Near-infrared discrimination of leafless saltcedar in wintertime Landsat TM

• Published in: International journal of remote sensing Vol. 29; no. 12; pp. 3577 - 3588
• Main Authors: Groeneveld, D. P., Watson, R. P.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 15.06.2008
• Subjects: Aerial photography; Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; canopies; classification; discrimination; Earth sciences; Earth, ocean, space; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Landsat; Q1; Q2; Q3; Remote sensing; Tamarix ramosissima; Teledetection and vegetation maps; USA, Arkansas R; USA, Colorado; Vegetation; weeds; winter; United States; Colorado; Arkansas River; Branching; Thematic Mapper; differentiation; density; aerial photography; Space remote sensing; Riparian vegetation; Landsat; near infrared radiation; vegetation; Plant leaf; North America; Spectral data; Branch; discrimination; riparian environment; Spectroscopical observation; Native species; Canopy(vegetation); Reflectance; high resolution
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/01431160701711078

To test a hypothesis that leafless riparian canopies enable accurate multi-spectral discrimination of saltcedar (Tamarix ramosissima Ledeb.) from other native species, winter Landsat TM5 data (16 November 2005) were analysed for a reach of the Arkansas River in Colorado, USA. Supporting spectroscopic analysis confirmed that saltcedar could not easily be discriminated from other riparian vegetation using TM5 data when in-leaf, but bare branches could be easily distinguished due to much lower reflectance than other riparian cover. Use of TM Band 4 (B4) allowed differentiation of wintertime saltcedar into four qualitative density classes judged from high-resolution low-oblique aerial photography: high (76%-100%), medium (51%-75%), low (16%-50%), and none (0%-15%). Spectral overlap was removed from the B4 saltcedar classification using TM Band 5 (B5) thresholds to eliminate low-reflectant wet areas and higher-reflectant multi-year darkened weed canopies. The accuracy of a classification algorithm that used B5 thresholds followed by a B4 density slice was judged against high-resolution aerial photography as providing 98% discrimination of saltcedar cover from other riparian cover and about 90% discrimination of the qualitative density classes. Applying this method to the 2835 km 2 riparian corridor study area, 1298 km 2 (45.78%) was identified as containing saltcedar, with over 43% having medium or greater density.