Crop Classification Based on Feature Band Set Construction and Object-Oriented Approach Using Hyperspectral Images
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Xia Zhang | Kun Shang | Lifu Zhang | Shudong Wang | Yanli Sun | Lifu Zhang | Shudong Wang | Xia Zhang | Yanli Sun | K. Shang
[1] A. Gitelson,et al. Three‐band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves , 2006 .
[2] A. Skidmore,et al. Spectral discrimination of vegetation types in a coastal wetland , 2003 .
[3] J. A. Schell,et al. Monitoring vegetation systems in the great plains with ERTS , 1973 .
[4] John R. Miller,et al. Assessing vineyard condition with hyperspectral indices: Leaf and canopy reflectance simulation in a row-structured discontinuous canopy , 2005 .
[5] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[6] T. Kailath. The Divergence and Bhattacharyya Distance Measures in Signal Selection , 1967 .
[7] Luis Alonso,et al. Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications , 2009 .
[8] P. Thenkabail,et al. Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics , 2000 .
[9] Nikos Koutsias,et al. Object-based classification using Quickbird imagery for delineating forest vegetation polygons in a Mediterranean test site , 2008 .
[10] Moon S. Kim,et al. Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance , 2000 .
[11] Paul D. Ayers,et al. Evaluation and Refinement of the Nitrogen Reflectance Index (NRI) for Site-Specific Fertilizer Management , 2001 .
[12] G. A. Blackburn,et al. Spectral indices for estimating photosynthetic pigment concentrations: A test using senescent tree leaves , 1998 .
[13] A. Getis. The Analysis of Spatial Association by Use of Distance Statistics , 2010 .
[14] S. Murmu,et al. Application of Fuzzy Logic and Neural Network in Crop Classification: A Review , 2015 .
[15] Lifu Zhang,et al. Progress in Hyperspectral Remote Sensing Science and Technology in China Over the Past Three Decades , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[16] L. Anselin. Local Indicators of Spatial Association—LISA , 2010 .
[17] L. Plümer,et al. Development of spectral indices for detecting and identifying plant diseases , 2013 .
[18] C. Field,et al. A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency , 1992 .
[19] Kenichi Tatsumi,et al. Crop classification of upland fields using Random forest of time-series Landsat 7 ETM+ data , 2015, Comput. Electron. Agric..
[20] Weiwei Sun,et al. Band Selection Using Improved Sparse Subspace Clustering for Hyperspectral Imagery Classification , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[21] Jun Zhou,et al. Hyperspectral Image Classification Based on Structured Sparse Logistic Regression and Three-Dimensional Wavelet Texture Features , 2013, IEEE Transactions on Geoscience and Remote Sensing.
[22] Matti Mottus,et al. Classification of crops across heterogeneous agricultural landscape in Kenya using AisaEAGLE imaging spectroscopy data , 2015, Int. J. Appl. Earth Obs. Geoinformation.
[23] A. Gitelson,et al. Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation , 1994 .
[24] P. Zarco-Tejada,et al. Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera , 2012 .
[25] John R. Miller,et al. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture , 2004 .
[26] S. Ghosh,et al. Development of an agricultural crops spectral library and classification of crops at cultivar level using hyperspectral data , 2007, Precision Agriculture.
[27] Jon Atli Benediktsson,et al. Recent Advances in Techniques for Hyperspectral Image Processing , 2009 .
[28] Xiuping Jia,et al. A patch‐based image classification by integrating hyperspectral data with GIS , 2006 .
[29] H. Govil,et al. Mapping Regolith and Gossan for Mineral Exploration in the Eastern Kumaon Himalaya, India using hyperion data and object oriented image classification , 2014 .
[30] Jon Atli Benediktsson,et al. SVM- and MRF-Based Method for Accurate Classification of Hyperspectral Images , 2010, IEEE Geoscience and Remote Sensing Letters.
[31] A. Gitelson,et al. Optical Properties and Nondestructive Estimation of Anthocyanin Content in Plant Leaves¶ , 2001, Photochemistry and photobiology.
[32] Liangpei Zhang,et al. On Combining Multiple Features for Hyperspectral Remote Sensing Image Classification , 2012, IEEE Transactions on Geoscience and Remote Sensing.
[33] Antonio J. Plaza,et al. This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1 Spectral–Spatial Hyperspectral Image Segmentation Using S , 2022 .
[34] P. Switzer,et al. A transformation for ordering multispectral data in terms of image quality with implications for noise removal , 1988 .
[35] S. Bhaskaran,et al. Per-pixel and object-oriented classification methods for mapping urban features using Ikonos satellite data , 2010 .
[36] Christopher Conrad,et al. Impact of feature selection on the accuracy and spatial uncertainty of per-field crop classification using Support Vector Machines , 2013 .
[37] J. Benediktsson,et al. Remotely Sensed Image Classification Using Sparse Representations of Morphological Attribute Profiles , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[38] A. Huete,et al. Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission , 2013 .
[39] P. Chavez,et al. STATISTICAL METHOD FOR SELECTING LANDSAT MSS RATIOS , 1982 .
[40] N. Broge,et al. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density , 2001 .
[41] Bingfang Wu,et al. Vegetation classification method with biochemical composition estimated from remote sensing data , 2011 .
[42] J. Roujean,et al. Estimating PAR absorbed by vegetation from bidirectional reflectance measurements , 1995 .
[43] Antonio J. Plaza,et al. This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1 Spectral–Spatial Classification of Hyperspectral Data Usi , 2022 .
[44] M. Cho,et al. Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data , 2015, Biological Invasions.
[45] G. Rondeaux,et al. Optimization of soil-adjusted vegetation indices , 1996 .
[46] John A. Richards,et al. Remote Sensing Digital Image Analysis , 1986 .
[47] Bagher Shirmohammadi,et al. Producing a landslide inventory map using pixel-based and object-oriented approaches optimized by Taguchi method , 2014 .
[48] Bo Du,et al. Ensemble manifold regularized sparse low-rank approximation for multiview feature embedding , 2015, Pattern Recognit..