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Identification of "ever-cropped" land (1984-2010) using Landsat annual maximum NDVI image composites: Southwestern Kansas case study.

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Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
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Published on: February 25, 2021

Generating land cover boundaries from remotely sensed data using object-based image analysis: overview and

Susan K Maxwell1

  • 1BioMedware Inc., 3526 W. Liberty Rd., Suite 100, Ann Arbor, MI 48103, United States. Maxwell@biomedware.com

Spatial and Spatio-Temporal Epidemiology
|December 8, 2010
PubMed
Summary

Object-based image analysis (OBIA) automates land cover mapping from satellite and aerial imagery. This study demonstrates OBIA

Keywords:
Landsataerial photographimage segmentationpesticide exposure

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Area of Science:

  • Environmental science
  • Remote sensing
  • Geographic information systems (GIS)

Background:

  • Satellite imagery and aerial photography are crucial for environmental mapping and health studies.
  • Manual land cover mapping is time-consuming and labor-intensive.
  • Automated boundary detection using object-based image analysis (OBIA) offers a more efficient approach.

Purpose of the Study:

  • To provide an overview of OBIA technology for land cover delineation.
  • To demonstrate OBIA's application in mapping land cover features at multiple scales.
  • To apply OBIA in the context of pesticide spray drift exposure assessment.

Main Methods:

  • Utilized high-resolution (1 m) aerial photographs and medium-resolution (30 m) Landsat time series data.
  • Applied object-based image analysis (OBIA) algorithms for automated feature delineation.
  • Compared multi-scale land cover mapping results.

Main Results:

  • OBIA successfully delineated land cover features from both high and medium resolution imagery.
  • The study demonstrated the effectiveness of OBIA for multi-scale environmental mapping.
  • Automated mapping facilitated a more efficient assessment of pesticide spray drift exposure.

Conclusions:

  • OBIA is a powerful tool for automating land cover mapping from diverse remote sensing data.
  • Multi-scale OBIA applications enhance environmental and health-related spatial analyses.
  • Automated land cover delineation improves the efficiency and accuracy of environmental exposure assessments.