Using VHR multispectral remote sensing and LIDAR data to determine the geomorphological effects of overbank flow on a floodplain (the Vistula River, Poland)

AbstractUsing remote sensing extended on geological and topographical maps and verified by the field work, we present the flood management and study the geomorphic features of the floodplain of a large, sand bed, untrained but embanked river in order to determine the flood hazard and to predict future flood scenarios. In geomorphological mapping, we focus on the landforms: crevasse channels and splays, flood basin, chute channels, side arms, floodplain channels, dunes and fields of aeolian sand. We base the flood risk assessment on consultations with environmental engineers who design new technical structures that control inundation (cut-off walls and lattice levees). We describe a levee breach as a result of piping (inner erosion) in a high hydraulic gradient condition and its effect (scour hole) as an erosional landform consistent with the repetitive pattern of erosion and deposition formed by an overbank flow on a floodplain. We reveal an existence of homogenous morphodynamic reaches in the river valley.

Download Full-text

Mapping the Urban Atmospheric Carbon Stock by LiDAR and WorldView-3 Data

Forests ◽

10.3390/f12060692 ◽

2021 ◽

Vol 12 (6) ◽

pp. 692

Author(s):

MD Abdul Mueed Choudhury ◽

Ernesto Marcheggiani ◽

Andrea Galli ◽

Giuseppe Modica ◽

Ben Somers

Keyword(s):

Remote Sensing ◽

Urban Area ◽

Tree Species ◽

Carbon Stock ◽

Dominant Species ◽

Remote Sensing Data ◽

Data Sources ◽

Lidar Data ◽

Urban Tree ◽

Sensing Data

Currently, the worsening impacts of urbanizations have been impelled to the importance of monitoring and management of existing urban trees, securing sustainable use of the available green spaces. Urban tree species identification and evaluation of their roles in atmospheric Carbon Stock (CS) are still among the prime concerns for city planners regarding initiating a convenient and easily adaptive urban green planning and management system. A detailed methodology on the urban tree carbon stock calibration and mapping was conducted in the urban area of Brussels, Belgium. A comparative analysis of the mapping outcomes was assessed to define the convenience and efficiency of two different remote sensing data sources, Light Detection and Ranging (LiDAR) and WorldView-3 (WV-3), in a unique urban area. The mapping results were validated against field estimated carbon stocks. At the initial stage, dominant tree species were identified and classified using the high-resolution WorldView3 image, leading to the final carbon stock mapping based on the dominant species. An object-based image analysis approach was employed to attain an overall accuracy (OA) of 71% during the classification of the dominant species. The field estimations of carbon stock for each plot were done utilizing an allometric model based on the field tree dendrometric data. Later based on the correlation among the field data and the variables (i.e., Normalized Difference Vegetation Index, NDVI and Crown Height Model, CHM) extracted from the available remote sensing data, the carbon stock mapping and validation had been done in a GIS environment. The calibrated NDVI and CHM had been used to compute possible carbon stock in either case of the WV-3 image and LiDAR data, respectively. A comparative discussion has been introduced to bring out the issues, especially for the developing countries, where WV-3 data could be a better solution over the hardly available LiDAR data. This study could assist city planners in understanding and deciding the applicability of remote sensing data sources based on their availability and the level of expediency, ensuring a sustainable urban green management system.

Download Full-text