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MODELAÇÃO DINÂMICA DA PERIGOSIDADE A MOVIMENTOS DE VERTENTE E DESENVOLVIMENTO DE UM PROTÓTIPO DE SISTEMA DE ALERTA À ESCALA REGIONAL MOVALERT

Authors

Publications

Susceptibility assessment of shallow slides failure and run-out
Publication . Melo, Raquel; Zêzere, José; Rocha, Jorge; Oliveira, Sérgio
The research is focused on the susceptibility assessment of shallow slides in the region north of Lisbon (Portugal), by modelling the failure and run-out areas separately. The shallow slides failure is evaluated using a statistical method (logistic regression). The existence of shallow slides inventories occurred in distinct periods allowed the separation of data into two independent groups (training and validation) and the adoption of the temporal criterion for the independent validation. The latter revealed an Area Under the Receiver Operating Characteristic curve of 0.90, which reflects a very good predictive capacity of the logistic regression model. For the run-out assessment, a simple cellular automata model is implemented through the following sequential steps: a) pre-processing and establishment of transition rules; b) integration of variables; and c) temporal indexing and simulation. The pre-processing step includes the creation of a database with the modelling inputs. The transition rules are directly related with the motion of the displaced mass. In this context, the likely traveling directions are identified, both horizontally and vertically. The integration of transition rules is performed using the algorithm Path Distance, from ESRI. For the temporal indexing, we use the Markov chains analysis to estimate a transition area matrix, which records the number of cells that is expected to change location over a specified time. The last stage refers to the cellular automata model simulation, i.e. to the spatial distribution of the landslide displaced mass. The run-out modelling, using the cellular automata model proposed, provided good results, with an overlap between the simulation and the real cases of 77%. Lastly, a final shallow slide susceptibility map was constructed including both failure and run-out areas. This work accomplished a combination of low-cost methodology with limited input data that allowed a good performance of the landslide susceptibility assessment and can be easily applied to other regions.
Regional rainfall thresholds for landslide occurrence using a centenary database
Publication . Vaz, Teresa; Zêzere, José; Pereira, Susana; Oliveira, Sérgio Cruz; Garcia, Ricardo A. C.; Quaresma, Ivânia
This work proposes a comprehensive method to assess rainfall thresholds for landslide initiation using a centenary landslide database associated with a single centenary daily rainfall data set. The method is applied to the Lisbon region and includes the rainfall return period analysis that was used to identify the critical rainfall combination (cumulated rainfall duration) related to each landslide event. The spatial representativeness of the reference rain gauge is evaluated and the rainfall thresholds are assessed and calibrated using the receiver operating characteristic (ROC) metrics. Results show that landslide events located up to 10 km from the rain gauge can be used to calculate the rainfall thresholds in the study area; however, these thresholds may be used with acceptable confidence up to 50 km from the rain gauge. The rainfall thresholds obtained using linear and potential regression perform well in ROC metrics. However, the intermediate thresholds based on the probability of landslide events established in the zone between the lower-limit threshold and the upper-limit threshold are much more informative as they indicate the probability of landslide event occurrence given rainfall exceeding the threshold. This information can be easily included in landslide early warning systems, especially when combined with the probability of rainfall above each threshold.
Susceptibility assessment of shallow slides failure and run-out
Publication . Melo, Raquel; Zêzere, José; Rocha, Jorge; Oliveira, Sérgio
The research is focused on the susceptibility assessment of shallow slides in the region north of Lisbon (Portugal), by modelling the failure and run-out areas separately. The shallow slides failure is evaluated using a statistical method (logistic regression). The existence of shallow slides inventories occurred in distinct periods allowed the separation of data into two independent groups (training and validation) and the adoption of the temporal criterion for the independent validation. The latter revealed an Area Under the Receiver Operating Characteristic curve of 0.90, which reflects a very good predictive capacity of the logistic regression model. For the run-out assessment, a simple cellular automata model is implemented through the following sequential steps: a) pre-processing and establishment of transition rules; b) integration of variables; and c) temporal indexing and simulation. The pre-processing step includes the creation of a database with the modelling inputs. The transition rules are directly related with the motion of the displaced mass. In this context, the likely traveling directions are identified, both horizontally and vertically. The integration of transition rules is performed using the algorithm Path Distance, from ESRI. For the temporal indexing, we use the Markov chains analysis to estimate a transition area matrix, which records the number of cells that is expected to change location over a specified time. The last stage refers to the cellular automata model simulation, i.e. to the spatial distribution of the landslide displaced mass. The run-out modelling, using the cellular automata model proposed, provided good results, with an overlap between the simulation and the real cases of 77%. Lastly, a final shallow slide susceptibility map was constructed including both failure and run-out areas. This work accomplished a combination of low-cost methodology with limited input data that allowed a good performance of the landslide susceptibility assessment and can be easily applied to other regions.
Land use/land cover change detection and urban sprawl analysis
Publication . Viana, Cláudia M.; Oliveira, Sandra; Oliveira, Sérgio; Rocha, Jorge
This study presents a proposed application of the Time-Weighted Dynamic Time Warping (TWDTW) method for urban sprawl analysis. Four spectral indices were computed from a long time-series of Landsat satellite imagery, corresponding to 48 scenes acquired between 2006 and 2018. The spectral indices were the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built Index (NDBI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Bareness Index (NDBaI), which when processed resulted in 192 different images. The R package dtwSat was used for image processing, since it represents one of the few open source software programs available for processing large time-series datasets. The method was tested applied in the Alentejo Region of Southern Portugal; traditionally a rural region, where urban sprawl presents risks for the preservation of agricultural systems and for ecosystem sustainability. The sprawl analysis was integrated in a Geographic Information System (GIS), in which we computed an Expansion Index to quantitatively assess the three main urban land expansion types: infill, extension, and leapfrog. The results show that, between 2007 and 2012, the main changes are due to extension (50 ha), but with a significant amount of infill (36 ha) and leapfrog growth (4 ha), with this latter being the worst-case scenario. However, in the subsequent period, 2012-2017, urban growth decreased to about 10 ha, comprising both infill and extension, but notably leapfrog expansion disappeared. Our methodology proved to be flexible for managing irregular sampling and an out-of-phase time-series. The procedure offers a quantitative means of assessing urban sprawl dynamics and represents a potential strategy for defining sustainable urban development.

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Funders

Funding agency

Fundação para a Ciência e a Tecnologia

Funding programme

OE

Funding Award Number

SFRH/BPD/85827/2012

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