Diffuse Attenuation Coefficient (Kd) from ICESat-2 ATLAS Spaceborne Lidar Using Random-Forest Regression

This study investigates a new method for measuring water turbidity—specifically, the diffuse attenuation coefficient of downwelling irradiance Kd —using data from a spaceborne, green-wavelength lidar aboard the National Aeronautics and Space Administration's ICESat-2 satellite. The method enables us to fill nearshore data voids in existing Kd data sets and provides a more direct measurement approach than methods based on passive multispectral satellite imagery. Furthermore, in contrast to other lidar-based methods, it does not rely on extensive signal processing or the availability of the system impulse response function, and it is designed to be applied globally rather than at a specific geographic location. The model was tested using Kd measurements from the National Oceanic and Atmospheric Administration's Visible Infrared Imaging Radiometer Suite sensor at 94 coastal sites spanning the globe, with Kd values ranging from 0.05 to 3.6 m –1 . The results demonstrate the efficacy of the approach and serve as a benchmark for future machine-learning regression studies of turbidity using ICESat-2.

Effects of biological works within the integrated watershed management of torrent catchments in the area of Grdelica Gorge and Vranjska Valley (Serbia)

Integrated watershed management is based on the application of various biological and technical works, and administration measure to reduce the degradation process. The paper presents an analysis of the effects of performed biological works as part of integrated watershed management within the Grdelica Gorge and Vranjska Valley. Extensive erosion control works were carried out in the second half of the 20th century. As vegetation is one of the key factors in mitigating the erosion process, the paper presents the trend of connecting the surface with the vegetation cover, which results from implemented biological measures. Using multispectral satellite imagery (Landsat missions) for 1972, 1986, 1996, and 2017, the vegetation index (Normalized Difference Vegetation Index – NDVI) was analyzed in torrent basins, which were afforested to control severe erosion processes. The increasing trend of vegetated areas was recorded in period from 1986 to 1996 (very low vegetation coverage 40.19 % in 1986 and 8.19 % in 1996, respectively), which continues to grow until 2017 when the very low vegetation coverage was 0.26 %, and moderately high vegetation coverage was 50.63 %.

The Prospect of Global Coral Reef Bathymetry by Combining Ice, Cloud, and Land Elevation Satellite-2 Altimetry With Multispectral Satellite Imagery

Empirical methods for estimating shallow-water bathymetry using passive multispectral satellite imagery are robust and globally applicable, in theory, but they require copious local measurements of water depth for algorithm calibration. Such calibration data have historically been unavailable for most locations, but NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), a satellite-based LiDAR, might hold unique promise to fill this critical data gap. Although ICESat-2 was not designed as a marine altimeter, its ATLAS sensor consists of six green (532 nm) lasers that can penetrate a water surface and return photons reflected by the seabed, thereby generating bathymetric profiles. Utilizing TCarta’s NSF SBIR-funded Space-Based Laser Bathymetry Extraction Tool and ICESat-2’s ATL03 geolocated photon data product, we have compared ICESat-2 bathymetric retrievals with a portfolio of soundings acquired in situ using a vessel-mounted single-beam echosounder. This analysis demonstrated very high correlation (R2 = 0.96) between the field and space-based bathymetry data. The comparisons were made at multiple Caribbean and Pacific coral reef sites over water depths ranging from 1 to 20 m. Results suggest that ICESat-2 could be an effective approach for calibrating and validating empirical and radiative transfer methods, alike, for estimating shallow-water bathymetry from remote sensing imagery, thereby enabling the immediate potential for shallow-water bathymetric mapping of Earth’s reefs.

The Accuracy of Satellite Derived Bathymetry in Coastal and Shallow Water Zone

Precise and accurate bathymetric measurements are conventionally acquired by means of ship-based acoustic equipment. Nevertheless, recent multispectral satellite imagery has been utilised as a substitute source to map the seabed topography which indicates new revolution in hydrographic surveying. This study assesses the satellite bathymetric depth’s accuracy based on the vertical uncertainty as stated in the Standards for Hydrographic Surveys issued by the International Hydrographic Organization. Two empirical algorithms, namely, Dierssen’s and Stumpf’s approaches have been adopted to model the seafloor topography over the coastal and shallow water at Tanjung Kupang, Malaysia. The outcomes demonstrate a decent correlation between the derived water depths and the sounding values acquired from a ship-based acoustic survey. For instance, a total of 1,215 out of the 1,367 generated water depths by Stumpf’s model have hit the minimum standard of survey in S-44. Similarly, out of the 1,367 samples from Diessen’s model, 1,211 samples have met the minimum requirement listed in the survey standard. The results demonstrate both imageries derived bathymetry models convey promising results which can be ultilised for bathymetric mapping application. Therefore, this imagery derived bathymetry can be considered as an alternative bathymetric surveying technique to supply cost-effective solution and survey data to support the Blue Economy and Sustainable Development Goals 14.

Post-Hurricane Vegetative Debris Assessment Using Spectral Indices Derived from Satellite Imagery

Transportation systems are vulnerable to hurricanes and yet their recovery plays a critical role in returning a community to its pre-hurricane state. Vegetative debris is among the most significant causes of disruptions on transportation infrastructure. Therefore, identifying the driving factors of hurricane-caused debris generation can help clear roadways faster and improve the recovery time of infrastructure systems. Previous studies on hurricane debris assessment are generally based on field data collection, which is expensive, time consuming, and dangerous. With the availability and convenience of remote sensing powered by the simple yet accurate estimations on the vigor of vegetation or density of manufactured features, spectral indices can change the way that emergency planners prepare for and perform vegetative debris removal operations. Thus, this study proposes a data fusion framework combining multispectral satellite imagery and various vector data to evaluate post-hurricane vegetative debris with an exploratory analysis in small geographical units. Actual debris removal data were obtained from the City of Tallahassee, Florida after Hurricane Michael (2018) and aggregated into U.S. Census Block Groups along with four groups of datasets representing vegetation, storm surge, land use, and socioeconomics. Findings suggest that vegetation and other land characteristics are more determinant factors on debris generation, and Modified Soil-Adjusted Vegetation Index (MSAVI2) outperforms other vegetation indices for hurricane debris assessment. The proposed framework can help better identify equipment stack locations and temporary debris collection centers while providing resilience enhancements with a focus on the transportation infrastructure.