Quantifying coconut palm extent on Pacific islands using spectral and textural analysis of very high resolution imagery

References

• Bartolucci, L. A., B. F. Robinson, and L. F. Silva. 1977. “Field Measurements of the Spectral Response of Natural Waters.” Photogrammetric Engineering and Remote Sensing 43 (5): 595–598.
   Web of Science ®Google Scholar
• Booth, D. J., and R. B. Oldfield. 1989. “A Comparison of Classification Algorithms in Terms of Speed and Accuracy after the Application of A Post-Classification Modal Filter.” International Journal of Remote Sensing 10 (7): 1271–1276. doi:10.1080/01431168908903965.
   Web of Science ®Google Scholar
• Boulesteix, A. L., S. Janitza, J. Kruppa, and I. R. König. 2012. “Overview of Random Forest Methodology and Practical Guidance with Emphasis on Computational Biology and Bioinformatics.” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2 (6): 493–507. doi:10.1002/widm.1072.
   Web of Science ®Google Scholar
• Breiman, L. 1996. Out-of-Bag Estimation. Berkeley, CA: University of California Berkeley. https://www.stat.berkeley.edu/~breiman/OOBestimation.pdf
   Google Scholar
• Breiman, L. 2001. “Random Forests.” Machine Learning 45 (1): 5–32. doi:10.1023/A:1010933404324.
   Web of Science ®Google Scholar
• Bricher, P. K., A. Lucieer, J. Shaw, A. Terauds, and D. M. Bergstrom. 2013. “Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling.” PLOS ONE 8 (8): 1–15. doi:10.1371/journal.pone.0072093.
   Web of Science ®Google Scholar
• Briggs, A. A., H. S. Young, D. J. McCauley, S. A. Hathaway, R. Dirzo, and R. N. Fisher. 2012. “Effects of Spatial Subsidies and Habitat Structure on the Foraging Ecology and Size of Geckos.” PLOS ONE 7 (8). doi:10.1371/journal.pone.0041364.
   Web of Science ®Google Scholar
• Carlson, K. M., L. M. Curran, G. P. Asner, A. M. Pittman, S. N. Trigg, and J. M. Adeney. 2013. “Carbon Emissions from Forest Conversion by Kalimantan Oil Palm Plantations.” Nature Climate Change 3 (3): 283–287. doi:10.1038/nclimate1702.
   Web of Science ®Google Scholar
• Chen, C., A. Liaw, and L. Breiman. 2004. Using Random Forest to Learn Imbalanced Data. Berkeley, CA: University of California Berkeley. https://statistics.berkeley.edu/sites/default/files/tech-reports/666.pdf
   Google Scholar
• Clausi, D. A. 2002. “An Analysis of Co-Occurrence Texture Statistics as a Function of Grey Level Quantization.” Canadian Journal of Remote Sensing 28 (1): 45–62. doi:10.5589/m02-004.
   Web of Science ®Google Scholar
• Collen, J. D., D. W. Garton, and J. P. A. Gardner. 2009. “Shoreline Changes and Sediment Redistribution at Palmyra Atoll (Equatorial Pacific Ocean): 1874–Present.” Journal of Coastal Research 25 (3): 711–722. doi:10.2112/08-1007.1.
   Web of Science ®Google Scholar
• Cross, M. D., T. A. Scambos, F. Pacifici, and W. E. Marshall. 2018. “Validating the Use of Metre-Scale Multi-Spectral Satellite Image Data for Identifying Tropical Forest Tree Species.” International Journal of Remote Sensing 39 (11): 3723–3752. doi:10.1080/01431161.2018.1448482.
   Web of Science ®Google Scholar
• Cutler, D. R., T. C. Edwards, K. H. Jr., B. A. Cutler, K. T. Hess, J. Gibson, and J. J. Lawler. 2007. “Random Forests for Classification in Ecology.” Ecology 88 (11): 2783–2792. doi:10.1890/07-0539.1.
   PubMed Web of Science ®Google Scholar
• Dawson, E. Y. 1959. “Changes in Palmyra Atoll and Its Vegetation through the Activites of Man, 1913-1958.” Pacific Naturalist 1 (2): 1–51.
   Google Scholar
• Evans, J. S., and S. A. Cushman. 2009. “Gradient Modeling of Conifer Species Using Random Forests.” Landscape Ecology 24 (5): 673–683. doi:10.1007/s10980-009-9341-0.
   Web of Science ®Google Scholar
• Fine, P. V. A. 2002. “The Invasibility of Tropical Forests by Exotic Plants.” Journal of Tropical Ecology 18 (05): 687–705. doi:10.1017/S0266467402002456.
   Google Scholar
• Fordham, D. A., and B. W. Brook. 2010. “Why Tropical Island Endemics are Acutely Susceptible to Global Change.” Biodiversity and Conservation 19 (2): 329–342. doi:10.1007/s10531-008-9529-7.
   Web of Science ®Google Scholar
• Fosberg, F. R. 1957. “Description and Occurrence of Atoll Phosphate Rock in Micronesia.” American Journal of Science 255: 584–592. doi:10.2475/ajs.255.8.584.
   Web of Science ®Google Scholar
• Genuer, R., J. M. Poggi, and C. Tuleau-Malot. 2010. “Variable Selection Using Random Forests.” Pattern Recognition Letters 31 (14): 2225–2236. doi:10.1016/j.patrec.2010.03.014.
   Web of Science ®Google Scholar
• Goldberg, W. M. 2016. “Atolls of the World: Revisiting the Original Checklist.” Atoll Research Bulletin 610: 1–47. doi:10.5479/si.0077-5630.610.
   Google Scholar
• Gordon, H. R., and M. Wang. 1992. “Surface-Roughness Considerations for Atmospheric Correction of Ocean Color Sensors. II: Error in the Retrieved Water-Leaving Radiance.” Applied Optics 31 (21): 4261–4267. doi:10.1364/AO.31.004261.
   PubMed Web of Science ®Google Scholar
• Gregorutti, B., B. Michel, and P. Saint-Pierre. 2017. “Correlation and Variable Importance in Random Forests.” Statistics and Computing 27 (3): 659–678. doi:10.1007/s11222-016-9646-1.
   Web of Science ®Google Scholar
• Hall-Beyer, M. 2017a. “Practical Guidelines for Choosing GLCM Textures to Use in Landscape Classification Tasks over a Range of Moderate Spatial Scales.” International Journal of Remote Sensing 38 (5): 1312–1338. doi:10.1080/01431161.2016.1278314.
   Web of Science ®Google Scholar
• Hall-Beyer, M. 2017b. GLCM Texture: A Tutorial. Version 3.0. Calgary, Alberta: University of Calgary. doi:10.11575/PRISM/33280.
   Google Scholar
• Hammond, T. O., and D. L. Verbyla. 1996. “Optimistic Bias in Classification Accuracy Assessment.” International Journal of Remote Sensing 17 (6): 1261–1266. doi:10.1080/01431169608949085.
   Web of Science ®Google Scholar
• Han, H., X. Guo, and H. Yu. 2016. “Variable Selection Using Mean Decrease Accuracy and Mean Decrease Gini Based on Random Forest.” In 7th IEEE International Conference on Software Engineering and Service Science (ICSESS), 219–224. Beijing, China: IEEE. doi:10.1109/ICSESS.2016.7883053.
   Google Scholar
• Handler, A. T., D. S. Gruner, W. P. Haines, M. W. Lange, and K. Y. Kaneshiro. 2007. “Arthropod Surveys on Palmyra Atoll, Line Islands, and Insights into the Decline of the Native Tree Pisonia Grandis (Nyctaginaceae).” Pacific Science 61 (4): 485–502. doi:10.2984/1534-6188(2007)61[485:asopal]2.0.co;2.
   Web of Science ®Google Scholar
• Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, et al. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (6160): 850–853. doi:10.1126/science.1244693.
   PubMed Web of Science ®Google Scholar
• Haralick, R. M., K. Shanmugan, and I. Dinstein. 1973. “Textural Features for Image Classification.” IEEE Transactions on Systems, Man and Cybernetics 3 (6): 610–621. doi:10.1109/TSMC.1973.4309314.
   Web of Science ®Google Scholar
• Hathaway, S. A., K. McEachern, and R. N. Fisher. 2011. Terrestrial Forest Management Plan for Palmyra Atoll: U.S. Geological Survey Open-File Report 2011–1007.
   Google Scholar
• Hijmans, R. J. 2017. Raster: Geographic Data Analysis and Modeling. R Package Version 2.6-7. https://cran.r-project.org/package=raster
   Google Scholar
• Huang, C., and G. Asner. 2009. “Applications of Remote Sensing to Alien Invasive Plant Studies.” Sensors 9 (6): 4869–4889. doi:10.3390/s90604869.
   PubMed Web of Science ®Google Scholar
• Huang, X., X. Liu, and L. Zhang. 2014. “A Multichannel Gray Level Co-Occurrence Matrix for Multi/Hyperspectral Image Texture Representation.” Remote Sensing 6 (9): 8424–8445. doi:10.3390/rs6098424.
   Web of Science ®Google Scholar
• Immitzer, M., C. Atzberger, and T. Koukal. 2012. “Tree Species Classification with Random Forest Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data.” Remote Sensing 4 (9): 2661–2693. doi:10.3390/rs4092661.
   Web of Science ®Google Scholar
• Irons, J. R., and G. W. Petersen. 1981. “Texture Transforms of Remote Sensing Data.” Remote Sensing of Environment 11: 359–370. doi:10.1016/0034-4257(81)90033-X.
   Web of Science ®Google Scholar
• Janitza, S., and R. Hornung. 2018. “On the Overestimation of Random Forest’s out-Of-Bag Error.” PLOS ONE 13. doi:10.1371/journal.pone.0201904.
   PubMed Web of Science ®Google Scholar
• Kaszta, Ż., R. Van De Kerchove, A. Ramoelo, M. A. Cho, S. Madonsela, R. Mathieu, and E. Wolff. 2016. “Seasonal Separation of African Savanna Components Using WorldView-2 Imagery: A Comparison of Pixeland Object-Based Approaches and Selected Classification Algorithms.” Remote Sensing 8 (9): 763. doi:10.3390/rs8090763.
   Web of Science ®Google Scholar
• Kepler, A. K., and C. B. Kepler. 1994. "The NaturalHistory of Caroline Atoll, Southern Line Islands: Part I. History,Physiography, Botany, and Isle Descriptions." Atoll ResearchBulletin 397: 1-225. doi:10.5479/si.00775630.397.1.
   Google Scholar
• Koh, L. P., J. Miettinen, S. C. Liew, and J. Ghazoul. 2011. “Remotely Sensed Evidence of Tropical Peatland Conversion to Oil Palm.” Proceedings of the National Academy of Sciences 108 (12): 5127–5132. doi:10.1073/pnas.1018776108.
   PubMed Web of Science ®Google Scholar
• Komba Mayossa, P. C., G. C. d’Eeckenbrugge, F. Borne, S. Gadal, and G. Viennois. 2015. “Developing a Method to Map Coconut Agrosystems from High-Resolution Satellite Images.” In 27th International Cartographic Conference, 16th General Assembly. Rio de Janeiro, Brazil: International Cartographic Association. doi:10.13140/RG.2.1.4618.8244.
   Google Scholar
• Krauss, B. 1979. “Palmyra: It’s a Pioneer Life at the Copra Plantation.” The Honolulu Advertiser, September 17.
   Google Scholar
• Krauss, K. W., J. A. Duberstein, N. Cormier, H. S. Young, and S. A. Hathaway. 2015. “Proximity to Encroaching Coconut Palm Limits Native Forest Water Use and Persistence on a Pacific Atoll.” Ecohydrology 8: 1514–1524. doi:10.1002/eco.1601.
   Web of Science ®Google Scholar
• Lafferty, K. D., S. A. Hathaway, A. S. Wegmann, F. S. Shipley, A. R. Backlin, J. Helm, and R. N. Fisher. 2010. “Stomach Nematodes (Mastophorus Muris) in Rats (Rattus Rattus) are Associated with Coconut (Cocos Nucifera) Habitat at Palmyra Atoll.” Journal of Parasitology 96 (1): 16–20. doi:10.1645/GE-2180.1.
   PubMed Web of Science ®Google Scholar
• Le Louarn, M., P. Clergeau, E. Briche, and M. Deschamps-Cottin. 2017. “‘Kill Two Birds with One Stone’: Urban Tree Species Classification Using Bi-Temporal Pléiades Images to Study Nesting Preferences of an Invasive Bird.” Remote Sensing 9 (9): 916. doi:10.3390/rs9090916.
   Web of Science ®Google Scholar
• Lee, J. S. H., S. Wich, A. Widayati, and L. P. Koh. 2016. “Detecting Industrial Oil Palm Plantations on Landsat Images with Google Earth Engine.” Remote Sensing Applications: Society and Environment 4: 219–224. doi:10.1016/j.rsase.2016.11.003.
   Google Scholar
• Lelong, C. C. D., C. D. J. Lesponne, N. Lamanda, G. Lainé, and E. Malézieux. 2004. “Understanding the Spatial Structure of Agroforestry Systems Using Very High Resolution Remote Sensing: An Application to Coconut-Based Systems in Melanesia.” In 1st World Congress of Agroforestry: Working Together for Sustainable Land Use Systems, edited by P. K. R. Nair, 191. Gainesville, FL: University of Florida.
   Google Scholar
• Li, H., L. Jing, and Y. Tang. 2017. “Assessment of Pansharpening Methods Applied to WorldView-2 Imagery Fusion.” Sensors 17 (1): 89. doi:10.3390/s17010089.
   PubMed Web of Science ®Google Scholar
• Li, W., H. Fu, L. Yu, and A. Cracknell. 2016. “Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images.” Remote Sensing 9 (1): 22. doi:10.3390/rs9010022.
   Web of Science ®Google Scholar
• Liaw, A., and M. Wiener. 2002. “Classification and Regression by RandomForest.” R News 2: 18–22.
   Google Scholar
• Liu, D., and F. Xia. 2010. “Assessing Object-Based Classification: Advantages and Limitations.” Remote Sensing Letters 1 (4): 187–194. doi:10.1080/01431161003743173.
   Web of Science ®Google Scholar
• Ma, L., M. Li, X. Ma, L. Cheng, P. Du, and Y. Liu. 2017. “A Review of Supervised Object-Based Land-Cover Image Classification.” ISPRS Journal of Photogrammetry and Remote Sensing 130: 277–293. doi:10.1016/j.isprsjprs.2017.06.001.
   Web of Science ®Google Scholar
• Marceau, D. J., P. J. Howarth, J. M. Dubois, and D. J. Gratton. 1990. “Evaluation Of The Grey-Level Co-Occurrence Matrix Method For Land-Cover Classification Using Spot Imagery.” IEEE Transactions on Geoscience and Remote Sensing 28 (4): 513–519. doi:10.1109/TGRS.1990.572937.
   Web of Science ®Google Scholar
• McCauley, D. J., P. A. DeSalles, H. S. Young, R. B. Dunbar, R. Dirzo, M. M. Mills, and F. Micheli. 2012. “From Wing to Wing: The Persistence of Long Ecological Interaction Chains in Less-Disturbed Ecosystems.” Scientific Reports 2: 409. doi:10.1038/srep00409.
   PubMed Web of Science ®Google Scholar
• Millard, K., and M. Richardson. 2015. “On the Importance of Training Data Sample Selection in Random Forest Image Classification: A Case Study in Peatland Ecosystem Mapping.” Remote Sensing 7 (7): 8489–8515. doi:10.3390/rs70708489.
   Web of Science ®Google Scholar
• Mueller-Dombois, D., and F. R. Fosberg. 1998. “Vegetation of the Tropical Pacific Islands.” In Ecological Studies, edited by M. M. Caldwell, G. Heldmaier, O. L. Lange, H. A. Mooney, E.-D. Schulze, and U. Sommer, 132. New York, NY: Springer. doi:10.1007/978-1-4419-8686-3.
   Google Scholar
• Murray, H., A. Lucieer, and R. Williams. 2010. “Texture-Based Classification of Sub-Antarctic Vegetation Communities on Heard Island.” International Journal of Applied Earth Observation and Geoinformation 12 (3): 138–149. doi:10.1016/j.jag.2010.01.006.
   Web of Science ®Google Scholar
• Myint, S. W., N. S.-N. Lam, and J. M. Tyler. 2004. “Wavelets for Urban Spatial Feature Discrimination: Comparisons with Fractal, Spatial Autocorrelation, and Spatial Co-Occurrence Approaches.” Photogrammetric Engineering and Remote Sensing 70 (7): 803–812. doi:10.14358/PERS.70.7.803.
   Web of Science ®Google Scholar
• Ozdemir, I., and A. Karnieli. 2011. “Predicting Forest Structural Parameters Using the Image Texture Derived from Worldview-2 Multispectral Imagery in a Dryland Forest, Israel.” International Journal of Applied Earth Observation and Geoinformation 13 (5): 701–710. doi:10.1016/j.jag.2011.05.006.
   Web of Science ®Google Scholar
• Pacifici, F. 2016. “Validation of the DigitalGlobe Surface Reflectance Product.” In International Geoscience and Remote Sensing Symposium (IGARSS) 2016, 1973–1975. Beijing, China: IEEE. doi:10.1109/IGARSS.2016.7729508.
   Google Scholar
• Pacifici, F., M. Chini, and W. J. Emery. 2009. “A Neural Network Approach Using Multi-Scale Textural Metrics from Very High-Resolution Panchromatic Imagery for Urban Land-Use Classification.” Remote Sensing of Environment 113 (6): 1276–1292. doi:10.1016/j.rse.2009.02.014.
   Web of Science ®Google Scholar
• Pal, M. 2005. “Random Forest Classifier for Remote Sensing Classification.” International Journal of Remote Sensing 26 (1): 217–222. doi:10.1080/01431160412331269698.
   Web of Science ®Google Scholar
• Pal, M., and P. M. Mather. 2003. “An Assessment of the Effectiveness of Decision Tree Methods for Land Cover Classification.” Remote Sensing of Environment 86 (4): 554–565. doi:10.1016/S0034-4257(03)00132-9.
   Web of Science ®Google Scholar
• Pratomo, J., M. Kuffer, J. Martinez, and D. Kohli. 2017. “Coupling Uncertainties with Accuracy Assessment in Object-Based Slum Detections, Case Study: Jakarta, Indonesia.” Remote Sensing 9 (11): 1164. doi:10.3390/rs9111164.
   Web of Science ®Google Scholar
• Puissant, A., J. Hirscha, and C. Webera. 2005. “The Utility of Texture Analysis to Improve Per-Pixel Classification for High to Very High Spatial Resolution Imagery.” International Journal of Remote Sensing 26 (4): 733–745. doi:10.1080/01431160512331316838.
   Web of Science ®Google Scholar
• QGIS Development Team. 2009. “QGIS Geographic Information System.” Open Source Geospatial Foundation (OSGEO). http://qgis.osgeo.org
   Google Scholar
• R Core Team. 2016. “R: A Language and Environment for Statistical Computing.” Vienna, Austria: R Foundation for Statistical Computing. https://www.r-project.org/
   Google Scholar
• Rejmánek, M., and D. M. Richardson. 2013. “Trees and Shrubs as Invasive Alien Species - 2013 Update of the Global Database.” Diversity and Distributions 19 (8): 1093–1094. doi:10.1111/ddi.12075.
   Web of Science ®Google Scholar
• Rock, J. F. 1916. “Palmyra Island with a Description of Its Flora.” College of Hawaii Publications: Bulletin 4: 1–53.
   Google Scholar
• Rodriguez-Galiano, V. F., M. Chica-Olmo, F. Abarca-Hernandez, P. M. Atkinson, and C. Jeganathan. 2012a. “Random Forest Classification of Mediterranean Land Cover Using Multi-Seasonal Imagery and Multi-Seasonal Texture.” Remote Sensing of Environment 121: 93–107. doi:10.1016/j.rse.2011.12.003.
   Web of Science ®Google Scholar
• Rodriguez-Galiano, V. F., B. Ghimire, J. Rogan, M. Chica-Olmo, and J. P. Rigol-Sanchez. 2012b. “An Assessment of the Effectiveness of a Random Forest Classifier for Land-Cover Classification.” ISPRS Journal of Photogrammetry and Remote Sensing 67 (1): 93–104. doi:10.1016/j.isprsjprs.2011.11.002.
   Web of Science ®Google Scholar
• Seddon, A. W. R., M. Macias-Fauria, P. R. Long, D. Benz, and K. J. Willis. 2016. “Sensitivity of Global Terrestrial Ecosystems to Climate Variability.” Nature 531 (7593): 229–232. doi:10.1038/nature16986.
   PubMed Web of Science ®Google Scholar
• Shiraishi, T., T. Motohka, R. B. Thapa, M. Watanabe, and M. Shimada. 2014. “Comparative Assessment of Supervised Classifiers for Land Use-Land Cover Classification in a Tropical Region Using Time-Series PALSAR Mosaic Data.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7 (4): 1186–1199. doi:10.1109/jstars.2014.2313572.
   Web of Science ®Google Scholar
• Smith, M. J. 2015. “A Comparison of DG AComp, FLAASH and QUAC Atmospheric Compensation Algorithms Using WorldView-2 Imagery.” M.S. diss., University of Colorado.
   Google Scholar
• Song, C., C. E. Woodcock, K. C. Seto, M. P. Lenney, and S. A. Macomber. 2001. “Classification and Change Detection Using Landsat TM Data: When and How to Correct Atmospheric Effects?” Remote Sensing of Environment 75 (2): 230–244. doi:10.1016/S0034-4257(00)00169-3.
   Web of Science ®Google Scholar
• Srestasathiern, P., and P. Rakwatin. 2014. “Oil Palm Tree Detection with High Resolution Multi-Spectral Satellite Imagery.” Remote Sensing 6 (10): 9749–9774. doi:10.3390/rs6109749.
   Web of Science ®Google Scholar
• Stehman, S. V. 2009. “Sampling Designs for Accuracy Assessment of Land Cover.” International Journal of Remote Sensing 30 (20): 5243–5272. doi:10.1080/01431160903131000.
   Web of Science ®Google Scholar
• Thenkabail, P. S., N. Stucky, B. W. Griscom, M. S. Ashton, J. Diels, B. Van der Meer, and E. Enclona. 2004. “Biomass Estimations and Carbon Stock Calculations in the Oil Palm Plantations of African Derived Savannas Using IKONOS Data.” International Journal of Remote Sensing 10 (23): 5447–5472. doi:10.1080/01431160412331291279.
   Web of Science ®Google Scholar
• Vergara, N. T., and P. K. R. Nair. 1985. “Agroforestry in the South Pacific Region — An Overview.” Agroforestry Systems 3 (4): 363–379. doi:10.1007/bf00055718.
   Google Scholar
• Walker, T. A. 1991. “Pisonia Islands of the Great Barrier Reef. Part I. The Distribution, Abundance and Dispersal by Seabirds of Pisonia Grandis.” Atoll Research Bulletin 348–354 (350): 1–23. doi:10.5479/si.00775630.350-1.1.
   Google Scholar
• Wang, T., H. Zhang, H. Lin, and C. Fang. 2016. “Textural-Spectral Feature-Based Species Classification of Mangroves in Mai Po Nature Reserve from Worldview-3 Imagery.” Remote Sensing 8 (1): 24. doi:10.3390/rs8010024.
   Web of Science ®Google Scholar
• Wegmann, A. S. 2005. Palmyra Atoll National Wildlife Refuge Forest Type Map. Honolulu, HI: U.S. Fish and Wildlife Service.
   Google Scholar
• Wegmann, A. S. 2009. “Limitations to Tree Seedling Recruitment at Palmyra Atoll.” PhD diss., University of Hawaiʻi at Manoa.
   Google Scholar
• Wester, L. 1985. “Checklist of the Vascular Plants of the Northern Line Islands.” Atoll Research Bulletin 287: 1–38. doi:10.5479/si.00775630.287.1.
   Google Scholar
• Young, H. S., D. J. McCauley, A. Pollock, and R. Dirzo. 2014. “Differential Plant Damage Due to Litterfall in Palm-Dominated Forest Stands in a Central Pacific Atoll.” Journal of Tropical Ecology 30 (3): 231–236. doi:10.1017/S026646741400008X.
   Web of Science ®Google Scholar
• Young, H. S., A. Miller-Ter Kuile, D. J. McCauley, and R. Dirzo. 2017. “Cascading Community and Ecosystem Consequences of Introduced Coconut Palms (Cocos Nucifera) in Tropical Islands.” Canadian Journal of Zoology 95 (3): 139–148. doi:10.1139/cjz-2016-0107.
   Web of Science ®Google Scholar
• Young, H. S., T. K. Raab, D. J. McCauley, A. A. Briggs, and R. Dirzo. 2010. “The Coconut Palm, Cocos Nucifera, Impacts Forest Composition and Soil Characteristics at Palmyra Atoll, Central Pacific.” Journal of Vegetation Science 21 (6): 1058–1068. doi:10.1111/j.1654-1103.2010.01219.x.
   Web of Science ®Google Scholar
• Yu, Q., P. Gong, N. Clinton, G. Biging, M. Kelly, and D. Schirokauer. 2006. “Object-Based Detailed Vegetation Classification with Airborne High Spatial Resolution Remote Sensing Imagery.” Photogrammetric Engineering and Remote Sensing 72 (7): 799–811. doi:10.14358/pers.72.7.799.
   Web of Science ®Google Scholar
• Zhen, Z., L. J. Quackenbush, S. V. Stehman, and L. Zhang. 2013. “Impact of Training and Validation Sample Selection on Classification Accuracy and Accuracy Assessment When Using Reference Polygons in Object-Based Classification.” International Journal of Remote Sensing 34 (19): 6914–6930. doi:10.1080/01431161.2013.810822.
   Web of Science ®Google Scholar
• Zvoleff, A. 2016. “Glcm: Calculate Textures from Grey-Level Co-Occurrence Matrices (Glcms).” R Package Version 1.6.1.. https://cran.r-project.org/package=glcm
   Google Scholar