Synthetic aperture radar interferometry is an imaging technique for measuring the topography of a surface, its changes over time, and other changes in the detailed characteristic of the surface. By exploiting the phase of the coherent radar signal, interferometry has transformed radar remote sensing from a largely interpretive science to a quantitative tool, with applications in cartography, geodesy, land cover characterization, and natural hazards. This paper reviews the techniques of interferometry, systems and limitations, and applications in a rapidly growing area of science and engineering.

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Synthetic aperture radar interferometry

Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy

Landsliding in response to rainfall involves physical processes that operate on disparate timescales. Relationships between these timescales guide development of a mathematical model that uses reduced forms of Richards equation to evaluate effects of rainfall infiltration on landslide occurrence, timing, depth, and acceleration in diverse situations. The longest pertinent timescale is A/D0, where D0 is the maximum hydraulic diffusivity of the soil and A is the catchment area that potentially affects groundwater pressures at a prospective landslide slip surface location with areal coordinates x, y and depth H. Times greater than A/D0 are necessary for establishment of steady background water pressures that develop at (x, y, H) in response to rainfall averaged over periods that commonly range from days to many decades. These steady groundwater pressures influence the propensity for landsliding at (x, y, H), but they do not trigger slope failure. Failure results from rainfall over a typically shorter timescale H2/D0 associated with transient pore pressure transmission during and following storms. Commonly, this timescale ranges from minutes to months. The shortest timescale affecting landslide responses to rainfall is H/g, where g is the magnitude of gravitational acceleration. Postfailure landslide motion occurs on this timescale, which indicates that the thinnest landslides accelerate most quickly if all other factors are constant. Effects of hydrologic processes on landslide processes across these diverse timescales are encapsulated by a response function, R(t*) = t*/π exp (−1/t*) − erfc (1/t*), which depends only on normalized time, t*. Use of R(t*) in conjunction with topographic data, rainfall intensity and duration information, an infinite-slope failure criterion, and Newton's second law predicts the timing, depth, and acceleration of rainfall-triggered landslides. Data from contrasting landslides that exhibit rapid, shallow motion and slow, deep-seated motion corroborate these predictions.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2000WR900090

Landslide triggering by rain infiltration

A copy of Guangbo jiemu bao [Broadcast Program Report] was being passed from hand to hand among a group of young people eager to be the first to read the article introducing the program "What Is Revolutionary Love?" It said: "… Young friends, you are certainly very concerned about this problem'. So, we would like you to meet the young women workers Meng Xiaoyu and Meng Yamei and the older cadre Miss Feng. They are the three leading characters in the short story ‘The Place of Love.’ Through the description of the love lives of these three, the story induces us to think deeply about two questions that merit further examination.

This is How the Discussion Started

The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan

Slope instability : the role of remote sensing and GIS in recognition, analysis and zonation

The aim of this paper is to discuss a number of issues related to the use of spatial information for landslide mapping over larger areas. The last few decades have shown very rapid development of the application of digital tools such as Geographic Information Systems, Digital Image Processing, Digital Photogrammetry and Global Positioning Systems. In landslide risk assessment at scales of 1:10,000 or smaller, GIS has become the standard tool. Much progress has been made in the generation of Digital Elevation Models obtained from different sources, ranging from SRTM to LIDAR, and these are used to generate landslide inventories. Landslide inventories can now make use of a variety of approaches, ranging from digital stereo image interpretation to automatic classification, based either on spectral or altitude differences, or a combination of both. Landslide inventory databases are becoming available to more countries and several are now also available through the Internet. A comprehensive landslide inventory is a basic requirement in order to be able to quantify both landslide hazard and risk. INTRODUCTION The first extensive papers on the use of spatial information in a digital context for landslide susceptibility mapping date back to the late seventies and early eighties of the last century. Among the pioneers in this field were Brabb and co-workers in California (Brabb et al., 1978) and Carrara and co-workers in Italy (Carrara et al., 1977). Nowadays, practically all research on landslide susceptibility and hazard mapping makes use of digital tools such as GIS, GPS and Remote Sensing. These tools also have defined, to a large extent, the type of analysis that can be carried out. It can be stated that GIS has determined, to a large degree, the current state of the art in landslide hazard and risk assessment. This is particularly so for landslide studies that cover larger areas. Glade and Crozier (2005) present an interesting discussion on the relation between data availability, model complexity and predictive capacity, based on earlier work by Grayson et al. (2002). They conclude that each type of model has an optimum data set (in terms of resolution, accuracy, and complexity) and that an increase in the data availability will not lead to an increase in the predictive capacity, when using models with the same complexity. In general it can be stated that data availability decreases with increasing size of study areas and therefore, the optimum complexity of the models used in hazard and risk analysis also decreases with scale. Advanced 3-D slope stability models can be used at site investigation scales when a detailed understanding of the subsurface conditions is available from boreholes, geophysical studies, and laboratory analysis, along with on-site monitoring of water conditions and landslide movement history. However, these types of data are typically available at too few locations to apply the same 3-D model approaches at mapping scales of 1:5000 or smaller. Landslide risk assessment intends to estimate the expected losses due to landslides for a particular area and time period. These losses can be direct or indirect, and can be physical, social, economic, or environmental in nature. Most of the published work on landslide risk assessment is limited to the estimation of direct physical losses to buildings and infrastructure, and to evaluations of human casualties/injuries (Alexander, 2005). When dealing with physical losses,

Mapping landslides : recent developments in the use of digital spatial information : keynote

Remote sensing and geographic information systems for geologic hazard mitigation

The necessity to identify and monitor slope movement is of paramount importance to reduce the socio-economic toll that every year is paid in developing as well as in developed countries. From the late 80's Italian and Swiss legislations regarding hydro-geological risks, have identified landslide hazard maps as essential tools to mitigate the risk associated to landslides. Several projects funded by the European Space Agency within the framework of its Data User Program (DUP), have investigated the feasibility and the operational applicability of spaceborne imagery to respond to the needs of governmental institutions that have a mandate in landslide analysis and prevention. Techniques based on SAR interferometry and on the combination of state of the art Remote Sensing observations with CIS modeling have been analysed in order to assess the contribution of Satellite Remote Sensing information in support to the practices of the Geological Risk Services Agencies.

SLAM, the development of an EO service to support the legal obligations of Swiss and Italian Geological Risk Services in landslide risk forecasting and prevention

Landslide is a common natural disaster occurring in Indonesia during the rainy season from November to February. Attempts have been made to develop an early warning system based on the rainfall derived from satellite observation. It is essential to verify the accuracy level of the rainfall threshold in predicting the occurrence of rainfall, causing landslides and non-landslides to model the lower limit that can be used as an early warning device of the landslides. In this analysis, modelling was carried out with an empirical (intensity—duration/ID) approach using 220 data of rainfall that triggered landslide with satellite-based TRMM in Indonesia territory. The intensity and duration of antecedent rainfall were utilized in rainfall threshold modelling. The rainfall threshold was validated with ROC analysis. This method used seven statistics indices and ROC curve to determine the accuracy rate of the rainfall threshold. The results showed empirical equation I = 7.83D−0.328 within the interval time 2–18 days. The results of the analysis of the ROC on the rainfall threshold indicate that the model has a good accuracy rate and can be used in an early warning system of landslide even though it still has a fairly high error rate.

C.J. van Westen

Papers

Slope instability : the role of remote sensing and GIS in recognition, analysis and zonation

Mapping landslides : recent developments in the use of digital spatial information : keynote

Remote sensing and geographic information systems for geologic hazard mitigation

SLAM, the development of an EO service to support the legal obligations of Swiss and Italian Geological Risk Services in landslide risk forecasting and prevention

Development of Landslide Early Warning System Based on the Satellite-Derived Rainfall Threshold in Indonesia