skip to main content


Title: Near-real-time MODIS-derived vegetation index data products and online services for CONUS based on NASA LANCE
Abstract

This paper describes a set of Near-Real-Time (NRT) Vegetation Index (VI) data products for the Conterminous United States (CONUS) based on Moderate Resolution Imaging Spectroradiometer (MODIS) data from Land, Atmosphere Near-real-time Capability for EOS (LANCE), an openly accessible NASA NRT Earth observation data repository. The data set offers a variety of commonly used VIs, including Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Mean-referenced Vegetation Condition Index (MVCI), Ratio to Median Vegetation Condition Index (RMVCI), and Ratio to previous-year Vegetation Condition Index (RVCI). LANCE enables the NRT monitoring of U.S. cropland vegetation conditions within 24 hours of observation. With more than 20 years of observations, this continuous data set enables geospatial time series analysis and change detection in many research fields such as agricultural monitoring, natural resource conservation, environmental modeling, and Earth system science. The complete set of VI data products described in the paper is openly distributed via Web Map Service (WMS) and Web Coverage Service (WCS) as well as the VegScape web application (https://nassgeodata.gmu.edu/VegScape/).

 
more » « less
Award ID(s):
1739705
NSF-PAR ID:
10381680
Author(s) / Creator(s):
; ; ; ; ; ; ;
Publisher / Repository:
Nature Publishing Group
Date Published:
Journal Name:
Scientific Data
Volume:
9
Issue:
1
ISSN:
2052-4463
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Understanding the past, present, and changing behavior of the climate requires close collaboration of a large number of researchers from many scientific domains. At present, the necessary interdisciplinary collaboration is greatly limited by the difficulties in discovering, sharing, and integrating climatic data due to the tremendously increasing data size. This paper discusses the methods and techniques for solving the inter-related problems encountered when transmitting, processing, and serving metadata for heterogeneous Earth System Observation and Modeling (ESOM) data. A cyberinfrastructure-based solution is proposed to enable effective cataloging and two-step search on big climatic datasets by leveraging state-of-the-art web service technologies and crawling the existing data centers. To validate its feasibility, the big dataset served by UCAR THREDDS Data Server (TDS), which provides Petabyte-level ESOM data and updates hundreds of terabytes of data every day, is used as the case study dataset. A complete workflow is designed to analyze the metadata structure in TDS and create an index for data parameters. A simplified registration model which defines constant information, delimits secondary information, and exploits spatial and temporal coherence in metadata is constructed. The model derives a sampling strategy for a high-performance concurrent web crawler bot which is used to mirror the essential metadata of the big data archive without overwhelming network and computing resources. The metadata model, crawler, and standard-compliant catalog service form an incremental search cyberinfrastructure, allowing scientists to search the big climatic datasets in near real-time. The proposed approach has been tested on UCAR TDS and the results prove that it achieves its design goal by at least boosting the crawling speed by 10 times and reducing the redundant metadata from 1.85 gigabytes to 2.2 megabytes, which is a significant breakthrough for making the current most non-searchable climate data servers searchable. 
    more » « less
  2. Abstract Background

    Exploring metagenomic contigs and “binning” them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure.

    Results

    We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time.

    In demonstration of BinaRena’s usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset.

    Conclusions

    BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted athttps://github.com/qiyunlab/binarena, together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data.

     
    more » « less
  3. Abstract

    Remote sensing imagery can provide critical information on the magnitude and extent of damage caused by forest pests and pathogens. However, monitoring short‐term changes in deciduous forest condition caused by defoliating insects is challenging and requires approaches that directly account for seasonal vegetation dynamics. We implemented a previously published harmonic modeling approach for forest condition monitoring in Google Earth Engine and systematically assessed the relative ability of condition change products generated using various model parameterizations for predicting pest abundances and defoliation during the 2016–2018 gypsy moth (Lymantria dispar) outbreak in southern New England. Our comparisons revealed that most models made reasonable predictions of changes in canopy condition and egg and larval abundances ofL. dispar, indicating a strong correlation between our harmonic‐based estimates of condition change and defoliator activity. The greatest differences in predictive ability were in the spectral domain, with assessments based on Tasseled Cap Greenness, Simple Ratio, and the Enhanced Vegetation Index ranking among the top models, and the commonly used Normalized Difference Vegetation Index consistently exhibiting poorer performance. We also observed notable differences in the magnitude of scores for different baseline periods. Additionally, we found that Landsat‐based condition scores better explained larval abundance than egg mass counts, which have historically been used as a proxy for later‐season larval abundance, indicating that our remote sensing approach may be more accurate and cost‐effective for generating consistent retrospective assessments ofL. disparpopulation abundance in addition to estimates of canopy damage. These findings provide important linkages between spectral changes detected using a harmonic modeling approach and biophysical aspects of defoliator activity, with potential to extend monitoring and prediction to regional or even continental scales.

     
    more » « less
  4. Abstract

    Seven three‐component ocean bottom seismometers (OBS) of the Ocean Observatories Initiative (OOI) Cabled Array on top of Axial Seamount are continuously streaming data in real time to the Incorporated Research Institutions for Seismology (IRIS). The OBS array records earthquakes from the submarine volcano which last erupted on 24 April 2015, about 4 months after the array came online. The OBS data have proven crucial in providing insight into the volcano structure and dynamics (Wilcock et al., 2016,https://doi.org/10.1126/science.aah5563). We implemented a real‐time double‐difference (RT‐DD) monitoring system that automatically computes high‐precision (tens of meters) locations of new earthquakes. The system's underlying double‐difference base catalog includes nearly 100,000 earthquakes and was computed using kurtosis phase onset picks, cross‐correlation phase delay times, and 3‐DPandSvelocity models to predict the data. The relocations reveal the fine‐scale structures of long‐lived, narrow (<200 m wide), outward dipping, convex faults on the east and west walls of the caldera that appear to form a figure 8‐shaped ring fault system. These faults accommodate stresses caused by the inflation of magma prior to and deflation during eruptions. The east fault is segmented and pulled apart in east‐west direction due to its interaction with the Juan de Fuca Ridge, which at this location forms an overlapping spreading center. The RT‐DD system enables the monitoring and rapid analysis of variations in fine‐scale seismic and fault properties and has the potential to improve prediction of timing and location of the next Axial eruption expected to occur in the 2022–2023 time frame.

     
    more » « less
  5. Abstract

    Using Magnetospheric Multiscale (MMS) observations and combined MHD/test particle simulations, we further explore characteristic ion velocity distributions in the plasma sheet boundary layer. The observations are characterized by earthward beams, which at a slightly later time are accompanied by weaker but faster tailward beams. Two events are presented showing different histories. The first event happens at entry from the lobe into the plasma sheet. Energy‐time dispersion indicates a source region about 25 tailward of the satellite. The second event follows the passage of a dipolarization front closer to Earth. In contrast to earlier MHD simulations, but in better qualitative agreement with the first observation, reconnection in the present simulation was initiated near. Simulated distributions right at the boundary are characterized by a single crescent‐shaped earthward beam, as discussed earlier (Birn, Hesse, et al., 2015,https://doi.org/10.1002/2015JA021573). Farther inside, or at a later time, the distributions now also show a simple reflected beam, evolving toward a more ring‐like distribution. The simulations provide insight into the acceleration sites: The innermost edges of the direct and reflected beams consist of ions accelerated in the vicinity of the reconnection site. This supports the validity of estimating the acceleration location based on a time‐of‐flight analysis (after Onsager et al., 1990,https://doi.org/10.1029/GL017i011p01837). However, this assumption becomes invalid at later times when the acceleration becomes dominated by the earthward propagating dipolarization electric field, such that earthward and tailward reflected beams are no longer accelerated at the same location and the same time.

     
    more » « less