scholarly journals Using raster and vector data to identify objects for classify in flood risk. A case study: Raciborz

2018 ◽  
Vol 29 ◽  
pp. 00026
Author(s):  
Mariusz Porczek ◽  
Dorota Rucińska ◽  
Stanisław Lewiński

The severe flood of 1997, which seriously affected Polish, Czech and German territories, gave impetus to research into the management of flood-prone areas. The material losses caused by the “Flood of the Millennium” totalled billions of Polish zloty. The extent of the disaster and of infrastructure repair costs changed the attitude of many branches of the economy, and of science. This is the direct result of consideration of the introduction of changes into spatial management and crisis management. At the same time, it focused the interest of many who were trained in analysing the vulnerability of land-use features to natural disasters such as floods. Research into the spatial distribution of geographic environmental features susceptible to flood in the Odra valley was conducted at the Faculty of Geography and Regional Studies of the University of Warsaw using Geographic Information Systems (GIS). This study seeks to examine the possibility of adapting vector and raster data and using them for land-use classification in the context of risk of flood and inundation damage. The analysed area of the city and surrounding area of Raciborz, on the upper Odra River, is a case study for identifying objects and lands susceptible to natural hazards based on publicly available satellite databases of the highest resolution, which is a very important factor in the quality of further risk analyses for applied use. The objective of the research was to create a 10×10-m-pixel raster network using raster data made available by ESA (Copernicus Land Monitoring Service) and vector data from Open Street Map.

2018 ◽  
Vol 14 (4) ◽  
pp. 181-191 ◽  
Author(s):  
Lucie Félicité Temgoua ◽  
Marie Caroline Momo Solefack ◽  
Vianny Nguimdo Voufo ◽  
Chrétien Tagne Belibi ◽  
Armand Tanougong

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jun Yang ◽  
Yuechen Li ◽  
Jianchao Xi ◽  
Chuang Li ◽  
Fuding Xie

We used buffer superposition, Delaunay triangulation skeleton line, and other methods to achieve the aggregation and amalgamation of the vector data, adopted the method of combining mathematical morphology and cellular automata to achieve the patch generalization of the raster data, and selected the two evaluation elements (namely, semantic consistency and semantic completeness) from the semantic perspective to conduct the contrast evaluation study on the generalization results from the two levels, respectively, namely, land type and map. The study results show that: (1) before and after the generalization, it is easier for the vector data to guarantee the area balance of the patch; the raster data’s aggregation of the small patch is more obvious. (2) Analyzing from the scale of the land type, most of the land use types of the two kinds of generalization result’s semantic consistency is above 0.6; the semantic completeness of all types of land use in raster data is relatively low. (3) Analyzing from the scale of map, the semantic consistency of the generalization results for the two kinds of data is close to 1, while, in the aspect of semantic completeness, the land type deletion situation of the raster data generalization result is more serious.


SIASAT ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 21-32
Author(s):  
Olusola Oladapo Makinde ◽  
Muhammad Ridwan ◽  
M. Yoserizal Saragih

Land uses involve important economic and environmental implications for policy issues. To monitor the trend in land use in tertiary institution, statistics on land use overtime must be developed. The study investigated the various uses of land in Obafemi Awolowo University (OAU); determine their size base on an area of land covered, and determine the major land uses in OAU to inform planners on the basic tool for institutional physical development and insight for enhancing planning. The Google earth pro and OAU base map were subsequently used to enhance visual interpretation and aid the identification and mapping of the various land use in the study area. Findings from the study show that the total landed area is 5,609 hectares. The undeveloped area constitutes more than half of the total landed area with 3382 hectares (60 %). A total of 1,216 hectares of land was set aside for agriculture purposes and research, the major land uses is residential with 456.74 hectares (45.18%); institutional uses had 257.02 hectares (25.42%); other uses had 115.97 hectares (11.47%); water bodies had 83.5 hectares (8.26%); transportation had 56.33 hectares (5.57%); commercial had 38.36 hectares (3.79%); and Recreation had 3.08 hectares (0.31 %), the least proportion of land use. The study concluded that land use should be monitored, regulated, and controlled by the various relevant planning and monitoring agencies of the university.   


Sign in / Sign up

Export Citation Format

Share Document