Evaluating the influence of the Red Edge band from RapidEye sensor in quantifying leaf area index for hydrological applications specifically focussing on plant canopy interception

Physics and Chemistry of the Earth, Parts A/B/C - Tập 100 - Trang 73-80 - 2017
Timothy Dube1, Onisimo Mutanga2, Mbulisi Sibanda2, Cletah Shoko2, Abel Chemura2,3
1Department of Geography and Environmental Science, University of Limpopo, Private Bag X1106 Sovenga, 0727, Polokwane, South Africa
2Discipline of Geography, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, P/Bag X01, Scottsville, Pietermaritzburg 3209, South Africa
3Department of Environmental Science & Technology, Chinhoyi University of Technology, P. Bag 7724 Chinhoyi, Zimbabwe

Tài liệu tham khảo

Adam, 2010, Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review, Wetl. Ecol. Manag., 18, 281, 10.1007/s11273-009-9169-z Adelabu, 2014, Evaluating the impact of red-edge band from Rapideye image for classifying insect defoliation levels, ISPRS J. Photogrammetry Remote Sens., 95, 34, 10.1016/j.isprsjprs.2014.05.013 Adelabu, 2014, Evaluating the impact of red–edge band from Rapideye Image for classifying insect defoliation levels, ISPRS J. Photogrammetry Remote Sens., 95, 34, 10.1016/j.isprsjprs.2014.05.013 Alcorn, 2013, Crown structure and vertical foliage distribution in 4-year-old plantation-grown Eucalyptus pilularis and Eucalyptus cloeziana, Trees, 27, 555, 10.1007/s00468-012-0809-1 Basuki, 2012, The potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass, Geocarto Int., 27, 329, 10.1080/10106049.2011.634928 Breiman, 2001, Random forests, Mach. Learn., 45, 5, 10.1023/A:1010933404324 Bulcock, 2010, Spatial mapping of leaf area index using hyperspectral remote sensing for hydrological applications with a particular focus on canopy interception, Hydrol. Earth Syst. Sci., 14, 383, 10.5194/hess-14-383-2010 Canisius, 2010, Comparison and evaluation of Medium Resolution Imaging Spectrometer leaf area index products across a range of land use, Remote Sens. Environ., 114, 950, 10.1016/j.rse.2009.12.010 Carlyle-Moses, 2011, 407 Carreiras, 2012, Understanding the relationship between aboveground biomass and ALOS PALSAR data in the forests of Guinea-Bissau (West Africa), Remote Sens. Environ., 121, 426, 10.1016/j.rse.2012.02.012 Carreiras, 2012, Understanding the relationship between aboveground biomass and ALOS PALSAR data in the forests of Guinea-Bissau (West Africa), Remote Sens. Environ., 121, 426, 10.1016/j.rse.2012.02.012 De'ath, 2007, Boosted trees for ecological modeling and prediction, Ecology, 88, 243, 10.1890/0012-9658(2007)88[243:BTFEMA]2.0.CO;2 Dube, 2015, Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas, ISPRS J. Photogrammetry Remote Sens., 108, 12, 10.1016/j.isprsjprs.2015.06.002 Dube, 2014, Intra-and-Inter species biomass prediction in a plantation forest: testing the utility of high spatial resolution Spaceborne multispectral RapidEye sensor and advanced machine learning algorithms, Sensors, 14, 15348, 10.3390/s140815348 Dube, 2017, Quantifying aboveground biomass in African environments: a review of the trade-offs between sensor estimation accuracy and costs, Trop. Ecol., 57, 393 Elith, 2008, A working guide to boosted regression trees, J. Animal Ecol., 77, 802, 10.1111/j.1365-2656.2008.01390.x Güneralp, 2014, Estimation of floodplain aboveground biomass using multispectral remote sensing and nonparametric modeling, Int. J. Appl. Earth Observ. Geoinformation, 33, 119, 10.1016/j.jag.2014.05.004 Huete, 2002, Overview of the radiometric and biophysical performance of the MODIS vegetation indices, Remote Sens. Environ., 83, 195, 10.1016/S0034-4257(02)00096-2 Jonckheere, 2004, Methods for leaf area index determination. Part I: theories, techniques and instruments, Agric. For. Meteorol, 121, 19, 10.1016/j.agrformet.2003.08.027 Kozak, 2007, Modelling crop canopy and residue rainfall interception effects on soil hydrological components for semi-arid agriculture, Hydrol. Process., 21, 229, 10.1002/hyp.6235 Lawrence, 2004, Classification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis, Remote Sens. Environ., 90, 331, 10.1016/j.rse.2004.01.007 Leathwick, 2006, Variation in demersal fish species richness in the oceans surrounding New Zealand: an analysis using boosted regression trees, Mar. Ecol. Prog. Ser., 321, 267, 10.3354/meps321267 Lee, 2004, Hyperspectral versus multispectral data for estimating leaf area index in four different biomes, Remote Sens. Environ., 91, 508, 10.1016/j.rse.2004.04.010 Lottering, 2012, Estimating the road edge effect on adjacent Eucalyptus grandis forests in KwaZulu-Natal, South Africa, using texture measures and an artificial neural network, J. Spatial Sci., 57, 153, 10.1080/14498596.2012.733617 Mariotto, 2013, Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission, Remote Sens. Environ., 139, 291, 10.1016/j.rse.2013.08.002 Moisen, 2006, Predicting tree species presence and basal area in Utah: a comparison of stochastic gradient boosting, generalized additive models, and tree-based methods, Ecol. Model., 199, 176, 10.1016/j.ecolmodel.2006.05.021 Mutanga, 2004, Narrow band vegetation indices overcome the saturation problem in biomass estimation, Int. J. Remote Sens., 25, 3999, 10.1080/01431160310001654923 Özçift, 2011, Random forests ensemble classifier trained with data resampling strategy to improve cardiac arrhythmia diagnosis, Comput. Biol. Med., 41, 265, 10.1016/j.compbiomed.2011.03.001 R Development Core Team, 2008 Savenije, 2004, The importance of interception and why we should delete the term evapotranspiration from our vocabulary, Hydrol. Process., 18, 1507, 10.1002/hyp.5563 Scott, 1997, Streamflow responses to afforestation with Eucalyptus grandis and Pinus patula and to felling in the Mokobulaan experimental catchments, South Africa, J. Hydrol., 199, 360, 10.1016/S0022-1694(96)03336-7 Sibanda, 2015, Examining the potential of Sentinel-2 MSI spectral resolution in quantifying above ground biomass across different fertilizer treatments, ISPRS J. Photogrammetry Remote Sens., 110, 55, 10.1016/j.isprsjprs.2015.10.005 Sibanda, 2016, Comparing the spectral settings of the new generation broad and narrow band sensors in estimating biomass of native grasses grown under different management practices, GIScience Remote Sens., 53, 614, 10.1080/15481603.2016.1221576 Thenkabail, 2004, Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests, Remote Sens. Environ., 90, 23, 10.1016/j.rse.2003.11.018 Wang, 2005, On the relationship of NDVI with leaf area index in a deciduous forest site, Remote Sens. Environ., 94, 244, 10.1016/j.rse.2004.10.006