USING GOOGLE EARTH PRO TO CREATE GEOLOGIC HAZARD ASSESSMENT MAPS ON STATEN ISLAND, NY

2016 ◽  
Author(s):  
Sean Thatcher ◽  
2000 ◽  
Vol 6 (3) ◽  
pp. 209-226 ◽  
Author(s):  
William C. Haneberg

Abstract The occurrence of potentially hazardous geologic events such as landslides, rock falls, earthquakes, floods, and debris flows can be predicted using two fundamentally different approaches: deterministic and probabilistic. The most significant difference between the two approaches to geologic hazard assessment is whether a process is envisioned to be the result of an exact causal relationship or if some element of random behavior is assumed to be part of the system. Although the assumption of random behavior may seem self-defeating, it can provide a useful tool for the solution of important problems as long as the randomness can be quantified using statistical models. Each of these two methods can be approached either rationally (sing models derived from accepted physical or chemical principles) or empirically (by studying the occurrence of events without explicit regard to their driving mechanism). The complexity of the geologic process commonly dictates which approach is used for a particular problem, ranging from rational deterministic models for relatively simple systems such as small landslides to empirical probabilistic models for complicated processes such as floods and earthquakes. Examples of each type of model are discussed throughout the paper, primarily within the context of slope stability and the recurrence of extreme events such as floods.


2018 ◽  
Author(s):  
Michael J. Lynch ◽  
◽  
Zhenming Wang ◽  
William Andrews ◽  
Matthew M. Crawford ◽  
...  

2020 ◽  
Vol 12 (6) ◽  
pp. 2433 ◽  
Author(s):  
Xiaoyi Shao ◽  
Siyuan Ma ◽  
Chong Xu ◽  
Lingling Shen ◽  
Yongkun Lu

Inventorying landslides in mountainous areas is of great importance for prevention of geologic hazards. This study aimed to establish a detailed landslide inventory of Baoshan City, Yunnan Province, China, based on a large set of high-resolution satellite images from Google Earth. The landslides of this region were divided into two groups, i.e., recent landslides and old landslides. The spatial distribution and geometric characteristics of the two kinds of landslides were analyzed, respectively. Results show that 2427 landslides are present in the study area, including 2144 recent landslides and 283 old landslides with a total area of 7.2 km2 and 97.6 km2, respectively. The recent landslides occurred primarily at steep slopes with higher elevation, while old landslides took place at gentle terrains. For the slope position, most landslides, whether old or recent, cluster near ridges. The lower boundary of the recent landslides is far away from the valley, while the accumulation area of the old landslide is closer to the valley. The H/L (height to length) ratios are basically the same for all landslides, ranging from 0.2 to 0.5. Old landslides have larger mobility, as their travel distances are longer than recent landslides at the same height. The results would be helpful for further understanding the development and spatial distribution of the landslides in Southwest China, and also provide essential support for the subsequent landslide susceptibility mapping and geologic hazard assessment in this area.


2015 ◽  
Vol 764-765 ◽  
pp. 1095-1099
Author(s):  
Shu Rong Yang ◽  
Yi Lung Yeh

This study focuses on 53 villages located in the slopelands of Pingtung County. Remote sensing image interpretation techniques are used to identify geologic hazard areas. GIS map overlay analysis of environmental geologic maps, landslide susceptibility maps and potential debris flow torrent maps provided by local and regional governments are used to further interpret and correctly identify the extent of the geologic hazard zone. This study successfully combines both GIS and GPS techniques, and according to data analysis results, constructs a slopeland village geologic hazard assessment method.


2017 ◽  
Vol 2017 (1) ◽  
pp. 1574-1593 ◽  
Author(s):  
Rodrigo Fernandes ◽  
Francisco Campuzano ◽  
David Brito ◽  
Manuela Juliano ◽  
Frank Braunschweig ◽  
...  

ABSTRACT 2017-244: The state-of-the-art in both operational oceanography, remote sensing, and computational capacity, enables now the possibility of developing near-real time, holistic automated services capable of dramatically improving maritime situational awareness to responding to oil spill emergencies. Based on the European satellite-based oil spill and vessel detection service – CleanSeaNet (EMSA – European Maritime Safety Agency), which distributes oil pollution detection standardized notification packages in less than 30 minutes, a new automated early warning system (EWS) for near-real time modelling and prediction of the detected oil spills was developed. This EWS provides 48-hour oil spill forecasts + 24-hour backward simulations, delivering results 5–10 minutes after the reception of the oil spill detection notifications. These forecasts are then distributed in multiple formats and platforms (e.g. Google Earth, e-mail). The oil spill fate and behaviour model used in this EWS is part of MOHID modelling system, and is coupled offline with metocean forecast solutions, taking advantage of autonomous models previously run in multiple institutions. The system is currently able to integrate various metocean forecasting systems, being agnostic about the data sources and applied locations, as long as their outputs comply with commonly adopted formats, including CF compliant files or CMEMS (Copernicus Marine Environment Monitoring Service). The EWS is currently operational in western Iberia, supporting Portuguese Maritime Authority, and is being expanded to neighbourhood regions (from Spain and Morocco) with high resolution metocean models (MARPOCS project funded by European Union Humanitarian Aid & Civil Protection). Taking advantage of the coupling of MOHID oil spill model and CleanSeaNet, an oil spill hazard assessment is made in the Portuguese continental coast, based on the cumulative analysis of drift model simulations from previously detected spills using metocean model data, for a period between 2011–2016. Although this EWS doesn’t replace on-demand operational oil spill forecasting systems, it supports maritime authorities with a fast first-guess forecast solution, allowing:Anticipation of tactical response (including visual inspection of the spill) and mitigation of the pollution episode;A more effective identification of the pollution source, and in case of suspected illegal spill, earlier actions towards effective prosecution of the polluter;In the other hand, the hazard assessment generated is a valuable instrument for the development of efficient planning and prevention strategies. The EWS can be connected to any satellite-based detection service (inside or outside Europe) as long as the detected oil slicks are automatically distributed in a structured and standardized data format similar to CleanSeaNet.


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