFI observations and consistent remote sensing data for high-resolution forest attribute mapping. While the published maps can be useful for visualization and other purposes, they are primarily meant as auxiliary information in model-assisted estimation where model-related biases can be mitigated, and field-based estimates improved. Therefore, additional calibration procedures were not applied, and especially high V and AGB values tend to be underestimated. Summarizing map values (pixel counting) over large regions such as countries or whole Europe will consequently result in biased estimates that need to be interpreted with care.</p> <p>The author list is sorted by last name except for the first and last authors who also serve as corresponding authors.</p> <p>Corresponding authors: <a href="mailto:Jukka.Miettinen@vtt.fi">Jukka.Miettinen@vtt.fi</a>, <a href="mailto:Johannes.Breidenbach@nibio.no">Johannes.Breidenbach@nibio.no</a></p>
National forest inventory data for a size-structured forest population model
<p>In forest communities, light competition is a key process for community assembly. Species' differences in seedling and sapling tolerance to shade cast by overstory trees is thought to determine species composition at late-successional stages. Most forests are distant from these late-successional equilibria, impeding a formal evaluation of their potential species composition. To extrapolate competitive equilibria from short-term data, we therefore introduce the JAB model, a parsimonious dynamic model with interacting size-structured populations, which focuses on sapling demography including the tolerance to overstory competition. We apply the JAB model to a two-"species" system from temperate European forests, i.e. the shade-tolerant species Fagus sylvatica L. and the group of all other competing species. Using Bayesian calibration with prior information from external Slovakian national forest inventory (NFI) data, we fit the JAB model to short timeseries from the German NFI. We use the posterior estimates of demographic rates to extrapolate that F. sylvatica will be the predominant species in 94% of the competitive equilibria, despite only predominating in 24% of the initial states. We further simulate counterfactual equilibria with parameters switched between species to assess the role of different demographic processes for competitive equilibria. These simulations confirm the hypothesis that the higher shade-tolerance of F. sylvatica saplings is key for its long-term predominance. Our results highlight the importance of demographic differences in early life stages for tree species assembly in forest communities.</p>
National forest inventory data for a size-structured forest population model
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National Forest and Soils Inventory of Mexico 2009-2014
This dataset contains plot estimates of dasometric indicators in all Mexican forest ecosystems. The dataset is from the National Forest and Soils Inventory (INFyS) of Mexico from the 2009-2014 cycle (n>26,000 sampling plots).
Repeated tree inventories of pine forests in South Florida's Big Cypress National Preserve
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Tree Inventory and Biometry Measurements, Tapajos National Forest, Para, Brazil, 2010
This dataset provides tree inventory, tree height, diameter at breast height (DBH), and estimated crown measurements from 30 plots located in the Tapajos National Forest, Para, Brazil collected in September 2010. The plots were located in primary forest, primary forest subject to reduced-impact selective logging (PFL) between 1999 and 2003, and secondary forest (SF) with different age and disturbance histories. Plots were centered on GLAS (the Geoscience Laser Altimeter System) LiDAR instrument footprints selected along two sensor acquisition tracks spanning a wide range in vertical structure and aboveground biomass.
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