Title: Spectral data discovery, access and analysis through EcoSIS toolkits
Presenting Author: Philip Townsend
Organization: University of Wisconsin
Co-Author(s): Clayton C. Kingdon, Justin Merz and Philip A. Townsend

Abstract:
Over the last decade, the application of hyperspectral data to estimate foliar traits in vegetation has exploded in use, including applications in agriculture and phenotyping, ecosystem functioning and biodiversity. There is an urgent need for a common set of software tools and open-source repository for those tools and spectral models derived from spectral data. Our effort focuses on developing the software, database/accessibility tools and web front- and back-ends needed to ensure open-source usage of spectral data among a large user community, including: data repositories, data processing tools, and spectral model distribution. Building on our previous EcoSIS.org effort, aim to greatly expand the functionality of open-source tools for spectral data analysis, thus reducing barriers to entry for new researchers wanting to make use of field and/or imaging spectroscopy. Our primary target audiences are users wishing to scale from ground measurements to imagery or simply to use existing published algorithms to predict foliar traits from new ground reflectance or imaging spectroscopy data. 

EcoSIS.org is an easy-to-use online database that we developed with NASA support for storing, documenting, and distributing vegetation-themed spectroscopic datasets. The EcoSIS data portal makes contribution of rigorously-attributed datasets intuitive and uncomplicated. Ancillary data, such as chemical and physiological traits, as well as spectroscopy metadata, are easily added to make datasets discoverable across the internet, facilitate synergistic studies, and provide data to inform remote sensing research. Datasets published via EcoSIS are eligible to receive a DOI, providing persistent access by the user community as required by peer-reviewed journals and funding agencies. Our current project will expand participation in EcoSIS by creating a suite of complementary open-source tools — the EcoSIS Toolkit — that make processing and preparation of spectral data straightforward, further removing the potential barriers to entry for those whose research would greatly benefit from the inclusion spectroscopy datasets and models.

Throughout the development process for all tools we are employing Agile practices to iteratively add and test new features. All software developed through this project use only open-source technologies and are licensed under the Apache Licence 2.0 (http://www.apache.org/licenses/LICENSE-2.0). We are developing: 1) the Ecological Spectral Model Library — EcoSML.org — an online repository that distributes model parameters, example code, and other supporting resources related to spectra-derived models used to predict sample traits from spectra; 2) EcoSIS SDK library packages for popular scientific open-source languages to interface with EcoSIS; 3) the Spectroscopy Data Abstraction Library (SpecDAL, https://specdal.github.io/), an open-source Python library. Inspired by GDAL (http://www.gdal.org/), SpecDAL provides functions and classes to work with data files from industry-standard portable field spectrometers as well as custom built instruments; 4) HyTools, a toolbox of open-source Python programs used to perform necessary processing of hyperspectral images, providing a source to new users for code that has either been part of closed-source software packages or developed by individual researchers on an ad hoc basis.  No comparable resources for these proposed functions are widely available, although there are some disparate sources on the web providing these functions.