Remote Sensing Applications to Support Locust Management and Research: Evaluating the Potential of Earth Observation for Locust Outbreaks in Different Regions

This dissertation focuses on satellite remote sensing applications for locust management and additional contributions to locust research. Specifically, the remote sensing-based characterization and interpretation of land surface cover and its dynamics are addressed with a special emphasis on the requirements of different locust species. At first, the aim of this dissertation is to provide a holistic overview of the existing applications using satellite data focusing on different locust species and thus, to present current and new opportunities. Furthermore, remote sensing and geospatial datasets are used in a model to categorize areas with ideal and less than ideal conditions for locust outbreaks. The benefit of up-to-date remote sensing data for preventive locust management is demonstrated using time-series-based Sentinel-2 land cover classification. Due to the diversity of the numerous locust species and their spatial distribution in different geographical locations, this research focuses mainly on two locust species, the Italian locust (Calliptamus italicus) and the Moroccan locust (Dociostaurus maroccanus), as well as on selected study areas within their extensive habitats, respectively. Both selected locust species caused numerous damages in Europe, the Caucasus, Central Asia and North Africa in the past. For both species, there is only a limited number of publications exploiting the capabilities of remote sensing methods. Therefore, this dissertation aims to explore the potential approaches of Earth observation datasets to support preventive locust management and research for both species.Die vorliegende Dissertation beschäftigt sich mit dem Einsatz der Satellitenfernerkundung im Bereich Heuschreckenmanagement und -forschung. Die fernerkundungsbasierte Charakterisierung und Interpretation der Landoberflächen-bedeckung und deren Dynamik stehen dabei - mit Fokus auf die Anforderungen der verschiedenen Heuschreckenarten - im Vordergrund. Ziel dieser Dissertation ist es zunächst, einen ganzheitlichen Überblick über vorhandene Anwendungen von Satellitendaten im Kontext Heuschreckenmanagement zu erarbeiten. Des Weiteren werden fernerkundungs- und geobasierten Datensätzen in einem Model verwendet, um Flächen mit idealen bzw. weniger idealen Bedingungen für Heuschreckenausbrüche zu kategorisieren. Der Vorteil von aktuellen Fernerkundungsdaten für präventives Heuschreckenmanagement wird anhand zeitreihenbasierten Sentinel-2 Landbedeckungsklassifikation demonstriert. Aufgrund der Vielfältigkeit der zahlreichen Heuschreckenarten und deren räumlicher Verteilung in verschiedenen geographischen Lagen, konzentriert sich diese Arbeit im Wesentlichen auf zwei Heuschreckenarten, die Italienische Schönschrecke (Calliptamus italicus) und die Marokkanische Wanderheuschrecke (Dociostaurus maroccanus), sowie auf ausgewählte Studiengebiete innerhalb deren weiträumigen Habitaten. Beide Heuschreckenarten verursachten zahlreiche Ausbrüche in der Vergangenheit mit Schäden in Europa, dem Kaukasus, Zentralasien und Nordafrika. Für beide Heuschreckenarten existieren nur wenige Forschungsarbeiten, die sich mit der Anwendung von Fern-erkundungsdaten auseinandersetzen. Vor diesem Hintergrund zielt diese Dissertation auf die Entwicklung von relevanten Methoden unter Einsatz von Fernerkundungsdaten für beide Heuschreckenarten ab, um präventives Heuschreckenmanagement und -forschung zu unterstützen.Данная диссертация раскрывает тему применения спутникового дистанционного зондирования для контроля саранчовых и проведения дополнительных исследований саранчи. В частности, особое внимание уделяется изучению потребностей различных видов саранчовых при описании характеристик земного покрова и его динамики на основе данных дистанционного зондирования. Первостепенная цель данной диссертации состоит в том, чтобы предоставить целостный обзор существующих приложений, использующих спутниковые данные, в разрезе различных видов саранчовых для того, чтобы раскрыть текущие и потенциальные возможности. Кроме того, дистанционное зондирование и наборы геопространственных данных используются для классификации территорий с идеальными и не идеальными условиями для нашествий саранчи. исследование сосредоточено в основном на двух видах саранчи, итальянского пруса (Calliptamus italicus) и марокканской саранче (Dociostaurus maroccanus), а также на определенных территориях, в пределах их обширногo местообитаний

Image and/or Video Transformation Using Interpretable Transformation Parameters

A computing system and method that can be used for performing transformations of images using machine-learned model(s) and interpretable user-specified parameters that control the transformations. More specifically, the machine-learned model can be used to perform transformation(s) on an image based on different parameter(s) of a user-specified conditioning vector. The systems and methods of the present disclosure allow for a user to specify desired values for defined characteristics of a transformation (e.g., area of transformation, degree of transformation, etc.) for one or more transformations of the defined characteristic(s) (e.g., transforming lack of facial displacement distortion to presence of a facial displacement distortion, transforming glasses frames to lack of glasses frames, unshaded to shaded, etc.)

Fractal extra dimension in Kaluza-Klein theory

Kaluza-Klein theory in which the geometry of an additional dimension is fractal has been considered. In such a theory the mass of an elementary electric charge appears to be many orders of magnitude smaller than the Planck mass, and the "tower" of masses which correspond to higher integer charges becomes aperiodic.Comment: 3 pages, accepted for publication in Phys.Rev.D (submitted on 3.28.2001

Application of Remote Sensing Data for Locust Research and Management-A Review

Recently, locust outbreaks around the world have destroyed agricultural and natural vegetation and caused massive damage endangering food security. Unusual heavy rainfalls in habitats of the desert locust (Schistocerca gregaria) and lack of monitoring due to political conflicts or inaccessibility of those habitats lead to massive desert locust outbreaks and swarms migrating over the Arabian Peninsula, East Africa, India and Pakistan. At the same time, swarms of the Moroccan locust (Dociostaurus maroccanus) in some Central Asian countries and swarms of the Italian locust (Calliptamus italicus) in Russia and China destroyed crops despite developed and ongoing monitoring and control measurements. These recent events underline that the risk and damage caused by locust pests is as present as ever and affects 100 million of human lives despite technical progress in locust monitoring, prediction and control approaches. Remote sensing has become one of the most important data sources in locust management. Since the 1980s, remote sensing data and applications have accompanied many locust management activities and contributed to an improved and more effective control of locust outbreaks and plagues. Recently, open-access remote sensing data archives as well as progress in cloud computing provide unprecedented opportunity for remote sensing-based locust management and research. Additionally, unmanned aerial vehicle (UAV) systems bring up new prospects for a more effective and faster locust control. Nevertheless, the full capacity of available remote sensing applications and possibilities have not been exploited yet. This review paper provides a comprehensive and quantitative overview of international research articles focusing on remote sensing application for locust management and research. We reviewed 110 articles published over the last four decades, and categorized them into different aspects and main research topics to summarize achievements and gaps for further research and application development. The results reveal a strong focus on three species-the desert locust, the migratory locust (Locusta migratoria), and the Australian plague locust (Chortoicetes terminifera)-and corresponding regions of interest. There is still a lack of international studies for other pest species such as the Italian locust, the Moroccan locust, the Central American locust (Schistocerca piceifrons), the South American locust (Schistocerca cancellata), the brown locust (Locustana pardalina) and the red locust (Nomadacris septemfasciata). In terms of applied sensors, most studies utilized Advanced Very-High-Resolution Radiometer (AVHRR), Satellite Pour l'Observation de la Terre VEGETATION (SPOT-VGT), Moderate-Resolution Imaging Spectroradiometer (MODIS) as well as Landsat data focusing mainly on vegetation monitoring or land cover mapping. Application of geomorphological metrics as well as radar-based soil moisture data is comparably rare despite previous acknowledgement of their importance for locust outbreaks. Despite great advance and usage of available remote sensing resources, we identify several gaps and potential for future research to further improve the understanding and capacities of the use of remote sensing in supporting locust outbreak- research and management

Feedback of observed interannual vegetation change: a regional climate model analysis for the West African monsoon

West Africa is a hot spot region for land–atmosphere coupling where atmospheric conditions and convective rainfall can strongly depend on surface characteristics. To investigate the effect of natural interannual vegetation changes on the West African monsoon precipitation, we implement satellite-derived dynamical datasets for vegetation fraction (VF), albedo and leaf area index into the Weather Research and Forecasting model. Two sets of 4-member ensembles with dynamic and static land surface description are used to extract vegetation-related changes in the interannual difference between August–September 2009 and 2010. The observed vegetation patterns retain a significant long-term memory of preceding rainfall patterns of at least 2 months. The interannual vegetation changes exhibit the strongest effect on latent heat fluxes and associated surface temperatures. We find a decrease (increase) of rainy hours over regions with higher (lower) VF during the day and the opposite during the night. The probability that maximum precipitation is shifted to nighttime (daytime) over higher (lower) VF is 12 % higher than by chance. We attribute this behaviour to horizontal circulations driven by differential heating. Over more vegetated regions, the divergence of moist air together with lower sensible heat fluxes hinders the initiation of deep convection during the day. During the night, mature convective systems cause an increase in the number of rainy hours over these regions. We identify this feedback in both water- and energy-limited regions of West Africa. The inclusion of observed dynamical surface information improved the spatial distribution of modelled rainfall in the Sahel with respect to observations, illustrating the potential of satellite data as a boundary constraint for atmospheric models

Voicemail Information Encoding for Better Call Direction

The present disclosure describes computer-implemented systems and methods for encoding information to outbound voicemail prompts with a computer-readable signature allowing for more efficient voicemail usage and enhanced voicemail privacy. In one embodiment, a computer readable signature is provided at the beginning of an outbound voicemail prompt to signify to a calling computing system it has reached the voicemail, and a computer readable signature is provided at the end of the outbound voicemail prompt to signify to the calling computing system that the outbound voicemail prompt has ended and the voicemail is recording

Spatio-temporal patterns and dynamics of net primary productivity for Kazakhstan

Monitoring of net primary productivity (NPP) is especially important for the fragile ecosystems in arid and semi-arid regions. Great interest exists in observing large-scale vegetation dynamics and understanding spatial and temporal patterns of NPP in these areas. In this study we present results of NPP obtained with the model BETHY/DLR for Kazakhstan for 2003-2011 and its spatial and temporal dynamics. The spatial distribution of vegetation productivity shows a gradient from North to South and clear differences between individual vegetation classes. The monthly NPP values show the highest productivity in June. Differences between rain-fed and irrigated areas indicate the dependency on water availability. Annual NPP variability was high for agricultural areas, but showed low values for natural vegetation. The analysis of different patterns in vegetation productivity provides valuable information for the identification of regions that are vulnerable to a possible climate change. This information may thus substantially support a sustainable land management

Monitoring Large-Scale Inland Water Dynamics by Fusing Sentinel-1 SAR and Sentinel-3 Altimetry Data and by Analyzing Causal Effects of Snowmelt

The warming climate is threatening to alter inland water resources on a global scale. Within all waterbody types, lake and river systems are vital not only for natural ecosystems but, also, for human society. Snowmelt phenology is also altered by global warming, and snowmelt is the primary water supply source for many river and lake systems around the globe. Hence, (1) monitoring snowmelt conditions, (2) tracking the dynamics of snowmelt-influenced river and lake systems, and (3) quantifying the causal effect of snowmelt conditions on these waterbodies are critical to understand the cryo-hydrosphere interactions under climate change. Previous studies utilized in-situ or multispectral sensors to track either the surface areas or water levels of waterbodies, which are constrained to small-scale regions and limited by cloud cover, respectively. On the contrary, in the present study, we employed the latest Sentinel-1 synthetic aperture radar (SAR) and Sentinel-3 altimetry data to grant a high-resolution, cloud-free, and illumination-independent comprehensive inland water dynamics monitoring strategy. Moreover, in contrast to previous studies utilizing in-house algorithms, we employed freely available cloud-based services to ensure a broad applicability with high efficiency. Based on altimetry and SAR data, the water level and the water-covered extent (WCE) (surface area of lakes and the flooded area of rivers) can be successfully measured. Furthermore, by fusing the water level and surface area information, for Lake Urmia, we can estimate the hypsometry and derive the water volume change. Additionally, for the Brahmaputra River, the variations of both the water level and the flooded area can be tracked. Last, but not least, together with the wet snow cover extent (WSCE) mapped with SAR imagery, we can analyze the influence of snowmelt conditions on water resource variations. The distributed lag model (DLM) initially developed in the econometrics discipline was employed, and the lagged causal effect of snowmelt conditions on inland water resources was eventually assessed

It pays to be nice, but not really nice: Asymmetric evaluations of prosociality across seven cultures.

Cultures differ in many important ways, but one trait appears to be universally valued: prosociality. For one’s reputation, around the world, it pays to be nice to others. However, recent research with American participants finds that evaluations of prosocial actions are asymmetric—relatively selfish actions are evaluated according to the magnitude of selfishness but evaluations of relatively generous actions are less sensitive to magnitude. Extremely generous actions are judged roughly as positively as modestly generous actions, but extremely selfish actions are judged much more negatively than modestly selfish actions (Klein & Epley, 2014). Here we test whether this asymmetry in evaluations of prosociality is culture-specific. Across 7 countries, 1,240 participants evaluated actors giving various amounts of money to a stranger. Along with relatively minor cross-cultural differences in evaluations of generous actions, we find cross-cultural similarities in the asymmetry in evaluations of prosociality. We discuss implications for how reputational inferences can enable the cooperation necessary for successful societies