Remote Sens. 2011, 3(6), 1139-1156; doi:10.3390/rs3061139
Article

Automatic Geographic Object Based Mapping of Streambed and Riparian Zone Extent from LiDAR Data in a Temperate Rural Urban Environment, Australia

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Received: 12 April 2011; in revised form: 5 May 2011 / Accepted: 17 May 2011 / Published: 30 May 2011
(This article belongs to the Special Issue Object-Based Image Analysis)
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Abstract: This research presents a time-effective approach for mapping streambed and riparian zone extent from high spatial resolution LiDAR derived products, i.e., digital terrain model, terrain slope and plant projective cover. Geographic object based image analysis (GEOBIA) has proven useful for feature extraction from high spatial resolution image data because of the capacity to reduce effects of reflectance variations of pixels making up individual objects and to include contextual and shape information. This functionality increases the likelihood of developing transferable and automated mapping approaches. LiDAR data covered parts of the Werribee Catchment in Victoria, Australia, which is characterized by urban, agricultural, and forested land cover types. Field data of streamside vegetation structure and physical form properties were used for both calibration of the mapping routines and validation of the mapping results. To improve the transferability of the rule set, the GEOBIA approach was developed for an area representing different riparian zone environments, i.e., urbanized, agricultural and hilly forested areas. Results show that mapping streambed extent (R2 = 0.93, RMSE = 3.6 m, n = 35) and riparian zone extent (R2 = 0.74, RMSE = 3.9, n = 35) from LiDAR derived products can be automated using GEOBIA to enable derivation of spatial information in an accurate and time-effective manner suited for natural resource management agencies.
Keywords: geographic object based image analysis (GEOBIA); LiDAR; streambed; riparian zone; Australia; pixel-based object resizing
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Johansen, K.; Tiede, D.; Blaschke, T.; Arroyo, L.A.; Phinn, S. Automatic Geographic Object Based Mapping of Streambed and Riparian Zone Extent from LiDAR Data in a Temperate Rural Urban Environment, Australia. Remote Sens. 2011, 3, 1139-1156.

AMA Style

Johansen K, Tiede D, Blaschke T, Arroyo LA, Phinn S. Automatic Geographic Object Based Mapping of Streambed and Riparian Zone Extent from LiDAR Data in a Temperate Rural Urban Environment, Australia. Remote Sensing. 2011; 3(6):1139-1156.

Chicago/Turabian Style

Johansen, Kasper; Tiede, Dirk; Blaschke, Thomas; Arroyo, Lara A.; Phinn, Stuart. 2011. "Automatic Geographic Object Based Mapping of Streambed and Riparian Zone Extent from LiDAR Data in a Temperate Rural Urban Environment, Australia." Remote Sens. 3, no. 6: 1139-1156.


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