A repeatable change detection approach to map extreme storm-related damages caused by intense surface runoff based on optical and SAR remote sensing: Evidence from three case studies in the South of France

Cerbelaud, Arnaud; Roupioz, Laure; Blanchet, Gwendoline; Breil, Pascal; Briottet, Xavier

doi:10.1016/j.isprsjprs.2021.10.013

Cited by 17 publications

(28 citation statements)

References 58 publications

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“…For the Alpes-Maritimes study area, the Tinée, Vésubie and Roya basins, representing 1400 km 2 of steep mountainous woodlands were examined. Selection of these 6 catchments corresponded to the regions of interest over which identification of SWF damages had already been conducted in [29] (see Section 2.2). In this paper, in relation to the work of Cerbelaud et al [29], evaluation of the IRIP method relied on plot territorial subdivision.…”

Section: Study Areasmentioning

confidence: 99%

“…Selection of these 6 catchments corresponded to the regions of interest over which identification of SWF damages had already been conducted in [29] (see Section 2.2). In this paper, in relation to the work of Cerbelaud et al [29], evaluation of the IRIP method relied on plot territorial subdivision. For this, the Aude and Alpes-Maritimes official department land cadastre datasets were retrieved.…”

Section: Study Areasmentioning

confidence: 99%

“…The goal of this paper is to use areas impacted by all kinds of extreme rainfall-related disturbances such as gullies, deposits, landslides or mudflows, as proxy data for SWF occurrence. Affected zones were identified using an optical and radar remote sensing-based probabilistic change detection method at 10 m spatial resolution developed in [28,29]. This new repeatable approach was designed specifically to allow for identification of ground deteriorations far from the main hydrographic network.…”

Section: Introductionmentioning

confidence: 99%

“…For this, the machine learning algorithm relies on intra-plot change pixel statistics of vegetation-specific spectral indices. Thanks to these proxy data, this study seeks to comprehensively investigate the quality and limitations of IRIP maps over six watersheds during two extreme Mediterranean events for which the satellite-based method was successfully validated [29]. In order to study the significance of different factors such as land use, pedology or topography on SWF occurrence, the sensitivity to the different IRIP input indicators is also analyzed through contingency statistics and logistic regression, allowing us to suggest improvements to the current methodology.…”

Section: Introductionmentioning

confidence: 99%

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Proxy Data of Surface Water Floods in Rural Areas: Application to the Evaluation of the IRIP Intense Runoff Mapping Method Based on Satellite Remote Sensing and Rainfall Radar

Cerbelaud

Breil

Blanchet

et al. 2022

Water

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Along with fluvial floods (FFs), surface water floods (SWFs) caused by extreme overland flow are one of the main flood hazards occurring after heavy rainfall. Using physics-based distributed hydrological models, surface runoff can be simulated from precipitation inputs to investigate regions prone to soil erosion, mudflows or landslides. Geomatics approaches have also been developed to map susceptibility towards intense surface runoff without explicit hydrological modeling or event-based rainfall forcing. However, in order for these methods to be applicable for prevention purposes, they need to be comprehensively evaluated using proxy data of runoff-related impacts following a given event. Here, the IRIP geomatics mapping model, or “Indicator of Intense Pluvial Runoff”, is faced with rainfall radar measurements and damage maps derived from satellite imagery and supervised classification algorithms. Six watersheds in the Aude and Alpes-Maritimes departments in the South of France are investigated over more than 2000 km2 of rural areas during two flash-flood events. The results of this study show that the greater the IRIP susceptibility scores, the more SWFs are detected by the remote sensing-based detection algorithm. Proportions of damaged plots become even larger when considering areas which experienced heavier precipitations. A negative relationship between the mean IRIP accumulation scores and the intensity of rainfall is found among damaged plots, confirming that SWFs preferably occur over potentially riskier areas where rainfall is lower. Land use and soil hydraulic conductivity are identified as the most relevant indicators for IRIP to define production areas responsible for downslope deteriorations. Multivariate logistic regression is also used to determine the relative weights of upstream and local topography, uphill production areas and rainfall intensity for explaining SWF occurrence. This work overall confirms the relevance of IRIP methodology while suggesting improvements to its core framework to implement better prevention strategies against SWF-related hazards.

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Section: Study Areasmentioning

confidence: 99%

Section: Study Areasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Proxy Data of Surface Water Floods in Rural Areas: Application to the Evaluation of the IRIP Intense Runoff Mapping Method Based on Satellite Remote Sensing and Rainfall Radar

Cerbelaud

Breil

Blanchet

et al. 2022

Water

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“…For mapping burned areas, the latter used a selection of spectral indices to compare the pre-fire and post-fire values. In [40], an automatic and repeatable plot-based change detection method, based on pre and post event Sentinel-1 and Sentinel-2 data, was designed and tested to map extreme storm-related damages. Most of the services are in the test or pre-operational phase and focus on localizing one type of change, with hindsight of events and/or using one type of remote sensing data being sometimes costly.…”

Section: Introductionmentioning

confidence: 99%

A New Earth Observation Service Based on Sentinel-1 and Sentinel-2 Time Series for the Monitoring of Redevelopment Sites in Wallonia, Belgium

Petit

Stasolla

Wyard

et al. 2022

Land

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Urban planning is a challenge, especially when it comes to limiting land take. In former industrial regions such as Wallonia, the presence of a large number of brownfields, here called “redevelopment sites”, opens up new opportunities for sustainable urban planning through their revalorization. The Walloon authorities are currently managing an inventory of more than 2200 sites, which requires a significant amount of time and resources to update. In this context, the Sentinel satellites and the Terrascope platform, the Sentinel Collaborative Ground Segment for Belgium, enabled us to deploy SARSAR, an Earth observation service used for the automated monitoring of redevelopment sites that generates regular and automatic change reports that are directly usable by the Walloon authorities. In this paper, we present the methodological aspects and implementation details of the service, which combines two well-known and robust methods: the Pruned Exact Linear Time method for change point detection and threshold-based classification, which assigns the detected changes to three different classes (vegetation, building and soil). The overall accuracy of the system is in the range of 70–90%, depending on the different methods and classes considered. Some remarks on the advantages and possible drawbacks of this approach are also provided.

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Classifying types of gully changes with unoccupied aircraft vehicles 3D multitemporal point clouds for training of satellite data analysis in Northwest Namibia

Vallejo,

Castillo,

Zahs

et al. 2024

Earth Surf Processes Landf

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The development of standardised data acquisition strategies and analytical workflows is crucial to quantify gully changes. In this study, we explore synergies between unoccupied aircraft vehicles (UAV) and satellite remote sensing in order to classify gully morphodynamics. Using Time Series Forest (TSF) and the Sentinel‐1 radar backscatter coefficient (σo), gully scenarios can be classified into four categories: gully topographical change, no change outside gully, no change inside gully, and non‐topographical change. In addition, a Random Forest (RF) classification is performed employing individual features obtained from elevation models and temporally aggregated datasets. Training data are generated from multitemporal UAV‐borne photogrammetric point clouds through a manual segmentation of different gullies in Namibia. This information is transferred from point clouds (sub‐m) to satellite imagery (10 m) generating training data at Sentinel‐1 pixel level. Results indicate that the TSF (on the σo Vertical‐Vertical polarisation) and RF (on temporally aggregated features) perform best when training and testing areas are located within the same geographical extent. Both approaches yield similar Total Accuracy (TA ≈ 79%–80%) and Cohen's Kappa value (Kappa ≈ 0.7), but TSF achieves superior Producer Accuracy (PA = 78.5%) and User Accuracy (UA = 84.6%) for the gully topographical change class. Additionally, the utilisation of TSF in Vertical‐Vertical polarisation is the most effective method if the testing and training areas are in different geographical locations, allowing gully identification with TA > 80% and Kappa = 0.49. However, this method presents limitations to precisely delineate the change types, as dynamics are rain‐driven and therefore are geographically related. In summary, by combining the complementary benefits of UAV‐based and satellite‐based solutions, this study opens a line of research for the study and classification of surface land dynamics and geomorphological feature extraction in regional extents.

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A repeatable change detection approach to map extreme storm-related damages caused by intense surface runoff based on optical and SAR remote sensing: Evidence from three case studies in the South of France

Cited by 17 publications

References 58 publications

Proxy Data of Surface Water Floods in Rural Areas: Application to the Evaluation of the IRIP Intense Runoff Mapping Method Based on Satellite Remote Sensing and Rainfall Radar

Proxy Data of Surface Water Floods in Rural Areas: Application to the Evaluation of the IRIP Intense Runoff Mapping Method Based on Satellite Remote Sensing and Rainfall Radar

A New Earth Observation Service Based on Sentinel-1 and Sentinel-2 Time Series for the Monitoring of Redevelopment Sites in Wallonia, Belgium

Classifying types of gully changes with unoccupied aircraft vehicles 3D multitemporal point clouds for training of satellite data analysis in Northwest Namibia

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