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

Remote Sensing

Kasper Johansen³  Dirk Tiede²  Thomas Blaschke²  Lara A. Arroyo¹ 

[1] Centro de Investigacion del Fuego, Fundacion General del Medio Ambiente de Castilla La Mancha, 45071 Toledo, Spain; E-Mail:;Z_GIS Centre for Geoinformatics, Salzburg University, Schillerstrasse 30, 5020 Salzburg, Austria; E-Mails:;Joint Remote Sensing Research Program, Centre for Spatial Environmental Research, School of Geography and Environmental Management, The University of Queensland, Brisbane, QLD 4072, Australia; E-Mail:

关键词: geographic object based image analysis (GEOBIA);    LiDAR;    streambed;    riparian zone;    Australia;    pixel-based object resizing;   

DOI  :  10.3390/rs3061139

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.