Processing Hyperion and ALI for forest classification

By D. Goodenough, A. Dyk, K. Niemann, J. Pearlman, Hao Chen, T. Han, M. Murdoch, C. West. IEEE Transactions on Geoscience and Remote Sensing, 2003

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View angle effects on the discrimination of soybean varieties and on the relationships between vegetation indices and yield using off-nadir Hyperion data (2009, methodology): “An algorithm to identify bad pixels and to reduce striping effects was applied over theHyperion images replacing abnormal vertical lines by the average response of adjacent columns (Goodenough et al., 2003).”
Fusion of Hyperspectral and LIDAR Remote Sensing Data for Classification of Complex Forest Areas (2008, methodology): “In [6], for example, Goodenough et al.”
A Comparison of Land Surface Water Mapping Using the Normalized Difference Water Index from TM, ETM+ and ALI (2013, background): “mapping [23,24], forest classification [25], and the evaluation of dissolved organic matter in lake”
Observing Changing Ecological Diversity in the Anthropocene (2013, background): “…CAO 0.5 Féret and Asner (2011) Sub-tropical broadleaf forest (F) AVIRIS 3.0 Carlson et al. (2007) Temperate broadleaf forest (F) EO-1 Hyperion 30.0 Goodenough et al. (2003) Temperate grasslands (S) AVIRIS 19.0 Carter et al. (2005) Temperate mixed forest (S) AVIRIS 20.0 Martin et al.…”