Global assessment of sand and dust storms

The specific objectives of the assessment are to: 1) Synthesise and highlight the environmental and socio-economic causes and impacts of SDS, as well as available technical measures for their mitigation, at the local, regional and global levels; 2) Show how the mitigation of SDS can yield multiple sustainable development benefits; 3) Synthesize information on current policy responses for mitigating SDS and 4) Present options for an improved strategy for mitigating SDS at the local, regional and global levels, building on existing institutions and agreements

Numerical simulation of Tehran dust storm on 2 june 2014: A case study of agricultural abandoned lands as emission sources

On 2 June 2014, at about 13 UTC, a dust storm arrived in Tehran as a severe hazard that caused injures, deaths, failures in power supply, and traffic disruption. Such an extreme event is not considered as common for the Tehran area, which has raised the question of the dust storm’s origin and the need for increasing citizens’ preparedness during such events. The analysis of the observational data and numerical simulations using coupled dust-atmospheric models showed that intensive convective activity occurred over the south and southwest of Tehran, which produced cold downdrafts and, consequently, high-velocity surface winds. Different dust source masks were used as an input for model hindcasts of the event (forecasts of the past event) to show the capability of the numerical models to perform high-quality forecasts in such events and to expand the knowledge on the storm’s formation and progression. In addition to the proven capability of the models, if engaged in operational use to contribute to the establishment of an early warning system for dust storms, another conclusion appeared as a highlight of this research: abandoned agricultural areas south of Tehran were responsible for over 50% of the airborne dust concentration within the dust storm that surged through Tehran. Such a dust source in the numerical simulation produced a PM10 surface dust concentration of several thousand µm/m3, which classifies it as a dust source hot-spot. The produced evidence indivisibly links issues of land degradation, extreme weather, environmental protection, and health and safety

Kartographie, Natural Resource Management

Die Technologien und Systeme im Bereich der satellitengestützten Erdbeobachtung haben sich in den letzten drei Jahrzehnten rasant entwickelt. Die Folge ist eine Fülle von Aufnahmesystemen und Bilddaten, die für zahlreiche Anwendungen im Bereich der Erderkundung heran gezogen werden können. Da die überwiegende Anzahl der Sensorsysteme für spezifische Applikationen ausgelegt ist, sind die Auswertemethoden und Strategien entsprechend vielfältig. Entsprechend werden Datensätze produziert, die für einige Anwendungen sehr nützlich sind, für andere aber unvollständig oder redundant. Die mathematische Fusion von Datensätzen unterschiedlicher Auflösung (geometrisch, spektral, zeitlich) bietet hierbei die Möglichkeit, mehrere Datensätze zu kombinieren und hierdurch das Informationspotenzial für die Auswertung zu optimieren. Datenfusion kann üblicher Weise in drei verschiedenen Ebenen durchgeführt werden: 1.) auf der Pixelebene, 2.) auf der Objektebene und 3.) auf der Entscheidungsebene.In der vorliegenden Arbeit wurden Konzepte und Techniken zur Fusion satellitengestützter Fernerkundungsdaten evaluiert und weiter entwickelt. Die Bewertung der Güte einer Fusion erfolgte vor dem Hintergrund der Anwendung im Bereich der visuellen Interpretation der Datensätze sowie zum Zwecke der Landnutzungskartierung auf Basis der verwendeten Datenquellen. Die untersuchten Datensätze entstammen der Erdbeobachtungsmission Earth Observation One (EO-1) der National Aeronautics and Space Administration (NASA) der USA. Die verwendeten Sensoren sind Hyperion (hyperspektral), ALI-ms (multispektral) und ALI-pan (panchromatisch).Im ersten Teil der Arbeit wurden Verfahren auf der Pixelebene evaluiert. Der zweite Teil der Arbeit beschäftigt sich mit dem Vergleich von Verfahren auf der Entscheidungsebene. In beiden Teilen der Arbeit wurden sowohl bestehende Verfahren evaluiert als auch neue Methoden implementiert (z. B. Radon und Fanbeam Fusion, Wavelength Based Decision Fusion und andere). Die Qualitätsanalyse der Fusionsmethoden erfolgte auf Basis visueller Vergleiche sowie statistischer Parameter (z. B. Maximum Spectral and Spatial Information Indicator, Transformed Divergence und andere). Abschließend wurde der Einsatz der bewerteten Fusionsmethoden für potenzielle Anwendungen im Bereich geographischer Fragestellungen diskutiert

Post-War Urban Damage Mapping Using InSAR: The Case of Mosul City in Iraq

Urban infrastructures have become imperative to human life. Any damage to these infrastructures as a result of detrimental activities would accrue huge economical costs and severe casualties. War in particular is a major anthropogenic calamity with immense collateral effects on the social and economic fabric of human nations. Therefore, damaged buildings assessment plays a prominent role in post-war resettlement and reconstruction of urban infrastructures. The data-analysis process of this assessment is essential to any post-disaster program and can be carried out via different formats. Synthetic Aperture Radar (SAR) data and Interferometric SAR (InSAR) techniques help us to establish a reliable and fast monitoring system for detecting post-war damages in urban areas. Along this thread, the present study aims to investigate the feasibility and mode of implementation of Sentinel-1 SAR data and InSAR techniques to estimate post-war damage in war-affected areas as opposed to using commercial high-resolution optical images. The study is presented in the form of a survey to identify urban areas damaged or destroyed by war (Islamic State of Iraq and the Levant, ISIL, or ISIS occupation) in the city of Mosul, Iraq, using Sentinel-1 (S1) data over the 2014–2017 period. Small BAseline Subset (SBAS), Persistent Scatterer Interferometry (PSI) and coherent-intensity-based analysis were also used to identify war-damaged buildings. Accuracy assessments for the proposed SAR-based mapping approach were conducted by comparing the destruction map to the available post-war destruction map of United Nations Institute for Training and Research (UNITAR); previously developed using optical very high-resolution images, drone imagery, and field visits. As the findings suggest, 40% of the entire city, the western sectors, especially the Old City, were affected most by ISIS war. The findings are also indicative of the efficiency of incorporating Sentinel-1 SAR data and InSAR technique to map post-war urban damages in Mosul. The proposed method could be widely used as a tool in damage assessment procedures in any post-war reconstruction programs

Multi-Source Remotely Sensed Data Combination: Projection Transformation Gap-Fill Procedure

In this work a new gap-fill technique entitled projection transformation has been developed and used for filling missed parts of remotely sensed imagery. In general techniques for filling missed area of an image are broken down into three main categories: multi-source techniques that take the advantages of other data sources (e.g. using cloud free images to reconstruct the cloudy areas of other images); the second ones fabricate the gap areas using non-gapped parts of an image itself, this group of techniques are referred to as single-source gap-fill procedures; and third group contains methods that make up a combination of both mentioned techniques, therefore they are called hybrid gap-fill procedures. Here a new developed multi-source methodology called projection transformation for filling a simulated gapped area in the Landsat7/ETM+ imagery is introduced. The auxiliary imagery to filling the gaps is an earlier obtained L7/ETM+ imagery. Ability of the technique was evaluated from three points of view: statistical accuracy measuring, visual comparison, and post classification accuracy assessment. These evaluation indicators are compared to the results obtained from a commonly used technique by the USGS as Local Linear Histogram Matching (LLHM) [1]. Results show the superiority of our technique over LLHM in almost all aspects of accuracy

Dust in Western Iran: the emergence of new sources in response to shrinking water bodies

Abstract We detected sources of dust in the Middle East that contribute to dust events in Western Iran in different seasons. By the analysis of the synoptic data, we identified 309 dusty days in Western Iran during the period 2000–2016. A dusty day is diagnosed if under low horizontal visibility (< 1 km), the dust in suspension is reported at least once a day in at least three synoptic stations. We identified dust sources in the Middle East based on the analysis of the MOD04L2 data from MODIS, the backward HYSPLIT trajectory model, and synoptic conditions. The most influential sources affecting Western Iran are located on the shore and northwest of Lake Tharthar, Hour-al-Azim Marsh, the shore of Razzaza, Habbaniyah Lakes, and West Hammar Marsh, which contributed to 110, 79, 59, 56, and 51 dusty days, respectively. The fluctuation of the surface water area largely contributes to the variability of dusty days in Western Iran. Indeed, the peak dust activity in Western Iran was during the period 2008–2012 in response to the substantial shrinkage of the main water bodies in Iraq. The main sources of dust influencing Western Iran are located in northern and eastern Saudi Arabia in spring, Deir ez-Zur in Syria’s Aleppo and Raqqa in summer, and Syria’s Homs and Al-Hasakah in winter and spring. Sources of dust in Western Iraq and in most parts of entire Iraq have, respectively, led to the formation of summer and spring dust events in Western Iran. Decreased precipitation in the Middle East from autumn 2007 to 2012 and the occurrence of severe droughts have also contributed to the shrinkage of lakes and wetlands, as well as the reduced agricultural productivity in the Middle East, all of which contributed to the intensification of dust activity in Western Iran in recent decades

Characterization of Hydrologic Sand and Dust Storm Sources in the Middle East

Due to diverse hydroclimatic conditions and human interventions, the Middle East hosts a variety of active sources of sand and dust storms (SDS). Discrimination of different types of SDS sources is the most important factor for adopting optimal mitigation measures to combat SDS. This study employed a binary mask-based modeling framework to identify Middle East SDS sources. Accordingly, using time series of remotely sensed data of land surface and atmospheric aerosol parameters, SDS sources covering an area of 1 million Km2 were identified with an overall accuracy of 82.6%. Considering the type of land use and spatial-temporal changes in water bodies, SDS sources were categorized into seven types in terms of origin. Desert sources have the largest share (>79%), whereas hydrologic sources accounted for about 8.4%. The results showed that water bodies had a declining trend after 2000. The occurrence of two severe drought periods in 2000–2001 and 2007–2012 led to a 52% decrease in water bodies and a 14–37% increase in SDS emission compared to the pre-2000 period. The latter drought period also led to a sharp decrease in groundwater resources across the region. Our results revealed that natural circumstances and drought actively contribute to the depletion of water resources that led to the formation of SDS sources in the Middle East, while the role of anthropogenic factors is predominant in the case of hydrologic SDS sources