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13,116 results for “mapping”
Tree Ring Data from the Lyford Mapped Tree Plot at Harvard Forest 1861-2014
Is it possible to reconstruct aboveground carbon/biomass from tree rings? If so, how far back in time can researchers go when using tree-ring data in the reconstruction of past biomass? Answers to these questions will have a significant impact on our understanding of dynamics in the terrestrial carbon sink. Long tree-ring records of biomass can reveal intra-annual to annual to multidecadal variations that cannot be resolved by forest census data that is not conducted annually. Additionally, while these dynamics might be resolved using remote sensing, most remotely-sensed products are only two decades or less in length. By having long records of carbon biomass, we can then identify not only the dominant drivers of biomass, but how the importance of these drivers might change during different eras as environmental factors change (e.g., climate, air pollution, disturbance). To test these and other questions, we collected tree-ring records from three 20m radius plots set within the Lyford Plot at the Harvard Forest. The Lyford Plot has been remeasured, on average, decadally since 1969. We can convert these data to biomass using allometric equations and compare tree-ring inferred aboveground biomass to the census data going back in time. Dye et al. (2016) have shown that these data fall within the range of uncertainty of census data sampled in similar plots going back to 1969. Dye, A., Barker Plotkin, A., Bishop, D., Pederson, N., Poulter, B. and Hessl, A., 2016. Comparing tree‐ring and permanent plot estimates of aboveground net primary production in three eastern US forests. Ecosphere, 7(9).
1830 Map of Land Cover and Cultural Features in Massachusetts
Background and Data Limitations The Massachusetts 1830 map series represents a unique data source that depicts land cover and cultural features during the historical period of widespread land clearing for agricultural. To our knowledge, Massachusetts is the only state in the US where detailed land cover information was comprehensively mapped at such an early date. As a result, these maps provide unusual insight into land cover and cultural patterns in 19th century New England. However, as with any historical data, the limitations and appropriate uses of these data must be recognized: (1) These maps were originally developed by many different surveyors across the state, with varying levels of effort and accuracy. (2) It is apparent that original mapping did not follow consistent surveying or drafting protocols; for instance, no consistent minimum mapping unit was identified or used by different surveyors; as a result, whereas some maps depict only large forest blocks, others also depict small wooded areas, suggesting that numerous smaller woodlands may have gone unmapped in many towns. Surveyors also were apparently not consistent in what they mapped as ‘woodlands’: comparison with independently collected tax valuation data from the same time period indicates substantial lack of consistency among towns in the relative amounts of ‘woodlands’, ‘unimproved’ lands, and ‘unimproveable’ lands that were mapped as ‘woodlands’ on the 1830 maps. In some instances, the lack of consistent mapping protocols resulted in substantially different patterns of forest cover being depicted on maps from adjoining towns that may in fact have had relatively similar forest patterns or in woodlands that ‘end’ at a town boundary. (3) The degree to which these maps represent approximations of ‘primary’ woodlands (i.e., areas that were never cleared for agriculture during the historical period, but were generally logged for wood products) varies considerably from town to town, depending on wheth
Mapped Trees in CRUI Land Use Project at Harvard Forest 1996-2006
Numerous variables related to land use disturbance and recovery processes influence forest composition, structure, and growth. We measured forest communities in six sites that were formerly plowed, pastured, or continuously forested woodlots in Prospect Hill to test predictions about species composition, stand structure, and productivity in response to agricultural land use legacies. A permanent 30 x 50 m plot gridded in 5 x 5 m sub-plots was established in each of the 6 sites. All trees at least 2.5 cm DBH (diameter at breast height, 1.3 m) were mapped visually in the field, marked with an aluminum tag, and their DBH recorded in summer 1996. Individual boles of multi-stemmed trees were measured separately and a composite single DBH was calculated. Standing dead trees were also mapped and their DBH recorded as well. The 1996 data were used to determine above ground woody biomass using allometric equations for individual trees. The permanent plots were re-surveyed ten years later in fall 2006. The status of each tree mapped in 1996 was recorded (alive, dead standing, dead fallen, forked) and DBH’s were re-measured. Additional trees that grew across the 2.5 cm DBH threshold during the ten-year period were mapped and their DBH’s measured. Composite diameters and above ground woody biomass were determined for forked trees as in 1996. The 2006 re-measurements were used to analyze changes in species composition, stand structure (density, diameter distribution), and mortality patterns among species and size classes, and to calculate net changes in above ground woody biomass across the ten-year period.
Annual Maps of Mean Winter Temperature for Eastern North America 1951-2009
We developed annual raster maps depicting spatiotemporal variation in mean winter temperature for the purposes of modeling the spread of the hemlock woolly adelgid. The maps are based on the PRISM and WorldClim datasets as described in methods.
Hemlock Mapped Tree Plot at Harvard Forest since 1990
Most of the central New England landscape was cleared for agriculture in the mid-19th century and then naturally reforested into "secondary forests" with the abandonment of agricultural land. Some sites, often poorly drained, remained forested, but were usually subjected to intensive fuelwood cutting or logging and are termed "primary forests." The Hemlock Woodlot was never cleared for agriculture, but has a history of cutting and natural disturbance. The hemlock woodlot is located in the center of Harvard Forest's Prospect Hill Tract, adjacent to a spruce-blackgum swamp. Soils are moist and rocky, with a thick organic layer. Hemlock dominates tree species composition (62% by basal area), with hardwoods and scattered large white pine comprising the remainder. Most of the trees are 100-150 years old, with a few hemlock trees up to 230 years old. While the site was never cleared for agriculture, it was logged several times and chestnut blight removed a chestnut-dominated overstory in the 1910s. The 0.72 ha stem-mapped plot is at the center of a 4-ha hemlock-dominated forest. This plot serves as a major reference site and is part of a network of hemlock forests that are being intensively sampled as the hemlock woolly adelgid arrives.
Lyford Mapped Tree Plot at Harvard Forest since 1969
Permanent forest plots provide an empirical understanding of forest change over time, and are an invaluable part of forestry and ecological research. Walter Lyford began measurements of a 2.88 ha red oak-red maple forest on the Prospect Hill Tract of Harvard Forest in 1969. All trees over 2 inches (5 cm) were mapped on very large-scale (1 inch = 5 feet) hand-drawn maps, and included live and dead trees, stumps, windthrows and other features such as stone walls, boulders, soil moisture and a damage boundary from the 1938 hurricane. All living and dead trees have been re-located and measured (diameter at breast height, canopy class for live trees; condition, decay class, diameter, bole length and stem orientation for fallen dead trees) in 1969, 1975, 1987-1992, 2001, and 2011. In 2001, the original, hand-drawn maps were digitized using ArcView GIS. From 1969 to 2011, red oak (Quercus rubra) increased its dominance of the stand’s total basal area from 52% to 60%; however, red maple (Acer rubrum) has become relatively less abundant, decreasing from 30% to 23%. While red oak and red maple continue to account for the majority of the basal area in the stand, the secondary species experienced a dramatic increase in relative abundance of individuals in the stand; yellow birch (Betula alleghaniensis), black birch (Betula lenta), American chestnut (Castanea dentata), American beech (Fagus grandifolia), witch hazel (Hamamelis virginiana), eastern white pine (Pinus strobus), and eastern hemlock (Tsuga canadensis) have increased from comprising 25% of the individuals in the stand in 1969 to comprising 52% in 2011. The total biomass of living individuals is increasing linearly (R2=0.99, p=0.0002), which implies that the stand has not yet experienced an age-induced decrease in biomass accumulation.
Overstory Mapped Tree Plots at Harvard Forest since 1990
These plots were established and mapped in 1990 for an experiment designed to study the effects of selective overstory tree mortality. The planned manipulation was to kill and leave standing one species in each of four plots, to simulate mortality by a species-specific pathogen. This manipulation was never done, for logistical reasons and because the appearance of the hemlock woolly adelgid provided a more pressing "natural" experiment to study; however, the plots are maintained and have been used in other studies. There are four 50m x 50m plots, located in a mixed hardwood forest (red oak and maple species are major components), north of the experimental hurricane. Tree data from the control plot of the experimental hurricane study could be added to this set for some analyses, since all the plots are in the same general area and forest type, and similar types of measurements were made on all of these trees. Tree diameter and condition were re-surveyed in these plots in Autumns 2003, 2013 and 2023, and saplings growing into the "tree" size class of greater than or equal to 5cm diameter were measured, tagged and mapped.
Annual Maps of Forest Harvest Events in Maine from LANDSAT Imagery 1986-2019
We used Landsat satellite imagery and forest inventory plot measurements to develop a time series of annual maps representing potential forest harvest events for the state of Maine in the Northeastern US for the years 1986 to 2019. We first generated a set of LandTrendr temporal segmentation results for three different spectral indices. Change results were filtered to remove events greater than two years in duration, then results were combined using a seven-parameter degenerate decision trees model that determined a set of thresholds on disturbance patch size, magnitude of spectral change, and change “votes” across indices. We found that we were able to detect harvest events that removed at least 30% of total basal area with a mean F1 score of 0.72 (σ = 0.02) with a mean false negative error rate (omission) of 0.32 (σ = 0.02) and mean false positive error rate (commission) of 0.23 (σ = 0.03), and these scores further improve when maps are masked to remove human land use (built and agriculture) and water based on National Land Cover Dataset and JRC Global Surface Water classifications (mean F1 = 0.73, σ = 0.02). Comparisons with an out-of-sample reference dataset and an existing national forest disturbance dataset indicate our forest harvest maps are a locally accurate source of information for characterizing spatial and temporal variability in long-term harvest patterns across the industrial forests of northern Maine. Here, we provide annual ensemble-based maps of potential harvest events; cross-validated results, which give an indication of detection agreement across subsets of our forest inventory reference datasets; and ancillary datasets that can be used to mask false detections in urban and agricultural land uses and water.
Invasive Species Mapping at Harvard Forest 2005
We are monitoring vegetation at the Harvard Forest for invasive plant populations with respect to land use history and other factors. Using our historical database for the Harvard Forest Prospect Hill tract, we have begun mapping the current distribution of non-native plants as a function of past land use. The 320 ha tract of Prospect Hill is mapped by parcels with known land-use history, soils, vegetation composition, and long-term vegetation dynamics. We plan to conduct annual vegetation surveys at Harvard Forest and the adjacent Quabbin Reservation to document six key non-native species currently present in the area: A. petiolata, the non-native shrubs B. thunbergii, Rhamnus cathartica, R. frangula, Lonicera spp. and the climbing vine, Celastrus orbiculatus. We will map the GPS coordinates and record cover estimates of each species and conduct spatial analyses on these data using our extensive records and GIS maps of land use histories at these locations. Detailed site histories will be determined certain species of interest, using field and archival records. Using similar techniques, we also plan to monitor invasive plant populations at key experimental plots (including the hemlock removal experiment at Simes Tract, and the "recovery phase" of the Chronic N addition plots). Together, these landscape-level studies will provide a novel historical context for understanding biological invasions in a historical context.
Massachusetts Growing Degree Day and Precipitation Maps 2003
A regression model that estimates monthly temperature and precipitation as a function of latitude, longitude, and elevation for the New England area was used to estimate annual growing degree days and precipitation for the state of Massachusetts. For details of the regression model please see the published paper (Ollinger, S.V., Aber, J.D., Federer, C.A., Lovett, G.M., Ellis, J.M., 1995. Modeling Physical and Chemical Climate of the Northeastern United States for a Geographic Information System. US Dept of Agriculture, Forest Service, Radnor, PA, USA).
Indicative distribution maps for Ecosystem Functional Groups - Level 3 of IUCN Global Ecosystem Typology
<p>This dataset includes the current version of the indicative distribution maps and profiles for <strong>Ecosystem Functional Groups</strong> - Level 3 of IUCN Global Ecosystem Typology (v2.1). Please refer to Keith <em>et al.</em> (2020) and Keith et al. (2022).</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes for each functional group of ecosystems to enable any ecosystem type to be assigned to a group.</p> <p>Maps are indicative of global distribution patterns and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Most maps were prepared using a coarse-scale template (e.g. ecoregions), but some were compiled from higher resolution spatial data where available (see details in profiles). Higher resolution mapping is planned in future publications.</p> <p>We emphasise that spatial representation of Ecosystem Functional Groups does not follow higher-order groupings described in respective ecoregion classifications. Consequently, when Ecosystem Functional Groups are aggregated into<strong> functional biomes</strong> (Level 2 of the Global Ecosystem Typology), spatial patterns may differ from those of biogeographic biomes. Differences reflect the distinctions between functional and biogeographic interpretations of the term, “biome”.</p>
Forest disturbances in Europe mapped at high spatial detail and in near-real-time: Logging in protected Estonian forests
<p><strong>Data description</strong></p> <p>These datasets were generated for the Geostory "Forest disturbances in Europe mapped at high spatial detail and in near-real-time: Logging in protected Estonian forests" in the context of the Open Earth Monitor Cyberinfrastructure project.</p> <p>We used open source high-resolution Sentinel-1 satellite data to develop a wall-to-wall map of forest disturbances in the four-year period between the start of 2020 and end of 2023 in Estonia. First results are presented. The methodology is based on RADD-alerts developed for the pan-tropics (Reiche et al. 2021). Three years (2017-2019) of imagery was used as a historical period, and detections were generated for ~4 years (2020-2023). Winter images from November through March were not included as frozen conditions can introduce false detections. This will be addressed in the next version. Disclaimer: Disturbance maps have not been validated.</p> <p>Two additional layers are provided for visualization: a forest baseline layer (<em>forestcover</em>), masking out non-forest disturbance detections, was derived from Copernicus 10m 2018 forest cover density and GLAD 30m 2019 tree removal datasets, and a protected areas layer (<em>natura</em>), which displays the extent of Natura 2000 coverage in Estonia.</p> <p>'.SLD' files are provided for visualization (note: the <em>disturbance</em> .SLC file must be adjusted to contain appropriate time reference fields).</p> <p><strong>Naming Convention</strong></p> <p>To ensure consistency and ease of use across and within the projects, we follow the standard Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describes important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. For instance:</p> <ul> <li>disturbance_radd_c_10m_s_20200101_20200131_eu_epsg.3035_v20240222.tif</li> </ul> <p>with the following fields:</p> <ul> <li>Generic variable name: <strong>disturbance</strong></li> <li>Variable procedure combination i.e. method standard: <strong>radd</strong></li> <li>Position in the probability distribution / variable type: <strong>c</strong></li> <li>Spatial support: <strong>10m</strong></li> <li>Depth reference or depth interval e.g. below ("b"), above ("a") ground or at surface ("s"): <strong>s</strong></li> <li>Time reference begin time (YYYYMMDD): <strong>20200101</strong></li> <li>Time reference end time: <strong>20200131</strong></li> <li>Bounding box (2 letters max): <strong>eu </strong></li> <li>EPSG code: <strong>epsg.3035</strong></li> <li>Version code i.e. creation date: <strong>v20240222</strong></li> </ul> <p><strong>Source Data</strong></p> <p>Disturbance maps:</p> <p>Contains modified Copernicus Sentinel data [2017-2023] and Generated using European Union's EEA-10 Copernicus DEM; https://doi.org/10.5270/ESA-c5d3d65</p> <p>Forest baseline:</p> <p>Generated using European Union's Copernicus Land Monitoring Service information; https://doi.org/10.2909/486f77da-d605-423e-93a9-680760ab6791 and GLAD tree removal; https://doi.org/10.1016/j.rse.2023.113797</p> <p>Natura 2000: </p> <p>Generated using European Environmental Agency's Natura 2000 layers; https://sdi.eea.europa.eu/data/dae737fd-7ee1-4b0a-9eb7-1954eec00c65</p>
INTERPNT Software for Mapping Trees Using Distance Measurements
The INTERPNT method can be used to produce accurate maps of trees based solely on tree diameter and tree-to-tree distance measurements. For additional details on the technique please see the published paper (Boose, E. R., E. F. Boose and A. L. Lezberg. 1998. A practical method for mapping trees using distance measurements. Ecology 79: 819-827). Additional information is contained in the documentation that accompanies the program. The Abstract from the paper is reproduced below. "Accurate maps of the locations of trees are useful for many ecological studies but are often difficult to obtain with traditional surveying methods because the trees hinder line of sight measurements. An alternative method, inspired by earlier work of F. Rohlf and J. Archie, is presented. This "Interpoint method" is based solely on tree diameter and tree-to-tree distance measurements. A computer performs the necessary triangulation and detects gross errors. The Interpoint method was used to map trees in seven long-term study plots at the Harvard Forest, ranging from 0.25 ha (200 trees) to 0.80 ha (889 trees). The question of accumulation of error was addressed though a computer simulation designed to model field conditions as closely as possible. The simulation showed that the technique is highly accurate and that errors accumulate quite slowly if measurements are made with reasonable care (e.g., average predicted location errors after 1,000 trees and after 10,000 trees were 9 cm and 15 cm, respectively, for measurement errors comparable to field conditions; similar values were obtained in an independent survey of one of the field plots). The technique requires only measuring tapes, a computer, and two or three field personnel. Previous field experience is not required. The Interpoint method is a good choice for mapping trees where a high level of accuracy is desired, especially where expensive surveying equipment and trained personnel are not available."
Imputed Forest Composition Map for New England Screened by Species Range Boundaries 2001-2006
Initializing forest landscape models (FLMs) to simulate changes in tree species composition requires accurate fine-scale forest attribute information mapped contiguously over large areas. Nearest-neighbor imputation maps have high potential for use as the initial condition within FLMs, but the tendency for field plots to be imputed over large geographical distances results in species frequently mapped outside of their home ranges, which is problematic. We developed an approach for evaluating and selecting field plots for imputation based on their similarity in feature-space, their species composition, and their geographical distance between source and imputation to produce a map that is appropriate for initializing an FLM. We applied this approach to map 13m ha of forest throughout the six New England states (Rhode Island, Connecticut, Massachusetts, New Hampshire, Vermont, and Maine). The map itself is a .img raster file of FIA plot CN numbers. To access FIA data from this map, one has to link the mapcodes in this map to FIA data supplied by USDA FIA database (https://apps.fs.usda.gov/fia/datamart/datamart.html). Due to plot confidentiality and integrity concerns, pixels containing FIA plots were always assigned to some other plot than the actual one found there.
Harvard Forest CTFS-ForestGEO Mapped Forest Plot since 2014
To investigate the forest dynamics across a larger range of scales in which many processes operate, Harvard Forest (HF) researchers, with assistance from the Center for Tropical Forest Science (CTFS) and the Smithsonian Institute’s Forest Global Earth Observatory (ForestGEO), completed an initial census of all woody stems within a 35 ha plot located at the Harvard Forest in 2014. The HF MegaPlot is part of a global array of large-scale plots established by CTFS whose goals are to increase sampling efforts into temperate forests to explore ecosystem processes beyond population dynamics and biodiversity. The geography and size of the HF MegaPlot (500 m x 700 m) is designed to include a continuous, expansive, and varied natural forest landscape. The strategic plot location will yield opportunities for the study of forest dynamics and demography while capturing a large amount of existing NSF funded LTER (Long Term Ecological Research) science infrastructure (e.g. eddy flux towers, gauged sections of a small watershed, existing smaller permanent plots) and a century of observations and studies. The HF MegaPlot will enable an integrated study of ecosystem processes (e.g., biogeochemistry, hydrology, carbon dynamics) and forest dynamics by melding the past with current and future forest research. The second census was conducted during the summers of 2018 and 2019 but did not contain the central swamp portion of the plot.
Forest Type Maps for New England from Historical Studies 1912-1956
This data package contains 3 GIS layers showing generalized forest types across New England as delineated in older forestry publications. These were digitized so that they can be used to illustrate broad vegetation patterns across the region in modern publications. These GIS layers include maps drawn by Hawley and Hawes (1912), RT Fisher (1933), and Westveld and the Committee on Silviculture, New England Section, Society of American Foresters (1956).
Historical Plat Maps of Dane County Digitized and Converted to GIS (1962-2005)
We constructed a time-series spatial dataset of parcel boundaries for the period 1962-2005, in roughly 4-year intervals, by digitizing historical plat maps for Dane County and combining them with the 2005 GIS digital parcel dataset. The resulting datasets enable the consistent tracking of subdivision and development for all parcels over a given time frame. The process involved 1) dissolving and merging the 2005 digital Dane County parcel dataset based on contiguity and name, 2) further merging 2005 parcels based on the hard copy 2005 Plat book, and then 3) the reverse chronological merging of parcels to reconstruct previous years, at 4-year intervals, based on historical plat books. Additional land use information such as 1) whether a structure was actually constructed (using the companion digitized aerial photo dataset), 2) cover crop, and 3) permeable surface area, can be added to these datasets at a later date.
Species-level map of Smith Island, VA from remote sensing 2003
Species-level vegetation map for Smith Island off the tip of the Delmarva Peninsula in Virginia. Created by Charles M. Bachmann of the Naval Research Laboratory based classification of hyperspectral imagery using 3-season data (two PROBE2 scenes and a Hymap scene).
3D Mapping of Neurofibrillary Tangle Burden in the Human Medial Temporal Lobe
Open the record for dataset details and reuse information.
A global map of terrestrial habitat types
<p>We provide a global spatially explicit characterization of 47 (version 001) terrestrial habitat types, as defined in the International Union for Conservation of Nature (IUCN) habitat classification scheme, which is widely used in ecological analyses, including for assessing species’ Area of Habitat. We produced this novel habitat map by creating a global decision tree that intersects the best currently available global data on land cover, climate and land use. The maps broaden our understanding of habitats globally, assist in constructing area of habitat (AOH) refinements and are relevant for broad-scale ecological studies and future IUCN Red List assessments. We hope that these data and outlined framework will spur further development of biodiversity-relevant habitat maps at global scales. An interactive interface helping to navigate the map can be found at on the Naturemap website ( https://explorer.naturemap.earth/map).</p> <p>Provided is the code to recreate the map (to made available soon), the global composite image at native -100m Copernicus resolution for level 1 and level 2 and layers of aggregated fractional cover (unit: [0-1] * 1000) at 1km for level 1 and level 2.</p> <p>Starting with version 004 there changemasks for the years 2016, 2017, 2018 and 2019 are supplied. Changemasks for the composite masks show the changed grid cells and their new values with earlier years being nested in later years, e.g. using the changemask for 2019 includes all changes up to 2019. For the fractional cover estimates at ~1km resolution, new fractional cover changemasks are supplied as subtraction (before - after) between the previous and current year (unit range: [-1 to 1] * 1000).</p> <p>We highlight that only changes in land cover are considered since most of the ancillary layers (e.g. pasture, forest management, climate, etc...) are static and thus not all changes in habitats can be found. We therefore recommend end users to continue using the 2015 dataset unless specific habitat updates to habitat are needed.</p> <p><strong>Citation:</strong></p> <p>Please cite the published paper and state the used version of the habitat map</p> <p>Jung, M., Dahal, P.R., Butchart, S.H.M., Donald, P.F., De Lamo, X., Lesiv, M., Kapos, V., Rondinini, C., Visconti, P., (2020). A global map of terrestrial habitat types. Sci. Data 7, 256. <a href="https://doi.org/10.1038/s41597-020-00599-8">https://doi.org/10.1038/s41597-020-00599-8</a></p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.