{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T21:03:27Z","timestamp":1771535007431,"version":"3.50.1"},"reference-count":93,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,14]],"date-time":"2019-09-14T00:00:00Z","timestamp":1568419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Despite increasing the number of studies for mapping remote sensing insect-induced forest infestations, applying novel approaches for mapping and identifying its triggers are still developing. This study was accomplished to test the performance of Geographic Object-Based Image Analysis (GEOBIA) TreeNet for discerning insect-infested forests induced by defoliators from healthy forests using Landsat 8 OLI and ancillary data in the broadleaved mixed Hyrcanian forests. Moreover, it has studied mutual associations between the intensity of forest defoliation and the severity of forest fires under TerraClimate-derived climate hazards by analyzing panel data models within the TreeNet-derived insect-infested forest objects. The TreeNet optimal performance was obtained after building 333 trees with a sensitivity of 93.7% for detecting insect-infested objects with the contribution of the top 22 influential variables from 95 input object features. Accordingly, top image-derived features were the mean of the second principal component (PC2), the mean of the red channel derived from the gray-level co-occurrence matrix (GLCM), and the mean values of the normalized difference water index (NDWI) and the global environment monitoring index (GEMI). However, tree species type has been considered as the second rank for discriminating forest-infested objects from non-forest-infested objects. The panel data models using random effects indicated that the intensity of maximum temperatures of the current and previous years, the drought and soil-moisture deficiency of the current year, and the severity of forest fires of the previous year could significantly trigger the insect outbreaks. However, maximum temperatures were the only significant triggers of forest fires. This research proposes testing the combination of object features of Landsat 8 OLI with other data for monitoring near-real-time defoliation and pathogens in forests.<\/jats:p>","DOI":"10.3390\/s19183965","type":"journal-article","created":{"date-parts":[[2019,9,16]],"date-time":"2019-09-16T03:17:57Z","timestamp":1568603877000},"page":"3965","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Climate-Triggered Insect Defoliators and Forest Fires Using Multitemporal Landsat and TerraClimate Data in NE Iran: An Application of GEOBIA TreeNet and Panel Data Analysis"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8048-8792","authenticated-orcid":false,"given":"Omid","family":"Abdi","sequence":"first","affiliation":[{"name":"Institute for Cartography, Department of Geosciences, Faculty of Environmental Sciences, TU Dresden, 01069 Dresden, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"399","DOI":"10.2307\/2937153","article-title":"Multicentury, Regional-Scale Patterns of Western Spruce Budworm Outbreaks","volume":"63","author":"Swetnam","year":"1993","journal-title":"Ecol. Monogr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"377","DOI":"10.5424\/fs\/2013223-04417","article-title":"Remote Monitoring of Forest Insect Defoliation. A Review","volume":"22","author":"Olthoff","year":"2013","journal-title":"For. Syst."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"S296","DOI":"10.4039\/tce.2016.11","article-title":"Remote sensing of forest pest damage: A review and lessons learned from a Canadian perspective","volume":"148","author":"Hall","year":"2016","journal-title":"Can. Entomol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2017.07.007","article-title":"Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak","volume":"131","author":"Dash","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_5","first-page":"49","article-title":"Remote sensing of forest insect disturbances: Current state and future directions","volume":"60","author":"Senf","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/S0167-9473(01)00065-2","article-title":"Stochastic gradient boosting","volume":"38","author":"Friedman","year":"2002","journal-title":"Comput. Stat. Data Anal."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"170191","DOI":"10.1038\/sdata.2017.191","article-title":"TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958\u20132015","volume":"5","author":"Abatzoglou","year":"2018","journal-title":"Sci. Data"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1177\/0309133314550670","article-title":"Object-based extraction of bark beetle (Ips typographus L.) infestations using multi-date LANDSAT and SPOT satellite imagery","volume":"38","author":"Latifi","year":"2014","journal-title":"Prog. Phys. Geogr. Earth Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.foreco.2014.02.037","article-title":"Spatial and temporal patterns of Landsat-based detection of tree mortality caused by a mountain pine beetle outbreak in Colorado, USA","volume":"322","author":"Meddens","year":"2014","journal-title":"For. Ecol. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3983","DOI":"10.1016\/j.rse.2008.07.008","article-title":"Estimating the effect of gypsy moth defoliation using MODIS","volume":"112","author":"Townsend","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"706","DOI":"10.1080\/07038992.2016.1220828","article-title":"Using Landsat to Assess the Relationship between Spatiotemporal Patterns of Western Spruce Budworm Outbreaks and Regional-Scale Weather Variability","volume":"42","author":"Senf","year":"2016","journal-title":"Can. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/j.rse.2009.11.005","article-title":"Landsat TM\/ETM+ and tree-ring based assessment of spatiotemporal patterns of the autumnal moth (Epirrita autumnata) in northernmost Fennoscandia","volume":"114","author":"Babst","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.rse.2011.12.023","article-title":"A general Landsat model to predict canopy defoliation in broadleaf deciduous forests","volume":"119","author":"Townsend","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/j.foreco.2015.03.005","article-title":"Remote monitoring of defoliation by the beech leaf-mining weevil Rhynchaenus fagi in northern Spain","volume":"347","author":"Olthoff","year":"2015","journal-title":"For. Ecol. Manag."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.rse.2013.01.002","article-title":"Evaluating methods to detect bark beetle-caused tree mortality using single-date and multi-date Landsat imagery","volume":"132","author":"Meddens","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1220","DOI":"10.3390\/rs5031220","article-title":"Area-Based Mapping of Defoliation of Scots Pine Stands Using Airborne Scanning LiDAR","volume":"5","author":"Vastaranta","year":"2013","journal-title":"Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.isprsjprs.2014.05.013","article-title":"Evaluating the impact of red-edge band from Rapideye image for classifying insect defoliation levels","volume":"95","author":"Adelabu","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3680","DOI":"10.1016\/j.rse.2008.05.005","article-title":"Estimation of insect infestation dynamics using a temporal sequence of Landsat data","volume":"112","author":"Goodwin","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1007\/s10980-011-9608-0","article-title":"Spatial prediction of caterpillar (Ormiscodes) defoliation in Patagonian Nothofagus forests","volume":"26","author":"Paritsis","year":"2011","journal-title":"Landsc. Ecol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.rse.2013.05.008","article-title":"Using a remotely sensed optimized Disturbance Index to detect insect defoliation in the Apostle Islands, Wisconsin, USA","volume":"136","author":"Thayn","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1007\/s10342-009-0331-1","article-title":"Object-orientated image analysis for the semi-automatic detection of dead trees following a spruce bark beetle (Ips typographus) outbreak","volume":"129","author":"Heurich","year":"2010","journal-title":"Eur. J. For. Res."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Blaschke, T., Lang, S., and Hay, G.J. (2008). Geographic Object-Based Image Analysis (GEOBIA): A new name for a new discipline. Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications, Springer.","DOI":"10.1007\/978-3-540-77058-9"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1007\/s10661-013-3389-7","article-title":"Spatial characterization of bark beetle infestations by a multidate synergy of SPOT and Landsat imagery","volume":"186","author":"Latifi","year":"2014","journal-title":"Environ. Monit. Assess."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.foreco.2014.03.042","article-title":"Drought-triggered western spruce budworm outbreaks in the interior Pacific Northwest: A multi-century dendrochronological record","volume":"324","author":"Flower","year":"2014","journal-title":"For. Ecol. Manag."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1126\/science.aaa9933","article-title":"Temperate forest health in an era of emerging megadisturbance","volume":"349","author":"Millar","year":"2015","journal-title":"Science"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1111\/geb.12558","article-title":"Biotic disturbances in Northern Hemisphere forests\u2014A synthesis of recent data, uncertainties and implications for forest monitoring and modelling","volume":"26","author":"Kautz","year":"2017","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1068","DOI":"10.1111\/ecog.04239","article-title":"Anomalous outbreaks of an invasive defoliator and native bark beetle facilitated by warm temperatures, changes in precipitation and interspecific interactions","volume":"42","author":"Ward","year":"2019","journal-title":"Ecography"},{"key":"ref_28","unstructured":"Ryan, M.G., and Vose, J.M. (2019, August 02). Effects of Climatic Variability and Change on Forest Ecosystems: A Comprehensive Science Synthesis for the U.S. Forest Sector, Available online: https:\/\/www.fs.usda.gov\/treesearch\/pubs\/42651."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1007\/s11027-007-9127-0","article-title":"Role of winter temperature and climate change on the survival and future range expansion of the hemlock woolly adelgid (Adelges tsugae) in eastern North America","volume":"13","author":"Paradis","year":"2008","journal-title":"Mitig. Adapt. Strateg. Glob. Chang."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1890\/06-0512","article-title":"Impact of minimum winter temperatures on the population dynamics of Dendroctonus frontalis","volume":"17","author":"Ylioja","year":"2007","journal-title":"Ecol. Appl."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1007\/s40725-018-0075-6","article-title":"Forest Insects and Climate Change","volume":"4","author":"Pureswaran","year":"2018","journal-title":"Curr. For. Rep."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2071","DOI":"10.1111\/j.1365-2486.2010.02370.x","article-title":"Rapid northwards expansion of a forest insect pest attributed to spring phenology matching with sub-Arctic birch","volume":"17","author":"Jepsen","year":"2011","journal-title":"Glob. Chang. Biol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.foreco.2016.04.051","article-title":"Observed and anticipated impacts of drought on forest insects and diseases in the United States","volume":"380","author":"Kolb","year":"2016","journal-title":"For. Ecol. Manag."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.foreco.2018.09.006","article-title":"Tree mortality following drought in the central and southern Sierra Nevada, California, U.S","volume":"432","author":"Fettig","year":"2019","journal-title":"For. Ecol. Manag."},{"key":"ref_35","unstructured":"Littell, J.S., Peterson, D.L., Riley, K.L., Liu, Y., and Luce, C.H. (2016). Fire and Drought, Effects of Drought on Forests and Rangelands in the United States: A Comprehensive Science Synthesis."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1051\/forest:2006044","article-title":"Effects of drought and heat on forest insect populations in relation to the 2003 drought in Western Europe","volume":"63","author":"Rouault","year":"2006","journal-title":"Ann. For. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1010","DOI":"10.1139\/x03-026","article-title":"A tree-ring reconstruction of western spruce budworm outbreaks in the San Juan Mountains, Colorado, U.S.A","volume":"33","author":"Ryerson","year":"2003","journal-title":"Can. J. For. Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"375","DOI":"10.4039\/Ent116375-3","article-title":"Relating weather to outbreaks of western spruce budworm, Choristoneura occidentalis (Lepidoptera: Tortricidae), in British Columbia","volume":"116","author":"Thomson","year":"1984","journal-title":"Can. Entomol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1016\/j.rse.2017.04.005","article-title":"Assessing the impact of emerging forest disease on wildfire using Landsat and KOMPSAT-2 data","volume":"195","author":"Chen","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"81","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_41","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.foreco.2016.02.004","article-title":"Fire severity and cumulative disturbance effects in the post-mountain pine beetle lodgepole pine forests of the Pole Creek Fire","volume":"366","author":"Agne","year":"2016","journal-title":"For. Ecol. Manag."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1890\/ES15-00037.1","article-title":"Does wildfire likelihood increase following insect outbreaks in conifer forests?","volume":"6","author":"Meigs","year":"2015","journal-title":"Ecosphere"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.foreco.2017.09.037","article-title":"Characterizing interactions between fire and other disturbances and their impacts on tree mortality in western U.S. Forests","volume":"405","author":"Kane","year":"2017","journal-title":"For. Ecol. Manag."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"544","DOI":"10.1016\/j.foreco.2012.10.020","article-title":"Low-severity fires increase susceptibility of lodgepole pine to mountain pine beetle outbreaks in Colorado","volume":"289","author":"Kulakowski","year":"2013","journal-title":"For. Ecol. Manag."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.foreco.2017.02.015","article-title":"Landscape-scale quantification of fire-induced change in canopy cover following mountain pine beetle outbreak and timber harvest","volume":"391","author":"McCarley","year":"2017","journal-title":"For. Ecol. Manag."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2176","DOI":"10.1002\/ldr.2744","article-title":"Analysing Spatial and Statistical Dependencies of Deforestation Affected by Residential Growth: Gorganrood Basin, Northeast Iran","volume":"28","author":"Shirvani","year":"2017","journal-title":"Land Degrad. Dev."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1080\/19475705.2016.1206629","article-title":"Spatial-statistical analysis of factors determining forest fires: A case study from Golestan, Northeast Iran","volume":"9","author":"Abdi","year":"2018","journal-title":"Geomat. Nat. Hazards Risk"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2525","DOI":"10.1002\/ldr.3025","article-title":"Spatiotemporal drought evaluation of Hyrcanian deciduous forests and semi-steppe rangelands using moderate resolution imaging spectroradiometer time series in Northeast Iran","volume":"29","author":"Abdi","year":"2018","journal-title":"Land Degrad. Dev."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.agrformet.2019.05.029","article-title":"Forest drought-induced diversity of Hyrcanian individual-tree mortality affected by meteorological and hydrological droughts by analyzing moderate resolution imaging spectroradiometer products and spatial autoregressive models over northeast Iran","volume":"275","author":"Abdi","year":"2019","journal-title":"Agric. For. Meteorol."},{"key":"ref_50","unstructured":"Setayeshgar, F. (2014, July 01). The Attack of Lymantria Dispar to 420 Hecatres of Hyrcanian Forests: Outbreak of Defoliators in the Forests. Available online: http:\/\/khorasannews.com\/?nid=18724&type=0."},{"key":"ref_51","first-page":"301","article-title":"The effect of leaf feeder moth (Erannis defoliaria & Operophtera brumata) on radial growth of 3 tree species in north of Iran (case study: Mashalak, Nowshahr)","volume":"15","author":"Ahangaran","year":"2007","journal-title":"Iran. J. For. Poplar Res."},{"key":"ref_52","first-page":"48","article-title":"Zelkova carpinifolia reservoir from Hyrcanian Forests, Northern Iran, a new sacrifice of Ophiostoma novo-ulmi","volume":"15","author":"Ahmadi","year":"2014","journal-title":"Biodiversitas"},{"key":"ref_53","unstructured":"F.A.O. (2019, July 20). Food Chain Crisis Early Warning Bulletin. Available online: www.fao.org\/food-chain-crisis."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"876","DOI":"10.1094\/PDIS-03-11-0153","article-title":"The Occurrence of Charcoal Disease Caused by Biscogniauxia mediterranea on Chestnut-Leaved Oak (Quercus castaneifolia) in the Golestan Forests of Iran","volume":"95","author":"Mirabolfathy","year":"2011","journal-title":"Plant Dis."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Sagheb Talebi, K., Sajedi, T., and Pourhashemi, M. (2014). Forests of Iran. A Treasure from the Past, a Hope for the Future, Springer.","DOI":"10.1007\/978-94-007-7371-4"},{"key":"ref_56","unstructured":"U.S. Geological Survey, Earth Resources Observation Science Center (2019). Collection-1 Landsat OLI Level-2 Surface Reflectance (SR) Science Product."},{"key":"ref_57","unstructured":"ASF DAAC (2019). PALSAR Radiometric Terrain Corrected High Res, ASF DAAC. Includes Material \u00a9 JAXA\/METI 2007."},{"key":"ref_58","unstructured":"Department of Natural Resources and Watershed Management of Golestan (1981\u20132011). The Booklets of Forest Management Plans: Jafarabad, Golriz, Tavir, Kohmian, Zarringol, Sorkhdari, Rezaeian, Qalemorian, Daland, Vatan, Nodeh-Bon-Qale, Minudasht, Takht, Loveh, Sijan-Kiaram, Korankaftar, Terjenli, Department of Natural Resources and Watershed Management of Golestan."},{"key":"ref_59","unstructured":"Google Earth Pro V 7.3.2.5491 (2019). Sousara, Golestan Province. 37\u00b0 00\u2019 47.58\u201dN, 55\u00b0 16\u2019 30.88\u201dE, Eye alt 10.17 km, Google LLC. DigitalGlobe 2019."},{"key":"ref_60","unstructured":"eCognition Developer (2014). T. 9.0 User Guide, Trimble Germany GmbH."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/0034-4257(90)90085-Z","article-title":"Calculating the vegetation index faster","volume":"34","author":"Crippen","year":"1990","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/BF00031911","article-title":"GEMI: A non-linear index to monitor global vegetation from satellites","volume":"101","author":"Pinty","year":"1992","journal-title":"Vegetatio"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1109\/36.134076","article-title":"Atmospherically resistant vegetation index (ARVI) for EOS-MODIS","volume":"30","author":"Kaufman","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/S0034-4257(96)00072-7","article-title":"Use of a green channel in remote sensing of global vegetation from EOS-MODIS","volume":"58","author":"Gitelson","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combinations for monitoring vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"3833","DOI":"10.1016\/j.rse.2008.06.006","article-title":"Development of a two-band enhanced vegetation index without a blue band","volume":"112","author":"Jiang","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0034-4257(96)00067-3","article-title":"NDWI\u2014A normalized difference water index for remote sensing of vegetation liquid water from space","volume":"58","author":"Gao","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1080\/01431168508948511","article-title":"Standardized principal components","volume":"6","author":"Singh","year":"1985","journal-title":"Int. J. Remote Sens."},{"key":"ref_69","unstructured":"Kauth, R.J., and Thomas, G.S. (1976). The Tasselled Cap\u2014A Graphic Description of the Spectral-Temporal Development of Agricultural Crops as Seen by Landsat, Purdue University."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural Features for Image Classification","volume":"3","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Navulur, K. (2006). Multispectral Image Analysis Using the Object-Oriented Paradigm, CRC Press.","DOI":"10.1201\/9781420043075"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1002\/hyp.3360050103","article-title":"Digital terrain modelling: A review of hydrological, geomorphological, and biological applications","volume":"5","author":"Moore","year":"1991","journal-title":"Hydrol. Process."},{"key":"ref_73","unstructured":"Wilson, J.P., and Gallant, J.C. (2000). Terrain Analysis. Principles and Applications, John Wiley & Sons."},{"key":"ref_74","first-page":"23","article-title":"Index that quantifies topographic heterogeneity","volume":"5","author":"Riley","year":"1999","journal-title":"Intermt. J. Sci."},{"key":"ref_75","unstructured":"Salford Systems Ltd. (2018). Salford Predictive Modeler 8.3, Salford Systems Ltd."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1007\/BF02985802","article-title":"The elements of statistical learning: Data mining, inference and prediction","volume":"27","author":"Hastie","year":"2005","journal-title":"Math. Intell."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.biocon.2014.10.007","article-title":"Rapid multi-nation distribution assessment of a charismatic conservation species using open access ensemble model GIS predictions: Red panda (Ailurus fulgens) in the Hindu-Kush Himalaya region","volume":"181","author":"Kandel","year":"2015","journal-title":"Biol. Conserv."},{"key":"ref_78","unstructured":"ESRI (2019, May 01). How Fuzzy Overlay Works. Available online: http:\/\/desktop.arcgis.com\/en\/arcmap\/10.5\/tools\/spatial-analyst-toolbox\/how-fuzzy-overlay-works.htm."},{"key":"ref_79","unstructured":"Key, C.H., and Benson, N.C. (2019, August 02). Landscape Assessment: Remote Sensing of Severity, the Normalized Burn Ratio, Available online: http:\/\/pubs.er.usgs.gov\/publication\/2002085."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.rse.2006.12.006","article-title":"Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR)","volume":"109","author":"Miller","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_81","unstructured":"ESRI (2019, April 04). How Fuzzy Membership Works. Available online: http:\/\/desktop.arcgis.com\/en\/arcmap\/10.5\/tools\/spatial-analyst-toolbox\/how-fuzzy-membership-works.htm."},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Elhorst, J.P. (2014). Spatial Panel Data Models. Spatial Econometrics: From Cross-Sectional Data to Spatial Panels, Springer.","DOI":"10.1007\/978-3-642-40340-8"},{"key":"ref_83","unstructured":"Greene, W.H. (2002). Econometric Analysis, Prentice Hall. [5th ed.]."},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Fischer, M.M., and Getis, A. (2010). Spatial Panel Data Models. Handbook of Applied Spatial Analysis, Springer.","DOI":"10.1007\/978-3-642-03647-7"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1017\/psrm.2014.7","article-title":"Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data","volume":"3","author":"Bell","year":"2015","journal-title":"PSRM"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.2307\/1913827","article-title":"Specification Tests in Econometrics","volume":"46","author":"Hausman","year":"1978","journal-title":"Econometrica"},{"key":"ref_87","unstructured":"Baltagi, B.H. (2008). Econometric Analysis of Panel Data, John Wiley & Sons. [4th ed.]."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1002\/j.1537-2197.1993.tb13796.x","article-title":"Responses of Leaf Spectral Reflectance to Plant Stress","volume":"80","author":"Carter","year":"1993","journal-title":"Am. J. Bot."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1016\/S0176-1617(96)80070-8","article-title":"Narrow-band Reflectance Imagery Compared with ThermalImagery for Early Detection of Plant Stress","volume":"148","author":"Carter","year":"1996","journal-title":"J. Plant Physiol."},{"key":"ref_90","first-page":"1243","article-title":"Change Detection for Monitoring Forest Defoliation","volume":"60","author":"Muchoney","year":"1994","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"2701","DOI":"10.1080\/01431160310001642304","article-title":"Relationship between airborne multispectral image texture and aspen defoliation","volume":"25","author":"Moskal","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"014513","DOI":"10.1117\/1.JRS.13.014513","article-title":"Detecting and mapping Gonipterus scutellatus induced vegetation defoliation using WorldView-2 pan-sharpened image texture combinations and an artificial neural network","volume":"13","author":"Lottering","year":"2019","journal-title":"J. Appl. Remote Sens."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.foreco.2012.08.003","article-title":"A new invasive insect in Sweden\u2014Physokermes inopinatus: Tracing forest damage with satellite based remote sensing","volume":"285","author":"Olsson","year":"2012","journal-title":"For. Ecol. 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