Multisource classification for land-use mapping based on spectral, textural, and terrain information using landsat thematic mapper imagery: A Case Study of Semarang-Ungaran Area, Central Java

Automatic classification of remotely sensed digital data is recognised as a robust and efficient method for mapping various land-cover types over a large area. However when more abstract concept such as land-use is required the automatic classification methods cannot be fully useful. This is due to the fact that land-use is related to various landscape factors, and cannot be mapped merely based on its spectral reflectance. This study tried to develop a knowledge-based technique that incorporates textural and terrain information of the image scene into a spectral-based decision making process for land-use labelling. To do so. six reflective hands of Landsat Thematic Mapper (TM) covering Semarang-Ungaran area. Central Java, were used. In addition, all bands were then be filtered using the so-called textural filter, which can accentuate several statistical parameters within a given window. .1 variance parameter was chosen in order to extract heterogeneity within every 7x7 pixels. and the l'ariance values of the whole image dalaset were then stored as a set of texture-filtered bands. Three bands with the lowest 'between-band correlations' were chosen and added to the reflective bands. Based on the nine-layer image dataset, a standard multispectral classification using maximum likelihood algorithm was run. Parallel to this process, a visual interpretation using heads-up digitisation was carried out in order to generate a terrain unit map containing land characteristics relevant to spatial distribution of the land-use in the study area. Finally. the terrain unit map was superimposed with the tentative land-corer map derived from the multispectral classification process. A final land-use map was generated from the nnthisource data integration, controlled by a formalised knowledge about ecological relationship between land-cover. land-use, and land characteristics exist in the field. It was found that the overall accuracy level of the final land-use map is higher as compared to the result generated from six-band classification. However, the use of textural filter also created an 'edge-effect', which shows misclassified pixels alongside the borders of particular land-use categories. The edge-effect also leads to lower accuracy levels for the corresponding land-use categories. In addition, based on the research findings, further research agenda was also set up.

Combining Social Vulnerability and Physical Vulnerability to Analyse Landslide Risk at the Municipal Scale

In this work residents’ social vulnerability and buildings’ physical vulnerability of the Loures municipality (Portugal) were combined to locate the areas where the vulnerability is the highest, and to analyse the landslide risk. The social vulnerability of Loures was assessed using the Geographic Basis for Information Reference (BGRI) terrain units by combining sensitivity and lack of resilience based on the population and housing Census 2011 data. The physical vulnerability was assessed in a previous study based on an inquiry of a pool of European landslide experts and a sub-pool of landslide experts who know the study area. A matrix approach was used to cross the classes of the social and physical vulnerabilities. Finally, the landslide risk was analysed for each terrain unit considering the combined vulnerability, the buildings’ economic value and the landslide susceptibility for a specific landslide magnitude (3-metre-deep rotational slide). Results show that 0.9% of the population reside in the area of the municipality where 75% of the future landslide should occur, and 0.8% of the buildings of the municipality—which represent a value of EUR 146,170,000—are also located in this dangerous area. This approach is reproducible: the risk analysis can be applied for another magnitude scenario in Loures, and the combined vulnerability can be assessed in any Portuguese municipality thanks to the availability of the data.

A Multiple Natural Hazards Assessment Model Based on Geomorphic Terrain Units

A Multiple Natural Hazards Assessment (MNHA) procedural model was developed to provide stakeholders (e.g., community planners and decision makers) with a clear methodology that examines the landscape as a probabilistic-based composite measure of the natural hazards at a terrain mapping unit scale. The model consists of four phases: (1) data collection; (2) individual natural hazard assessment (INHA); (3) Geomorphic Terrain Unit (GTU) development; and (4) composite MNHA classification. The model was tested in a case study across southern Davis County, Utah. Six hazards were integrated within a GIS model, producing a nonweighted probabilistic-based multi-hazard classification across GTUs. Examination of the results by stakeholders showed great potential for the model. During the evaluation workshop, stakeholders concurred that normalizing the class values using a simple frequency-based scale makes it easier to discern the differences in composite hazardousness across the community. The model is easily expanded to include objective or subjective weighting factors.

A Multiple Natural Hazards Assessment Model Based on Geomorphic Terrain Units

A Multiple Natural Hazards Assessment (MNHA) procedural model was developed to provide stakeholders (e.g., community planners and decision makers) with a clear methodology that examines the landscape as a probabilistic-based composite measure of the natural hazards at a terrain mapping unit scale. The model consists of four phases: (1) data collection; (2) individual natural hazard assessment (INHA); (3) Geomorphic Terrain Unit (GTU) development; and (4) composite MNHA classification. The model was tested in a case study across southern Davis County, Utah. Six hazards were integrated within a GIS model, producing a nonweighted probabilistic-based multi-hazard classification across GTUs. Examination of the results by stakeholders showed great potential for the model. During the evaluation workshop, stakeholders concurred that normalizing the class values using a simple frequency-based scale makes it easier to discern the differences in composite hazardousness across the community. The model is easily expanded to include objective or subjective weighting factors.

Identifikasi Medan untuk Keterlintasan Rel Kereta Api antara Gundih–Karangsono Kabupaten Grobogan

This reseach aimed to 1) identify the characteristics terrain for railway track between Gundih-Karangsono, 2) evaluate the capability of terrain and faffecting factors of damages on the track. Field survey and laboratory analysis were used to collect stratified sampling based primary data namely slope, points load index, structure of rock, erosion, mass movement, permeability, soil texture, water degree, potential volume change. Secondary data consists of rainfall, topography map, geology map, soil map and landuse map. Factors that cause train stripe between Gundih-Karangsono often experience damage are: points load index in every terrain unit 3 kg/cm² (very weak), soil texturs are clay and clay loam, soil permeabilities are 0,164-0,579 height of water is from 50-57 % and soil volume changing potential very high, from 6,4-6,5 cm.