Ground Stability Monitoring of Undermined and Landslide Prone Areas by Means of Sentinel-1 Multi-Temporal InSAR, Case Study from Slovakia

Speckle noise present in radar imagery caused by interaction of out –of-phase waves with a target, the objective of this paper is attempt to test filtering techniques consist of Lee, Frost and Gamma Map to identify a potential shrines area in Lembah Bujang using RADARSAT imageries. The multi-temporal images of RADARSAT for years 2003 and 2014 have been used filtering techniques in identifying potential shrines consist of have been used and tested to selected study areas with using processing software of ENVI 4.8 and ArcGIS 10.2. Based on mathematical morphology, the speckles in these images were reduced, once the reduction is achieved, the enhancement of archaeological sites is accomplished. The finding shows that Local Adaptive Filtering on GAMMA Map filter is the best techniques in identifying potential shrines areas at once as guidance to pursuing an area as official gazette historical site in Malaysia context.

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Social environmental vulnerability approach on the COVID-19 epoch: a case study in Blumenau (SC), Brazil

Research Society and Development ◽

10.33448/rsd-v10i10.18739 ◽

2021 ◽

Vol 10 (10) ◽

pp. e161101018739

Author(s):

Cristiane Mansur de Moraes Souza ◽

Bruno Jandir Mello ◽

Luciano Félix Florit ◽

Ângela Maria Cavalcanti Ramalho ◽

Yasmin Mansur de Moraes Souza ◽

...

Keyword(s):

Poor People ◽

Critical Question ◽

Environmental Vulnerability ◽

The Social ◽

Multi Temporal ◽

Spread Pattern ◽

Social Environmental ◽

Poverty Indicators ◽

Environmental Inequalities

There is a strong correlation between poverty indicators and the occurrence of diseases associated with environmental inequalities; therefore, it is highly necessary to explore the linkages between these inequalities and COVID- 19. This article describes a research designs made to study aspects of social environmental vulnerability that underlies the linkages between inequalities and COVID-19. This article aims to address this linkage. The objective is to explore aspects of social environmental vulnerability that underlies a case study at Blumenau, Brazil. The analysis is based on the critical question: Is there a relationship between social environmental vulnerability and COVID-19 at Blumenau? In Blumenau, where the study was carry out, the poor people are more likely to be affected from the risks arising out of the location of their homes, and this situation increases their vulnerability to floods, landslides, lack of water and exposure to open sewage. The methodology was divide into two steeps: (i) analysis of multi-temporal spread pattern of COVID-19 around the site; and (ii) analysis of the social environmental vulnerability and COVID-19 relationship. Results have shown that in Blumenau, there is a relationship between social environmental vulnerability and COVID-19. It can be said that COVID-19 emphases’ the social environmental situation in Blumenau. Based on our experience, we contend that an effective way to examine the linkages between inequalities and COVID-19 is to employ concepts and theories drawn from existing research to support guidelines, indicators and methods.

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ASSESSMENT OF SOCIAL VULNERABILITY TO THE IMPACT OF FLOOD HAZARD: A CASE STUDY OF KOPILI RIVER BASIN, ASSAM, INDIA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-5-455-2018 ◽

2018 ◽

Vol XLII-5 ◽

pp. 455-460

Author(s):

S. V. Shiva Prasad Sharma ◽

P. S. Roy ◽

V. Chakravarthi

Keyword(s):

Social Vulnerability ◽

Flood Hazard ◽

Vulnerability Index ◽

Social Vulnerability Index ◽

The Social ◽

Vulnerability Indicators ◽

Multi Temporal ◽

The Impact ◽

Vulnerable Zones

Abstract. In the present study, an attempt is made to understand the impact on Social Vulnerability of the Kopili basin due to various severities of flood hazard. The flood hazard is generated using multi-temporal historical satellite based analysis and integration of annual flood inundation layers. The census of India data of 2001 and 2011 is spatially joined with village database to study the impact at village level. Using 5 Census variables from both Census 2001 &amp; 2011 as vulnerability indicators, the Social Vulnerability Index (SVI) is derived and classified into various vulnerable zones namely Low, Moderate and High Vulnerable zones. The findings of the study show that the number of villages falling in Low and High Vulnerable zones had decreased during Census 2011 when compared to 2001 and a rise of 6% in villages falling in moderate vulnerable zones during 2011 is observed. The spatial database generated is useful to understand the impact of floods on the Social Vulnerability status of the basin and can be a useful input to further study the Physical, Economic and Environmental Vulnerabilities of the basin.

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Landsat thermal infrared to detect sub-canopy riparian flooding

10.5194/egusphere-egu21-13762 ◽

2021 ◽

Author(s):

Emanuel Storey ◽

Witold Krajewski ◽

Efthymios Nikolopoulos

Keyword(s):

Open Water ◽

Thermal Infrared ◽

Short Wave ◽

Mapping Technique ◽

Landsat 8 ◽

Infrared Observations ◽

Plant Canopies ◽

Multi Temporal ◽

Flood Detection

Satellite based flood detection can enhance understanding of risk to humans and infrastructures, geomorphic processes, and ecological effects.&#160; Such application of optical satellite imagery has been mostly limited to the detection of water exposed to sky, as plant canopies tend to obstruct water visibility in short electromagnetic wavelengths.&#160; This case study evaluates the utility in multi-temporal thermal infrared observations from Landsat 8 as a basis for detecting sub-canopy fluvial inundation resulting in ambient temperature change.We selected three flood events of 2016 and 2019 along sections of the Mississippi, Cedar, and Wapsipinicon Rivers located in Iowa, Minnesota, and Wisconsin, United States.&#160; Classification of sub-canopy water involved logical, threshold-exceedance criteria to capture thermal decline within channel-adjacent vegetated zones.&#160; Open water extent in the floods was mapped based on short-wave infrared thresholds determined parametrically from baseline (non-flooded) observations.&#160; Map accuracy was evaluated using higher-resolution (0.5&#8211;5.0 m) synchronic optical imagery.Results demonstrate improved ability to detect sub-canopy inundation when thermal infrared change is incorporated: sub-canopy flood class accuracy was comparable to that of open water in previous studies.&#160; The multi-temporal open-water mapping technique yielded high accuracy as compared to similar studies.&#160; This research highlights the utility of Landsat thermal infrared data for monitoring riparian inundation and for validating other remotely sensed and simulated flood maps.

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Integration of Satellite Remote Sensing Techniques and Landscape Metrics to Characterize Land Cover Change and Dynamics

Geographic Information Analysis for Sustainable Development and Economic Planning - Advances in Geospatial Technologies ◽

10.4018/978-1-4666-1924-1.ch016 ◽

2013 ◽

pp. 228-244

Author(s):

Carmelo Riccardo Fichera ◽

Giuseppe Modica ◽

Maurizio Pollino

Keyword(s):

Remote Sensing ◽

Land Cover ◽

Landscape Metrics ◽

Landsat Images ◽

Aerial Photos ◽

Multi Temporal ◽

Urban Rural ◽

Remote Sensing Techniques

One of the most relevant applications of Remote Sensing (RS) techniques is related to the analysis and the characterization of Land Cover (LC) and its change, very useful to efficiently undertake land planning and management policies. Here, a case study is described, conducted in the area of Avellino (Southern Italy) by means of RS in combination with GIS and landscape metrics. A multi-temporal dataset of RS imagery has been used: aerial photos (1954, 1974, 1990), Landsat images (MSS 1975, TM 1985 and 1993, ETM+ 2004), and digital orthophotos (1994 and 2006). To characterize the dynamics of changes during a fifty year period (1954-2004), the approach has integrated temporal trend analysis and landscape metrics, focusing on the urban-rural gradient. Aerial photos and satellite images have been classified to obtain maps of LC changes, for fixed intervals: 1954-1985 and 1985-2004. LC pattern and its change are linked to both natural and social processes, whose driving role has been clearly demonstrated in the case analysed. In fact, after the disastrous Irpinia earthquake (1980), the local specific zoning laws and urban plans have significantly addressed landscape changes.

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Advanced radar-interpretation of InSAR time series for mapping and characterization of geological processes

Natural Hazards and Earth System Science ◽

10.5194/nhess-11-865-2011 ◽

2011 ◽

Vol 11 (3) ◽

pp. 865-881 ◽

Cited By ~ 69

Author(s):

F. Cigna ◽

C. Del Ventisette ◽

V. Liguori ◽

N. Casagli

Keyword(s):

Time Series ◽

Field Surveys ◽

Synthetic Aperture Radar Interferometry ◽

Geological Processes ◽

Multi Temporal ◽

Under Sampling ◽

Temporal Measures

Abstract. We present a new post-processing methodology for the analysis of InSAR (Synthetic Aperture Radar Interferometry) multi-temporal measures, based on the temporal under-sampling of displacement time series, the identification of potential changes occurring during the monitoring period and, eventually, the classification of different deformation behaviours. The potentials of this approach for the analysis of geological processes were tested on the case study of Naro (Italy), specifically selected due to its geological setting and related ground instability of unknown causes that occurred in February 2005. The time series analysis of past (ERS1/2 descending data; 1992–2000) and current (RADARSAT-1 ascending data; 2003–2007) ground movements highlighted significant displacement rates (up to 6 mm yr−1) in 2003–2007, followed by a post-event stabilization. The deformational behaviours of instable areas involved in the 2005 event were also detected, clarifying typology and kinematics of ground instability. The urban sectors affected and unaffected by the event were finally mapped, consequently re-defining and enlarging the influenced area previously detected by field observations. Through the integration of InSAR data and conventional field surveys (i.e. geological, geomorphologic and geostructural campaigns), the causes of instability were finally attributed to tectonics.

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