Stream channel erosion in a rapidly urbanizing region of the US–Mexico border: documenting the importance of channel hardpoints with Structure‐from‐Motion photogrammetry

Urbanization can lead to accelerated stream channel erosion, especially in areas experiencing rapid population growth, unregulated urban development on erodible soils, and variable enforcement of environmental regulations. A combination of field surveys and Structure‐from‐Motion (SfM) photogrammetry techniques was used to document spatial patterns in stream channel geometry in a rapidly urbanizing watershed, Los Laureles Canyon (LLCW), in Tijuana, Mexico. Ground‐based SfM photogrammetry was used to map channel dimensions with 1 to 2 cm vertical mean error for four stream reaches (100–300 m long) that were highly variable and difficult to survey with a differential GPS. Regional channel geometry curves for LLCW had statistically larger slopes and intercepts compared with regional curves developed for comparable, undisturbed reference channels. Cross‐sectional areas of channels downstream of hardpoints, such as concrete reaches or culverts, were up to 64 times greater than reference channels, with enlargement persisting, in some cases, up to 230 m downstream. Percentage impervious cover was not a good predictor of channel enlargement. Proximity to upstream hardpoint, and lack of riparian and bank vegetation paired with highly erodible bed and bank materials may account for the instability of the highly enlarged and unstable cross‐sections. Channel erosion due to urbanization accounts for approximately 25–40% of the total sediment budget for the watershed, and channel erosion downstream of hardpoints accounts for one‐third of all channel erosion. Channels downstream of hardpoints should be stabilized to prevent increased inputs of sediment to the Tijuana Estuary and local hazards near the structures, especially in areas with urban settlements near the stream channel. Copyright © 2017 John Wiley & Sons, Ltd.     

Using visibility analysis to improve point density and processing time of SfM-MVS techniques for 3D reconstruction of landforms

Image network geometry, including the number and orientation of images, impacts the error, coverage, and processing time of 3D terrain mapping performed using structure-from-motion and multiview-stereo (SfM-MVS). Few studies have quantified trade-offs in error and processing time or ways to optimize image acquisition in diverse topographic conditions. Here, we determine suitable camera locations for image acquisition by minimizing the occlusion produced by topography. Viewshed analysis is used to select the suitable images, which requires a preliminary digital elevation model (DEM), potential camera locations, and sensor parameters. One aerial and two ground-based image collections were used to analyse differences between SfM-MVS models produced using: (1) all available images (ALL); (2) images selected using conventional methods (CON); and (3) images selected using the viewshed analysis (VIEW). The resulting models were compared with benchmark point clouds acquired by a terrestrial laser scanner (TLS) and TLS-derived DEMs. The VIEW datasets produced denser point clouds (28–32% more points) and DEMs with up to 66% reduction in error compared with CON datasets due to reduction of gaps in the DEM. VIEW datasets reduced processing time by 37–76% compared with ALL, with no reduction in coverage or increase in error. DEMs produced with ALL and VIEW datasets had similar slope and roughness, while slight differences that may be locally important were observed for the CON dataset. The new method helps optimize SfM-MVS image collection strategies that significantly reduce the number of images required with minimal loss in coverage or accuracy over complex surfaces. © 2020 John Wiley & Sons, Ltd.     

Rapid increase in copper concentrations in a new marina, San Diego Bay

Concentrations of copper in water rose rapidly following the introduction of boats to a new marina in San Diego Bay. Two months after the marina reached half its capacity, a majority of water samples exceeded chronic and acute criteria for dissolved copper, and copper concentrations in several samples exceeded the highest concentrations observed in another marina that has been listed as an impaired water body. A box model suggested that a small fraction of the leached copper was sequestered in sediment. Copper concentrations in water entering the marina from the bay was more than half the chronic concentration limit, so only 50% of marina boat capacity could be accommodated without exceeding the chronic criterion more than 50% of the time. Copper concentrations in water may increase rapidly following boat introduction in small marinas, but could return to pre-introduction levels by controlling boat numbers or reducing use of copper-based paints.     

Next-generation robotic planetary reconnaissance missions: A paradigm shift

A fundamentally new scientific mission concept for remote planetary surface and subsurface reconnaissance will soon replace the engineering and safety constrained mission designs of the past, allowing for optimal acquisition of geologic, paleohydrologic, paleoclimatic, and possible astrobiologic information of Mars and other extraterrestrial targets. Traditional missions have performed local ground-level reconnaissance through rovers and immobile landers, or global mapping performed by an orbiter. The former is safety and engineering constrained, affording limited detailed reconnaissance of a single site at the expense of a regional understanding, while the latter returns immense datasets, often overlooking detailed information of local and regional significance. A “tier-scalable” paradigm integrates multi-tier (orbitatmosphereground) and multi-agent (orbiterblimpsrovers/sensorwebs) hierarchical mission architectures, not only introducing mission redundancy and safety, but enabling and optimizing intelligent, unconstrained, and distributed science-driven exploration of prime locations on Mars and elsewhere, allowing for increased science return, and paving the way towards fully autonomous robotic missions.     

Estimation of vegetation LAI from hyperspectral reflectance data: Effects of soil type and plant architecture

The retrieval of canopy biophysical variables is known to be affected by confounding factors such as plant type and background reflectance. The effects of soil type and plant architecture on the retrieval of vegetation leaf area index (LAI) from hyperspectral data were assessed in this study. In situ measurements of LAI were related to reflectances in the red and near-infrared and also to five widely used spectral vegetation indices (VIs). The study confirmed that the spectral contrast between leaves and soil background determines the strength of the LAI–reflectance relationship. It was shown that within a given vegetation species, the optimum spectral regions for LAI estimation were similar across the investigated VIs, indicating that the various VIs are basically summarizing the same spectral information for a given vegetation species. Cross-validated results revealed that, narrow-band PVI was less influenced by soil background effects (0.15 ≤ RMSE_cv ≤ 0.56). The results suggest that, when using remote sensing VIs for LAI estimation, not only is the choice of VI of importance but also prior knowledge of plant architecture and soil background. Hence, some kind of landscape stratification is required before using hyperspectral imagery for large-scale mapping of vegetation biophysical variables.     

MERIS and the red-edge position

The Medium Resolution Imaging Spectrometer (MERIS) is a payload component of Envisat-1. MERIS will be operated over land with a standard 15 band setting acquiring images with a 300 m spatial resolution. The red-edge position (REP) is a promising variable for deriving foliar chlorophyll concentration, which plays an important role in ecosystem processes. The objectives of this paper are: (1) to study which factors effect the REP of vegetation, (2) to study whether this REP can be derived from the MERIS standard band setting and (3) to show what REP represents at the scale of MERIS data. Two different data sets were explored for simulating the REP using MERIS bands: (1) simulated data using reflectance models and (2) airborne reflectance spectra of an agricultural area obtained by the airborne visible-infrared imaging spectrometer (AVIRIS). A “linear method”, assuming a straight slope of the reflectance spectrum around the midpoint of the slope, was a robust method for determining the REP and the MERIS bands at 665, 708.75, 753.75 and 778.75 nm could be used for applying the “linear method” for REP estimation. Results of the translation to the scale of MERIS data were very promising for applying MERIS at, for instance, the ecosystem level.