Remote Sensing the Urban Landscape

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Remote Sensing the Urban Landscape Urban landscape are composed of a diverse assemblage of materials (concrete, asphalt, metal, plastic, shingles, glass, water, grass, shrubbery, trees, and soil) arranged by humans in complex ways to build housing, transportation, utilities, commercial and industrial facilities, and recreational landscape. Remote Sensing data collection and processing provide basic human spatial services for urban studies and applications. Detailed urban land information is required by: City, county, and regional councils of government which legislate zoning regulations to hopefully improve the quality of life in the urbanized areas City and state departments of commerce which are mandated to stimulate development, often to increase the tax base Tax assessor offices which maintain legal geographic descriptions of every parcel of land, assess its value County and state departments of transportation that maintain existing facilities, build new facilities, and prepare future transportation demand Public and private utility companies (water, sewer, gas, electricity, telephone, cable) to plan and provide the most efficient cost-effective services Departments of parks, recreation, and tourism to improve facilities Departments of emergency management for mitigating destruction and allocating resources in the event of a disaster Private real estate companies which are paid to find the ideal location for industrial, commercial, and residential development Developers who continually build residential, commercial, and industrial facilities to stay business.

Disasters Requiring Immediate Emergency Response Chlorine gas gas Disasters Requiring Immediate Emergency Response Mudslide

Disasters Requiring Immediate Emergency Response On December 24, 2004, tsunami swept across the Indian Ocean, spawned by a magnitude 9.0 earthquake off the coast of Sumatra. The Indonesia province of Aceh was hit the hardest by the earthquake and tsunamis. The IKONOS images show that the town of Lhoknga was completely destroyed. Disasters Requiring Immediate Emergency Response On December 24, 2004, tsunami swept across the Indian Ocean, spawned by a magnitude 9.0 earthquake off the coast of Sumatra. Aside from Indonesia, the island nation of Sri Lanka likely suffered the most casualties. The QuickBird image acquired on December 26, 2009 illustrates that the water is flowing out of the inundated area and back to ocean, creating turbulence offshore.

Disasters Requiring Immediate Emergency Response On April 6, 2009 (yesterday), a magnitude 6.3 earthquake hit central Italy. The SRTM image illustrate the topography of the central Apennine Mountains and the faults along which the earthquake occurred. Disasters Requiring Immediate Emergency Response On May 12, 2008, a magnitude 8.0 earthquake hit Wenchun, China (the 19 th deadliest earthquake of all time).

Temporal and Spatial Characteristics of Urban Attributes and Remote Sensing Systems There are a number of remote sensing systems that currently provide some of the desired urban/socio-economic information when the spatial resolution required is poorer than 5 x 5 m and the temporal resolution is between 1 and 55 days. Very high spatial resolution data (<1 x 1 m) is required to satisfy many of the socio-economic data requirements. USGS (Anderson) Classification System 1 Urban or Built-up 11 Residential 111 Single-Family Residential 1111 House, houseboat, hut, tent 1112 Mobile home 112 Multiple-Family Residential 1121 Duplex 1122 Triplex 1123 Apartment Complex or Condominium 1124 Mobile home (trailer) park

Urban/Suburban Applications and the Minimum Resolutions Required

Urban/Suburban Applications and the Minimum Resolutions Required Clear polygons represent the spatial and temporal characteristics of selected urban attributes Temporal Resolution in minutes Gray boxes depict the spatial and temporal characteristics of the remote sensing systems that may be used to extract the required urban information

Urban/Suburban Spectral Resolution Considerations USGS Level III land-cover is best acquired using the visible (0.4-0.7 µm), near IR (0.7-1.1 µm), middle-ir (1.5-2.5 µm), and/or panchromatic (0.5-0.7 µm) portions of the spectrum. Building perimeter, area, and height information is best acquired using black-and-white panchromatic (0.5-0.7 µm) or color imagery (0.4-0.7 µm). TIR (3-12 µm) information may be used to obtain urban temperature measurements and study the effects of urban heat island. QuickBird satellite image 0.6-m spatial resolution

QuickBird satellite image 2.5-m spatial resolution Urban/Suburban Spatial Resolution Considerations Generally, the higher the spatial resolution of remote sensing data, the more detailed information that can be extracted in the urban environment. But how do we know what spatial resolution imagery to use for a specific urban application? Some references are available.

Nominal Spatial Resolution (Ground-Resolved Distance) Rule: There needs to be a minimum of four spatial observations (e.g., pixels) within an urban object to identify it. Or, the sensor spatial resolution should be onehalf the width of the smallest object of interest. For example, to identify mobile homes that are 5 meters wide, the minimum spatial resolution is less than 2.5 x 2.5 m pixels. Urban/Suburban Temporal Resolution Considerations Stages of Development: Original state Partial or complete clearing Land subdivision Roads Buildings Landscaping

Urban/Suburban Temporal Resolution Considerations Stages of Development: Original state Partial or complete clearing Land subdivision Roads Buildings Landscaping Residential Land Use Prior to investigating how residential land use appears on remotely sensed data, it is important to introduce the concept of Form and Function. Basically, the function of a building often dictates its form. For example, the need to house a single family often results in the creation of a detached dwelling composed of several attached rooms. Quality of Life Indicator A research topic.

Single Family Residential Multiple-family Residential

Transportation Infrastructure Temporal Spatial Resolution Resolution T1 - general road centerline 1-5 years 1-30 m T2 - precise road width 1-2 years 0.25-0.5 m T3 - traffic count studies 5-10 min 0.25-0.5 m T4 - parking studies 10-60 min 0.25-0.5 m

The Dalton Highway and Trans-Alaska-Pipeline Commercial and Services An extended USGS land-use and land-cover classification system represents a common-sense hierarchical system that can be aggregated back to level I and II. 1. Central Business District 2. Automotive and Boat 3. Department Stores 4. Finance and Construction 5. Food and Drug 6. Funeral and Cemetery 7. House and Garden 8. Recreation 9. Warehousing/Shipping 10. Public Buildings and Facilities (administration, fire, police, postal, libraries... 11. Education 12. Medical.

Commercial and Services

Recreation

Recreation

Industrial Land Use Industries often have unique assemblages of raw materials, equipment, final products and waste, as well as buildings that characterize the industry. 1. Mechanical-processing Industries 2. Chemical-processing Industries 3. Heat-processing Industries 4. Transportation Infrastructure 5. Communications and Utilities. Processing: Chemical

Processing: Mechanical Industry: Extractive

Socioeconomic Characteristics Population Estimations Energy Demand and Conservation Quality of Life Indicators Building Lot Adjacent Amenities Adjacent Hazards Remote Sensing Assisted Population Estimation Population estimation can be performed at the local, regional, and national level based on: counts of individual dwelling units, measurement of land areas, and land use classification.

Dwelling Unit Estimation Technique Assumptions: imagery must be of sufficient spatial resolution (0.3-5 m) to identify individual structures even through tree cover and whether they are residential, commercial, or industrial buildings; some estimate of the average number of persons per dwelling unit must be available, and it is assumed all dwelling units are occupied. Urban/surburban attributes that may be extracted from remote sensor data and used to assess housing quality and/or quality of life

Impervious Surface: is defined as any impenetrable material that prevents infiltration of water into the soil. Rooftops Roads Sidewalks Parking lots Driveways Other manmade concrete surfaces Environmental Impact of Impervious Surface Areas Impervious surface has been identified as a key environmental indicator due to its impacts on water systems and its role in transportation and concentration of pollutants. Studies about the relationship between ISA and watershed suggested that: < 10% slightly impacted 10%-25% water quality is impacted > 25% water quality is degraded

Methods for Extraction of Impervious Surface Areas 1. Manual delineation through aerial photography 2. Classification of middle resolution remote sensing data 3. Sub-pixel methods 4. Estimation from land-use and land-cover data and impervious surface coefficient 5. ISA extraction from high spatial resolution remote sensing data Comparison of Orthophotos and QuickBird-2 images

Extracted impervious surface areas from orthophotos (top) and QuickBird-2 (bottom)

The result indicates that 10.3% of the state land are covered by the ISA. Only sixteen towns in the state have ISA cover less than 10%.. ISA Non-ISA