Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery

By Le Wang, Wayne P. Sousa, Peng Gong. 2004

463 citations recorded by the source corpus.

Subfields: Atmospheric Science, Ecology, Media Technology

View Paper: https://www.semanticscholar.org/paper/bcb1c029c403b15e68004ae9938c62ccd563787d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

In Ecology

In Media Technology

Citations in the corpus

Object based image analysis for remote sensing (2010, background): “Formangroves on the Caribbean coast of Panama,Wang et al. (2004) were able to enhance spectral separability among mangrove species by taking the object as the basic spatial unit, as opposed to the pixel.”
A Review of Wetland Remote Sensing (2017, unknown): “[9] compared three classification methods for IKONOS images to map mangroves, pixel-based and object-based classification and the integration of the pixel- and object-based classification.”
Forest Type Mapping using Object-specific Texture Measures from Multispectral Ikonos Imagery: Segmentation Quality and Image Classification Issues (2009, methodology): “Even though there have been a number of attempts to determine optimal segmentation (Wang et al., 2004a; Kim and Madden, 2006; Feitosa et al., 2006; Kim et al., 2008), there are no specific guidelines on this issue and the selection procedure remains highly dependent on trial-and-error methods which…”
Enhanced forest cover mapping using spectral unmixing and object-based classification of multi-temporal Landsat imagery (2017, methodology): “…mapping forest cover at high spatial resolutions (Agarwal et al., 2013; Dorren et al., 2003; Oruc et al., 2004), comparative studies indicate that coupling pixel-based and OBIA techniques can improve the accuracy of forest type classifications (Aguirre-Gutiérrez et al., 2012; Wang et al., 2004).”
A Review of Remote Sensing Image Classification Techniques: the Role of Spatio-contextual Information (2014, methodology): “Many studies have proven that significant higher accuracy has been achieved with object-based approaches [Benz et al., 2004; Wang et al., 2004; Myint et al., 2011].”
Texture and Scale in Object-Based Analysis of Subdecimeter Resolution Unmanned Aerial Vehicle (UAV) Imagery (2009, methodology): “An optimal scale parameter can be determined by using class separability indices [ 22 ] or by analyzing local variance [23].”
Multivariate correlations between imagery and field measurements across scales: comparing pixel aggregation and image segmentation (2010, methodology): “Wang et al. (2004) reported classification accuracies with image objects were higher than the same classification method using a pixel-based approach.”