Droughts are amongst the most destructive natural disasters in the world. In large regions of Africa, where water is a limiting factor and people strongly rely on rain-fed agriculture, droughts have ...frequently led to crop failure, food shortages and even humanitarian crises. In eastern and southern Africa, major drought episodes have been linked to El Niño-Southern Oscillation (ENSO) events. In this context and with limited in-situ data available, remote sensing provides valuable opportunities for continent-wide assessment of droughts with high spatial and temporal resolutions. This study aimed to monitor agriculturally relevant droughts over Africa between 2000–2016 with a specific focus on growing seasons using remote sensing-based drought indices. Special attention was paid to the observation of drought dynamics during major ENSO episodes to illuminate the connection between ENSO and droughts in eastern and southern Africa. We utilized Tropical Rainfall Measuring Mission (TRMM)-based Standardized Precipitation Index (SPI) with 0 . 25 ∘ resolution and Moderate-resolution Imaging Spectroradiometer (MODIS)-derived Vegetation Condition Index (VCI) with 500 m resolution as indices for analysing the spatio-temporal patterns of droughts. We combined the drought indices with information on the timing of site-specific growing seasons derived from MODIS-based multi-annual average of Normalized Difference Vegetation Index (NDVI). We proved the applicability of SPI-3 and VCI as indices for a comprehensive continental-scale monitoring of agriculturally relevant droughts. The years 2009 and 2011 could be revealed as major drought years in eastern Africa, whereas southern Africa was affected by severe droughts in 2003 and 2015/2016. Drought episodes occurred over large parts of southern Africa during strong El Niño events. We observed a mixed drought pattern in eastern Africa, where areas with two growing seasons were frequently affected by droughts during La Niña and zones of unimodal rainfall regimes showed droughts during the onset of El Niño. During La Niña 2010/2011, large parts of cropland areas in Somalia (88%), Sudan (64%) and South Sudan (51%) were affected by severe to extreme droughts during the growing seasons. However, no universal El Niño- or La Niña-related response pattern of droughts could be deduced for the observation period of 16 years. In this regard, we discussed multi-year atmospheric fluctuations and characteristics of ENSO variants as further influences on the interconnection between ENSO and droughts. By utilizing remote sensing-based drought indices focussed on agricultural zones and periods, this study attempts to contribute to a better understanding of spatio-temporal patterns of droughts affecting agriculture in Africa, which can be essential for implementing strategies of drought hazard mitigation.
Large scale databases are critical for helping scientists decipher long-term patterns in human evolution. This paper describes the conception and development of such a research database and ...illustrates how big data can be harnessed to formulate new ideas about the past. The Role of Culture in Early Expansions of Humans (ROCEEH) is a transdisciplinary research center whose aim is to study the origins of culture and the multifaceted aspects of human expansions across Africa and Eurasia over the last three million years. To support its research, the ROCEEH team developed an online tool named the ROCEEH Out of Africa Database (ROAD) and implemented its web-based applications. ROAD integrates geographical data as well as archaeological, paleoanthropological, paleontological and paleobotanical content within a robust chronological framework. In fact, a unique feature of ROAD is its ability to dynamically link scientific data both spatially and temporally, thereby allowing its reuse in ways that were not originally conceived. The data stem from published sources spanning the last 150 years, including those generated by the research team. Descriptions of these data rely on the development of a standardized vocabulary and profit from online explanations of each table and attribute. By synthesizing legacy data, ROAD facilitates the reuse of heritage data in novel ways. Database queries yield structured information in a variety of interoperable formats. By visualizing data on maps, users can explore this vast dataset and develop their own theories. By downloading data, users can conduct further quantitative analyses, for example with Geographic Information Systems, modeling programs and artificial intelligence. In this paper, we demonstrate the innovative nature of ROAD and show how it helps scientists studying human evolution to access datasets from different fields, thereby connecting the social and natural sciences. Because it permits the reuse of "old" data in new ways, ROAD is now an indispensable tool for researchers of human evolution and paleogeography.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Approximately one million refugees of the Rohingya minority population in Myanmar crossed the border to Bangladesh on 25 August 2017, seeking shelter from systematic oppression and persecution. This ...led to a dramatic expansion of the Kutupalong refugee camp within a couple of months and a decrease of vegetation in the surrounding forests. As many humanitarian organizations demand frameworks for camp monitoring and environmental impact analysis, this study suggests a workflow based on spaceborne radar imagery to measure the expansion of settlements and the decrease of forests. Eleven image pairs of Sentinel-1 and ALOS-2, as well as a digital elevation model, were used for a supervised land cover classification. These were trained on automatically-derived reference areas retrieved from multispectral images to reduce required user input and increase transferability. Results show an overall decrease of vegetation of 1500 hectares, of which 20% were used to expand the camp and 80% were deforested, which matches findings from other studies of this case. The time-series analysis reduced the impact of seasonal variations on the results, and accuracies between 88% and 95% were achieved. The most important input variables for the classification were vegetation indices based on synthetic aperture radar (SAR) backscatter intensity, but topographic parameters also played a role.
In Ho Chi Minh City (HCMC), Vietnam, though at present flooding is merely a recurring nuisance, there is increasing concern that a combination of impending climate change and rapid urbanization will ...significantly exacerbate the situation. Given the significant measures taken in HCMC to reduce groundwater extraction and sea-level rise (SLR) inundation since the most recent subsidence studies, we aim to update and contribute to the subsidence information of HCMC with continuous temporal coverage from 2017 to 2019. In this study, we use Persistent Scatterer Interferometry (PSI) with Copernicus Sentinel-1 data and open source tools to determine current subsidence rates within the urban center of HCMC. Additionally, the scalability of this method and use of freely accessible data allows for continuous updating and monitoring of this high-vulnerability region. The observed average subsidence rates were 3.3 mm per year with a maximum local subsidence of 5.3 cm per year. These results largely align with findings of previous studies and reflect similar spatial distributed subsidence patterns. Inundation risk awareness is enhanced by not only continued improved subsidence analysis, but also incorporating latest advancements in Digital Elevation Model (DEM) accuracy. This study compares local differences between traditionally used AW3D30 DEM with the CoastalDEM. Our findings indicate that although we identify lower than previously accepted elevations in the urban core, that stabilization of subsidence is observed in this same region.
Ongoing urbanization leads to steady growth of urban areas. In the case of highly dynamic change of municipalities, due to the rates of change, responsible administrations often are challenged or ...struggle with capturing present states of urban sites or accurately planning future urban development. An interest for urban planning lies on socio-economic conditions, as consumption and production of disposable goods are related to economic possibilities. Therefore, we developed an approach to generate relevant parameters for infrastructure planning by means of remote sensing and spatial analysis. In this study, the single building defines the spatial unit for the parameters. In the case city Belmopan (Belize), based on WorldView-1 data we manually define a city covering building dataset. Residential buildings are classified to eight building types which are locally adapted to Belmopan. A random forest (RF) classifier is trained with locally collected training data. Through household interviews focusing on household assets, income and educational level, a socio-economic point (SEP) scaling is defined, which correlates very well with the defined building typology. In order to assign socio-economic parameters to the single building, five socio-economic classes (SEC) are established based on SEP statistics for the building types. The RF building type classification resulted in high accuracies. Focusing on the three categories to describe residential socio-economic states allowed high correlations between the defined building and socio-economic points. Based on the SEP we projected a citywide residential socio-economic building classification to support supply and disposal infrastructure planning.
In the face of growing 21st-century urban challenges, this study emphasizes the role of remote sensing data in objectively defining urban structure types (USTs) based on morphology. While numerous ...UST delineation approaches exist, few are universally applicable due to data constraints or impractical class schemes. This article attempts to tackle this challenge by summarizing important approaches dealing with the computation of USTs and to condense their contributions to the field of research within a single comprehensive framework. Hereby, this framework not only serves as a conjunctive reference for currently existing implementations, but is also independent regarding the input data, spatial scale, or targeted purpose of the mapping. It consists of four major steps: (1) the collection of suitable data sources to describe the building morphology as a key input, (2) the definition of a spatial mapping unit, (3) the parameterization of the mapping units, and (4) the final classification of the mapping units into urban structure types. We outline how these tasks can lead to a UST classification which fits the users’ needs based on their available input data. At the same time, the framework can serve as a protocol for future studies where USTs are mapped, or new approaches are presented. This article closes with an application example for three different cities to underline the flexibility and applicability of the proposed framework while maintaining maximized objectivity and comparability. We recommend this framework as a guideline for the use-specific mapping of USTs and hope to contribute to past and future research on this topic by fostering the implementation of this concept for the spatial analysis and a better understanding of complex urban environments.
The archaeological record is one piece of the puzzle in understanding the evolution of humans, helping to trace the cultural connections between different species and their technologies, as well as ...their expansion in time and space. Here we demonstrate a method for mapping the boundaries, centers, and peripheries of ancient cultures, as well as the technological similarities between different cultures. The proposed workflow includes: a systematic collection of archaeological information in a database; a process to infer the similarities between assemblages and generate a network; and finally, a graphical method for big data visualization, a technique also used in social media analysis. We present the geography of multiple cultural complexes that span several stages of cultural evolution from the Lower to the Upper Paleolithic (Stone Age) and involve several species of the genus Homo. Finally, we discuss some alternative trajectories in which this workflow can be developed further.
Soil erosion represents one of the most important global issues with serious effects on agriculture and water quality, especially in developing countries, such as Ethiopia, where rapid population ...growth and climatic changes affect widely mountainous areas. The Meskay catchment is a head catchment of the Jemma Basin draining into the Blue Nile (Central Ethiopia) and is characterized by high relief energy. Thus, it is exposed to high degradation dynamics, especially in the lower parts of the catchment. In this study, we aim at the geomorphological assessment of soil erosion susceptibilities. First, a geomorphological map was generated based on remote sensing observations. In particular, we mapped three categories of landforms related to (i) sheet erosion, (ii) gully erosion, and (iii) badlands using a high-resolution digital elevation model (DEM). The map was validated by a detailed field survey. Subsequently, we used the three categories as dependent variables in a probabilistic modelling approach to derive the spatial distribution of the specific process susceptibilities. In this study we applied the maximum entropy model (MaxEnt). The independent variables were derived from a set of spatial attributes describing the lithology, terrain, and land cover based on remote sensing data and DEMs. As a result, we produced three separate susceptibility maps for sheet and gully erosion as well as badlands. The resulting susceptibility maps showed good to excellent prediction performance. Moreover, to explore the mutual overlap of the three susceptibility maps, we generated a combined map as a color composite where each color represents one component of water erosion. The latter map yields useful information for land-use managers and planning purposes.
In this article we describe an online database about human evolution, called the ROCEEH Out of Africa Database (ROAD), and discuss our experience in aggregating Palaeolithic data from ROAD in the ...ARIADNE data processing pipeline. As of April 2023, ROAD contains more than 2400 localities in Africa and Eurasia dating between three million and 20,000 years ago. The database is transdisciplinary by nature and includes cultural artefacts, human and animal fossils, and plant remains. These finds are stored in a relational database, which is part of a structured, web-based, geographic information system. The process of preparing ROAD data for integration with ARIADNE taught us lessons about our own dataset, which we share here.
Vietnam is exposed to different types of floods that cause severe economic losses, damage to infrastructure, and loss of life. Reliable information on the drivers, patterns and dynamics of flood risk ...is crucial for the identification, prioritization and planning of risk reduction and adaptation measures. Here, we present a systematic review of existing flood risk assessments in Vietnam. We evaluate the current status, persisting gaps, and challenges regarding the understanding and assessment of flood risk in the country. The literature review revealed that: (i) 65 % of the reviewed papers did not provide a clear definition of flood risk, (ii) assessments had a tendency to prioritize physical and environmental drivers of risk over social, economic or governance‐related drivers, (iii) future‐oriented assessments tended to focus on hazard and exposure trends, while vulnerability scenarios were often lacking, (iv) large and middle‐sized cities were assessed more frequently than others, (v) only few studies engaged with relevant local stakeholders for the assessment of risk and the development of potential solutions, and (vi) ecosystem‐based adaptation and flood risk insurance solutions were rarely considered. Based on these findings, we point out several directions for future research on flood risk in Vietnam.