{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T22:51:42Z","timestamp":1773096702288,"version":"3.50.1"},"reference-count":42,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2019,2,1]],"date-time":"2019-02-01T00:00:00Z","timestamp":1548979200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science, Systems, and Applications, Inc. in support of NASA\u2019s DEVELOP National Program","award":["Contract NNL16AA05C and cooperative agreement NNX14AB60A"],"award-info":[{"award-number":["Contract NNL16AA05C and cooperative agreement NNX14AB60A"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Spruce beetle-induced (Dendroctonus rufipennis (Kirby)) mortality on the Kenai Peninsula has been hypothesized by local ecologists to result in the conversion of forest to grassland and subsequent increased fire danger. This hypothesis stands in contrast to empirical studies in the continental US which suggested that beetle mortality has only a negligible effect on fire danger. In response, we conducted a study using Landsat data and modeling techniques to map land cover change in the Kenai Peninsula and to integrate change maps with other geospatial data to predictively map fire danger for the same region. We collected Landsat imagery to map land cover change at roughly five-year intervals following a severe, mid-1990s beetle infestation to the present. Land cover classification was performed at each time step and used to quantify grassland encroachment patterns over time. The maps of land cover change along with digital elevation models (DEMs), temperature, and historical fire data were used to map and assess wildfire danger across the study area. Results indicate the highest wildfire danger tended to occur in herbaceous and black spruce land cover types, suggesting that the relationship between spruce beetle damage and wildfire danger in costal Alaskan forested ecosystems differs from the relationship between the two in the forests of the coterminous United States. These change detection analyses and fire danger predictions provide the Kenai National Wildlife Refuge (KENWR) ecologists and other forest managers a better understanding of the extent and magnitude of grassland conversion and subsequent change in fire danger following the 1990s spruce beetle outbreak.<\/jats:p>","DOI":"10.3390\/rs11030283","type":"journal-article","created":{"date-parts":[[2019,2,1]],"date-time":"2019-02-01T03:08:05Z","timestamp":1548990485000},"page":"283","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Satellite-Based Assessment of Grassland Conversion and Related Fire Disturbance in the Kenai Peninsula, Alaska"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9887-8003","authenticated-orcid":false,"given":"Katherine A.","family":"Hess","sequence":"first","affiliation":[{"name":"NASA DEVELOP National Program, NASA Langley Research Center MS 307, Hampton, VA 23681, USA"},{"name":"Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]},{"given":"Cheila","family":"Cullen","sequence":"additional","affiliation":[{"name":"NASA DEVELOP National Program, NASA Langley Research Center MS 307, Hampton, VA 23681, USA"},{"name":"NOAA-Crest Center, The City University of New York, Bronx, NY 10453, USA"}]},{"given":"Jeanette","family":"Cobian-I\u00f1iguez","sequence":"additional","affiliation":[{"name":"NASA DEVELOP National Program, NASA Langley Research Center MS 307, Hampton, VA 23681, USA"},{"name":"Department of Mechanical Engineering, University of California, Riverside, CA 92521, USA"}]},{"given":"Jacob S.","family":"Ramthun","sequence":"additional","affiliation":[{"name":"NASA DEVELOP National Program, NASA Langley Research Center MS 307, Hampton, VA 23681, USA"},{"name":"Department of Geography, University of South Carolina, Columbia, SC 29208, USA"}]},{"given":"Victor","family":"Lenske","sequence":"additional","affiliation":[{"name":"NASA DEVELOP National Program, NASA Langley Research Center MS 307, Hampton, VA 23681, USA"},{"name":"Science Systems and Applications, Inc., 10210 Greenbelt Rd, Lanham, MD 20706, USA"}]},{"given":"Dawn R.","family":"Magness","sequence":"additional","affiliation":[{"name":"Kenai National Wildlife Refuge, U.S. Fish and Wildlife Service, Soldotna, AK 99669, USA"}]},{"given":"John D.","family":"Bolten","sequence":"additional","affiliation":[{"name":"Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Mail Code 617.0, Greenbelt, MD 20771, USA"}]},{"given":"Adrianna C.","family":"Foster","sequence":"additional","affiliation":[{"name":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, 1295 Knoles Dr., Flagstaff, AZ 86011, USA"}]},{"given":"Joseph","family":"Spruce","sequence":"additional","affiliation":[{"name":"Science Systems and Applications, Inc., 10210 Greenbelt Rd, Lanham, MD 20706, USA"},{"name":"Science Systems and Applications, Inc., Consultant, 88384 Diamondhead Drive East, Diamondhead, MS 39525, USA"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,1]]},"reference":[{"key":"ref_1","unstructured":"United States Forest Service (2018, June 27). Available online: https:\/\/www.adn.com\/opinions\/2017\/08\/30\/spruce-beetle-devastation-returns-to-southcentral-alaska-and-moves-north\/."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.foreco.2006.02.051","article-title":"Vegetation change and forest regeneration on the Kenai Peninsula, Alaska following a spruce beetle outbreak, 1987-2000","volume":"227","author":"Boucher","year":"2006","journal-title":"For. Ecol. Manag."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Viereck, L.A., Dyrness, C.T., Batten, A.R., and Wenzlick, K.J. (1992). The Alaska Vegetation Classification, United States Department of Agriculture. Technical Report.","DOI":"10.2737\/PNW-GTR-286"},{"key":"ref_4","unstructured":"United States Forest Service (USFS) (2018, December 20). Spruce Beetle, Available online: https:\/\/www.fs.usda.gov\/Internet\/FSE_DOCUMENTS\/stelprdb5303039.pdf."},{"key":"ref_5","unstructured":"Alaska Division of Forestry (2018, December 20). What\u2019s Bugging Alaska\u2019s Forests? Spruce Beetle Facts and Figures, Available online: http:\/\/forestry.alaska.gov\/insects\/sprucebeetle."},{"key":"ref_6","unstructured":"Colorado State Forest Service (2018, December 20). Available online: https:\/\/csfs.colostate.edu\/media\/sites\/22\/2014\/02\/Spruce-Beetle-QuickGuide-FM2014-1.pdf."},{"key":"ref_7","first-page":"23","article-title":"Modelling spruce bark beetle infestation probability","volume":"15","author":"Zolubas","year":"2009","journal-title":"Balt. For."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.foreco.2012.02.036","article-title":"Fuels and fire behavior dynamics in bark beetle-attacked forests in Western North America and implications for fire management","volume":"275","author":"Jenkins","year":"2012","journal-title":"For. Ecol. Manag."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.foreco.2006.02.050","article-title":"Spruce beetles and forest ecosystems in south-central Alaska: A review of 30 years of research","volume":"227","author":"Werner","year":"2006","journal-title":"For. Ecol. Manag."},{"key":"ref_10","unstructured":"Rothermel, R.C. (1994, January 26\u201328). Some fire behavior modeling concepts for fire management systems. Proceedings of the 12th Conference on Fire and Forest Meterology, Jekyll Island, GA, USA."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1931","DOI":"10.1139\/x05-129","article-title":"Wetland drying and succession across the Kenai Peninsula Lowlands, south-central Alaska","volume":"35","author":"Klein","year":"2005","journal-title":"Can. J. For. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.foreco.2006.02.038","article-title":"Spruce beetle outbreaks on the Kenai Peninsula, Alaska, and Kluane National Park and Reserve, Yukon Territory: Relationship to summer temperatures and regional differences in disturbance regimes","volume":"227","author":"Berg","year":"2006","journal-title":"For. Ecol. Manag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1525\/bio.2010.60.8.6","article-title":"Climate change and bark beetles of the western United States and Canada: Direct and indirect effects","volume":"60","author":"Bentz","year":"2010","journal-title":"BioScience"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"21","DOI":"10.3390\/f5010021","article-title":"Spruce beetle biology, ecology and management in the Rocky Mountains: An addendum to spruce beetle in the Rockies","volume":"5","author":"Jenkins","year":"2014","journal-title":"Forests"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.foreco.2012.02.005","article-title":"Effects of bark beetle-caused tree mortality on wildfire","volume":"271","author":"Hicke","year":"2012","journal-title":"For. Ecol. Manag."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1890\/15-1121","article-title":"Fire severity unaffected by spruce beetle outbreak in spruce-fir forests in southwestern Colorado","volume":"26","author":"Andrus","year":"2016","journal-title":"Ecol. Appl."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.foreco.2006.02.042","article-title":"Fire history of white and Lutz spruce forests on the Kenai Peninsula, Alaska, over the last two millennia as determined from soil charcoal","volume":"227","author":"Berg","year":"2006","journal-title":"For. Ecol. Manag."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.foreco.2016.03.036","article-title":"Forest-landscape structure mediates effects of a spruce bark beetle (Dendroctonus rufipennis) outbreak on subsequent likelihood of burning in Alaskan boreal forest","volume":"369","author":"Hansen","year":"2016","journal-title":"For. Ecol. Manag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3571","DOI":"10.1016\/j.foreco.2008.02.039","article-title":"White spruce regeneration following a major spruce beetle outbreak in forests on the Kenai Peninsula, Alaska","volume":"255","author":"Boggs","year":"2008","journal-title":"For. Ecol. Manag."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1071\/WF9980159","article-title":"Fuel Models and Fire Potential from Satellite and Surface Observations","volume":"8","author":"Burgan","year":"1998","journal-title":"Int. J. Wildland Fire"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1080\/02693799608902082","article-title":"Mapping the spatial distribution of forest fire danger using GIS","volume":"10","author":"Chuvieco","year":"1996","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_22","first-page":"41","article-title":"Use of imaging spectroscopy and LIDAR to characterize fuels for fire behavior prediction","volume":"11","author":"Stavros","year":"2018","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3970","DOI":"10.3390\/s8063970","article-title":"Spatio-temporal analysis of forest fire risk and danger using LANDSAT imagery","volume":"8","author":"Saglam","year":"2008","journal-title":"Sensors"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"540","DOI":"10.3390\/rs6010540","article-title":"Modeling fire danger in Galicia and Asturias (Spain) from MODIS images","volume":"6","author":"Bisquert","year":"2014","journal-title":"Remote Sens."},{"key":"ref_25","first-page":"563","article-title":"Global fire mapping and fire danger estimation using AVHRR images","volume":"60","author":"Chuvieco","year":"1994","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_26","unstructured":"United States Board on Geographic Names (2018, December 20). Feature Detail Report for: Kenai Peninsula, Available online: http:\/\/geonames.usgs.gov\/apex\/f?p=gnispq:3:::NO::P3_FID:1404582."},{"key":"ref_27","unstructured":"Bureau of Land Management (2018, December 20). Alaska Wildland Fire History, 1940\u20132017, Available online: https:\/\/fire.ak.blm.gov\/content\/maps\/."},{"key":"ref_28","unstructured":"Fryer, J.L. (2014). Fire Regimes of Alaskan Black Spruce Communities. Fire Effects Information System, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory (Producer). Available online: https:\/\/www.fs.fed.us\/database\/feis\/fire_regimes\/AK_black_spruce\/all.html."},{"key":"ref_29","unstructured":"Abrahamson, I. (2015). Picea glauca, White Spruce. Fire Effects Information System, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory (Producer). Available online: https:\/\/www.fs.fed.us\/database\/feis\/plants\/tree\/picgla\/all.html."},{"key":"ref_30","unstructured":"Fryer, J.L. (2014). Picea\u00a0mariana. Fire Effects Information System, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory (Producer). Available online: https:\/\/www.fs.fed.us\/database\/feis\/plants\/tree\/picmar\/all.html."},{"key":"ref_31","unstructured":"Abrahamson, I.L. (2014). Fire Regimes of Alaskan White Spruce Communities. Fire Effects Information System, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory (Producer). Available online: https:\/\/www.fs.fed.us\/database\/feis\/fire_regimes\/AK_white_spruce\/all.html."},{"key":"ref_32","unstructured":"Oldemeyer, J.L., and Regelin, W.L. (1987). Forest Succession, Habitat Management, and Moose on the Kenai National Wildlife Refuge, Swedish Wildlife Research."},{"key":"ref_33","unstructured":"Chuvieco, E., Salas, J., and Vega, C. (1997). Remote Sensing and GIS for Long-Term Fire Risk Mapping, Universidad de Alcal\u00e1. Mega Fires Project, A Review of Remote Sensing Methods for the Study of Large Wildland Fires."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1071\/WF01033","article-title":"Fire modeling and information system technology","volume":"10","author":"Andrews","year":"2001","journal-title":"Int. J. Wildland Fire"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.apgeog.2014.01.011","article-title":"Modeling the spatial variation of the explanatory factors of human-caused wildfires in Spain using geographically weighted logistic regression","volume":"48","author":"Rodrigues","year":"2014","journal-title":"Appl. Geogr."},{"key":"ref_36","unstructured":"Stojanova, D., Panov, P., Kobler, A., Dzeroski, S., and Taskova, K. (2006, January 9\u201314). Learning to predict forest fires with different data mining techniques. Proceedings of the 9th International multi conference Information Society IS 2006, Ljubljana, Slovenia."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Guo, F., Zhang, L., Jin, S., Tigabu, M., Su, Z., and Wang, W. (2016). Modeling anthropogenic fire occurrence in the boreal forest of China using logistic regression and random forests. Forests, 7.","DOI":"10.3390\/f7110250"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1879","DOI":"10.1007\/s11069-016-2160-0","article-title":"Building probabilistic models of fire occurrence and fire risk zoning using logistic regression in Shanxi Province, China","volume":"81","author":"Pan","year":"2016","journal-title":"Nat. Hazards"},{"key":"ref_39","first-page":"1","article-title":"Forest fire risk zone mapping from satellite imagery and GIS","volume":"4","author":"Jaiswal","year":"2002","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/j.envsoft.2017.12.019","article-title":"Wildfire susceptibility mapping: Deterministic vs. stochastic approaches","volume":"101","author":"Leuenberger","year":"2018","journal-title":"Environ. Model. Softw."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1489","DOI":"10.1007\/s11069-016-2637-x","article-title":"Evolution of forest fires in Portugal: From spatio-temporal point events to smoothed density maps","volume":"85","author":"Tonini","year":"2017","journal-title":"Nat. Hazards"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.isprsjprs.2014.03.011","article-title":"Operational perspective of remote sensing-based forest fire danger forecasting systems","volume":"104","author":"Chowdhury","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/3\/283\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:30:05Z","timestamp":1760185805000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/3\/283"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,2,1]]},"references-count":42,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2019,2]]}},"alternative-id":["rs11030283"],"URL":"https:\/\/doi.org\/10.3390\/rs11030283","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,2,1]]}}}