Urban morphology analysis by remote sensing and gis technique, case study: Georgetown, Penang

This paper was analysed the potential of applications of satellite remote sensing to urban planning research in urban morphology. Urban morphology is the study of the form of human settlements and the process of their formation and transformation. It is an approach in designing urban form that considers both physical and spatial components of the urban structure. The study conducted in Georgetown, Penang purposely main to identify the evolution of urban morphology and the land use expansion. In addition, Penang is well known for its heritage character, especially in the city of Georgetown with more than 200 years of urban history. Four series of temporal satellite SPOT 5 J on year 2004, 2007, 2009 and 2014 have been used in detecting an expansion of land use development aided by ERDAS IMAGINE 2014. Three types of land uses have been classified namely build-up areas, un-built and water bodies show a good accuracy with achieved above 85%. The result shows the built-up area significantly increased due to the rapid development in urban areas. Simultaneously, this study provides an understanding and strengthening a relation between urban planning and remote sensing applications in creating sustainable and resilience of the city and future societies as well

Landslide mapping and monitoring by using radar and optical remote sensing: examples from the EC-FP7 project SAFER

This paper focuses on the Landslide Thematic services of the EU-funded FP7-SPACE project SAFER (Services and Applications For Emergency Response) for inventory mapping, monitoring and rapid mapping by using Earth Observation (EO). We exploited satellite Interferometric Synthetic Aperture Radar (InSAR) and Object-Based Image Analysis (OBIA), and discuss example applications in South Tyrol and Abruzzo (Italy), Lower Austria (Austria), Lubietova (Slovakia) and the Kaohsiung County (Taiwan). These case studies showcase the significance of radar and optical EO data, InSAR and OBIA methods for landslide mapping and monitoring in different geological environments and during all phases of emergency management: mitigation, preparedness, crisis and recovery

Digital surface modelling and 3D information extraction from spaceborne very high resolution stereo pairs

This report discusses the potentials of VHR stereo imagery for automatic digital surface modelling (DSM) and 3D information extraction on large metropolitan cities. Stereo images acquired by GeoEye-1 on Dakar and Guatemala City and by WorldView-2 on Panama City, Constitucion (Chile), Kabul, Teheran, Kathmandu and San Salvador were processed following a rigorous photogrammetric approach. The work focusing on evaluating the quality of the DSMs in relation to the image and terrain characteristics and, among the possible DSM’s application, present a solution for buildings height estimation. The size of the datasets, the variety of case studies and the complexity of the scenarios allow to critically analyzing the potentials of VHR stereo imagery for 3D landscape modeling for natural hazards assessment.JRC.G.2-Global security and crisis managemen

Technical note: use of remote sensing for landslide studies in Europe

Within the framework of FP7, an EU-funded SafeLand project, a questionnaire was prepared to collect information about the use of remote sensing for landslide study and to evaluate its actual application in landslide detection, mapping and monitoring. The questionnaire was designed using a Google form and was disseminated among end-users and researchers involved in landslide studies in Europe. In total, 49 answers from 17 different European countries were collected. The outcomes showed that landslide detection and mapping is mainly performed with aerial photos, often associated with optical and radar imagery. Concerning landslide monitoring, satellite radars prevail over the other types of data. Remote sensing is mainly used for detection/mapping and monitoring of slides, flows and lateral spreads with a preferably large scale of analysis (1:5000–1:25 000). All the compilers integrate remote sensing data with other thematic data, mainly geological maps, landslide inventory maps and DTMs and derived maps. According to the research and working experience of the compilers, remote sensing is generally considered to have a medium effectiveness/reliability for landslide studies. <br><br> The results of the questionnaire can contribute to an overall sketch of the use of remote sensing in current landslide studies and show that remote sensing can be considered a powerful and well-established instrument for landslide mapping, monitoring and hazard analysis

Automated spatiotemporal landslide mapping over large areas using RapidEye time series data

In the past, different approaches for automated landslide identification based on multispectral satellite remote sensing were developed to focus on the analysis of the spatial distribution of landslide occurrences related to distinct triggering events. However, many regions, including southern Kyrgyzstan, experience ongoing process activity requiring continual multi-temporal analysis. For this purpose, an automated object-oriented landslide mapping approach has been developed based on RapidEye time series data complemented by relief information. The approach builds on analyzing temporal NDVI-trajectories for the separation between landslide-related surface changes and other land cover changes. To accommodate the variety of landslide phenomena occurring in the 7500 km2 study area, a combination of pixel-based multiple thresholds and object-oriented analysis has been implemented including the discrimination of uncertainty-related landslide likelihood classes. Applying the approach to the whole study area for the time period between 2009 and 2013 has resulted in the multi-temporal identification of 471 landslide objects. A quantitative accuracy assessment for two independent validation sites has revealed overall high mapping accuracy (Quality Percentage: 80%), proving the suitability of the developed approach for efficient spatiotemporal landslide mapping over large areas, representing an important prerequisite for objective landslide hazard and risk assessment at the regional scale

Landslides

Landslides - Investigation and Monitoring offers a comprehensive overview of recent developments in the field of mass movements and landslide hazards. Chapter authors use in situ measurements, modeling, and remotely sensed data and methods to study landslides. This book provides a thorough overview of the latest efforts by international researchers on landslides and opens new possible research directions for further novel developments

Advances on the investigation of landslides by space-borne synthetic aperture radar interferometry

Landslides are destructive geohazards to people and infrastructure, resulting in hundreds of deaths and billions of dollars of damage every year. Therefore, mapping the rate of deformation of such geohazards and understanding their mechanics is of paramount importance to mitigate the resulting impacts and properly manage the associated risks. In this paper, the main outcomes relevant to the joint European Space Agency (ESA) and the Chinese Ministry of Science and Technology (MOST) Dragon-5 initiative cooperation project ID 59,339 “Earth observation for seismic hazard assessment and landslide early warning system” are reported. The primary goals of the project are to further develop advanced SAR/InSAR and optical techniques to investigate seismic hazards and risks, detect potential landslides in wide regions, and demonstrate EO-based landslide early warning system over selected landslides. This work only focuses on the landslide hazard content of the project, and thus, in order to achieve these objectives, the following tasks were developed up to now: a) a procedure for phase unwrapping errors and tropospheric delay correction; b) an improvement of a cross-platform SAR offset tracking method for the retrieval of long-term ground displacements; c) the application of polarimetric SAR interferometry (PolInSAR) to increase the number and quality of monitoring points in landslide-prone areas; d) the semiautomatic mapping and preliminary classification of active displacement areas on wide regions; e) the modeling and identification of landslides in order to identify triggering factors or predict future displacements; and f) the application of an InSAR-based landslide early warning system on a selected site. The achieved results, which mainly focus on specific sensitive regions, provide essential assets for planning present and future scientific activities devoted to identifying, mapping, characterizing, monitoring and predicting landslides, as well as for the implementation of early warning systems.This work was supported by the ESA-MOST China DRAGON-5 project with ref. 59339, by the Spanish Ministry of Science and Innovation, the State Agency of Research (AEI), and the European Funds for Regional Development under grant [grant number PID2020-117303GB-C22], by the Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital in the framework of the project CIAICO/2021/335, by the Natural Science Foundation of China [grant numbers 41874005 and 41929001], the Fundamental Research Funds for the Central University [grant numbers 300102269712 and 300102269303], and China Geological Survey Project [grant numbers DD20190637 and DD20190647]. Xiaojie Liu and Liuru Hu have been funded by Chinese Scholarship Council Grants Ref. [grant number 202006560031] and [grant number 202004180062], respectively