The scarcity of data poses a challenging obstacle for the study of natural disasters, especially in developing countries where the social vulnerability plays as important a role as the physical vulnerability.  The work presented in this thesis is oriented towards the demonstration of the usefulness of press archives as a data source for the temporal and spatial analysis of landslides in Tegucigalpa, Honduras for the period between 1980 and 2005.  In the last four decades, Tegucigalpa has been characterized by a disorganized urban growth that has significantly contributed to the destabilization of the city’s slopes.  In the first part of the thesis, a description of the database compilation procedure is provided.  The limitations of using data derived from press archives have also been addressed to indicate how these affect the subsequent landslide analyses.  In the second part, the temporal richness offered by press archives has allowed the establishment of rainfall thresholds for landslide occurrence.  Through the use of the critical rainfall intensity method, the analysis of rainfall thresholds for 7, 15, 30 and 60 antecedent days shows that the number of yielded false alarms increases with the threshold duration.  A new method based on the rainfall frequency contour lines was proposed to improve the distinction between days with and without landslides.  This method also offers the possibility to identify the landslides that may only occur with a major contribution of anthropogenic disturbances as well as those landslides induced by high-magnitude rainfall events.  In the third part, the matrix method has been employed to construct two landslide susceptibility maps: one based on the multi-temporal press-based landslide inventory and a second one based on the landslide inventory derived from an aerial photograph interpretation carried out in 2014.  Despite the low spatial accuracy provided by the press archives in locating the landslides, both maps exhibit 69% of consistency in the susceptibility classes and a good agreement in the areas with the highest propensity to landslides.  Finally, the integration of these studies with major actions required to improve the process of landslide data collection is proposed to prepare Tegucigalpa for future landslides.

完善的崩塌地資料庫有助於地區土地利用的適宜性評估、與環境保護措施之研訂。目前，崩塌地地理空間資料(Geospatial data)的產生方法主要為：人為判釋經正射糾正(Ortho-rectification)的遙測影像，基於該影像，將辨識目標數位化(Digitizing)。然而，遙測影像的「正射糾正」與「人為判釋」往往不敷災後的緊急需求。為促進資料收集效率，本研究試圖發展一套自動化流程：以「未經糾正的遙測影像」為判釋對象，判釋作業以「物件式影像分類(Object-based classification)技術」進行，並利用「現存地形資料」，實現自動判釋所產生之辨識成果的地理對位(Georeferencing)與過濾篩選；最後，以「與現存各類輔助資料的套疊分析成果」為其屬性，以便利崩塌地地理空間資料的後續應用。 物件式影像分類分為為「影像分割(Image segmentation)」與「物件分類」兩步驟。於影像分割階段，採用多重解析度分割法(Multiresolution segmentation algorithm)─由於陰影下各類地物的影像光譜差異較不明顯，為避免陰影區之錯誤分割，賦予陰影區較小的尺度參數(Scale parameter)；於物件分類階段，基於訓練資料，以「線性核函數的支持向量機(Support Vector Machine, SVM, with a linear kernel)」為分類器，偵測「非雲與植被區」，並輸出為向量式資料(Vector data)。而後基於現存地形資料，以光線追蹤法(Ray-tracing algorithm)進行分類器輸出向量式資料的地理對位，並自訂第二階段的地形特徵過濾準則。實驗成果顯示，此自動化流程產出的崩塌地地理空間資料─其生產者精度(Producer’s accuracy)與使用者精度(User’s accuracy)分別介於0.85~0.99與0.44~0.96。