International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 RiskCity Exercise 5: Generating an elements at risk database Cees van Westen (ed)

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Elements at risk / Assets What may be impacted by a hazard event?

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 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 too much time

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 If you don’t have data You have to: Generate mapping units Create the attribute data for: Urban land use Number of buildings Population

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Flowchart: do it yourself option High res image Boundaries Landuse Nr Buildings Input data Population Polygonize Screen digitize boundaries Mapping units Interpret land use type Sample # buildings by landuse type Calculate # based on land use type Calculate # based on land use type & building #

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 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 $) 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:

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Digitizing maps X Y Scanning (automatic digitizing) Editing Improving Vectorizing Apply attributes X Y Manual digitizing Raster mode Vector mode Sensor Improving Apply attributes Digital Landscape Model

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 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

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Digitizing mapping units High res image Digitize segments Added segment Digitize a new point Create a node / remove a node Select points and move them Select lines and rename / delete them

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Check segments Digitize segmentsCheck segments Added segment 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)

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 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

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Landuse classification Urban landuse mapping:

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Fill in missing parts

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Estimating number of buildings Methods: 1. Count all buildings in the map…. 2. Sample buildings for landuse types 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)

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Estimating population distribution Link the number of people per building to land use type Daytime_population:=nr_buildings * person_building * daytime

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 If you have available data

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Number of buildings Areavacant:=iff(isundef(building_map),area,0) Area_building:=iff(isundef(building_map),?,area) Building:=iff(isundef(building_map),0,1) 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.

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 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

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Building height & floorspace DEM from Lidar Division by avg. building height DEM from topomap minus Masking out areas without buildings Landuse map

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Altitude of objects Command Line Lidar DEM Topo DEM

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 Calculate number of floors Altitude_dif=LidarDEM-TopoDem floor_nr=iff(Altitude_dif <3,0, Altitude_dif /3) Floors:=iff(isundef(building_map),0,fl oor_nr)

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 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

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 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

International Institute for Geo-Information Science and Earth Observation (ITC) ISL 2004 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