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Questions and Answers
What type of materials are urban landscapes composed of?
What type of materials are urban landscapes composed of?
Remote sensing provides a detailed ground-level view of urban landscapes.
Remote sensing provides a detailed ground-level view of urban landscapes.
False
Name one type of remote sensing used for urban landscapes.
Name one type of remote sensing used for urban landscapes.
Aerial photos or satellite imagery
The urban/suburban development cycle can be identified by the presence or absence of ______________.
The urban/suburban development cycle can be identified by the presence or absence of ______________.
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How often is urban remote sensing typically collected?
How often is urban remote sensing typically collected?
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Higher spatial resolution in urban remote sensing provides less detailed information.
Higher spatial resolution in urban remote sensing provides less detailed information.
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Match the elements to their corresponding characteristics in urban landscapes.
Match the elements to their corresponding characteristics in urban landscapes.
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What is the importance of up-to-date information about urban areas?
What is the importance of up-to-date information about urban areas?
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What is a significant advantage of remote sensing compared to traditional census sources?
What is a significant advantage of remote sensing compared to traditional census sources?
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Traditional census sources frequently capture spatial details about urban areas.
Traditional census sources frequently capture spatial details about urban areas.
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Name one study that linked changes in urban vegetation to social changes.
Name one study that linked changes in urban vegetation to social changes.
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What is the dominant spatial scale of individual features in urban mosaics?
What is the dominant spatial scale of individual features in urban mosaics?
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Remote sensing makes available a vast amount of data with continuous __________ and __________ coverage.
Remote sensing makes available a vast amount of data with continuous __________ and __________ coverage.
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Match the following studies with their focus:
Match the following studies with their focus:
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Shuttle Radar Topography Mission (SRTM) data has a resolution of 15 meters.
Shuttle Radar Topography Mission (SRTM) data has a resolution of 15 meters.
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What technique is used to map urban extent and quantify physical properties in recent research?
What technique is used to map urban extent and quantify physical properties in recent research?
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What is required for effective change detection using remote sensing?
What is required for effective change detection using remote sensing?
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Urban areas are characterized by very high __________ intensity due to the abundance of buildings.
Urban areas are characterized by very high __________ intensity due to the abundance of buildings.
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Developing countries are experiencing a decline in population and urban expansion.
Developing countries are experiencing a decline in population and urban expansion.
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Match the following urban data sources with their primary characteristics:
Match the following urban data sources with their primary characteristics:
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What does remote sensing provide that is often not available from traditional census sources?
What does remote sensing provide that is often not available from traditional census sources?
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Which sensor is NOT mentioned as having sufficient resolution for distinguishing individual features in urban areas?
Which sensor is NOT mentioned as having sufficient resolution for distinguishing individual features in urban areas?
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What parameters can be derived from SRTM data?
What parameters can be derived from SRTM data?
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Spectral mixture analysis focuses on spectrally homogeneous pixels in urban areas.
Spectral mixture analysis focuses on spectrally homogeneous pixels in urban areas.
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What primarily causes sea-level rise due to global warming?
What primarily causes sea-level rise due to global warming?
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Relative sea-level change is solely due to the rise in the sea surface height.
Relative sea-level change is solely due to the rise in the sea surface height.
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Name two sources of uncertainty in using tide gauge records.
Name two sources of uncertainty in using tide gauge records.
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The melting ice caps and mountain glaciers add _______ to the oceans, resulting in sea-level rise.
The melting ice caps and mountain glaciers add _______ to the oceans, resulting in sea-level rise.
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Match the following causes or factors of sea-level change with their descriptions:
Match the following causes or factors of sea-level change with their descriptions:
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Which of the following pollutants is NOT included in the calculation of the Air Quality Index (AQI)?
Which of the following pollutants is NOT included in the calculation of the Air Quality Index (AQI)?
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AQI values above 100 are considered satisfactory for all populations.
AQI values above 100 are considered satisfactory for all populations.
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What does PM in PM2.5 and PM10 stand for?
What does PM in PM2.5 and PM10 stand for?
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The AQI is determined by the component having the highest C/Climit ratio where C is the concentration and __________ is the air quality standard for each component.
The AQI is determined by the component having the highest C/Climit ratio where C is the concentration and __________ is the air quality standard for each component.
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Match the following components of the Air Quality Index (AQI) with their respective pollutants:
Match the following components of the Air Quality Index (AQI) with their respective pollutants:
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What is the primary purpose of establishing National Ambient Air Quality Standards in the UAE?
What is the primary purpose of establishing National Ambient Air Quality Standards in the UAE?
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Remote sensing is commonly used for monitoring air quality.
Remote sensing is commonly used for monitoring air quality.
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What is the role of remote sensing in air quality monitoring?
What is the role of remote sensing in air quality monitoring?
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What is the main advantage of satellite altimetry in studying sea level changes?
What is the main advantage of satellite altimetry in studying sea level changes?
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The TOPEX/Poseidon satellite was launched in 1995.
The TOPEX/Poseidon satellite was launched in 1995.
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What is the estimated rate of sea level rise according to the TOPEX/Poseidon satellite data during the period from 1993 to 1998?
What is the estimated rate of sea level rise according to the TOPEX/Poseidon satellite data during the period from 1993 to 1998?
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The primary impact of sea level rise includes increased vulnerability to coastal _____ damage and flooding.
The primary impact of sea level rise includes increased vulnerability to coastal _____ damage and flooding.
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Match the impacts of sea level rise with their classifications:
Match the impacts of sea level rise with their classifications:
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What requires a high level of accuracy in satellite altimetry for sea level measurements?
What requires a high level of accuracy in satellite altimetry for sea level measurements?
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The combination of tide gauges and satellite altimetry has estimated the sea level rise rate as consistent over time.
The combination of tide gauges and satellite altimetry has estimated the sea level rise rate as consistent over time.
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Name one secondary impact of sea level rise.
Name one secondary impact of sea level rise.
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Study Notes
Remote Sensing and GIS in Urban Studies
- Half of the world's population lives in urban areas (United Nations 2001).
- Urban growth has significant impacts at local, regional, and global scales (Berry, 1990).
- Problems associated with urban expansion include the loss of agricultural land and natural vegetation, uncontrolled urban sprawl, increased traffic congestion, and degradation of air and water quality.
- Remote sensing is a consistent and effective tool for characterizing the urban environment, facilitating urban planning and decision-making, the study of local and regional environmental processes, and the sustainability of cities and their hinterlands.
- Satellite systems are capable of providing timely and accurate information about existing land use and land cover.
- Earlier urban studies primarily relied on photointerpreted data for census and socioeconomic prediction.
- With the introduction of multiple spectral bands, particularly thermal infrared (Landsat MSS), Landsat TM, and SPOT, the focus of research shifted towards land use and land cover classification.
- This lecture will focus on the identification and delineation of the urban environment, urban area classification, measurement and monitoring of physical properties of urban areas, analysis of physical characteristics and demographic/socioeconomic patterns of urban environments, and monitoring urban changes and growth over time.
- The first three topics address technical issues, while the last two topics are social science applications.
- Remotely sensed data can define urban areas for use in social science studies.
- Consistent definitions of "urban" vary significantly across countries (United Nations, 2001), often based on different parameters.
- Urban areas can be defined by administrative boundaries or population density, but most boundaries don't align with administrative divisions, creating difficulties for comparative studies.
- Defining urban areas based on population density thresholds that differ by country complicates comparative studies.
- Defining urban areas solely by administrative boundaries or population density doesn't account for the broader spatial extent of built-up areas.
- Satellite imagery offers a consistent and spatially referenced method for defining urban extents.
- Existing literature on urban delineation often focuses on individual cities rather than comparative studies.
- The book Remote Sensing and Urban Analysis (Donnay et al, 2001) provides methodologies and algorithms to enhance urban delineation and characterization.
- Various methods, such as data fusion from different satellites with different spatial and spectral resolutions, can be utilized to identify urban features, building types, and building density.
- Delineating urban areas is challenging; classifying urban land uses is even more so, as urban environments encompass a diverse mix of materials and land use classes (buildings, infrastructure, transportation, parks).
- Mixed pixels in urban areas, which are combinations of spectrally distinct land cover types, are often misclassified as other land cover classes by standard classification techniques.
- A minimum ground resolution of 1–5 m is required to accurately identify urban classes like single-family and multi-family residential.
- High spatial resolution often comes with reduced temporal resolution and smaller areal coverage.
- Combining satellite-derived classifications with ancillary data (socioeconomic variables like population or housing density from census data or digital elevation models) enhances urban classifications. Recent technical advancements, such as hyperspectral data, provide improved urban classification methods.
- The use of hyperspectral data has limitations in applicability to social science due to its reliance on airborne sensors.
- Urban areas impact local weather, climate, and regional/global atmospheric systems. Changes in solar radiation absorption, surface temperature, evapotranspiration, and pollutant concentrations are key effects.
- Remote sensing data effectively measures physical properties difficult or costly to obtain in situ, specifically in developing countries.
- The urban heat island (UHI) effect, measured as the difference between urban and rural temperatures, has been studied since the 1930s.
- Differences in remotely-sensed heat island temperatures and standard/mobile station measurements arise from urban geometry (roof and treetop overrepresentation), the complex coupling between the surface and air in urban environments, and the different scales of climatic phenomena in the urban atmosphere.
- Methods for measuring physical characteristics and analyzing demographic/socioeconomic patterns focus on integrating remote sensing data with socioeconomic data to enhance urban classification.
- Traditional census data is crucial but lacks spatial details and is rarely updated.
- Remote sensing offers frequent temporal and spatial coverage for monitoring urban growth and change.
- In change detection studies using remote sensing, images must be atmospherically and zenith-angle-corrected and co-registered to minimize error in land-cover estimations.
- Diverse literature exists on change studies, although primarily focused on individual cities.
- Numerous studies demonstrate integrating remote sensing data with socioeconomic information improves urban classification accuracy.
- Examples of research include using vegetation indices (NDVI) and night-time lights to understand urban growth and its socioeconomic implications.
- Various physical parameters are measured, including vegetation, ozone, dust, and overall air quality in urban areas, with spectral signatures enabling the derivation from remote sensing data.
- Urban vegetation significantly influences wind, temperature, moisture, and precipitation, impacting urban planning (heating/cooling needs, pollutant dispersion, etc.)
- Remote sensing and GIS have been used for mapping urban vegetation for urban studies.
- Remote sensing is a vital tool for creating spatial maps of air quality over extended regions where ground measurements are lacking.
- PM2.5 and PM10 concentrations are derived by measuring aerosol optical depth through algorithms such as Dark Target and Deep Blue in combination with in-situ ground measurements.
- Other measured physical parameters include ozone, dust, and overall air quality in urban areas.
- Spectral signatures and electromagnetic radiation with matter can derive estimates of physical parameters.
- Several studies correlate socioeconomic data from censuses with characteristics derived from satellite imagery
- Research using U.S. Census data and Landsat data demonstrates linear correlations between population density and vegetation cover.
- Long-term ecological research efforts, such as the one conducted by the LTER network, investigate the interactions between ecological and socioeconomic systems in urban areas.
Other Physical Parameters
- Other measured physical parameters include vegetation, ozone, dust, and overall quality in urban areas.
- Spectral signature and interaction of electromagnetic radiation with matter are used to derive estimations from remote sensing data.
Urban Vegetation
- Urban vegetation impacts wind, temperature, moisture, and precipitation regimes, affecting urban planning (heating/cooling and pollutant dispersion).
- Remote sensing and GIS are used to map and assess urban vegetation. A review of methods for mapping urban vegetation was given (Neyns, R.; Canters, F. Remote Sensing of Urban Vegetation with High-Resolution Satellite Data, Remote Sens. 2022).
Air Quality
- Remote sensing is used to map air quality over extended regions (where ground-based measurements are lacking)
- Some publications analyze the effect of urban morphology on air quality using remote sensing and GIS. (Examples include Kokkonen, Tom V et al. "The effect of urban morphological characteristics on the spatial variation of PM2.5 air quality in downtown Nanjing." Environmental science: atmospheres vol. 1,7 481–497. 26 Aug. 2021).
- NASA's Total Ozone Mapping Spectrometer (TOMS) and other sensors measure ozone concentration.
- The launch of Aura in 2004 allows measurements of ozone, particulate matter, temperature, etc., in the troposphere (from ground level to about 10 km), at a ground resolution of 12-24 km.
Ozone, Dust, Smoke, Aerosol
- Ozone concentration measured by NASA's Total Ozone Mapping Spectrometer (TOMS) and subsequent sensors (OMI).
- These sensors offer long-term datasets of daily measurements, but have limited spatial resolution (approximately 100 km at the equator for TOMS).
- The launch of Aura in 2004 enables the measurement of ozone, particulate matter, temperature, etc., in the troposphere (ground level to ~10 km), with a resolution of 12–24 km.
Urban Heat Island
- The urban heat island (UHI) effect is the difference between urban and rural temperatures, studied since the 1930s. Remote sensing emerged as a tool for assessing the UHI effect starting in the 1970s.
- Differences between remotely-sensed UHI and standard/mobile station measurements are partly due to urban geometry (overrepresentation of roofs and treetops), surface-air coupling, and climatic phenomena scales.
- Several studies have focused on indirect measurements of the UHI effect, including correlation between vegetation index (NDVI) and temperatures, and combinations of NDVI and nighttime lights.
- Urban population growth can also be used to predict the urban heat island (Karl, 1988).
- The EPA has resources regarding UHI.
Analysis of Physical Characteristics and Demographics/Socioeconomic Patterns
- Initiatives in the remote-sensing community focus on integrating remote sensing with socioeconomic data for accurate urban classification.
- Satellite imagery alone often yields insufficient results for specific urban applications.
- Combining satellite data with socioeconomic variables is essential for accurate urban classifications.
Demographic/Socioeconomic Parameters
- Research studied correlations between census/surveyed population data and land cover (e.g., Yuan et al., 1997, and Radeloff et al., 2000).
- Correlations exist between biophysical and social variables, but the relationships aren't always universal across varying spatial scales (Walsh et al., 1999).
- Combining satellite data with census data can be effective for assessing quality of life and environmental impact.
- Research (Pozzi and Small, 2002) focused on correlations between population density (from U.S. Census) and vegetation cover (from Landsat). For large cities, a linear correlation was found, but accurately characterizing urban landscapes with 30-meter resolution Landsat imagery is difficult.
- The Long-Term Ecological Research (LTER) Network studies ecological and socioeconomic systems within urban areas (like Baltimore and Phoenix).
- LTER studies examine the impacts of developments on nutrients, energy, and water fluxes and interactions.
Monitoring Urban Growth
- Traditional census data is useful for capturing socioeconomic and demographic changes, but lacks spatial detail and frequent updates.
- Remote sensing offers more continuous spatial and temporal coverage for effective urban growth and change monitoring.
- Remote-sensing imagery for change detection studies needs atmospheric and zenith-angle corrections for accurate land cover change estimations.
Monitoring Urban Growth (Continued)
- Despite ample literature on change studies, many rely on traditional land cover classifications.
- Research examples integrate remote sensing with socioeconomic data to understand urban growth indicators (e.g., vegetation changes), especially in developing countries experiencing rapid growth.
Monitoring Urban Growth (Continued)
- Numerous studies utilize remote sensing and GIS for modeling urban growth dynamics.
- Models are developed utilizing satellite imagery for urban growth modeling examples (Luo, Jun & Yu, Danlin & Miao Xin, (2008). Modeling Urban Growth Using GIS and Remote Sensing). .
- Various studies examine urban growth using machine learning algorithms and ArcGIS, demonstrating its potential for predicting urban growth Examples include papers by Xuecao Li and Peng Gong, Hanoon, S.K.; Abdullah, A.F.; Shafri, H.Z.M.; Wayayok, A..
- Many cities in developing countries experience rapid population growth and consequent urban expansion. Remote sensing provides observations of urban expansion often unavailable from other data sources.
Recent Applications and New Developments
- Spectral mixture analysis and linear mixture models quantify urban extent and physical properties from satellite imagery using multiple spectral bands (Small, 2001, 2002a, 2002b).
- Operational sensors (Landsat, SPOT) have lower spatial resolution than needed to distinguish individual urban features, which results in mixed pixels.
- Identifying distinct urban features necessitates higher spatial resolution (typically 10–20 m).
- Spectral mixture analysis models quantify mixed pixels using fractional abundance of distinct spectral endmembers (vegetation, water, high albedo).
- Shuttle Radar Topography Mission (SRTM) data aids in identifying urban infrastructure, and potentially for deriving urban extents, boundaries, vegetation heights, and building volumes.
- The application of time-series data from operational linescan systems, like Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS), is used to inventory human settlements from nighttime visible/near-infrared emission.
- Datasets of stable city lights, fire, gas flares, and lights from fishing boats have been generated.
- These datasets aid in exploring the relationship between night-time light emissions and socioeconomic characteristics (population, economic activity, electricity consumption) for urban areas.
- Examples of studies using such resources include mapping urban areas and estimating population size/GDP over time (Sutton et al. 2001 and Sutton & Costanza, 2002). The Center for International Earth Science Information Network (CIESIN) is developing a global dataset of populations and area extents.
Recent Applications and New Developments (Continued)
- This section involves the use of time series (time-series) data from satellite-derived systems to create georeferenced inventories of human settlements
- The data from these satellites are used to establish global datasets of populations and urban extents
- Data is typically at high spatial resolution (30 m), and covers a wide range of urban areas and environments
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Description
Test your knowledge on the composition and characteristics of urban landscapes as well as the role of remote sensing in urban studies. This quiz covers various aspects including materials used, the urban development cycle, and the advantages of using remote sensing for spatial data collection in urban areas.
