[ES_JOBS_NET] Staff Scientist Airborne Remote Sensing Data Products, NEON

Christine Wiedinmyer christin at ucar.edu
Fri Sep 12 07:13:32 MDT 2014


The National Ecological Observatory Network (NEON) is a $430 million 
dollar observatory project dedicated to understanding how changes in 
climate, land use and invasive species impact ecology. For the next 
three decades NEON will collect a comprehensive range of ecological data 
on a continental scale across 20 eco-climatic domains representing US 
ecosystems. NEON will use cutting edge technology including an airborne 
observation platform that will capture images of regional landscapes and 
vegetation; mobile, re-locatable, and fixed data collection sites with 
automated ground sensors to monitor soil and atmosphere; and trained 
field crews who will observe and sample populations of diverse organisms 
and collect soil and water data. A leading edge cyber-infrastructure 
will calibrate, store and publish this information. The Observatory will 
grow to 300+ personnel and will be the first of its kind designed to 
detect and enable forecasting of ecological change at continental scales.

The AOP Algorithm Scientist will be a member of the AOP science team 
contributing to the development and generation of data products 
developed from data acquired from the AOP remote sensing platform and 
released by NEON to the community. This collaborative effort requires a 
broadly-trained scientist well-versed in and eager to learn the breadth 
of NEON scientific efforts, since AOP works with the NEON's science, 
cyberinfrastructure, and education teams, as well as the external 
community, to define and create the data products and manage their 
lifecycle. The AOP Algorithm Scientist will develop sensor data 
processing algorithms, software, and validation approaches to produce 
high quality science data products from the airborne imaging 
spectrometer, waveform-LiDAR, and high-resolution digital camera data, 
as well as support initial processing of data. The Staff Scientist is 
also directly involved in airborne operations and will serve as liaison 
with NEON's Cyber Infrastructure product team and will be an active 
member of the Remote Sensing Integrated Product Team co-led by the Data 
Products group.

*_Essential Duties and Responsibilities:_*
. Design, develop, and implement scientific algorithms and documentation 
(Algorithm Theoretical Baseline Documents) for application of airborne 
imaging spectroscopy, discrete and waveform LiDAR, and high-resolution 
digital camera imagery to terrestrial ecology.
. Work with the Cyber Infrastructure product team within NEON to 
implement AOP processing algorithms into the production segment.
. Automate and/or improve processing software and algorithms.
. Contribute to developing the science rationale for data products, 
developing and prototyping algorithms for their generation, and engaging 
all stakeholders in vetting the produced materials. The incumbent will 
help to define NEON's strategy to scale ecological data across multiple 
temporal and spatial scales in support of continental-scale ecological 
. Run existing software and algorithms to generate Level 1 airborne 
remote sensing data products.
. Perform quality control on data products to ensure their use by the 
science community.
. Develop uncertainty estimates and quality flags for remote sensing 
data products.
. Engage the user community through meetings, workshops, and working 
groups, to ensure the utility and veracity of NEON data products.
. Follow NEON and site specific, safety and environmental protection 
requirements, policy and procedures.

*_Required Education, Experience, Knowledge, Skills:_*
. Ph.D. in physical sciences, computational sciences, remote sensing, 
applied mathematics or related science field, or an MS in one of these 
areas and equivalent experience.
. Postdoctoral experience is preferred, but not required.
. Application of remote sensing theory to biological and/or physical 
. Knowledge of remote sensing programming languages and visualization 
tools, including at least one of the following: IDL, MatLab, Python, 
NCL, ENVI, or R.
. Experience building novel algorithms in support of LiDAR and/or 
hyperspectral data processing.
. Experience with atmospheric correction of imaging spectrometer data 
using ATCOR or similar processing programs.
. Experience integrating remote sensing data with a variety of 
ground-based data, including measurements of biophysical/biochemical 
. Effective oral and written communication skills.
. Demonstrated ability to write technical and scientific documents.

*_Preferred Education, Experience, Knowledge, Skills:_*
. Familiarity with a variety of remote sensing platforms, e.g. AVIRIS, 
. Familiarity with data processing workflows in a production environment.
. Programming experience (C/C++, Java, Python, etc.).
. Demonstrated skill in developing scientific algorithm design and 
development for processing of large remote sensing datasets.
. Knowledge of data analysis and statistical methods for processing 
remote sensing data.
. Knowledge of imaging spectrometers, LiDAR, high resolution imagery and 
the application of these remote sensing technologies to terrestrial ecology.
. Knowledge of optical pointing models and application of standard 
geolocation techniques including the use of geodetic datums.
. Experience working in a collaborative scientific or engineering 
. Ability to work independently and as part of an active science team.

Must have permanent authorization for US employment.

- See more at: 
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