Hierarchical Object-Based Mapping of Riverscape Units and in-Stream Mesohabitats Using LiDAR and VHR Imagery

Abstract

Abstract:In this paper, we present a new, semi-automated methodology for mapping hydromorphological indicators of rivers at a regional scale using multisource remote sensing (RS) data. This novel approach is based on the integration of spectral and topographic information within a multilevel, geographic, object-based image analysis (GEOBIA). Different segmentation levels were generated based on the two sources of Remote Sensing (RS) data, namely very-high spatial resolution, near-infrared imagery (VHR) and high-resolution LiDAR topography. At each level, different input object features were tested with Machine Learning classifiers for mapping riverscape units and in-stream mesohabitats. The GEOBIA approach proved to be a powerful tool for analyzing the river system at different levels of detail and for coupling spectral and topographic datasets, allowing for the delineation of the natural fluvial corridor with its primary riverscape units (e.g., water channel, unvegetated sediment bars, riparian densely-vegetated units, etc.) and in-stream mesohabitats with a high level of accuracy, respectively of K = 0.91 and K = 0.83. This method is flexible and can be adapted to different sources of data, with the potential to be implemented at regional scales in the future. The analyzed dataset, composed of VHR imagery and LiDAR data, is nowadays increasingly available at larger scales, notably through European Member States. At the same time, this methodology provides a tool for monitoring and characterizing the hydromorphological status of river systems continuously along the entire channel network and coherently through time, opening novel and significant perspectives to river science and management, notably for planning and targeting actions.

RGB SAR products: methods and applications

“…In the following, we consider two applications: river morphology [Mangelsdorf et al, 2013] and urban area mapping. In river morphology, it is fundamental to extract precisely the stream contours, which is prior to the calculation of its geomorphological parameters [Demarchi et al, 2016]. Rivers are a sub-category of the macro-class "Water/Weak scatterers" we previously defined.…”

A Qualitative Hydro-Geomorphic Prediction of the Destiny of the Mojana Region (Magdalena-Cauca Basin, Colombia), to Inform Large Scale Decision Making

“…(v) Identification and measurement of morphological characteristics at different scales (e.g., the river valley, the floodplain, the bankfull, the islands, the bars, etc.) should be made at different time instants with an homogeneous approach-a process that requires a wide set of good quality, whole coverage, aerial or satellite photographs (a very interesting example is given in [44]). (vi) A geomorphic classification possibly based on the River Style approach (similar, but more refined than the Rapid River Assessment of Section 2.2, Table 3) would usefully identify homogeneous geomorphic reaches.…”

Multi-Temporal Image Analysis for Fluvial Morphological Characterization with Application to Albanian Rivers

“…Geospatial sciences, including geomatics and geostatistics, provide a wide set of tools that permit detection of water systems, such as rivers, and allow implementing models and processing procedures for the analysis of such resources. A wide range of river science topics and management applications has benefited from the use of satellite data, including river restoration [4][5][6][7], aquatic habitats characterization [8][9][10][11][12], understanding biodiversity and ecosystem functioning of riverine environments [12][13][14][15], hazard mapping and river management at the catchment scale [16][17][18], as well as mapping of morphological changes [19][20][21]. In addition, river studies can take advantage of the use of Digital Elevation Models (DEMs) and aerial orthophotos [11,17,22], where a more detailed dataset generally corresponds to a reduction of the covered area.…”

“…Manual operations are however particularly costly, especially for broad study areas to be analyzed over time. Classification techniques are also applied to multi-band imagery to detect water and vegetation classes [11,25,26]. In [27], the active channel was detected by means of proprietary software implementing an object-oriented classification algorithm.…”