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  1. 3551

    SPNHC + TDWG 2018 Conference

    SPNHC + TDWG 2018 Conference Theme:聽Collections and Data in an Uncertain World New Zealand lies at the south-west end of a vast horseshoe-shaped zone of intense volcanism and earthquakes. This zone extends, essentially unbroken, around the margins of the 鈥�
  2. 3552

    Plot NEON RGB Camera Imagery in Python

    Plot NEON RGB Camera Imagery in Python This tutorial introduces NEON RGB camera images ( Data Product DP3.30010.001 ) and uses the Python package rasterio to read in and plot the camera data in Python. In this lesson, we will read in an RGB camera tile 鈥�
  3. 3553

    Remote Sensing Data Science Challenge Yields Positive Results

    Remote Sensing Data Science Challenge Yields Positive Results The NEON project is聽producing a vast treasure trove of open access remote sensing data. Can computer algorithms help ecologists make sense of it all? A team of ecologists and data scientists at 鈥�
  4. 3554

    NEON-QUBES Faculty Mentoring Network Brings Quantitative Methods to Undergraduate Classrooms

    NEON-QUBES Faculty Mentoring Network Brings Quantitative Methods to Undergraduate Classrooms The NSF鈥檚 National Ecological Observatory Network (NEON) and other observatory networks are bringing ecology into the era of "big data." How are undergraduate 鈥�
  5. 3555

    NEON AOP Hyperspectral Data in HDF5 format with Python

    NEON AOP Hyperspectral Data in HDF5 format with Python In this introductory tutorial, we demonstrate how to read NEON AOP hyperspectral reflectance (Level 3, tiled) data in Python. This starts with the fundamental steps of reading in and exploring the 鈥�
  6. 3556

    Read in and visualize hyperspectral data in Python using functions

    Read in and visualize hyperspectral data in Python using functions In this tutorial, you will learn how to efficiently read in hdf5 reflectance data and metadata, plot a single band and Red-Green-Blue (RGB) band combinations of a reflectance data tile 鈥�
  7. 3557

    Calculate NDVI & Extract Spectra Using Masks in Python

    Calculate NDVI & Extract Spectra Using Masks in Python In this tutorial, we will calculate the Normalized Difference Vegetation Index (NDVI) from hyperspectral reflectance data using Python functions. This tutorial uses the Level 3 Spectrometer 鈥�
  8. 3558

    Plot a Spectral Signature in Python - Tiled Data

    Plot a Spectral Signature in Python - Tiled Data In this tutorial, we will learn how to extract and plot a spectral profile from a single pixel of a reflectance band in a NEON hyperspectral HDF5 file. This tutorial uses the mosaiced or tiled NEON data 鈥�
  9. 3559

    Classify a Lidar Raster in Python

    Classify a Lidar Raster in Python This tutorial covers how to read in a NEON lidar Canopy Height Model (CHM) geotiff file into a Python rasterio object, shows some basic information about the raster data, and then ends with classifying the CHM into height 鈥�
  10. 3560

    Unsupervised Spectral Classification in Python: KMeans & PCA

    Unsupervised Spectral Classification in Python: KMeans & PCA In this tutorial, we will use the Spectral Python (SPy) package to run a KMeans unsupervised classification algorithm and then we will run Principal Component Analysis to reduce data 鈥�
  11. 3561

    Calibrating Soil Sensors? It's a Dirty Job, But We Had To Do It

    Calibrating Soil Sensors? It's a Dirty Job, But We Had To Do It Accurately determining soil moisture can sometimes be tricky because differences in soil composition and structure can lead to lower accuracy of sensor-based measurements. To ensure data 鈥�
  12. 3562

    STEAC Nomination Form

    STEAC Nomination Form We are currently not accepting new applications According to its Charter, the STEAC is an advisory body to the NEON Project and will provide strategic advice to Battelle, the NEON Principal Investigator (PI), and NEON Project staff 鈥�
  13. 3563

    Science, Technology & Education Advisory Committee聽(STEAC)

    Science, Technology & Education Advisory Committee聽(STEAC) AG真人百家乐官方网站 the NEON STEAC The Science, Technology & Education Advisory Committee (STEAC) is an advisory body to the NEON Program that provides strategic advice to Battelle, the NEON Principal 鈥�
  14. 3564

    Send in the Drones: Exploring the Future of Airborne Remote Sensing

    Send in the Drones: Exploring the Future of Airborne Remote Sensing Could drones be part of the NEON program's arsenal of data collection platforms one day? Drones are gaining popularity in environmental and agricultural applications. Farmers use drones 鈥�
  15. 3565

    Application Deadline: NSF INCLUDES Conference - Bringing Conversations on Diversity and Inclusion in Data Science to the Environmental Sciences

    Application Deadline: NSF INCLUDES Conference - Bringing Conversations on Diversity and Inclusion in Data Science to the Environmental Sciences Important Dates October 1, 2018: Application Deadline Early November: Notifications of Acceptance April 2-4, 鈥�
  16. 3566

    NEON Remote Sensing Flights Over Crested Butte Gather Data for LBNL Watershed Study

    NEON Remote Sensing Flights Over Crested Butte Gather Data for LBNL Watershed Study A study led by Lawrence Berkley National Laboratory (LBNL) has used the NEON Assignable Assets Program to gather airborne remote sensing data near Crested Butte, Colorado. 鈥�
  17. 3567

    The Next Steps for the NEON Project: Educate, Facilitate and Inspire

    The Next Steps for the NEON Project: Educate, Facilitate and Inspire By聽 Sharon Collinge , Past Observatory Directory and Chief Scientist 2018 is an exciting year for the NEON project. The construction of the observatory is nearing completion, with almost 鈥�
  18. 3568

    AmeriFlux Annual PI Meeting

    AmeriFlux Annual PI Meeting This event is cohosted by the Department of Energy and Ameriflux. NEON will attend to discuss synergies and opportunities for collaboration between Ameriflux and NEON. Did you know that NEON's 47 flux towers collect Ameriflux 鈥�
  19. 3569

    Harnessing Natural History Collections Data for Addressing National Challenges

    Harnessing Natural History Collections Data for Addressing National Challenges The goal of the workshop is to synthesize a set of goals and objectives for the next phase of the national effort to deploy the data held in our natural history collections for 鈥�
  20. 3570

    Advanced Phenology Information System (APIS) Annual Meeting

    Advanced Phenology Information System (APIS) Annual Meeting This is a workshop for a funded NASA proposal to create an open-access repository of tools for retrieval and analysis of phenology data. The proposal specifically points to NEON data as essential 鈥�
  21. 3571

    USA-NPN 10th Anniversary Event

    USA-NPN 10th Anniversary Event This symposium features talks on the current status of phenology research as part of the 10 year anniversary of the National Phenology Network. Research scientist, Katie Jones from the NEON project will be attending this 鈥�
  22. 3572

    Arctic Data Committee Polar Data Planning Summit

    Arctic Data Committee Polar Data Planning Summit Dates and Location 22 - 24 May 2018 UMC 415-417, University Memorial Center 1669 Euclid Ave, Boulder, Colorado, 80309 (corner of Broadway and Euclid) University of Colorado Boulder Boulder, Colorado聽 USA 鈥�
  23. 3573

    West Big Data Innovation Hub Open Annual All Hands Meeting 2018

    West Big Data Innovation Hub Open Annual All Hands Meeting 2018 Attending the聽West Big Data Innovation Hub Open Annual All Hands Meeting 2018? Stop by the聽3:30pm - Poster Session & Lightening Talks to learn more about a NEON collaboration called EDSIN: 鈥�
  24. 3574

    Southern Sierra Critical Zone Observatory 2018 Annual Meeting

    Southern Sierra Critical Zone Observatory 2018 Annual Meeting Each year the Southern Sierra Critical Zone Observatory hosts an annual team meeting. Given that the Observatory functions as a distributed network of researchers and staff, this meeting is one 鈥�
  25. 3575

    Explore NEON Workshop

    Explore NEON Workshop 鈥� Explore NEON Workshop 鈥�

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The National Ecological Observatory Network is a major facility fully funded by the U.S. National Science Foundation.

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