Geographic Object-Based Image Analysis (GEOBIA): A new name for a new discipline

By Geoffrey J. Hay, Guillermo Castilla. 2008

560 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Media Technology

View Paper: https://www.semanticscholar.org/paper/8f53e5a22f7be3a7ab54fcad22dd37af8880c624

How researchers see this paper

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

In Artificial Intelligence

1. Luigi Lombardo
2. Thomas Blaschke
3. Brian Alan Johnson
4. Zhixiao Xie
5. Yoshio Inoue
6. Eiji Sakaiya

In Media Technology

1. Thomas Blaschke
2. Liangpei Zhang
3. Gong Cheng
4. Junwei Han
5. Lucian Dragut
6. Xin Huang
7. Darius Phiri
8. Norman Kerle

Citations in the corpus

• Accounting for covariate distributions in slope-unit-based landslide susceptibility models. A case study in the alpine environment (2019, background): “In turn, OBIA generates new geographic infor-88 mation in a GIS-ready format which can be used to address a wide array of scientific issues89 (Hay and Castilla, 2008).90 Several examples are already available where OBIA has been tested to provide landslide91 inventories in a semi-automated and…”
• Assessing object-based classification: advantages and limitations (2009, background): “While a number of studies have shown the advantages of object-based classification over pixel-based classification, less attention has been paid to its potential limitations (Hay and Castilla 2008, Kampouraki et al. 2008).”
• Geographic Object-Based Image Analysis – Towards a new paradigm (2014, unknown): “Synthesizing existing definitions (Hay and Castilla, 2008; Hay and Blaschke, 2010) we may state that GEOBIA is a ‘recent’ approach (including theory, methods, and tools) to partition remote sensing imagery into meaningful image-objects, and assess their characteristics through scale.”
• Algorithms for semantic segmentation of multispectral remote sensing imagery using deep learning (2017, unknown): “According to Hay and Castilla (2008), GEOBIA involves the development of “automated methods to partition remote sensing imagery into meaningful image-objects, and assessing their characteristics through spatial, spectral and temporal scales, so as to generate new geographic information in GIS-ready…”
• Object based image analysis for remote sensing (2010, methodology): “, 2001, 2003), and OBIA is inextricably linked to multiscale analysis concepts (Burnett and Blaschke, 2003; Benz et al., 2004; Lang, 2008; Hay and Castilla, 2008), even if single levels are targeted for specific applications (Lang and Langanke, 2006; Lang, 2008; Weinke et al.”