Integrating Remote Sensing and Social Science - The correlation of urban morphology with socioeconomic parameters

The alignment, small-scale transitions and characteristics of buildings, streets and open spaces constitute a heterogeneous urban morphology. The urban morphology is the physical reflection of a society that created it, influenced by historical, social, cultural, economic, political, demographic and natural conditions as well as their developments. Within the complex urban environment homogeneous physical patterns and sectors of similar building types, structural alignments or similar built-up densities can be localized and classified. Accordingly, it is assumed that urban societies also feature a distinctive socioeconomic urban morphology that is strongly correlated with the characteristics of a city’s physical morphology: Social groups settle spatially with one’s peer more or less segregated from other social groups according to, amongst other things, their economic status. This study focuses on the analysis, whether the static physical urban morphology correlates with socioeconomic parameters of its inhabitants – here with the example indicators income and value of property. Therefore, the study explores on the capabilities of high resolution optical satellite data (Ikonos) to classify patterns of urban morphology based on physical parameters. In addition a household questionnaire was developed to investigate on the cities socioeconomic morphology

Sehen, was nicht verborgen bleiben darf: Der Welt Erbe im Blick von Satelliten

Der Artikel zeigt beispielhaft einige Beiträge der satellitengestützten Fernerkundung zur Dokumentation von Stätten des Weltkulturerbes

Sehen, was nicht verborgen blieben darf: Der Welt Erbe im Blick von Satelliten

Der Artikel zeigt beispielhaft einige Beiträge der satellitengestützten Fernerkundung zur Dokumentation von Stätten des Weltkulturerbes

Assessment of human immediate response capability related to tsunami threats in Indonesia at a sub-national scale

Human immediate response is contextualized into different time compartments reflecting the tsunami early warning chain. Based on the different time compartments the available response time and evacuation time is quantified. The latter incorporates accessibility of safe areas determined by a hazard assessment, as well as environmental and demographic impacts on evacuation speed properties assessed using a Cost Distance Weighting GIS approach. Approximately 4.35 million Indonesians live in tsunami endangered areas on the southern coasts of Sumatra, Java and Bali and have between 20 and 150 min to reach a tsunami-safe area. Most endangered areas feature longer estimated-evacuation times and hence the population possesses a weak immediate response capability leaving them more vulnerable to being directly impacted by a tsunami. At a sub-national scale these hotspots were identified and include: the Mentawai islands off the Sumatra coast, various sub-districts on Sumatra and west and east Java. Based on the presented approach a temporal dynamic estimation of casualties and displacements as a function of available response time is obtained for the entire coastal area. As an example, a worst case tsunami scenario for Kuta (Bali) results in casualties of 25 000 with an optimal response time (direct evacuation when receiving a tsunami warning) and 120 000 for minimal response time (no evacuation). The estimated casualties correspond well to observed/reported values and overall model uncertainty is low with a standard error of 5%. The results obtained allow for prioritization of intervention measures such as early warning chain, evacuation and contingency planning, awareness and preparedness strategies down to a sub-district level and can be used in tsunami early warning decision support

Assessment of wildfire activity development trends for Eastern Australia using multi-sensor earth observation data

Increased fire activity across the Amazon, Australia, and even the Arctic regions has received wide recognition in the global media in recent years. Large-scale, long-term analyses are required to postulate if these incidents are merely peaks within the natural oscillation, or rather the consequence of a linearly rising trend. While extensive datasets are available to facilitate the investigation of the extent and frequency of wildfires, no means has been available to also study the severity of the burnings on a comparable scale. This is now possible through a dataset recently published by the German Aerospace Center (DLR). This study exploits the possibilities of this new dataset by exemplarily analyzing fire severity trends on the Australian East coast for the past 20 years. The analyzed data is based on 3,503 tiles of the ESA Sentinel-3 OLCI instrument, extended by 9,612 granules of the NASA MODIS MOD09/MYD09 product. Rising trends in fire severity could be found for the states of New South Wales and Victoria, which could be attributed mainly to developments in the temperate climate zone featuring hot summers without a dry season (Cfa). Within this climate zone, the ecological units featuring needleleaf and evergreen forest are found to be mainly responsible for the increasing trend development. The results show a general, statistically significant shift of fire activity towards the affection of more woody, ecologically valuable vegetation

Wildfire extreme events: Large-scale developments in fire activity of New South Wales, Australia

Disastrous wildfires have occurred in many parts of the world during the last two years (2019 and 2020), most notably in South America, Australia, the United States, and regions north of the polar circle. Such extreme wildfire events pose a pervasive threat to human lives and property and have thus been widely recognized in the global media. This study focusses on large-scale developments in fire activity. It investigates the occurrence of burnt areas regarding several relevant parameters, namely fire extent, fire severity and fire seasonality. The entirety of those parameters allows an extensive insight regarding large-scale, long-term fire activity trends. The burnt area derivation process, which is fully automated, is described in the literature (see reference below). The analysis is based on an extensive set of satellite data, specifically 9,612 granules of the MODIS MOD09/MYD09 product in conjunction with 3,503 tiles of the OLCI (Ocean and Land Colour Instrument) instrument onboard Sentinel-3. The study design consists of two parts: Firstly, the long-term temporal variability in fire activity, covering the time span from 2000 until 2020, is analyzed for the study region of New South Wales, Australia. Secondly, the large-scale spatial variability is investigated by comparing the New South Wales extreme events in 2019/2020 with events of comparable magnitude in California, US and the Siberian taiga. The study shows that New South Wales features an upward trend regarding the extent of yearly affected area, as well as a shift towards a prolongated end of the fire season towards the Autumn months. It also shows the exceptionality of the Australian wildfire activity in comparison with other geographical regions

Research products across space missions: a prototype for central storage, visualization and usability

For planetary sciences, the main archives to archived access to mission data are ESA's Planetary Science Archive (PSA) and the Planetary Data System (PSA) nodes in the USA. Along with recent and upcoming planetary missions the amount of different data (remote sensing/in-situ data, derived products) increases constantly and serves as basis for scientific research resulting in derived scientific data and information. Within missions to Mercury (BepiColombo), the Outer Solar System moons (JUICE), and asteroids (NASA`s DAWN), one way of scientific analysis, the systematic mapping of surfaces, has received new impulses, also in Europe. These systematic surface analyses are based on the numeric and visual comparison and combination of different remote sensing data sets, such as optical image data, spectral-/hyperspectral sensor data, radar images, and/or derived products like digital terrain models. The analyses mainly results in map figures, data, and profiles/diagrams, and serves for describing research investigations within scientific publications