Linganisha mbinu

	Landslide Susceptibility Mapping	Uchanganuzi wa Uhatarishaji wa Kutetemeka kwa Uwezekano (PSHA)
Nyanja	Disaster Studies	Uhandisi wa Ujenzi
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	2006	1968
Mwanzilishi	Fausto Guzzetti, Paola Reichenbach and colleagues (CNR-IRPI; statistical landslide susceptibility tradition)	C. Allin Cornell
Aina	Spatial statistical classification pipeline over mapping units	Quantitative probabilistic framework
Chanzo asilia	Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., & Guzzetti, F. (2018). A review of statistically-based landslide susceptibility models. Earth-Science Reviews, 180, 60-91.	Cornell, C. A. (1968). Engineering seismic risk analysis. Bulletin of the Seismological Society of America, 58(5), 1583–1606.
Majina mbadala	Landslide Susceptibility Modeling, Slope-Failure Susceptibility Mapping, Statistical Landslide Hazard Mapping, Landslide Probability Mapping	PSHA, seismic hazard analysis, probabilistic earthquake hazard assessment, Cornell-McGuire method
Zinazohusiana	3	1
Muhtasari	Landslide susceptibility mapping estimates where slope failures are likely to occur by statistically relating a mapped inventory of past landslides to the terrain conditions that predispose a slope to fail. The premise, articulated across the statistical landslide literature that Guzzetti, Reichenbach, and colleagues helped systematize, is that landslides recur under geological and morphological conditions similar to those that produced them before, so the spatial pattern of past failures reveals the susceptibility of as-yet unfailed terrain. The analyst partitions the landscape into mapping units, characterizes each by conditioning factors such as slope, aspect, lithology, and land cover, and fits a classifier — logistic regression, discriminant analysis, or machine learning — to predict the probability of failure. Reichenbach and co-authors' 2018 review of 565 studies catalogued the methods, factors, and validation practices, while Guzzetti and co-workers' 2006 paper established how to rigorously assess model quality. The output is a zonation ranking terrain from low to high susceptibility. Susceptibility maps describe spatial likelihood, not when or how large a failure will be.	Probabilistic Seismic Hazard Analysis (PSHA) is a quantitative engineering framework used in civil and geotechnical engineering to estimate the likelihood that ground shaking will exceed a specified intensity level at a site within a given time window. By combining earthquake source geometry, recurrence statistics, and ground-motion attenuation models, PSHA produces hazard curves and maps that inform seismic design codes, infrastructure planning, and risk management decisions.