Time series analysis of vegetation phenology and cloud cover conditions affecting airborne remote sensing operations and data products from the national ecological observatory network (NEON)

Publication Type: Conference Paper

Authors: J. Musinsky, M. Haynes, T. Goulden

Source: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), (2017)

Keywords: ecology, Airborne remote sensing, NEON, Phenology, remote sensing, hyperspectral imaging, vegetation, Vegetation mapping, geophysical image processing, vegetation structure, optical radar, remote sensing by laser beam, Meteorology, Clouds, data acquisition, image registration, time series, airborne remote sensing operations, high-resolution hyperspectral imagery, discrete waveform lidar, high-resolution digital photography, United States, remote sensing data, canopy biochemistry, vegetation states, AOP flight campaigns, cloud cover, satellite observations, national phenocam network, time series analysis, vegetation phenology, terrestrial sites, aquatic sites, NEON airborne subsystem, data products, NEON airborne observation platform, National Ecological Observatory Network, MODIS, VIIRS, Green products, hyperspectral


Abstract

The National Ecological Observatory Network (NEON) airborne observation platform (AOP) is collecting co-registered high-resolution hyperspectral imagery, discrete and waveform lidar, and high-resolution digital photography across 48 terrestrial and 32 aquatic sites throughout the United States on an annual basis over the next 30 years. These remote sensing data, made freely available to the public, enable researchers to characterize vegetation structure and canopy biochemistry at multiple scales and contribute to our understanding of ecosystem forcings and responses as represented by vegetation states and processes. In an effort to minimize inter-annual phenological variability among data sets collected over multiple years while reducing atmospheric impacts on spectral reflectance retrievals, AOP flight campaigns are scheduled so that data acquisition occurs during the period of mean peak greenness at each site and when cloud cover represents less than 10% of sky coverage. This paper describes how satellite observations from MODIS and VIIRS combined with phenophase observations from the national phenocam network are used to optimize data acquisition and ensure that high quality data products are produced by NEON`s airborne subsystem. Validation of the methods is also explored.

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