Mapping and modelling mass movements and gullies in mountainous areas using remote sensing and GIS techniques

This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.

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“…Success-rate curves (Zinck et al 2001;Chung and Fabbri 2003;Fig. 4) plot the percentage of correctly classified objects (e.g.…”

Section: Cutoff-dependent Accuracy Statisticsmentioning

confidence: 99%

Recommendations for the quantitative analysis of landslide risk

Corominas

Westen

Frattini

et al. 2013

Bull Eng Geol Environ

710

666

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“…Remote sensing is an efficient complement to field methods to map gully development at specific time intervals; gullies are often developed in ramified badlands which are easier to map (Zinck et al 2001). Field observations are generally restricted to short time periods (Sharma, 1979;Oostwoud Wijdenes et al, 2000;Vandekerckhove et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

Semi-automatic delineation of badlands using contrast in vegetation activity: a case study in the lower Chambal valley, India

Ranga

Rompaey

Poesen

et al. 2015

Geocarto International

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Population growth worldwide leads to an increasing pressure on the land. Recent studies reported that many areas covered by badlands are decreasing because parts of badlands are being levelled and converted into arable land. It is important to monitor these changes for environmental planning. This paper proposes a remote-sensing based detection method which allows mapping of badland dynamics based on seasonal vegetation changes in the lower Chambal valley, India. Supervised classification was applied on three Landsat (Thematic Mapper) images, from 3 different seasons; January (winter), April (summer) and October (post-monsoon). Different band selection methods were applied to get the best classification. Validation was done by ground referencing and a GeoEye-1 satellite image. The image from January performed best with overall accuracy of 87% and 0.69 of kappa. This method opens the possibilities of using semi-automatic classification for the Chambal badlands which is so far mapped with manual interpretations only.

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“…Por lo tanto, debido a la confluencia conjunta de estos factores se supone que la distribución espacial de procesos de erosión no obedece a una relación aleatoria (Zinck et al, 2001;Huabin et al, 2005). Se realizó un inventario de los procesos de erosión observables en la imagen aé-rea de la misión CARTA (2005).…”

Section: Distribución Espacial De Los Procesos De Erosión Y Sus Factounclassified

Análisis espacial de susceptibilidad de erosión en una cuenca hidrográfica del trópico húmedo de Costa Rica

Pérez-Rubio

Mende

2017

Rev. Ambientales.

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Los artículos publicados se distribuye bajo una Licencia Creative Commons Atribución 4.0 Internacional (CC BY 4.0) basada en una obra en http://www. revistas.una.ac.cr/ambientales., lo que implica la posibilidad de que los lectores puedan de forma gratuita descargar, almacenar, copiar y distribuir la versión final aprobada y publicada del artículo, siempre y cuando se mencione la fuente y autoría de la obra.

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Mapping and modelling mass movements and gullies in mountainous areas using remote sensing and GIS techniques

Cited by 56 publications

References 16 publications

Recommendations for the quantitative analysis of landslide risk

Recommendations for the quantitative analysis of landslide risk

Semi-automatic delineation of badlands using contrast in vegetation activity: a case study in the lower Chambal valley, India

Análisis espacial de susceptibilidad de erosión en una cuenca hidrográfica del trópico húmedo de Costa Rica

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