@conference { w:whitsitt-neat-2011,
	title = {Constrained data acquisition for mobile citizen science applications},
	booktitle = {Proceedings of the compilation of the co-located workshops on DSM{\textquoteright}11, TMC{\textquoteright}11, AGERE!{\textquoteright}11, AOOPES{\textquoteright}11, NEAT{\textquoteright}11, \& VMIL{\textquoteright}11},
	series = {SPLASH {\textquoteright}11 Workshops},
	year = {2011},
	pages = {267{\textendash}272},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {<p>The popularity and ubiquity of personal mobile computing devices{\textendash}-coupled with their powerful sensing capabilities{\textendash}-allow their application in the structured collection of data for societal benefit and science applications. Citizen scientists are willing users and active contributors to scientific research and applications, but if they gather data in an unconstrained or ad hoc manner, their efforts may be of little scientific value. In this paper, we present a user interface for a mobile device which is properly constrained to permit the gathering of valid scientific data. This helps to achieve the goal that any individual with a basic familiarity of the device (but not of the science) should be able to obtain useful data with little learning required. As a use case for this concept, we present a mobile application that allows users to collect location-stamped images to supplement satellite data for climate change research.</p>},
	keywords = {citizen scientist, domain-specific modeling, iphone, mobile phone programming},
	isbn = {978-1-4503-1183-0},
	doi = {10.1145/2095050.2095095},
	url = {http://dx.doi.org/10.1145/2095050.2095095},
	author = {Sean Whitsitt and Armando Barreto and Maribel Hudson and Hussain Al-Helal and Diyang Chu and Kamel Didan and Jonathan Sprinkle}
}
@conference {c:whitsitt-prose-2010,
	title = {Citizen Science in Support of Vegetation Index and Phenology Research},
	booktitle = {Phenology Research and Observations of Southwest Ecosystems Symposium (PROSE)},
	year = {2010},
	month = {October},
	abstract = {<p>Vegetation indices (VIs) are simple transformations of images into proxy measures of greenness and vegetation health and change over time. They are also used to derive information about the land surface phenology status, providing extensive spatial coverage and direct support for global ecosystem models. These measurements however contain large uncertainties and errors. A new suite of mobile devices, equipped with geo-location, image capture, and transmission capabilities could aid with vegetation phenology observations and documentation. The iPhone, with its wide distribution and array of sensors, can contribute significantly to the field of citizen science. In this project we are developing an end-to-end system for the collection, processing, and visualization of land surface vegetation phenology. The system consists of a client-server application and a Google Earth based visualization model. The client side (an iPhone app) intuitively guides the observer to capture up to three images per location: a close-up image of leaves, flowers, or fruits, an individual plant image, and a panoramic landscape image. The iPhone automatically embeds location, orientation, date/time, and other metadata with the images and allows the observer to add text comments. The images are then transmitted to the server, where they are validated, post-processed, archived, and made available to the interactive visualization system. The images are separated into primary colors and processed into a greenness index comparable to the classical VI. These measurements are then plotted against satellite based VI time series to aid in their validation and the characterization of the location phenology. With this effort we hope to recruit global observers into contributing to the field of land surface vegetation change detection and characterization.</p>},
	author = {Sean Whitsitt and Armando Barreto and Sundaresh Ram and Hussain Al-Helal and Maribel Hudson and Diyang Chu and Jonathan Sprinkle and Kamel Didan}
}
