Texture and Scale in Object-Based Analysis of Subdecimeter Resolution Unmanned Aerial Vehicle (UAV) Imagery

By Andrea S. Laliberte, Albert Rango. IEEE Transactions on Geoscience and Remote Sensing, 2009

345 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Media Technology

View Paper: https://www.semanticscholar.org/paper/dd0beaaa333ef79d7a440005cc07291e7fb2e616

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Citations in the corpus

Object-based change detection (2012, background): “Although square windows are trivial to implement, they are biased along their diagonals and will likely straddle the boundary between two landscape features, especially when a large window size is used (Laliberte and Rango 2009).”
High Throughput Field Phenotyping of Wheat Plant Height and Growth Rate in Field Plot Trials Using UAV Based Remote Sensing (2016, background): “For environmental monitoring, examples include modelling of the temporal changes in landslide dynamics [18]; 3D reconstruction of fluvial topography of UK streams [19]; monitoring of rangeland [20,21] and conservation applications such as surveying of habitats and animal numbers [22].”
Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management (2009, methodology): “Image analysis techniques such as the use of image texture and object-based image analysis have improved the accuracy of rangeland classifications from UAV imaging (14).”
Segment Optimization and Data-Driven Thresholding for Knowledge-Based Landslide Detection by Object-Based Image Analysis (2011, methodology): “Image segmentation, a method of dividing the image into nonoverlapping regions or segments, is the first major step in OOA, and its quality controls the accuracy of image classification, such as for land cover [9].”
Evaluation of UAV imagery for mapping Silybum marianum weed patches (2017, methodology): “Classification accuracy among grass, shrub, and bare soil has been improved using several texture measures estimated from UAV imagery of rangelands (Laliberte and Rango 2009).”
Unmanned Aerial Vehicle for Remote Sensing Applications - A Review (2019, background): “Most of the existing texture descriptors used for VHR imagery could be directly applied to UHR images [82,83].”
Object-oriented mapping of landslides using Random Forests (2011, background): “Considering their large computational burden and frequent reports on strong correlations among several GLCM derivatives (Hall-Beyer, 2007; Laliberte & Rango, 2009), a subset of five texture measures was selected for this study.”
Multispectral Remote Sensing from Unmanned Aircraft: Image Processing Workflows and Applications for Rangeland Environments (2011, background): “Using texture and/or the intensity-hue-saturation components can compensate for the low radiometric and spectral resolution of consumer cameras [9,21], although the lack of a near infrared band poses certain limitations for vegetation characterization.”