Knowledge-based crop classification of a Landsat thematic mapper image

By L. Janssen, H. Middelkoop. 1992

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Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities (2020, background): “sensing images at pixel level or subpixel level [23]–[25], through labeling each pixel in the remote sensing images with a semantic class, because the spatial resolution of remote sensing images is very low—the size of a pixel is similar to the sizes of the objects of interest [26].”
Object extraction and revision by image analysis using existing geodata and knowledge: current status and steps towards operational systems☆ (2004, background): “…land changes, urban and site mapping and monitoring in Goldberg et al. (1988), McKeown (1988), Mollerjensen (1990), Srinivasan and Richards (1990), Janssen and Middelkoop (1992), Janssen et al. (1990), Lees and Ritman (1991), Middelkoop and Janssen (1991), Ton et al. (1991), Verly et al. (1992),…”
A Survey on Object Detection in Optical Remote Sensing Images (2016, unknown): “…2005), and other more general object extraction applications like landslide, bridges, vehicles, urban land changes, crops, drainage channels, forests in (Chaudhuri and Samal, 2008; Janssen and Middelkoop, 1992; Martha et al., 2011; Moon et al., 2002; Solberg, 1999; Tchoku et al., 1996; Wang, 1993).”