Integrating volunteered smartphone data with multispectral remote sensing to estimate forest fuels

References

• Agee, J. K., and C. N. Skinner. 2005. “Basic Principles of Forest Fuel Reduction Treatments.” Forest Ecology and Management 211 (12): 83–96. doi:10.1016/j.foreco.2005.01.034.
   Web of Science ®Google Scholar
• Arnett, J., N. C. Coops, S. E. Gergel, R. W. Falls, and R. Baker. 2014. “Detecting Stand Replacing Disturbance Using RapidEye Imagery : A Tasseled Cap Transformation and Modified Disturbance Index.” Canadian Journal of Remote Sensing 40 (1): 1–37. doi:10.1080/07038992.2014.899878.
   Web of Science ®Google Scholar
• Arroyo, L. A., C. Pascual, and J. Manzanera. 2008. “Fire Models and Methods to Map Fuel Types: The Role of Remote Sensing.” Forest Ecology and Management 256 (6): 1239–1252. doi:10.1016/j.foreco.2008.06.048.
   Web of Science ®Google Scholar
• Bakillah, M., S. Liang, A. Mobasheri, J. Jokar Arsanjani, and A. Zipf. 2014. “Fine-resolution Population Mapping Using OpenStreetMap Points-of-Interest.” International Journal of Geographical Information Science October (April): 1–22. doi:10.1080/13658816.2014.964247.
   Web of Science ®Google Scholar
• Barnes, E. M., T. R. Clarke, and S. E. Richards. 2000. “Coincident Detection of Crop Water Stress, Nitrogen Status and Canopy Density Using Ground-based Multispectral Data.” In Proceedings of the Fifth International Conference on Precision Agriculture, edited by P. C. Robert, R. H. Rust, and W. E. Larson, 16–19. Bloomington, MN: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America. http://ddr.nal.usda.gov/bitstream/10113/4190/1/IND43939070.pdf.
   Google Scholar
• Bonney, R., H. Ballard, R. Jordan, and E. McCallie. 2009. “Public Participation in Scientific Research: Defining the Field and Assessing Its Potential for Informal Science Education. A CAISE Inquiry Group Report.” Online Submission, July. http://eric.ed.gov/?id=ED519688.
   Google Scholar
• CDED (Canadian Digital Elevation Data). 2014. Geobase.ca. http://www.geobase.ca/geobase/en/data/cded/description.html.
   Google Scholar
• Chavez, P. S. 1996. “Image-based Atmospheric Corrections-revisited and Improved.” Photogrammetric Engineering and Remote Sensing 62 (9): 1025–1035. http://www.unc.edu/courses/2008spring/geog/577/001/www/Chavez96-PERS.pdf.
   Web of Science ®Google Scholar
• Chirici, G. 2012. “K-NN FOREST: A Software for the Non-parametric Prediction and Mapping of Environmental Variables by the K-nearest Neighbors Algorithm.” European Journal of Remote Sensing November: 433–442. doi:10.5721/EuJRS20124536.
   Web of Science ®Google Scholar
• Cohen, J. 2000. “Preventing Disaster: Home Ignitability in the Wildland-urban Interface.” Journal of Forestry 98 (3): 15–21. http://www.ingentaconnect.com/content/saf/jof/2000/00000098/00000003/art00008.
   Web of Science ®Google Scholar
• Craglia, M., K. de Bie, D. Jackson, M. Pesaresi, G. Remetey-Fülöpp, C. Wang, A. Annoni et al. 2012. “Digital Earth 2020: Towards the Vision for the Next Decade.” International Journal of Digital Earth 5 (1): 4–21. doi:10.1080/17538947.2011.638500.
   Web of Science ®Google Scholar
• Crookston, N. L., and A. O. Finley. 2008. “yaImpute: An R Package for kNN Imputation.” Journal of Statistical Software 23 (10). http://ddr.nal.usda.gov/handle/10113/16688.
   Google Scholar
• Dickinson, J. L., and R. L. Crain. 2014. “Socially Networked Citizen Science and the Crowd-sourcing of Pro-environmental Collective Actions.” In Online Collective Action, edited by N. Agarwal, M. Lim, and R. T. Wigand, 133–152. Lecture Notes in Social Networks. Vienna: Springer.
   Google Scholar
• Ehlers, M., P. Woodgate, A. Annoni, and S. Schade. 2014. “Advancing Digital Earth: Beyond the Next Generation.” International Journal of Digital Earth 7 (1): 3–16. doi:10.1080/17538947.2013.814449.
   Web of Science ®Google Scholar
• Eitel, J. U. H., L. A. Vierling, M. E. Litvak, D. S. Long, U. Schulthess, A. A. Ager, D. J. Krofcheck, and L. Stoscheck. 2011. “Broadband, Red-Edge Information from Satellites Improves Early Stress Detection in a New Mexico Conifer Woodland.” Remote Sensing of Environment 115 (12): 3640–3646. doi:10.1016/j.rse.2011.09.002.
   Web of Science ®Google Scholar
• Erickson, T., W. A. Kellogg, and I. B. M. T. J. Watson. 2000. “Social Translucence : An Approach to Designing Systems That Support Social Processes.” ACM Transactions on Computer-Human Interaction 7 (1): 59–83.
   Google Scholar
• Ersts, P. J., N. Horning, and K. Koy. 2013. Event Visualization Tool (eVis). New York: Center for Biodiversity and Conservation's Biodiversity Informtics Facility at the American Museum of Natural History; QGIS Project.
   Google Scholar
• Falkowski, M. J., P. E. Gessler, P. Morgan, A. T. Hudak, and A. M. S. Smith. 2005. “Characterizing and Mapping Forest Fire Fuels Using ASTER Imagery and Gradient Modeling.” Forest Ecology and Management 217: 129–146. doi:10.1016/j.foreco.2005.06.013.
   Web of Science ®Google Scholar
• Ferster, C. J., and N. C. Coops. 2013. “A Review of Earth Observation Using Mobile Personal Communication Devices.” Computers & Geosciences 51 (February): 339–349. doi:10.1016/j.cageo.2012.09.009.
   Web of Science ®Google Scholar
• Ferster, C. J., and N. C. Coops. 2014. “Assessing the Quality of Forest Fuel Loading Data Collected Using Public Participation Methods and Smartphones.” International Journal of Wildland Fire 23 (4): 585–590. doi:10.1071/WF13173.
   Web of Science ®Google Scholar
• Ferster, C. J., N. C. Coops, H. W. Harshaw, R. A. Kozak, and M. J. Meitner. 2013. “An Exploratory Assessment of a Smartphone Application for Public Participation in Forest Fuels Measurement in the Wildland-urban Interface.” Forests 4 (4): 1199–1219. doi:10.3390/f4041199.
   Web of Science ®Google Scholar
• Gitelson, A. A., M. N. Merzlyak, and H. K. Lichtenthaler. 1996. “Detection of Red Edge Position and Chlorophyll Content by Reflectance Measurements Near 700 Nm.” Journal of Plant Physiology 148 (3–4): 501–508. doi:10.1016/S0176-1617(96)80285-9.
   Web of Science ®Google Scholar
• Goodchild, M. F. 2007. “Citizens as Sensors: The World of Volunteered Geography.” GeoJournal 69 (4): 211–221. doi:10.1007/s10708-007-9111-y.
   Google Scholar
• Gore, A. 1998. “The Digital Earth.” Australian Surveyor 43 (2): 89–91. doi:10.1080/00050326.1998.10441850.
   Google Scholar
• Gumley, L., R. Holz, D. Parker, B. Flynn, and B. Bellon. 2010. “SatCam: An iPhone Application for Community Participation in Satellite Cloud Product Validation.” In International Geoscience and Remote Sensing Symposium (IGARSS). Honolulu, HI. http://www.igarss2010.org/Papers/ViewPapers_MS.asp?PaperNum=3926.
   Google Scholar
• Hardy, C. 2005. “Wildland Fire Hazard and Risk: Problems, Definitions, and Context.” Forest Ecology and Management 211 (1–2): 73–82. doi:10.1016/j.foreco.2005.01.029.
   Web of Science ®Google Scholar
• Harris, L. M., T. K. McGee, and B. L. McFarlane. 2011. “Implementation of Wildfire Risk Management by Local Governments in Alberta, Canada.” Journal of Environmental Planning and Management 54 (4): 457–475. doi:10.1080/09640568.2010.515881.
   Web of Science ®Google Scholar
• Hengl, T. 2006. “Finding the Right Pixel Size.” Computers & Geosciences 32 (9): 1283–1298. doi:10.1016/j.cageo.2005.11.008.
   Web of Science ®Google Scholar
• Hermosilla, T., L. A. Ruiz, A. N. Kazakova, N. C. Coops, and L. Monika Moskal. 2014. “Estimation of Forest Structure and Canopy Fuel Parameters from Small-footprint Full-waveform LiDAR Data.” International Journal of Wildland Fire 23 (2): 224. doi:10.1071/WF13086.
   Web of Science ®Google Scholar
• Hope, G. D., D. A. Lloyd, W. R. Mitchell, W. R. Erickson, W. L. Harper, and B. M. Wikeem. 1991. “Ponderosa Pine Zone.” In Ecosystems of British Columbia, edited by D. V. Meidinger and J. Pojar, BC Special, 139–151. Victoria: Research Branch, BC Ministry of Forests.
   Google Scholar
• Hudak, A., N. Crookston, J. Evans, D. Hall, and M. Falkowski. 2008. “Nearest Neighbor Imputation of Species-level, Plot-Scale Forest Structure Attributes from LiDAR Data.” Remote Sensing of Environment 112 (5): 2232–2245. doi:10.1016/j.rse.2007.10.009.
   Web of Science ®Google Scholar
• Iacovides, I., C. Jennett, C. Cornish-Trestrail, and A. L. Cox. 2013. “Do Games Attract or Sustain Engagement in Citizen Science?” In CHI ’13 Extended Abstracts on Human Factors in Computing Systems on – CHI EA'13, edited by W. E. Mackay, S. A. Brewster, and S. Bødker, 1101. New York: ACM Press.
   Google Scholar
• Jokar Arsanjani, J., M. Helbich, M. Bakillah, J. Hagenauer, and A. Zipf. 2013. “Toward Mapping Land-use Patterns from Volunteered Geographic Information.” International Journal of Geographical Information Science 27 (12): 2264–2278. doi:10.1080/13658816.2013.800871.
   Web of Science ®Google Scholar
• Keane, R. E., R. Burgan, and J. W. Van Wagtendonk. 2001. “Mapping Wildland Fuels for Fire Management Across Multiple Scales: Integrating Remote Sensing, GIS, and Biophysical Modeling.” International Journal of Wildland Fire 10 (4): 301–319. doi:10.1071/WF01028.
   Web of Science ®Google Scholar
• Lillesand, T. M. 2002. “Combining Satellite Remote Sensing and Volunteer Secchi Disk Measurement for Lake Transparency Monitoring.” In Proceedings: National Monitoring Conference, National Water Quality Monitoring Council, 1–11. Madison, WI: University of Wisconsin. http://acwi.gov/monitoring/conference/2002/Papers-AlphabeticalbyFirstName/ThomasLillesand-Satellite.pdf.
   Google Scholar
• Mahalanobis, P. C. 1936. “On the Generalized Distance in Statistics.” Proceedings of the National Institute of Sciences 12: 49–55.
   Google Scholar
• Maxwell, W. G., and F. R. Ward. 1976. Photo Series for Quantifying Forest Residues in the Coastal Douglas-Fir--Hemlock Type, Coastal Douglas-Fir--Hardwood Type. Portland, OR. http://library.wur.nl/WebQuery/clc/330741.
   Google Scholar
• Morrow, B., K. Johnston, and J. Davies. 2008. Rating Interface Wildfire Threats in British Columbia. Fuel. Victoria, BC: Ministry of Forests and Range Protection Branch.
   Google Scholar
• Mullin, M. D., and R. Sukthankar. 2000. “Complete Cross-validation for Nearest Neighbor Classifiers.” In International Conference on Machine Learning (ICML), 639–646. San Francisco, CA: Morgan Kaufmann. http://www.cs.cmu.edu/~rahuls/pub/icml2000-rahuls.pdf.
   Google Scholar
• Open Data Catalogue. 2014. City of Kelowna. http://www.kelowna.ca/CM/Page3936.aspx.
   Google Scholar
• Packalen, P., H. Temesgen, and M. Maltamo. 2012. “Variable Selection Strategies for Nearest Neighbor Imputation Methods Used in Remote Sensing Based Forest Inventory.” Journal of Remote Sensing 38 (5): 557–569. http://pubs.casi.ca/doi/abs/10.5589/m12-046.
   Web of Science ®Google Scholar
• Peterson, S. H., and J. Franklin. 2012. “Mapping Fuels in Yosemite National Park.” Canadian Journal of Forest Research 17 ( November 2012): 7–17. http://www.nrcresearchpress.com/doi/full/10.1139/cjfr-2012-0213.
   Google Scholar
• Pratihast, A., B. DeVries, V. Avitabile, S. de Bruin, L. Kooistra, M. Tekle, and M. Herold. 2014. “Combining Satellite Data and Community-based Observations for Forest Monitoring.” Forests 5 (10): 2464–2489. doi:10.3390/f5102464.
   Web of Science ®Google Scholar
• Pratihast, A. K., M. Herold, V. Avitabile, S. de Bruin, H. Bartholomeus, C. M. Souza, and L. Ribbe. 2013. “Mobile Devices for Community-based REDD+ Monitoring: A Case Study for Central Vietnam.” Sensors (Basel, Switzerland) 13 (1): 21–38. doi:10.3390/s130100021.
   Web of Science ®Google Scholar
• Raddick, M. J., G. Bracey, P. L. Gay, C. J. Lintott, P. Murray, K. Schawinski, A. S. Szalay, and J. Vandenberg. 2010. “Galaxy Zoo: Exploring the Motivations of Citizen Science Volunteers.” Astronomy Education Review 9 (1): 010103. doi:10.3847/AER2009036.
   Google Scholar
• Radeloff, V. C., R. B. Hammer, S. I. Stewart, J. S. Fried, S. S. Holcomb, and J. F. McKeefry. 2005. “The Wildland–urban Interface in the United States.” Ecological Applications 15 (3): 799–805. doi:10.1890/04-1413.
   Web of Science ®Google Scholar
• R Development Core Team. 2011. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. http://www.r-project.org/.
   Google Scholar
• Riaño, D., and E. Chuvieco. 2002. “Generation of Fuel Type Maps from Landsat TM Images and Ancillary Data in Mediterranean Ecosystems.” Canadian Journal of Forest Research 1315: 1301–1315. doi:10.1139/X02-052.
   Web of Science ®Google Scholar
• Sauer, J. R., J. E. Hines, and J. Fallon. 2008. The North American Breeding Bird Survey, Results and Analysis 1966-2007. Version. Laurel, MD. http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:The+North+American+breeding+bird+survey,+results+and+analysis+1966-2007#0.
   Google Scholar
• Sauer, J. R., W. A. Link, J. D. Nichols, and J. A. Royle. 2005. “Using the North American Breeding Bird Survey as a Tool for Conservation: A Critique of Bart et al. (2004).” Journal of Wildlife Management 69 (4): 1321–1326. doi:10.2193/0022-541X(2005)69[1321:UTNABB]2.0.CO;2.
   Web of Science ®Google Scholar
• Schuster, C., M. Förster, and B. Kleinschmit. 2012. “Testing the Red Edge Channel for Improving Land-use Classifications Based on High-resolution Multi-spectral Satellite Data.” International Journal of Remote Sensing 33 (17): 5583–5599. doi:10.1080/01431161.2012.666812.
   Web of Science ®Google Scholar
• See, L., A. Comber, C. Salk, S. Fritz, M. van der Velde, C. Perger, C. Schill, I. McCallum, F. Kraxner, and M. Obersteiner. 2013. “Comparing the Quality of Crowdsourced Data Contributed by Expert and Non-experts.” Edited by T. Preis. PLoS One 8 (7): e69958. doi:10.1371/journal.pone.0069958.
   PubMed Web of Science ®Google Scholar
• Sherry, A., and R. K. Henson. 2005. “Conducting and Interpreting Canonical Correlation Analysis in Personality Research: A User-friendly Primer.” Journal of Personality Assessment 84 (1): 37–48. doi:10.1207/s15327752jpa8401_09.
   PubMed Web of Science ®Google Scholar
• Shindler, B. A., E. Toman, and S. M. McCaffrey. 2009. “Public Perspectives of Fire, Fuels and the Forest Service in the Great Lakes Region: A Survey of Citizen–agency Communication and Trust.” International Journal of Wildland Fire 18 (2): 157. doi:10.1071/WF07135.
   Web of Science ®Google Scholar
• Shirk, J. L., H. L. Ballard, C. C. Wilderman, T. Phillips, A. Wiggins, R. Jordan. 2012. “Public Participation in Scientific Research: A Framework for Deliberate Design.” Ecology and Society 17 (2): 29–48. doi:10.5751/ES-04705-170229.
   Web of Science ®Google Scholar
• Sikkink, P. G., and R. E. Keane. 2008. “A Comparison of Five Sampling Techniques to Estimate Surface Fuel Loading in Montane Forests.” International Journal of Wildland Fire 17 (3): 363. doi:10.1071/WF07003.
   Web of Science ®Google Scholar
• Stage, A. R., and N. L. Crookston. 2007. “Partitioning Error Components for Accuracy-assessment of Near-neighbor Methods of Imputation.” Forest Science 53 (1): 62–72. http://www.ingentaconnect.com/content/saf/fs/2007/00000053/00000001/art00007.
   Web of Science ®Google Scholar
• Sullivan, B. L., J. L. Aycrigg, J. H. Barry, R. E. Bonney, N. Bruns, C. B. Cooper, T. Damoulas et al. 2014. “The eBird Enterprise: An Integrated Approach to Development and Application of Citizen Science.” Biological Conservation 169 (January): 31–40. doi:10.1016/j.biocon.2013.11.003.
   Web of Science ®Google Scholar
• Taylor, S. W., R. G. Pike, and M. E. Alexander. 1997. Field Guide to the Canadian Forest Fire Behavior Prediction (FBP) System. 1st ed. Victoria, BC: Natural Resources Canada, Canadian Forest Service, Pacific Forestry Centre. FRDA Handbook 012. http://www.cfs.nrcan.gc.ca/publications?id=25139.
   Google Scholar
• Toman, E., B. Shindler, and M. Brunson. 2006. “Fire and Fuel Management Communication Strategies: Citizen Evaluations of Agency Outreach Activities.” Society & Natural Resources 19 (4): 321–336. doi:10.1080/08941920500519206.
   Web of Science ®Google Scholar
• Tucker, C. J. 1979. “Red and Photographic Infrared Linear Combinations for Monitoring Vegetation.” Remote Sensing of Environment 8: 127–150. http://linkinghub.elsevier.com/retrieve/pii/0034425779900130.
   Web of Science ®Google Scholar
• Ver Hoef, J. M., and H. Temesgen. 2013. “A Comparison of the Spatial Linear Model to Nearest Neighbor (k-NN) Methods for Forestry Applications.” PLoS One 8 (3): e59129. doi:10.1371/journal.pone.0059129.
   Google Scholar
• Zandbergen, P. A. 2009. “Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning.” Transactions in GIS 13 (June): 5–25. doi:10.1111/j.1467-9671.2009.01152.x.
   Web of Science ®Google Scholar
• Zandbergen, P. A., and S. J. Barbeau. 2011. “Positional Accuracy of Assisted GPS Data from High-sensitivity GPS-enabled Mobile Phones.” Journal of Navigation 64 (3): 381–399. doi:10.1017/S0373463311000051.
   Web of Science ®Google Scholar