Fusion of airborne hyperspectral and LiDAR canopy-height data for estimating fractional cover of tall woody plants, herbaceous vegetation, and other soil cover types in a semi-arid savanna ecosystem

References

• Ahlstrom, A., M. R. Raupach, G. Schurgers, B. Smith, A. Arneth, M. Jung, M. Reichstein, et al. 2015. ”The Dominant Role of Semi-Arid Ecosystems in the Trend and Variability of the Land CO2 Sink.” Science. doi:10.1126/science.aaa1668.
   PubMed Web of Science ®Google Scholar
• Alonzo, M., J. P. McFadden, D. J. Nowak, and D. A. Roberts. 2016. “Mapping Urban Forest Structure and Function Using Hyperspectral Imagery and Lidar Data.” Urban Forestry & Urban Greening 17: 135–147. doi:10.1016/j.ufug.2016.04.003.
   Web of Science ®Google Scholar
• Archer, S. R., E. M. Andersen, K. I. Predick, S. Schwinning, R. J. Steidl, and S. R. Woods. 2017. “Woody Plant Encroachment: Causes and Consequences.” Rangeland Systems. doi:10.1007/978-3-319-46709-2_2.
   Google Scholar
• Asner, G. P. and D. B. Lobell. 2000. “A Biogeophysical Approach for Automated SWIR Unmixing of Soils and Vegetation.” Remote Sensing of Environment 74: 99–112. doi:10.1016/s0034-4257(00)00126-7.
   Web of Science ®Google Scholar
• Asner, G. P. and K. B. Heidebrecht. 2002. “Spectral Unmixing of Vegetation, Soil and Dry Carbon Cover in Arid Regions: Comparing Multispectral and Hyperspectral Observations.” International Journal of Remote Sensing 23: 3939–3958. doi:10.1080/01431160110115960.
   Web of Science ®Google Scholar
• Asner, G. P., D. E. Knapp, T. Kennedy-Bowdoin, M. O. Jones, R. E. Martin, J. Boardman, and R. F. Hughes. 2008. “Invasive Species Detection in Hawaiian Rainforests Using Airborne Imaging Spectroscopy and LiDar.” Remote Sensing of Environment. doi:10.1016/j.rse.2007.11.016.
   Web of Science ®Google Scholar
• Asner, G. P., S. R. Levick, and I. P. J. Smit. 2011. “Remote Sensing of Fractional Cover and Biochemistry in Savannas.” In Ecosystem Function in Savannas: Measurement and Modeling at Landscape to Global Scales, edited by M. J. Hill and N. P. Hanan. Boca Raton, FL: CRC Press. doi:10.1201/b10275.
   Google Scholar
• Barger, N. N., S. R. Archer, J. L. Campbell, C.-Y. Huang, J. A. Morton, and A. K. Knapp. 2011. “Woody Plant Proliferation in North American Drylands: A Synthesis of Impacts on Ecosystem Carbon Balance.” Journal of Geophysical Research 116. doi:10.1029/2010jg001506.
   Web of Science ®Google Scholar
• Belgiu, M. and L. Drăguţ. 2016. “Random Forest in Remote Sensing: A Review of Applications and Future Directions.” ISPRS Journal of Photogrammetry and Remote Sensing 114: 24–31.
   Web of Science ®Google Scholar
• Belnap, J., B. Weber, and B. Büdel. 2016. “Biological Soil Crusts as an Organizing Principle in Drylands.” Biological Soil Crusts: An Organizing Principle in Drylands. doi:10.1007/978-3-319-30214-0_1.
   Google Scholar
• Biederman, J. A., R. L. Scott, T. W. Bell, D. R. Bowling, S. Dore, J. Garatuza-Payan, T. E. Kolb, et al. 2017. ”CO Exchange and Evapotranspiration Across Dryland Ecosystems of Southwestern North America.” Global Change Biology 23 (10): 4204–4221.
   PubMed Web of Science ®Google Scholar
• Brandt, M., P. Hiernaux, T. Tagesson, A. Verger, K. Rasmussen, A. Aziz Diouf, C. Mbow, E. Mougin, and R. Fensholt. 2016. “Woody Plant Cover Estimation in Drylands from Earth Observation Based Seasonal Metrics.” Remote Sensing of Environment 172: 28–38. doi:10.1016/j.rse.2015.10.036.
   Web of Science ®Google Scholar
• Brandt, M., C. J. Tucker, A. Kariryaa, K. Rasmussen, C. Abel, J. Small, J. Chave, et al. 2020. ”An Unexpectedly Large Count of Trees in the West African Sahara and Sahel.” Nature 587 (7832): 78–82. doi:10.1038/s41586-020-2824-5.
   PubMed Web of Science ®Google Scholar
• Clark, M. L., D. A. Roberts, J. J. Ewel, and D. B. Clark. 2011. “Estimation of Tropical Rain Forest Aboveground Biomass with Small-Footprint Lidar and Hyperspectral Sensors.” Remote Sensing of Environment 115: 2931–2942. doi:10.1016/j.rse.2010.08.029.
   Web of Science ®Google Scholar
• Colditz, R. 2015. “An Evaluation of Different Training Sample Allocation Schemes for Discrete and Continuous Land Cover Classification Using Decision Tree-Based Algorithms.” Remote Sensing 7: 9655–9681. doi:10.3390/rs70809655.
   Web of Science ®Google Scholar
• Colgan, M., C. Baldeck, J.-B. Féret, and G. Asner. 2012. “Mapping Savanna Tree Species at Ecosystem Scales Using Support Vector Machine Classification and BRDF Correction on Airborne Hyperspectral and LiDar Data.” Remote Sensing 4: 3462–3480. doi:10.3390/rs4113462.
   Web of Science ®Google Scholar
• Congalton, R. G. and K. Green. 2019. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. 3rd ed. Boca Raton: CRC Press.
   Google Scholar
• Dashti, H., N. F. Glenn, S. Ustin, J. J. Mitchell, Y. Qi, N. T. Ilangakoon, A. N. Flores, et al. 2019. “Empirical Methods for Remote Sensing of Nitrogen in Drylands May Lead to Unreliable Interpretation of Ecosystem Function.” IEEE Transactions on Geoscience and Remote Sensing. doi:10.1109/tgrs.2018.2889318.
   Google Scholar
• Dashti, H., A. Poley, N. F. Glenn, N. Ilangakoon, L. Spaete, D. Roberts, J. Enterkine, A. N. Flores, S. L. Ustin, and J. J. Mitchell. 2019. “Regional Scale Dryland Vegetation Classification with an Integrated Lidar-Hyperspectral Approach.” Remote Sensing. doi:10.3390/rs11182141.
   Web of Science ®Google Scholar
• Dettweiler-Robinson, E., M. Nuanez, and M. E. Litvak. 2018. ”Biocrust Contribution to Ecosystem Carbon Fluxes Varies Along an Elevational Gradient.” Ecosphere 9 (6): e02315. Wiley doi:10.1002/ecs2.2315.
   Web of Science ®Google Scholar
• Devine, A. P., R. A. McDonald, T. Quaife, and I. M. D. Maclean. 2017. “Determinants of Woody Encroachment and Cover in African Savannas.” Oecologia 183 (4): 939–951. doi:10.1007/s00442-017-3807-6.
   PubMed Web of Science ®Google Scholar
• Eldridge, D. J., S. Reed, S. K. Travers, M. A. Bowker, F. T. Maestre, J. Ding, C. Havrilla, et al. 2020. ”The Pervasive and Multifaceted Influence of Biocrusts on Water in the World’s Drylands.” Global Change Biology 26 (10): 6003–6014. doi:10.1111/gcb.15232.
   PubMed Web of Science ®Google Scholar
• France, G., D. Hooftman, F. van Langevelde, E. Veenendaal, M. W. Steven, and J. Lloyd. 2017. ”MODIS VCF Should Not Be Used to Detect Discontinuities in Tree Cover Due to Binning Bias. A Comment on Hanan Et Al. (2014) and Staver and Hansen (2015).” Global Ecology and Biogeography: A Journal of Macroecology 26 (7): 854–859. Wiley.
   Web of Science ®Google Scholar
• Gallery, W. 2014. NEON Imaging Spectrometer Level 1B Calibrated Radiance. NEON.DOC.001210vA. NEON (National Ecological Observatory Network).
   Google Scholar
• Gallery, W. 2019. NEON Algorithm Theoretical Basis Document(atbd):Cameramosaic. NEON.DOC.005052vA. NEON (National Ecological Observatory Network).
   Google Scholar
• Gao, L., Z. Han, D. Hong, B. Zhang, and J. Chanussot. 2022. “CyCu-Net: Cycle-Consistency Unmixing Network by Learning Cascaded Autoencoders.” IEEE Transactions on Geoscience and Remote Sensing. doi:10.1109/tgrs.2021.3064958.
   Web of Science ®Google Scholar
• Gao, L., Z. Wang, L. Zhuang, H. Yu, B. Zhang, and J. Chanussot. 2022. “Using Low-Rank Representation of Abundance Maps and Nonnegative Tensor Factorization for Hyperspectral Nonlinear Unmixing.” IEEE Transactions on Geoscience and Remote Sensing. doi:10.1109/tgrs.2021.3065990.
   Web of Science ®Google Scholar
• Gillan, J. K., G. E. Ponce‐campos, T. L. Swetnam, A. Gorlier, P. Heilman, and M. P. McClaran. 2021. “Innovations to Expand Drone Data Collection and Analysis for Rangeland Monitoring.” Ecosphere 12. doi:10.1002/ecs2.3649.
   Web of Science ®Google Scholar
• Gornish, E. S., H. Ganjurjav, M. Liang, J. L. Simonis, and M. P. McClaran. 2021. ”Identifying Restoration Opportunities Beneath Native Mesquite Canopies.” Restoration Ecology 29: 2. Wiley. doi:10.1111/rec.13334.
   Web of Science ®Google Scholar
• Goulden, T. 2018. L3 Discrete LiDar Processing and QA Informan on for 2018 SRER 2. NEON AOP QA Report. NEON (National Ecological Observatory Network).
   Google Scholar
• Goulden, T. and Scholl V.2019. NEON Algorithm Theoretical Basis Document (ATBD): Ecosystem Structure. NEON.DOC.002387vA. NEON (National Ecological Observatory Network).
   Google Scholar
• Han, Z., D. Hong, L. Gao, B. Zhang, and J. Chanussot. 2021. “Deep Half-Siamese Networks for Hyperspectral Unmixing.” IEEE Geoscience and Remote Sensing Letters. doi:10.1109/lgrs.2020.3011941.
   PubMed Web of Science ®Google Scholar
• Han, Z., D. Hong, L. Gao, J. Yao, B. Zhang, and J. Chanussot. 2022. “Multimodal Hyperspectral Unmixing: Insights from Attention Networks.” IEEE Transactions on Geoscience and Remote Sensing. doi:10.1109/tgrs.2022.3155794.
   Web of Science ®Google Scholar
• Hansen, M. C., R. S. DeFries, J. R. G. Townshend, M. Carroll, C. Dimiceli, and R. A. Sohlberg. 2003. “Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm.” Earth Interactions. doi:10.1175/1087-3562(2003)007<0001:gptcaa>2.0.co;2.
   Web of Science ®Google Scholar
• Hartley, A. J., N. MacBean, G. Georgievski, and S. Bontemps. 2017. ”Uncertainty in Plant Functional Type Distributions and Its Impact on Land Surface Models.” Remote Sensing of Environment 203 (December): 71–89. Elsevier. 10.1016/j.rse.2017.07.037.
   Web of Science ®Google Scholar
• Heylen, R., M. Parente, and P. Gader. 2014. “A Review of Nonlinear Hyperspectral Unmixing Methods.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. doi:10.1109/jstars.2014.2320576.
   Google Scholar
• Hill, L. J. R., J.-P. Guerschman, A. S. Marks, and D. J. Barrett. 2013. ”Use of Vegetation Index ‘Fingerprints’ from Hyperion Data to Characterize Vegetation States Within Land Cover/land Use Types in an Australian Tropical Savanna.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6 (2): 309–319. Institute of Electrical and Electronics Engineers (IEEE) doi:10.1109/JSTARS.2012.2222873.
   Web of Science ®Google Scholar
• Hong, D., L. Gao, J. Yao, N. Yokoya, J. Chanussot, U. Heiden, and B. Zhang. 2021. “Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing.” IEEE Transactions on Neural Networks and Learning Systems. doi:10.1109/tnnls.2021.3082289.
   Web of Science ®Google Scholar
• Hong, D., L. Gao, N. Yokoya, J. Yao, J. Chanussot, Q. Du, and B. Zhang. 2021. “More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification.” IEEE Transactions on Geoscience and Remote Sensing. doi:10.1109/tgrs.2020.3016820.
   PubMed Web of Science ®Google Scholar
• Huang, C.-Y., S. E. Marsh, M. P. McClaran, and S. R. Archer. 2007. “Postfire Stand Structure in a Semiarid Savanna: Cross-Scale Challenges Estimating Biomass.” Ecological Applications: A Publication of the Ecological Society of America 17 (7): 1899–1910. doi:10.1890/06-1968.1.
   PubMed Web of Science ®Google Scholar
• Huang, C.-Y., S. R. Archer, M. P. McClaran, and S. E. Marsh. 2018. “Shrub Encroachment into Grasslands: End of an Era?” PeerJ 6 (September): e5474. doi:10.7717/peerj.5474.
   PubMed Web of Science ®Google Scholar
• Jia, K., S. Liang, S. Liu, Y. Li, Z. Xiao, Y. Yao, B. Jiang, et al. 2015. ”Global Land Surface Fractional Vegetation Cover Estimation Using General Regression Neural Networks from MODIS Surface Reflectance.” IEEE Transactions on Geoscience and Remote Sensing: A Publication of the IEEE Geoscience and Remote Sensing Society 539:4787–4796. Institute of Electrical and Electronics Engineers (IEEE). 10.1109/TGRS.2015.2409563
   Web of Science ®Google Scholar
• Jiapaer, G., X. Chen, and A. Bao. 2011. ”A Comparison of Methods for Estimating Fractional Vegetation Cover in Arid Regions.” Agricultural and Forest Meteorology 151 (12): 1698–1710. Elsevier BV.
   Web of Science ®Google Scholar
• Karpowicz, B. and Kampe T. 2015. NEON Imaging Spectrometer Radiance to Reflectance Algorithm Theoretical Basis Document. NEON.DOC.001288vA. NEON (National Ecological Observatory Network).
   Google Scholar
• Khosravipour, A., A. K. Skidmore, M. Isenburg, T. Wang, and Y. A. Hussin. 2014. “Generating Pit-Free Canopy Height Models from Airborne Lidar.” Photogrammetric Engineering & Remote Sensing 80: 863–872. doi:10.14358/pers.80.9.863.
   Web of Science ®Google Scholar
• Lunt, I. D., L. M. Winsemius, S. P. McDonald, J. W. Morgan, and R. L. Dehaan. 2010. “How Widespread is Woody Plant Encroachment in Temperate Australia? Changes in Woody Vegetation Cover in Lowland Woodland and Coastal Ecosystems in Victoria from 1989 to 2005.” Journal of Biogeography 37: 722–732. doi:10.1111/j.1365-2699.2009.02255.x.
   Web of Science ®Google Scholar
• MacBean, N., R. L. Scott, J. A. Biederman, P. Peylin, T. Kolb, M. E. Litvak, P. Krishnan, et al. 2021. ”Dynamic Global Vegetation Models Underestimate Net CO2 Flux Mean and Inter-Annual Variability in Dryland Ecosystems.” Environmental Research Letters. doi:10.1088/1748-9326/ac1a38.
   Web of Science ®Google Scholar
• Maestre, F. T., C. Escolar, M. Ladrón Guevara, J. L. Quero, R. Lázaro, M. Delgado-Baquerizo, V. Ochoa, M. Berdugo, B. Gozalo, and A. Gallardo. 2014. ”Changes in Biocrust Cover Drive Carbon Cycle Responses to Climate Change in Drylands.” Global Change Biology 20 (8): 2697–2698. Wiley doi:10.1111/gcb.12659.
   Web of Science ®Google Scholar
• Maggiori, E., A. Plaza, and Y. Tarabalka. 2018. “Models for Hyperspectral Image Analysis: From Unmixing to Object-Based Classification.” Mathematical Models for Remote Sensing Image Processing. doi:10.1007/978-3-319-66330-2_2.
   Google Scholar
• Marconi, S., S. J. Graves, B. G. Weinstein, S. Bohlman, and E. P. White. 2021. “Estimating Individual-Level Plant Traits at Scale.” Ecological Applications: A Publication of the Ecological Society of America 31 (4): e02300. doi:10.1002/eap.2300.
   PubMed Web of Science ®Google Scholar
• McClaran, M. P. 2003. “A Century of Vegetation Change on the Santa Rita Experimental Range.” In Santa Rita Experimental Range: 100 Years (1903 to 2003) of Accomplishments and Contributions. Proceedings RMRS-P-30. Ogden, UT: US Department of Agriculture Forest Service.
   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.
   Web of Science ®Google Scholar
• Mishra, N. B. and K. A. Crews. 2014. ”Estimating Fractional Land Cover in Semi-Arid Central Kalahari: The Impact of Mapping Method (Spectral Unmixing Vs. Object-Based Image Analysis) and Vegetation Morphology.” Geocarto International 29 (8): 860–877. Informa UK Limited.
   Web of Science ®Google Scholar
• Myers-Smith, I. H., B. C. Forbes, M. Wilmking, M. Hallinger, T. Lantz, D. Blok, K. D. Tape, et al. 2011. ”Shrub Expansion in Tundra Ecosystems: Dynamics, Impacts and Research Priorities”. Environmental Research Letters 6: 045509. doi:10.1088/1748-9326/6/4/045509.
   Web of Science ®Google Scholar
• Naidoo, L., M. A. Cho, R. Mathieu, and G. Asner. 2012. ”Classification of Savanna Tree Species, in the Greater Kruger National Park Region, by Integrating Hyperspectral and LiDar Data in a Random Forest Data Mining Environment.” ISPRS Journal of Photogrammetry and Remote Sensing: Official Publication of the International Society for Photogrammetry and Remote Sensing 69 April, Elsevier BV: 167–179. 10.1016/j.isprsjprs.2012.03.005.
   Web of Science ®Google Scholar
• National Land Cover Database (NLCD). 2020. 2016 Shrubland Fractional Components for the Western U.S. (Ver. 3.0, July 2020). 10.5066/P9MJVQSQ.
   Google Scholar
• Scott, R. L., J. A. Biederman, E. P. Hamerlynck, and G. A. Barron-Gafford. 2015. ”The Carbon Balance Pivot Point of Southwestern U.S. Semiarid Ecosystems: Insights from the 21st Century Drought.” Journal of Geophysical Research: Biogeosciences 120 (12): 2612–2624. American Geophysical Union (AGU).
   Web of Science ®Google Scholar
• Smith, W. K., M. P. Dannenberg, D. Yan, S. Herrmann, M. L. Barnes, G. A. Barron-Gafford, J. A. Biederman, et al. 2019. ”Remote Sensing of Dryland Ecosystem Structure and Function: Progress, Challenges, and Opportunities”. Remote Sensing of Environment 233: 111401. doi:10.1016/j.rse.2019.111401.
   Web of Science ®Google Scholar
• Staver, A. C. and C. H. Matthew. 2015. ”Analysis of Stable States in Global Savannas: Is the CART Pulling the Horse? - a Comment.” Global Ecology and Biogeography: A Journal of Macroecology 24 (8): 985–987. Wiley doi:10.1111/geb.12285.
   Web of Science ®Google Scholar
• Staver, A., A. Carla, C. Staver, J. Botha, and L. Hedin. 2017. “Soils and Fire Jointly Determine Vegetation Structure in an African Savanna.” The New Phytologist 216: 1151–1160. doi:10.1111/nph.14738.
   PubMed Web of Science ®Google Scholar
• Swatantran, A., R. Dubayah, D. Roberts, M. Hofton, and J. Bryan Blair. 2011. “Mapping Biomass and Stress in the Sierra Nevada Using Lidar and Hyperspectral Data Fusion.” Remote Sensing of Environment 115: 2917–2930. doi:10.1016/j.rse.2010.08.027.
   Web of Science ®Google Scholar
• Tiribelli, F., T. Kitzberger, and J. Manuel Morales. 2018. ”Changes in Vegetation Structure and Fuel Characteristics Along Post-Fire Succession Promote Alternative Stable States and Positive Fire-Vegetation Feedbacks.” Journal of Vegetation Science: Official Organ of the International Association for Vegetation Science 29 (2): 147–156. Wiley.
   Web of Science ®Google Scholar
• Ustin, S. L., D. A. Roberts, J. A. Gamon, G. P. Asner, and R. O. Green. 2004. ”Using Imaging Spectroscopy to Study Ecosystem Processes and Properties.” Bioscience 54: 6–523. Oxford University Press (OUP). doi:10.1641/0006-3568(2004)054[0523:UISTSE]2.0.CO;2.
   Web of Science ®Google Scholar
• Varga, T. A. and G. P. Asner. 2008. “Hyperspectral and LiDar Remote Sensing of Fire Fuels in Hawaii Volcanoes National Park.” Ecological Applications: A Publication of the Ecological Society of America 18 (3): 613–623. doi:10.1890/07-1280.1.
   PubMed Web of Science ®Google Scholar
• Venter, Z. S., M. D. Cramer, and H.-J. Hawkins. 2018. “Drivers of Woody Plant Encroachment Over Africa.” Nature Communications 9 (1): 2272. doi:10.1038/s41467-018-04616-8.
   PubMed Web of Science ®Google Scholar
• Wanner, W., X. Li, and A. H. Strahler. 1995. “On the Derivation of Kernels for Kernel-Driven Models of Bidirectional Reflectance.” Journal of Geophysical Research. doi:10.1029/95jd02371.
   Web of Science ®Google Scholar
• Winter, M. E. 1999. “N-FINDR: An Algorithm for Fast Autonomous Spectral End-Member Determination in Hyperspectral Data.” Imaging Spectrometry V. doi:10.1117/12.366289.
   Google Scholar
• Wu, J.-C. and G.-C. Tsuei. 2013. “Comparison of Hyperspectral Endmember Extraction Algorithms.” Journal of Applied Remote Sensing 7: 073525. doi:10.1117/1.jrs.7.073525.
   Web of Science ®Google Scholar
• Xiao, J. and A. Moody. 2005. ”A Comparison of Methods for Estimating Fractional Green Vegetation Cover Within a Desert-To-Upland Transition Zone in Central New Mexico, USA.” Remote Sensing of the Environment 98: 2–3–250237–250. Elsevier BV.
   Web of Science ®Google Scholar
• Yang, L., S. Jin, P. Danielson, C. Homer, L. Gass, S. M. Bender, A. Case, et al. 2018. ”A New Generation of the United States National Land Cover Database: Requirements, Research Priorities, Design, and Implementation Strategies”. ISPRS Journal of Photogrammetry and Remote Sensing 146: 108–123. doi:10.1016/j.isprsjprs.2018.09.006.
   Web of Science ®Google Scholar
• Yang, X. and K. A. Crews. 2019. ”Fractional Woody Cover Mapping of Texas Savanna at Landsat Scale.” Land 8: 1–9. Multidisciplinary Digital Publishing Institute. doi:10.3390/land8010009.
   Web of Science ®Google Scholar
• Zhang, W., M. Brandt, Q. Wang, A. V. Prishchepov, C. J. Tucker, Y. Li, H. Lyu, and R. Fensholt. 2019. “From Woody Cover to Woody Canopies: How Sentinel-1 and Sentinel-2 Data Advance the Mapping of Woody Plants in Savannas.” Remote Sensing of Environment. doi:10.1016/j.rse.2019.111465.
   Web of Science ®Google Scholar