Transcript basesheet
International Institute for Geo-Information Science and Earth Observation (ITC) RiskCity Exercise 5: Generating an elements at risk database Cees van Westen (ed) ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Elements at risk / Assets • What may be impacted by a hazard event? ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Two options • When you don’t have any available data: • We assume that you have at least a high resolution image from Google Earth • When you have available data: • • • Building footprint map Lidar DSM Census data Depending on your interest in the topic you may select to either do Exercise 3.1 (creating a database by starting from scratch), or Exercise 3.2 (creating a database with available footprint information). You can also decide to do both exercises, although that might perhaps take a bit ISL much 2004 too time International Institute for Geo-Information Science and Earth Observation (ITC) If you don’t have data • You have to: • Generate mapping units • Create the attribute data for: • Urban land use • Number of buildings • Population ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Flowchart: do it yourself option High res image Input data Screen digitize boundaries Mapping units Boundaries Sample # buildings by landuse type Polygonize Interpret land use type Population ISL 2004 Calculate # based on land use type & building # Landuse Nr Buildings Calculate # based on land use type International Institute for Geo-Information Science and Earth Observation (ITC) Downloading imagery from Google Earth • Many area in the world are covered by high resolution imagery. Better first consult than download For detailed download you need Google Earth Pro (cost 400 US $) • • • • • • ISL 2004 You can download 4000 * 4800 resolution Here we don’t have Google Earth Pro on all computers. Only one in room 4 – 105 We have downloaded it already for you At home you might like to try the trial version of the Goolge Earth Pro, which allows to download high resolution images. Go to: http://earth.google.com/intl/en/product_comparison.html International Institute for Geo-Information Science and Earth Observation (ITC) Digitizing maps Scanning (automatic digitizing) Editing Y Improving Vectorizing Apply attributes X Raster mode Sensor Manual digitizing Improving Apply attributes Y Vector mode X ISL 2004 Digital Landscape Model International Institute for Geo-Information Science and Earth Observation (ITC) Digitizing mapping units Screen digitizing from high resolution image, on the basis of a digital road map Checking segments, and generation of polygons with unique identifiers ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Digitizing mapping units High res image Digitize segments Select lines and rename / delete them Added segment ISL 2004 Select points and move them Digitize a new point Create a node / remove a node International Institute for Geo-Information Science and Earth Observation (ITC) Check segments Before making polygons you have to make sure all lines are connected Error types: • Dead end in segment (1) • Intersection without node (2, 3) • Double line (4) • Self overlap (5) Digitize segments Added segment ISL 2004 Check segments International Institute for Geo-Information Science and Earth Observation (ITC) Determining land use Generation of land use legend, with relevant classes for vulnerability assessment, and keeping in mind population difference Interpreting predominant landuse from the high resolution image ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Landuse classification • Urban landuse mapping: ISL 2004 Name Com_business Com_hotel Com_market Com_shop Ind_hazardous Ind_industries Ind_warehouse Ins_fire Ins_hospital Ins_office Ins_police Ins_school Pub_cemetery Pub_cultural Pub_electricity Pub_religious Rec_flat_area Rec_park Rec_stadium Res_large Res_mod_single Res_multi Res_small_single Res_squatter River unknown Vac_car Vac_construction vac_damaged Vac_shrubs Code Com_b com_h com_m com_s ind_h ind_i ind_w ins_f ins_h ins_o ins_p ins_s Pub_g pub_c pub_e pub_r rec_f rec_p rec_s res_5 res_4 res_3 res_2 res_1 riv u vac_c vac_u vac_d vac_s Description Business offices Hotels Commercial area: market area Commercial: shops and shopping malls Hazadous material storage or manufacture Industries Warehouses and workshops Fire brigade Hospitals Office buildings Police station Institutional : schools Cemetery Institutional: cultural buildings such as musea, theaters Electricity installations Religious buildings such as churches, mosques or temples Recreational: flat area or foorball field Recreational: park area Recreational : stadium Residential: large free stading houses Residential, moderately sized single family houses Residential: multi storey buildings Residential, small single family houses, mostly in rows Residencial, low class houses: squatter areas River Vacant : car parking and busstation Vacant area which is prepared for building construction Area recently damaged by hazard events Vacant land with shrubs, trees and gress International Institute for Geo-Information Science and Earth Observation (ITC) Fill in missing parts ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Estimating number of buildings • Methods: Count all buildings in the map…. Sample buildings for landuse types 1. 2. Steps: • Calculate building size building_size:=iff(buildings_sampled=0,0, area/ buildings_sampled) • Average building size per land use type nr_buildings:=iff(isundef(buildings_sampled),area/avg_building_size, buildings_sampled) ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Estimating population distribution • Link the number of people per building to land use type • Daytime_population:=nr_buildings * person_building * daytime ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) If you have available data ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Number of buildings Cross: Building map with mapping units. •how much of the mapping unit is not built-up •how many individual buildings there are per mapping unit •the average building size for each urban land use. Areavacant:=iff(isundef(building_map),area,0) Area_building:=iff(isundef(building_map),?,area) Building:=iff(isundef(building_map),0,1) ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Aggregate results to mapping units • Calculate per mapping unit: • Total_area= total area per mapping unit • Total_vacant_area = total vacant area per mapping unit • Avg_Size = average building size per mapping unit • Nr_buildings = number of buildings per mapping unit • Percvacant:= Total_vacant_area /Total_area ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Building height & floorspace DEM from topomap DEM from Lidar minus Landuse map ISL 2004 Masking out areas without buildings Division by avg. building height International Institute for Geo-Information Science and Earth Observation (ITC) Altitude of objects Command Line Lidar DEM Topo DEM ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Calculate number of floors • Altitude_dif=LidarDEM-TopoDem • floor_nr=iff(Altitude_dif <3,0, Altitude_dif /3) • Floors:=iff(isundef(building_map),0,f oor_nr) ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Calculate height of buildings • First we cross the Building_map with the map Floors, which gives us all the combinations of floors per building type. • Then we calculate per building the maximum number of floors, and the total floor space for each building. • The resulting values are then read in the Cross table that links the mapping units with the building ID’s (Mapping_units_building). • And finally the total floorspace information is aggregated into the table Mapping_units_attributes ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Calculate floorspace • Floorspace:=Nr_floors*Area_building • Open the cross table Mapping_units_building. And join with the table Building_map. Read in the columns: Nr_floors and Floorspace • Aggregate to Table: Mapping_units_attributes • Nr_floors_avg =average number of floors per building in mapping unit • Floorspace = floorspace per mapping unit ISL 2004 International Institute for Geo-Information Science and Earth Observation (ITC) Population estimate • We have information on the population per ward. • We know the floorspace per mapping unit • We can therefore distribute the total population per ward over the mapping unit, also keeping in mind the land use types. • This exercise is not written out: something for the final project ISL 2004