A Fixed-Threshold Approach to Generate High-Resolution Vegetation Maps for IKONOS Imagery

Vegetation distribution maps from remote sensors play an important role in urban planning, environmental protecting and related policy making. The normalized difference vegetation index (NDVI) is the most popular approach to generate vegetation maps for remote sensing imagery. However, NDVI is usually used to generate lower resolution vegetation maps, and particularly the threshold needs to be chosen manually for extracting required vegetation information. To tackle this threshold selection problem for IKONOS imagery, a fixed-threshold approach is developed in this work, which integrates with an extended Tasseled Cap transformation and a designed image fusion method to generate high-resolution (1-meter) vegetation maps. Our experimental results are promising and show it can generate more accurate and useful vegetation maps for IKONOS imagery.

• Publication year

  2008

• Venue

  Italian National Conference on Sensors

• Publication date

  2008-07-01

• Fields of study

  Medicine, Computer Science, Environmental Science

• Identifiers
  DOI 10.3390/s8074308PMID 27879937PMCID 3697176
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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