No description is available. Visit https://dataone.org/datasets/NEON.D01.HOPB.DP4.00131.2017.09.2018.01.03.22.59.07 for complete metadata about this dataset.

Abstract

The NeonTreeCrowns dataset is a set of individual level crown estimates for 100 million trees at 37 geographic sites across the United States surveyed by the National Ecological Observation Network’s Airborne Observation Platform. Each rectangular bounding box crown prediction includes height, crown area, and spatial location.

How can I see the data?

A web server to look through predictions is available through idtrees.org

Dataset Organization

The shapefiles.zip contains 11,000 shapefiles, each corresponding to a 1km^2 RGB tile from NEON (ID: DP3.30010.001). For example "2019_SOAP_4_302000_4100000_image.shp" are the predictions from "2019_SOAP_4_302000_4100000_image.tif" available from the NEON data portal: https://data.neonscience.org/data-products/explore?search=camera. NEON's file convention refers to the year of data collection (2019), the four letter site code (SOAP), the sampling event (4), and the utm coordinate of the top left corner (302000_4100000). For NEON site abbreviations and utm zones see https://www.neonscience.org/field-sites/field-sites-map.

The predictions are also available as a single csv for each file. All available tiles for that site and year are combined into one large site. These data are not projected, but contain the utm coordinates for each bounding box (left, bottom, right, top). For both file types the following fields are available:

Height: The crown height measured in meters. Crown height is defined as the 99th quartile of all canopy height pixels from a LiDAR height model (ID: DP3.30015.001)

Area: The crown area in m² of the rectangular bounding box.

Label: All data in this release are "Tree".

Score: The confidence score from the DeepForest deep learning algorithm. The score ranges from 0 (low confidence) to 1 (high confidence)

How were predictions made?

The DeepForest algorithm is available as a python package: https://deepforest.readthedocs.io/. Predictions were overlaid on the LiDAR-derived canopy height model. Predictions with heights less than 3m were removed.

How were predictions validated?

Please see

Weinstein, B. G., Marconi, S., Bohlman, S. A., Zare, A., & White, E. P. (2020). Cross-site learning in deep learning RGB tree crown detection. Ecological Informatics, 56, 101061.

Weinstein, B., Marconi, S., Aubry-Kientz, M., Vincent, G., Senyondo, H., & White, E. (2020). DeepForest: A Python package for RGB deep learning tree crown delineation. bioRxiv.

Weinstein, Ben G., et al. "Individual tree-crown detection in RGB imagery using semi-supervised deep learning neural networks." Remote Sensing 11.11 (2019): 1309.

Were any sites removed?

Several sites were removed due to poor NEON data quality. GRSM and PUUM both had lower quality RGB data that made them unsuitable for prediction. NEON surveys are updated annually and we expect future flights to correct these errors. We removed the GUIL puerto rico site due to its very steep topography and poor sunangle during data collection. The DeepForest algorithm responded poorly to predicting crowns in intensely shaded areas where there was very little sun penetration. We are happy to make these data are available upon request.

# Contact

We welcome questions, ideas and general inquiries. The data can be used for many applications and we look forward to hearing from you. Contact ben.weinstein@weecology.org.

Geomorphology maps characterize aquatic reaches (approximately 1,000 meters in stream length) within wadeable streams at NEON aquatic sites. Raw survey data is collected with high-resolution total station survey equipment at each NEON wadeable stream site. Survey maps and channel metrics are produced and calculated using raw survey data geo-referenced to a global coordinate system. Geomorphology surveys are conducted at each site once every five years or immediately following a storm event deemed to have significantly altered stream morphology within the aquatic reach. Geomorphology surveys conducted immediately after a stochastic event will assess event magnitude by quantifying changes in channel geometry, bed composition, and biological habitat.Download these data from the NEON data portal.

Bathymetry of lake bottoms and non-wadeable streams for detecting environmental change as well as for determining lake morphology, estimating primary productivity, habitat features, and water quality.

The points in this file have been remotely and field validated by NEON specialists and have been determined to meet NEON criteria. To download published data collected as these locations visit https://data.neonscience.org/home.The sampling locations were created by stratifying vegetation types from the National Land Cover Database (NLCD). Points were distributed in each vegetation type using a spatially balanced system implemented in GIS called the Reversed Randomized Quadrant Recursive Raster (RRQRR) technique. Subsequently, the points went through a remote sensing and ground-truth procedures to validate the vegetation type and NEON criteria. For more information please contact the Permitting Department at NEON, contact information is available at www.neonscience.org. This layer is current as of July 2, 2024.

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Geomorphology maps characterize aquatic reaches (approximately 1,000 meters in stream length) within wadeable streams at NEON aquatic sites. Raw survey data is collected with high-resolution total station survey equipment at each NEON wadeable stream site. Survey maps and channel metrics are produced and calculated using raw survey data geo-referenced to a global coordinate system. Geomorphology surveys are conducted at each site once every five years or immediately following a storm event deemed to have significantly altered stream morphology within the aquatic reach. Geomorphology surveys conducted immediately after a stochastic event will assess event magnitude by quantifying changes in channel geometry, bed composition, and biological habitat.Download these data from the NEON data portal.

The points in this file have been remotely and field validated by NEON specialists and have been determined to meet NEON criteria. To download published data collected as these locations visit https://data.neonscience.org/home.The sampling locations were created by stratifying vegetation types from the National Land Cover Database (NLCD). Points were distributed in each vegetation type using a spatially balanced system implemented in GIS called the Reversed Randomized Quadrant Recursive Raster (RRQRR) technique. Subsequently, the points went through a remote sensing and ground-truth procedures to validate the vegetation type and NEON criteria. For more information please contact the Permitting Department at NEON, contact information is available at www.neonscience.org. This layer is current as of July 2, 2024.

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Geomorphology maps characterize aquatic reaches (approximately 1,000 meters in stream length) within wadeable streams at NEON aquatic sites. Raw survey data is collected with high-resolution total station survey equipment at each NEON wadeable stream site. Survey maps and channel metrics are produced and calculated using raw survey data geo-referenced to a global coordinate system. Geomorphology surveys are conducted at each site once every five years or immediately following a storm event deemed to have significantly altered stream morphology within the aquatic reach. Geomorphology surveys conducted immediately after a stochastic event will assess event magnitude by quantifying changes in channel geometry, bed composition, and biological habitat.Download these data from the NEON data portal.

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This data package contains identifiers, metadata, and a map of the locations where field measurements have been conducted at the East River Community Observatory located in the Upper Colorado River Basin, United States. The East River is the primary field site of the Watershed Function Scientific Focus Area (WFSFA) and the Rocky Mountain Biological Laboratory. Researchers from over 30 institutions generate highly diverse hydrological, biogeochemical, climate, vegetation, geological, remote sensing, and model data at the East River in collaboration with the WFSFA. Thus, the purpose of this data package is to maintain an inventory of the field locations and instrumentation to provide information on the field activities in the East River and coordinate data collected across different locations, researchers, and institutions. The data package contains (1) a README file with information on the various files, (2) three csv files describing the metadata collected for each surface point location, plot and region registered with the WF SFA, (3) csv files with metadata and contact information for each surface point location registered with the WF SFA, (4) a csv file with with metadata and contact information for plots, (5) a csv file with metadata for geographic regions and sub-regions within the watershed, (6) a compiled xlsx file with all the data and metadata which can be opened in Microsoft Excel, and (7) a kmz map of the locations plotted in the watershed which can be opened in Google Earth. Persistent location identifiers are determined by the WFSFA data management team and are used to track data and samples across locations. Researchers interested in having their East River measurement locations added in this list should reach out to the WFSFA data management team at wfsfa-data@googlegroups.com. Acknowledgements: Please cite this dataset if using any of the location metadata in other publications or derived products. If using the location metadata for the NEON hyperspectral campaign, additionally cite Chadwick et al. (2020). doi:10.15485/1618130.

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We propose joint observations with Chandra and XMMNewton of the superChandrasekhar mass white dwarf merger product Cas J005311. A first pilot XMMNewton observation revealed an astonishingly high Xray luminosityof Cas J005311 and its remarkable nebula which is strongly enriched in Neand Mg. The proposed ACISI observations will map the nebula and probechemical gradients across it, as necessary to unravel the evolutionaryhistory of the merger. We will search for Xray pulsations to test magneticfields and rotation of Cas J005311. Jointly, Chandra and XMMNewton will reveal the physical mechanisms powering the Xrays from the central star and the nebula. truncated!, Please see actual data for full text [truncated!, Please see actual data for full text]

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Geomorphology maps characterize aquatic reaches (approximately 1,000 meters in stream length) within wadeable streams at NEON aquatic sites. Raw survey data is collected with high-resolution total station survey equipment at each NEON wadeable stream site. Survey maps and channel metrics are produced and calculated using raw survey data geo-referenced to a global coordinate system. Geomorphology surveys are conducted at each site once every five years or immediately following a storm event deemed to have significantly altered stream morphology within the aquatic reach. Geomorphology surveys conducted immediately after a stochastic event will assess event magnitude by quantifying changes in channel geometry, bed composition, and biological habitat.Download these data from the NEON data portal.

Geomorphology maps characterize aquatic reaches (approximately 1,000 meters in stream length) within wadeable streams at NEON aquatic sites. Raw survey data is collected with high-resolution total station survey equipment at each NEON wadeable stream site. Survey maps and channel metrics are produced and calculated using raw survey data geo-referenced to a global coordinate system. Geomorphology surveys are conducted at each site once every five years or immediately following a storm event deemed to have significantly altered stream morphology within the aquatic reach. Geomorphology surveys conducted immediately after a stochastic event will assess event magnitude by quantifying changes in channel geometry, bed composition, and biological habitat.Download these data from the NEON data portal.

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