Large Area Aboveground Biomass and Carbon Stock Mapping in Woodlands in Mozambique with L-band Radar: Improving Accuracy by Accounting for Soil Moisture Effects Using the Water Cloud Model

Soil moisture effects limit radar-based aboveground biomass carbon (AGBC) prediction accuracy as well as lead to stripes between adjacent paths in regional mosaics due to varying soil moisture conditions on different acquisition dates. In this study, we utilised the semi-empirical water cloud model (WCM) to account for backscattering from soil moisture in AGBC retrieval from L-band radar imagery in central Mozambique, where woodland ecosystems dominate. Cross-validation results suggest that (1) the standard WCM effectively accounts for soil moisture effects, especially for areas with AGBC ≤ 20 tC/ha, and (2) the standard WCM significantly improved the quality of regional AGBC mosaics by reducing the stripes between adjacent paths caused by the difference in soil moisture conditions between different acquisition dates. By applying the standard WCM, the difference in mean predicted AGBC for the tested path with the largest soil moisture difference was reduced by 18.6%. The WCM is a valuable tool for AGBC mapping by reducing prediction uncertainties and striping effects in regional mosaics, especially in low-biomass areas including African woodlands and other woodland and savanna regions. It is repeatable for recent L-band data including ALOS-2 PALSAR-2, and upcoming SAOCOM and NISAR data.

Nautical Tourism in Marine Protected Areas (MPAs): Evaluating an Impact of Copper Emission from Antifouling Coating

Copper (Cu) has a narrow range between optimal concentrations as a micronutrient critical for phytoplankton growth and concentrations potentially toxic to living organisms. This sensitivity indicates an ecosystem vulnerability that threatens not only nature but also human health due to bioaccumulation. An important source of elevated Cu concentrations in coastal environments are biocides used as antifouling protection on ships. A pilot study conducted in the Marine Protected Area (MPA) of the Krka Estuary (Croatia) over a period of 16 months investigated the relationship between ship traffic and Cu concentrations. The aim was to contribute to more informed environmental management by assessing the associated risks. In the study presented here, Cu concentrations were monitored, analyzed, and correlated with vessel traffic. Observations revealed that the seasonal increase in maritime traffic caused by nautical tourism was associated with an increase in Cu concentrations of more than five times, posing a toxicity risk to the environment. In order to understand the distribution of copper emissions, a mapping of maritime traffic was carried out by counting transits, radar imagery, and drone photography. This approach has proven sufficient to identify the potential risks to the marine environment and human health, thus providing an effective assessment tool for marine stakeholders.

Evaluation of Satellite Imagery for Monitoring Pacific Walruses at a Large Coastal Haulout

Pacific walruses (Odobenus rosmarus divergens) are using coastal haulouts in the Chukchi Sea more often and in larger numbers to rest between foraging bouts in late summer and autumn in recent years, because climate warming has reduced availability of sea ice that historically had provided resting platforms near their preferred benthic feeding grounds. With greater numbers of walruses hauling out in large aggregations, new opportunities are presented for monitoring the population. Here we evaluate different types of satellite imagery for detecting and delineating the peripheries of walrus aggregations at a commonly used haulout near Point Lay, Alaska, in 2018–2020. We evaluated optical and radar imagery ranging in pixel resolutions from 40 m to ~1 m: specifically, optical imagery from Landsat, Sentinel-2, Planet Labs, and DigitalGlobe, and synthetic aperture radar (SAR) imagery from Sentinel-1 and TerraSAR-X. Three observers independently examined satellite images to detect walrus aggregations and digitized their peripheries using visual interpretation. We compared interpretations between observers and to high-resolution (~2 cm) ortho-corrected imagery collected by a small unoccupied aerial system (UAS). Roughly two-thirds of the time, clouds precluded clear optical views of the study area from satellite. SAR was unaffected by clouds (and darkness) and provided unambiguous signatures of walrus aggregations at the Point Lay haulout. Among imagery types with 4–10 m resolution, observers unanimously agreed on all detections of walruses, and attained an average 65% overlap (sd 12.0, n 100) in their delineations of aggregation boundaries. For imagery with ~1 m resolution, overlap agreement was higher (mean 85%, sd 3.0, n 11). We found that optical satellite sensors with moderate resolution and high revisitation rates, such as PlanetScope and Sentinel-2, demonstrated robust and repeatable qualities for monitoring walrus haulouts, but temporal gaps between observations due to clouds were common. SAR imagery also demonstrated robust capabilities for monitoring the Point Lay haulout, but more research is needed to evaluate SAR at haulouts with more complex local terrain and beach substrates.

New systemically measured sand mining budget for the Mekong Delta reveals rising trends and significant volume underestimations

The river beds of the Mekong Delta are some of the most intensively sand mined places in the world, however sand mining budgets are limited to rough and indirect estimates. Here, we provide a systematic, semi-physically based estimation of the Mekong Delta’s sand mining budget. We provide a quantified budget that overcomes limitations resulting from previous reliance on officially declared statistics and bathymetric surveys of short channel reaches. We apply Sentinel-1 radar imagery to monitor the distribution of sand mining activities using boat metrics-driven mining intensity maps correlated with a field-based bathymetry difference map derived from two extensive bathymetric surveys of ~100 km reaches in the Tiền River conducted in 2014 and 2017 that cover ~15% of the Mekong Delta. We then extrapolate the Tiền River findings to the broader Vietnamese Mekong Delta from 2015 to 2020 and measure a continuous increase of the extraction budget by ~25% between 2015 (38 Mm3/yr) and 2020 (47 Mm3/yr). We estimate a total sand mining budget of 254 Mm3 during the 6-year study period with an average annual rate of ~42 Mm3. Our semi-physically based annual rate differs from both official declarations provided and estimates from previous studies implying that a substantial portion of sand mining budget remains unaccounted for. Riverbed sand mining remains key threat to the Mekong Delta as it exacerbates or contributes to a multitude of other threats including dam construction effects on sedimentation, ongoing subsidence, sea level rise and recurring salt intrusion. This integrated study offers a new method that is readily implementable elsewhere to allow for extensive monitoring and quantification of sand mining activities that are vital for assessing future projections on environmental impacts.

A New Approach for the Analysis of Deep Convective Events: Thunderstorm Intensity Index

In this study, an investigation of a new thunderstorm intensity index (TSII) derived from lightning data is performed, along with its relationship to rain, wind, hail and waterspouts as well as instability indices (CAPE, LI, KI, and DLS). The study area is located in the northeastern Adriatic and includes various terrain types in a relatively small area (coastal, flatlands, hills and valleys, and mountain regions). The investigated period covers 11 years (2008–2018). The mathematical algorithm standing behind the TSII is based on the well-established methodology of lightning jump, allowing us to recognize areas where intensification in thunderstorms occurred. Our results suggest that these areas (with a positive TSII) experience significantly higher rain intensities and have higher total amounts of precipitation compared with areas where thunderstorms did not generate a TSII. Moreover, 76% of thunderstorm hail cases were associated with the presence of a TSII within a 15 km distance. The maximum reported wind speed also has higher values on a day with a TSII. Out of 27 waterspout events associated with lightning, 77% were related to a TSII. Due to the good spatial (3 km × 3 km) and high temporal (2 min) resolution of lightning data, the TSII can recognize even a local and short-lived intense system that is often misread by radars and satellites due to their inferior temporal resolution. The TSII is designed to be used as a climatological and diagnostic variable that could serve in lieu of more established data sources (e.g., station measurements and observations, radar imagery, etc.) if they are unavailable.