Search Results (6)

Sediment transport in alluvial channels is strongly controlled by the grain-size distribution of bed and suspended materials. This, in turn, influences river morphology by modifying the cross-sectional area and course of the channel. Statistical parameters such as mean, standard deviation, skewness, and kurtosis provide quantitative indicators of the energy conditions that control sediment transport and deposition. This study examines the depositional characteristics of sediments in the Ganga River in Varanasi City, India, employing a novel combination of linear discriminant function (LDF) and sediment transport index (STI). The LDF results reveal distinct depositional environments: Y₁ and Y₂ values indicate deposition in a low-energy fluvial environment similar to beaches, Y₃ values suggest shallow marine settings, and Y₄ values point to mixed deltaic and turbid current depositional environments. Additionally, CM diagrams show rolling and suspension as the dominant sediment transport mechanisms. Shear stress analysis combined with STI highlights significant depositional features, with minimal erosion observed throughout the study area. The study provides an operational framework for mapping erosion-deposition patterns on alluvial point bars that are transferable to other sand-bed rivers worldwide where detailed hydraulic data are limited but detailed grain-size and DEM information are available. Full article

Wildfires can drastically alter ecological landscapes in just a few days, while it takes years of post-fire recovery for vegetation to return to its former pre-fire state. Assessing changes in vegetation can help with understanding how the hydrological components in the wildfire-affected areas contribute to potential vegetation shifts. This case study of the Los Angeles Bobcat Fire in 2020 uses Google Earth Engine (GEE) and Python 3.10.18 to access and visualize variations in Difference Normalized Burn Ratio (dNBR) area, Normalized Difference Vegetation Index (NDVI), and OpenET’s evapotranspiration (ET) across three dominant National Land Cover Database (NLCD) vegetation classes and dNBR classes via monthly time series and seasonal analysis from 2016 to 2024. Burn severity was determined based on Landsat-derived dNBR thresholds defined by the United Nations Office for Outer Space Affairs UN-Spider Knowledge Portal. Our study showed a general reduction in dNBR class area percentages, with High Severity (HS) dropping from 15% to 0% and Moderate Severity (MS) dropping from 45% to 10%. Low-Severity (LS) areas returned to 25% after increasing to 49% in May of 2022, led by vegetation growth. The remaining area was classified as Unburned and Enhanced Regrowth. Within our time series analysis, HS areas showed rapid growth compared to MS and LS areas for both ET and NDVI. Seasonal analysis showed most burn severity levels and vegetation classes increasing in median ET and NDVI values while 2024’s wet season median NDVI decreased compared to 2023’s wet season. Despite ET and NDVI continuing to increase post-fire, recent 2024 NLCD data shows most Forests and Shrubs remain as Grasslands, with small patches recovering to pre-fire vegetation. Using GEE, Python, and available satellite imagery demonstrates how accessible analytical tools and data layers enable wide-ranging wildfire vegetation studies, advancing our understanding of the impact wildfires have on ecosystems. Full article

With the online wildlife trade and the demand for viral videos increasing, the trade in primates on TikTok is becoming more prevalent. Despite wildlife trading being banned on most social media platforms, the trade in primates persists. TikTok’s policies ban the sale of live animals, and specific terms related to wildlife trading are banned; however, these search-term bans are easy to get around, and sellers are still prolific on the site. This study documented primates for sale on TikTok using the search term “for sale monkey” over a four-month period (from mid-July to mid-November 2023) with the aim of determining how widespread primate trade is on TikTok, the legality of advertisements, and which countries advertise the most primates for sale. In total, 43 individual advertisements were identified, spanning six different genera of primates and five different countries. Spider monkeys, rhesus macaques, and common marmosets were found to be the most commonly advertised species on TikTok. All the spider monkeys were advertised from the USA, while the majority of the marmosets were advertised from the UK, and all of the rhesus macaques were advertised from Pakistan. The USA was the only country identified in this study that advertised a range of species, and the only species found in this study that was not advertised in the USA was the mona monkey. In total, 44% of all species recorded were classified as either Endangered or Critically Endangered, and it was found that Endangered species were more frequently sold illegally than non-Endangered species. The findings of this study underline a need for stricter primate legislation and wildlife law enforcement, especially if the UN’s sustainable development goals are to be achieved by 2030. They also show a need for TikTok to broaden their restrictions on wildlife trading on their app. Full article

This communication informs on how the UN-SPIDER program of the United Nations Office for Outer Space Affairs contributes to the efforts of the United Nations’ system to mobilize international cooperation to mitigate the risks related to natural hazards, to coordinate disaster relief efforts, and to facilitate the links between disaster response and recovery. This communication presents information on how UN-SPIDER shapes its advisory support to developing countries to contribute to the institutionalization of the use of space-based data, information, products, and services by government agencies in charge of disaster management. It does so by providing examples of step-by-step procedures developed using open software and open satellite imagery; information regarding some of the efforts carried out by the program to facilitate access to space-based information provided by mechanisms established by the space community to support disaster response efforts worldwide; and information on its advisory support to developing countries, including training efforts. Lastly, this paper shows that the approach implemented by UN-SPIDER is allowing national disaster management agencies and other government agencies and ministries to institutionalize the use of space-based data, information, products, and services. Full article

There is still insufficient information available for a streamlined impact assessment of tropical cyclones on coastal habitats, particularly in the Mozambique Channel. Using Sentinel-1 and Sentinel-2 data, along with socio-ecological parameters including mangrove forest health and population density, we modeled the extent of flooding and its impact following the ‘severe tropical storm’ Ana which occurred between the 20 January until 25 January over the Mozambique Channel. Focusing on regions hit by Ana, namely the Sofala and Zambezia regions and the Boeny and Melaky provinces in Mozambique and Madagascar, respectively, we adapted a model by the United Nations Platform for Space-Based Information for Disaster Management and Emergency Response (UN-SPIDER) to effectively assess storm impacts at a resolution of up to 10 m. Our results showed that in Mozambique, more than 195,977 people have been potentially affected by Ana, while in Madagascar this number was down to 79,003. The central region of Zambezia accounted for the majority of flooding occurrences, although the Boeny province accounted for most of the flooding as a proportion of its total area. The Sofala region of Mozambique displayed the highest-affected population and highest-affected urban area, with 108,400 exposed people. However, it was found that only a small proportion of affected areas in all regions of interest (ROIs) were urban areas, accounting for 1.4% of the flooded areas on average. Low mangrove normalized-difference vegetation index (NDVI) changes between before the 2021–2022 cyclone season were found throughout all ROIs, despite the appearance of degraded mangrove patches in the proximity of barren areas at a fine scale (<20 m). Finally, it was found that healthy mangrove forest ecosystems in the Mozambique Channel were effective in protecting highly populated areas from cyclonic events for up to 40 km, on average. Full article

Eastern Cape Province in South Africa has experienced extreme drought events during the last decade. In South Africa, different land management systems exist belonging to two different land tenure classes: commercial large scale farming and communal small-scale subsistence farming. Communal lands are often reported to be affected by land degradation and drought events among others considered as trigger for this process. Against this background, we analyzed vegetation response to drought in different land management and land tenure systems through assessing vegetation productivity trends and monitoring the intensity, frequency and distribution of the drought hazard in grasslands and communal and commercial croplands during drought and non-drought conditions. For the observation period 2000–2016, we used time series of 250 m Vegetation Condition Index (VCI) based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) and Climate Hazard Group InfraRed Precipitation with Station data (CHIRPS) precipitation data with 5 km resolution. For the assessment of vegetation dynamics, we: (1) analyzed vegetation productivity in Eastern Cape over the last 16 years with EVI; (2) analyzed the impact of drought events on vegetation productivity in grasslands as well as commercial and communal croplands; and (3) compared precipitation-vegetation dynamics between the drought season 2015/2016 and the non-drought season 2011/2012. Change in total annual vegetation productivity could detect drought years while drought dynamics during the season could be rather monitored by the VCI. Correlation of vegetation condition and precipitation indicated areas experiencing significant vegetation productivity trends showing low and even negative correlation coefficients indicating other drivers for productivity change and drought impact besides rainfall. Full article