A review of remote sensing applications for oil palm studies

References

• Askne, J. I. H., J. E. S. Fransson, M. Santoro, M. J. Soja, and L. M. H. Ulander. 2013. “Model-based Biomass Estimation of a Hemi-boreal Forest from Multitemporal TanDEM-X Acquisitions.” Remote Sensing 5 (11): 5574–5597.10.3390/rs5115574
   Web of Science ®Google Scholar
• Awal, M. A., W. Ishak, J. Endan, and M. Haniff. 2004. “Determination of Specific Leaf Area and Leaf Area-leaf Mass Relationship in Oil Palm Plantation.” Asian Journal of Plant Sciences 3 (3): 264–268.
   Google Scholar
• Aziz, N. A., W. Omar, R. Kassim, and N. Kamarudin. 2012. “Remote Sensing Measurement for Detection of Bagworm Infestation in Oil Palm Plantation.” MPOB Information Series 589. ISSN: . http://palmoilis.mpob.gov.my/publications/TOT/TT-502.pdf
   Google Scholar
• Balasundram, S. K., H. Memarian, and R. Khosla. 2013. “Estimating Oil Palm Yields Using Vegetation Indices Derived from QuickBird.” Life Science Journal 10 (4): 851–860.
   Google Scholar
• Basiron, Y. 2007. “Palm Oil Production through Sustainable Plantations.” European Journal of Lipid Science and Technology 109 (4): 289–295. doi:10.1002/ejlt.200600223.
   Web of Science ®Google Scholar
• Blaschke, T. 2010. “Object Based Image Analysis for Remote Sensing.” ISPRS Journal of Photogrammetry and Remote Sensing 65 (1): 2–16. doi:10.1016/j.isprsjprs.2009.06.004.
   Web of Science ®Google Scholar
• BPS. 2014. Statistik Kelapa Sawit Indonesia 2014. Jakarta: Badan Pusat Statistik.
   Google Scholar
• Breda, N. J. J. 2003. “Ground-based Measurements of Leaf Area Index: A Review of Methods, Instruments and Current Controversies.” Journal of Experimental Botany 54 (392): 2403–2417. doi:10.1093/jxb/erg263.
   PubMed Web of Science ®Google Scholar
• Breure, C. J. 2010. “Rate of Leaf Expansion: A Criterion for Identifying Oil Palm (Elaeis Guineensis Jacq.) Types Suitable for Planting at High Densities.” NJAS – Wageningen Journal of Life Sciences 57 (2): 141–147. doi:10.1016/j.njas.2010.03.001.
   Web of Science ®Google Scholar
• Brown, S. 1997. Estimating Biomass and Biomass Change of Tropical Forests: A Primer. Vol. 134. Rome: Food and Agriculture Organization.
   Google Scholar
• Buchanan, G. M., S. H. M. Butchart, G. Dutson, J. D. Pilgrim, M. K. Steininger, K. D. Bishop, and P. Mayaux. 2008. “Using Remote Sensing to Inform Conservation Status Assessment: Estimates of Recent Deforestation Rates on New Britain and the Impacts upon Endemic Birds.” Biological Conservation 141 (1): 56–66.10.1016/j.biocon.2007.08.023
   Web of Science ®Google Scholar
• Cartus, O., M. Santoro, and J. Kellndorfer. 2012. “Mapping Forest Aboveground Biomass in the Northeastern United States with ALOS PALSAR Dual-Polarization L-Band.” Remote Sensing of Environment 124: 466–478. doi:10.1016/j.rse.2012.05.029.
   Web of Science ®Google Scholar
• Chapin III, F. S., P. A. Matson, and P. Vitousek. 2011. Principles of Terrestrial Ecosystem Ecology. New York: Springer Science & Business Media.10.1007/978-1-4419-9504-9
   Google Scholar
• Chemura, A., I. van Duren, and L. M. van Leeuwen. 2015. “Determination of the Age of Oil Palm from Crown Projection Area Detected from WorldView-2 Multispectral Remote Sensing Data: The Case of Ejisu-Juaben District, Ghana.” ISPRS Journal of Photogrammetry and Remote Sensing 100: 118–127. doi:10.1016/j.isprsjprs.2014.07.013.
   Web of Science ®Google Scholar
• Cheng, Y., L. Yu, A. P. Cracknell, and P. Gong. 2016. “Oil Palm Mapping Using Landsat and PALSAR: A Case Study in Malaysia.” International Journal of Remote Sensing 37 (22): 5431–5442. doi:10.1080/01431161.2016.1241448.
   Web of Science ®Google Scholar
• Corley, R. H. V. 1973. “Effects of Plant Density on Growth and Yield of Oil Palm.” Experimental Agriculture 9 (2): 169–180.10.1017/S0014479700005639
   Web of Science ®Google Scholar
• Corley, R. H. V. 2009. “How Much Palm Oil Do We Need?” Environmental Science & Policy 12 (2): 134–139. doi:10.1016/j.envsci.2008.10.011.
   Web of Science ®Google Scholar
• Corley, R. H. V., and P. B. H. Tinker. 2008. The Oil Palm. John Wiley & Sons.
   Google Scholar
• Cracknell, A. P., K. D. Kanniah, K. P. Tan, and L. Wang. 2015. “Towards the Development of a Regional Version of MOD17 for the Determination of Gross and Net Primary Productivity of Oil Palm Trees.” International Journal of Remote Sensing 36 (1): 262–289. doi:10.1080/01431161.2014.995278.
   Web of Science ®Google Scholar
• Daliman, S., S. A. Rahman, S. A. Bakar, and I. Busu. 2014. “Segmentation of Oil Palm Area Based on GLCMSVM and NDVI.” IEEE TENSYMP 2014 – 2014 IEEE Region 10 Symposium.
   Google Scholar
• Dong, X., Q. Shaun, U. Yumiko, H. Cheng, and Z. Tao. 2015. “Feasibility Study of C- and L-Band SAR Time Series Data in Tracking Indonesian Plantation and Natural Forest Cover Changes.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8 (7): 3692–3699. doi:10.1109/JSTARS.2015.2400439.
   Web of Science ®Google Scholar
• Englhart, S., V. Keuck, and F. Siegert. 2011. “Aboveground Biomass Retrieval in Tropical Forests − The Potential of Combined X- and L-Band SAR Data Use.” Remote Sensing of Environment 115 (5): 1260–1271. doi:10.1016/j.rse.2011.01.008.
   Web of Science ®Google Scholar
• Fadaei, H., R. Ishii, R. Suzuki, and J. J. Kendawang. 2013. “Detection of Oil Palm and Acacia Plantation Areas Using Object Based Classification in Sarawak, Malaysia.” 34th Asian Conference on Remote Sensing 2013, ACRS 2013, October 2013.
   Google Scholar
• Fitzherbert, E. B., M. J. Struebig, A. C. Morel, F. Danielsen, C. A. Bruhl, P. F. Donald, and B. Phalan. 2008. “How will Oil Palm Expansion Affect Biodiversity?” Trends in Ecology & Evolution 23 (10): 538–545. doi:10.1016/j.tree.2008.06.012.
   PubMed Web of Science ®Google Scholar
• Foody, G. M., M. E. Cutler, J. McMorrow, D. Pelz, H. Tangki, D. S. Boyd, and I. Douglas. 2001. “Mapping the Biomass of Bornean Tropical Rain Forest from Remotely Sensed Data.” Global Ecology and Biogeography 10 (4): 379–387. doi:10.1046/j.1466-822X.2001.00248.x.
   Web of Science ®Google Scholar
• Hansen, S. B., R. Padfield, K. Syayuti, S. Evers, Z. Zakariah, and S. Mastura. 2015. “Trends in Global Palm Oil Sustainability Research.” Journal of Cleaner Production 100: 140–149. doi:10.1016/j.jclepro.2015.03.051.
   Web of Science ®Google Scholar
• Hartley, C. W. S. 1967. The Oil Palm. London: Longmans, Green.
   Google Scholar
• Henson, I. E., and K. C. Chang. 2003. “Oil Palm Plantations and Forest Loss: An Objective Appraisal.” Proceedings of the PIPOC 2003 International Palm Oil Congress. 960–974.
   Google Scholar
• Hoffmann, C., C. Weise, T. Koch, and K. Pauly. 2016. “From UAS Data Acquisition to Actionable Information – How an End-to-End Solution Helps Oil Palm Plantation Operators to Perform a More Sustainable Plantation Management.” ISPRS – International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1:1113–1120.10.5194/isprsarchives-XLI-B1-1113-2016
   Google Scholar
• Ibharim, N. A., M. A. Mustapha, T. Lihan, and A. G. Mazlan. 2015. “Mapping Mangrove Changes in the Matang Mangrove Forest Using Multi Temporal Satellite Imageries.” Ocean & Coastal Management 114: 64–76. doi:10.1016/j.ocecoaman.2015.06.005.
   Web of Science ®Google Scholar
• Ismail, A., and M. N. Mamat. 2002. “The Optimal Age of Oil Palm Replanting.” Oil Palm Industry Economic Journal 2 (1): 11–18.
   Google Scholar
• Jansen, L. J. M., and A. D. Gregorio. 2002. “Parametric Land Cover and Land-use Classifications as Tools for Environmental Change Detection.” Agriculture, Ecosystems & Environment 91 (1-3): 89–100. doi:10.1016/S0167-8809(01)00243-2.
   Web of Science ®Google Scholar
• JAXA/METI. 2010. ALOS PALSAR Imagery.
   Google Scholar
• Jebur, M. N., H. Z. M. Shafri, B. Pradhan, and M. S. Tehrany. 2014. “Per-pixel and Object-oriented Classification Methods for Mapping Urban Land Cover Extraction Using SPOT 5 Imagery.” Geocarto International 29 (7): 792–806.10.1080/10106049.2013.848944
   Web of Science ®Google Scholar
• Jennings, S., R. Nussbaum, N. Judd, T. Evans, T. Iacobelli, J. Jarvie, A. Lindhe, T. Synnott, C. Vallejos, and A. Yaroshenko. 2003. The High Conservation Value Forest Toolkit. Oxford: Proforest.
   Google Scholar
• Kang, C. S., K. D. Kanniah, Y. H. Kerr, and A. P. Cracknell. 2016. “Analysis of in situ Soil Moisture Data and Validation of SMOS Soil Moisture Products at Selected Agricultural Sites over a Tropical Region.” International Journal of Remote Sensing 37 (16): 3636–3654. doi:10.1080/01431161.2016.1201229.
   Web of Science ®Google Scholar
• Kanniah, K. D., K. P. Tan, and A. P. Cracknel. 2012. “UK-DMC 2 Satellite Data for Deriving Biophysical Parameters of Oil Palm Trees in Malaysia.” International Geoscience and Remote Sensing Symposium (IGARSS).
   Google Scholar
• Khalid, H., Z. Z. Zin, and J. M. Anderson. 1999. “Quantification of Oil Palm Biomass and Nutrient Value in a Mature Plantation. I. Above-ground Biomass.” Journal of Oil Palm Research 11 (1): 23–32.
   Google Scholar
• Khamiz, A., Z. Ismail, and A. T. Muhammad. 2005. “Nonlinear Growth Models for Modeling Oil Palm Yield Growth.” Journal of Mathematics and Statistics 1 (3): 225–233.10.3844/jmssp.2005.225.233
   Google Scholar
• Kho, L. K., and M. R. Jepsen. 2015. “Carbon Stock of Oil Palm Plantations and Tropical Forests in Malaysia: A Review.” Singapore Journal of Tropical Geography 36 (2): 249–266. doi:10.1111/sjtg.12100.
   Web of Science ®Google Scholar
• Koh, L. P., and D. S. Wilcove. 2008. “Is Oil Palm Agriculture Really Destroying Tropical Biodiversity?” Conservation Letters 1 (2): 60–64. doi:10.1111/j.1755-263X.2008.00011.x.
   Web of Science ®Google Scholar
• Koo, V. C., Y. K. Chan, V. Gobi, M. Y. Chua, C. H. Lim, C. S. Lim, C. C. Thum, et al. 2012. “A New Unmanned Aerial Vehicle Synthetic Aperture Radar for Environmental Monitoring.” Progress in Electromagnetics Research 122: 245–268.10.2528/PIER11092604
   Web of Science ®Google Scholar
• Lamade, E., and J.-P. Bouillet. 2005. “Carbon Storage and Global Change: The Role of Oil Palm.” Oléagineux, Corps Gras, Lipides 12 (2): 154–160.10.1051/ocl.2005.0154
   Google Scholar
• Lee, K. Y., and T. R. Bretschneider. 2010. “Segmentation of Dual-frequency Polarimetric Sar Data for an Improved Land Cover Classification.” 31st Asian Conference on Remote Sensing 2010, ACRS 2010, Hanoi.
   Google Scholar
• Li, L., J. Dong, S. N. Tenku, and X. Xiao. 2015. “Mapping Oil Palm Plantations in Cameroon Using PALSAR 50-M Orthorectified Mosaic Images.” Remote Sensing 7 (2): 1206–1224. doi:10.3390/rs70201206.
   Web of Science ®Google Scholar
• Liaghat, S., and S. K. Balasundram. 2010. “A Review: The Role of Remote Sensing in Precision Agriculture.” American Journal of Agricultural and Biological Sciences 5 (1): 50–55.10.3844/ajabssp.2010.50.55
   Google Scholar
• Liaghat, S., R. Ehsani, S. A. Mansor, H. Z. M. Shafri, S. Meon, S. Sankaran, and S. H. M. N. Azam. 2014. “Early Detection of Basal Stem Rot Disease (Ganoderma) in Oil Palms Based on Hyperspectral Reflectance Data Using Pattern Recognition Algorithms.” International Journal of Remote Sensing 35 (10): 3427–3439. doi:10.1080/01431161.2014.903353.
   Web of Science ®Google Scholar
• McMorrow, J. 2001. “Linear Regression Modelling for the Estimation of Oil Palm Age from Landsat TM.” International Journal of Remote Sensing 22 (12): 2243–2264. doi:10.1080/01431160117188.
   Web of Science ®Google Scholar
• Miettinen, J., S. C. Liew, and L. K. Kwoh. 2015. “Usability of Sentinel-1 Dual Polarization C-Band Data for Plantation Detection in Insular Southeast Asia.” ACRS 2015 − 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, Proceedings.
   Google Scholar
• Morel, A. C., J. B. Fisher, and Y. Malhi. 2012. “Evaluating the Potential to Monitor Aboveground Biomass in Forest and Oil Palm in Sabah, Malaysia, for 2000–2008 with Landsat ETM+ and ALOS-PALSAR.” International Journal of Remote Sensing 33 (11): 3614–3639. doi:10.1080/01431161.2011.631949.
   Web of Science ®Google Scholar
• Morel, A. C., S. S. Saatchi, Y. Malhi, N. J. Berry, L. Banin, D. Burslem, R. Nilus, and R. C. Ong. 2011. “Estimating Aboveground Biomass in Forest and Oil Palm Plantation in Sabah, Malaysian Borneo Using ALOS PALSAR Data.” Forest Ecology and Management 262 (9): 1786–1798. doi:10.1016/j.foreco.2011.07.008.
   Web of Science ®Google Scholar
• MPOC. 2014. “Palm Oil Fact Slides.” Malaysian Palm Oil Council. last modified 10 September 2015. Accessed January 13, 2017. http://www.mpoc.org.my/Palm_Oil_Fact_Slides.aspx
   Google Scholar
• Naert, B., R. Gal, A. U. Lubis, and J. Olivin. 1990. “A Preliminary Assessment of the Possibilities of Using Spatial Remote Sensing to Study Developments on an Oil Palm Plantation in North Sumatra.” Oléagineux (Paris) 45 (5): 201–214.
   Google Scholar
• Nooni, I. K., A. A. Duker, I. Van Duren, L. Addae-Wireko, and E. M. Osei Jr. 2014. “Support Vector Machine to Map Oil Palm in a Heterogeneous Environment.” International Journal of Remote Sensing 35 (13): 4778–4794.10.1080/01431161.2014.930201
   Web of Science ®Google Scholar
• Nordin, L. 1996. Application of AIRSAR Data to Oil Palm Tree Characterization. Kuala Lumpur: Malaysian Centre for Remote Sensing.
   Google Scholar
• Othman, H., A. T. Mohammed, F. M. Darus, M. H. Harun, and M. P. Zambri. 2011. “Best Management Practices for Oil Palm Cultivation on Peat: Ground Water-table Maintenance in Relation to Peat Subsidence and Estimation of CO2 Emissions at Sessang, Sarawak.” Journal of Oil Palm Research 23: 1078–1086.
   Web of Science ®Google Scholar
• Pittman, A. M., K. Carlson, L. M. Curran, and A. Ponette-Gonzalez. 2013. “NASA Satellite Data Used to Study the Impact of Oil Palm Expansion across Indonesian Borneo.” The Earth Observer 25 (5): 12–15.
   Google Scholar
• Pohl, C., K. L. Chong, and J. van Genderen. 2015. “Multisensor Approach to Oil Palm Plantation Monitoring Using Data Fusion and GIS.” In 36th Asian Conference on Remote Sensing ‘Fostering Resiient Growth in Asia’, Manila, Philippines.
   Google Scholar
• Quinones, M. J., and D. H. Hoekman. 2004. “Exploration of Factors Limiting Biomass Estimation by Polarimetric Radar in Tropical Forests.” IEEE Transactions on Geoscience and Remote Sensing 42 (1): 86–104. doi:10.1109/TGRS.2003.815402.
   Web of Science ®Google Scholar
• Razali, S., A. Marin, A. Nuruddin, H. Z. M. Shafri, and H. Hamid. 2014. “Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions.” Sensors 14 (5): 8259–8282.10.3390/s140508259
   PubMed Web of Science ®Google Scholar
• Razi, M. K. M., M. H. Ismail, and H. Z. M. Shafri. 2013. “Fusion Technique of LiDAR and Airphoto Imagery for Oil Palm Classification.” 34th Asian Conference on Remote Sensing 2013, ACRS 2013, Bali.
   Google Scholar
• RSPO. 2007. RSPO Principles and Criteria for Sustainable Palm Oil Production. Kuala Lumpur: Roundtable on Sustainable Palm Oil.
   Google Scholar
• Santos, C., and J. P. Messina. 2008. “Multi-sensor Data Fusion for Modeling African Palm in the Ecuadorian Amazon.” Photogrammetric Engineering & Remote Sensing 74 (6): 711–723. doi:10.14358/PERS.74.6.711.
   Web of Science ®Google Scholar
• Santoso, H., T. Gunawan, R. H. Jatmiko, W. Darmosarkoro, and B. Minasny. 2011. “Mapping and Identifying Basal Stem Rot Disease in Oil Palms in North Sumatra with QuickBird Imagery.” Precision Agriculture 12 (2): 233–248.10.1007/s11119-010-9172-7
   Web of Science ®Google Scholar
• Santoso, H., H. Tani, and X. Wang. 2016. “A Simple Method for Detection and Counting of Oil Palm Trees Using High-resolution Multispectral Satellite Imagery.” International Journal of Remote Sensing 37 (21): 5122–5134. doi:10.1080/01431161.2016.1226527.
   Web of Science ®Google Scholar
• Shafri, H. Z. M., M. I. Anuar, I. A. Seman, and N. M. Noor. 2011. “Spectral Discrimination of Healthy and Ganoderma-infected Oil Palms from Hyperspectral Data.” International Journal of Remote Sensing 32 (22): 7111–7129. doi:10.1080/01431161.2010.519003.
   Web of Science ®Google Scholar
• Shafri, H. Z. M., N. Hamdan, and M. I. Saripan. 2011. “Semi-automatic Detection and Counting of Oil Palm Trees from High Spatial Resolution Airborne Imagery.” International Journal of Remote Sensing 32 (8): 2095–2115. doi:10.1080/01431161003662928.
   Web of Science ®Google Scholar
• Shafri, H. Z. M., and N. Hamdan. 2009. “Hyperspectral Imagery for Mapping Disease Infection in Oil Palm Plantation Using Vegetation Indices and Red Edge Techniques.” American Journal of Applied Sciences 6 (6): 1031–1035.
   Google Scholar
• Shafri, H. Z. M., M. H. Ismail, M. K. M. Razi, M. I. Anuar, and A. R. Ahmad. 2012. “Application of LiDAR and Optical Data for Oil Palm Plantation Management in Malaysia.” Lidar Remote Sensing for Environmental Monitoring XIII 852608, Kyoto, Japan, November 19. doi: 10.1117/12.979631.
   Google Scholar
• Shashikant, V., A. R. M. Shariff, L. Nordin, and B. Pradhan. 2012. “Estimation of above Ground Biomass of Oil Palm Trees by PALSAR.” Humanities, Science and Engineering (CHUSER), 2012 IEEE Colloquium, Kota Kinabalu, Malaysia, December 3–4. doi: 10.1109/CHUSER.2012.6504430.
   Google Scholar
• Shen, H., P. Wu, Y. Liu, T. Ai, Y. Wang, and X. Liu. 2013. “A Spatial and Temporal Reflectance Fusion Model Considering Sensor Observation Differences.” International Journal of Remote Sensing 34 (12): 4367–4383. doi:10.1080/01431161.2013.777488.
   Web of Science ®Google Scholar
• Sim, C. K., K. Abdullah, M. Z. M. Jafri, and H. S. Lim. 2013. “Combination of Radar and Optical Remote Sensing Data for Land Cover/Use Mapping.” International Conference on Space Science and Communication, IconSpace. Melaka, Malaysia, July 1–3. doi: 10.1109/IconSpace.2013.6599469
   Google Scholar
• Singh, G., A. Darus, and J. Sukaimi. 1991. “Ganoderma – the Scourge of Oil Palm in the Coastal Area.” Proceedings of Ganoderma Workshop, Bangi, Selangor, Malaysia, September 11, 7–35.
   Google Scholar
• Singh, M., Y. Malhi, and S. Bhagwat. 2014a. “Biomass Estimation of Mixed Forest Landscape Using a Fourier Transform Texture-based Approach on Very-high-resolution Optical Satellite Imagery.” International Journal of Remote Sensing 35 (9): 3331–3349. doi:10.1080/01431161.2014.903441.
   Web of Science ®Google Scholar
• Singh, M., Y. Malhi, and S. Bhagwat. 2014b. “Evaluating Land Use and Aboveground Biomass Dynamics in an Oil Palm-dominated Landscape in Borneo Using Optical Remote Sensing.” Journal of Applied Remote Sensing 8 (1): 083695. doi:10.1117/1.JRS.8.083695.
   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
• Sunaryathy, P. I., S. Suhasman, K. D. Kanniah, and K. P. Tan. 2015. “Estimating Aboveground Biomass of Oil Palm Trees by Using the Destructive Method.” World Journal of Agricultural Research 3 (1): 17–19. doi:10.12691/wjar-3-1-4.
   Google Scholar
• Tan, K. T., K. T. Lee, A. R. Mohamed, and S. Bhatia. 2009. “Palm Oil: Addressing Issues and towards Sustainable Development.” Renewable and Sustainable Energy Reviews 13 (2): 420–427. doi:10.1016/j.rser.2007.10.001.
   Web of Science ®Google Scholar
• Tan, K. P., K. D. Kanniah, and A. P. Cracknell. 2012. “A Review of Remote Sensing Based Productivity Models and Their Suitability for Studying Oil Palm Productivity in Tropical Regions.” Progress in Physical Geography 36 (5): 655–679.10.1177/0309133312452187
   Web of Science ®Google Scholar
• Tan, K. P., K. D. Kanniah, and A. P. Cracknell. 2013. “Use of UK-DMC 2 and ALOS PALSAR for Studying the Age of Oil Palm Trees in Southern Peninsular Malaysia.” International Journal of Remote Sensing 34 (20): 7424–7446. doi:10.1080/01431161.2013.822601.
   Web of Science ®Google Scholar
• Tan, K. P., K. D. Kanniah, and A. P. Cracknell. 2014. “On the Upstream Inputs into the MODIS Primary Productivity Products Using Biometric Data from Oil Palm Plantations.” International Journal of Remote Sensing 35 (6): 2215–2246.
   Web of Science ®Google Scholar
• Teng, K. C., J. Y. Koay, S. H. Tey, K. S. Lim, H. T. Ewe, and H. T. Chuah. 2014. “A Dense Medium Microwave Backscattering Model for the Remote Sensing of Oil Palm.” IEEE Transactions on Geoscience and Remote Sensing 53 (6): 3250–3259. doi: 10.1109/TGRS.2014.2372796
   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 25 (23): 5447–5472. doi:10.1080/01431160412331291279.
   Web of Science ®Google Scholar
• UNEP. 2011. “Oil Palm Plantations: Threats and Opportunities for Tropical Ecosystems.” United Nations Environment Programme (UNEP), Global Environmental Alert Service (GEAS).
   Google Scholar
• USGS. 2010. Landsat 8 Imagery. Data available from U.S. Geological Survey. Accessed September 27 2010. https://lpdaac.usgs.gov/
   Google Scholar
• Watson, D. J. 1947. “Comparative Physiological Studies on the Growth of Field Crops: I. Variation in Net Assimilation Rate and Leaf Area between Species and Varieties, and within and between Years.” Annals of Botany 11 (1): 41–76. doi:10.2307/42907002.
   Google Scholar
• Wielaard, N. 2011. Impact of Oil Palm Plantations on Peatland Conversion in Sarawak 2005–2010, edited by Summary Report: SarVision.
   Google Scholar
• Wong-in, T., T. Kaewkongka, N. Cooharojananone, and R. Lipikorn. 2015. “Automatic Oil Palm Detection and Identification from Multi-scale Clustering and Normalized Cross Correlation.” In Industrial Engineering, Management Science and Applications 2015, edited by M. Gen, K. J. Kim, X. Huang, and Y. Hiroshi, 403–410. Berlin: Springer-Verlag.10.1007/978-3-662-47200-2
   Google Scholar