Geospatial methods provide timely and comprehensive urban forest information

Urban forests are unique and highly valued resources. However, trees in urban forests are often under greater stress than those in rural or undeveloped areas due to soil compaction, restricted growing spaces, high temperatures, and exposure to air and water pollution. In addition, conditions change more quickly in urban as opposed to rural and undeveloped settings. Subsequently, proactive management of urban forests can be challenging and requires the availability of current and comprehensive information. Geospatial tools, such as, geographic information systems (GIS), global positioning systems (GPS) and remote sensing, work extremely well together for gathering, analyzing, and reporting information. Many urban forest management questions could be quickly and effectively addressed using geospatial methods and tools. The geospatial tools can provide timely and extensive spatial data from which urban forest attributes can be derived, such as land cover, forest structure, species composition and condition, heat island effects, and carbon storage. Emerging geospatial tools that could be adapted for urban forest applications include data fusion, virtual reality, three-dimensional visualization, Internet delivery, modeling, and emergency response.

[1]  L. Wald,et al.  SAR imagery in urban area , 1999 .

[2]  Susan I. Stewart,et al.  The Changing Midwest Assessment: land cover, natural resources, and people , 2004 .

[3]  Claus Brenner,et al.  Extraction of buildings and trees in urban environments , 1999 .

[4]  R. Rowntree,et al.  Intensive surveys of structure and change in urban natural areas , 1988 .

[5]  Q. Guo,et al.  A comparison of standard and hybrid classifier methods for mapping hardwood mortality in areas affected by sudden oak death , 2004 .

[6]  R. Oren,et al.  THE EFFECT OF CROWN DIMENSIONS ON TRANSPARENCY AND THE ASSESSMENT OF TREE HEALTH , 2001 .

[7]  K. F. Wiersum,et al.  200 years of sustainability in forestry: Lessons from history , 1995 .

[8]  F. Duhme,et al.  GIS Assessment of Munich's Urban Forest Structure for Urban Planning , 2000, Arboriculture & Urban Forestry.

[9]  R. Jensen,et al.  Estimating Urban Leaf Area Using Field Measurements And Satellite Remote Sensing Data , 2005, Arboriculture & Urban Forestry.

[10]  M. Ridd,et al.  A Comparison of Four Algorithms for Change Detection in an Urban Environment , 1998 .

[11]  N. M. Kelly,et al.  WebGIS for Monitoring "Sudden Oak Death" in coastal California , 2003, Comput. Environ. Urban Syst..

[12]  R. Dubayah,et al.  Lidar Remote Sensing for Forestry , 2000, Journal of Forestry.

[13]  Frank Sapio,et al.  Remote sensing and forestry: collaborative implementation for a new century of forest information solutions. , 2000 .

[14]  D. Dellasala,et al.  Rate and pattern of forest disturbance in the Klamath-Siskiyou ecoregion, USA between 1972 and 1992 , 2002, Landscape Ecology.

[15]  G. Talarchek.  Indicators of Urban Forest Condition in New Orleans , 1987, Arboriculture & Urban Forestry.

[16]  M. Bauer,et al.  Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multitemporal Landsat remote sensing , 2005 .

[17]  D. Stow,et al.  An analysis of tree mortality in southern California using high spatial resolution remotely sensed spectral radiances: a climatic change scenario , 1993 .

[18]  C. Small.  Estimation of urban vegetation abundance by spectral mixture analysis , 2001 .

[19]  Tsuyoshi Honjo,et al.  Three-dimensional visualization forest of landscapes by VRML , 2003 .

[20]  C. Kontoes,et al.  The potential of kernel classification techniques for land use mapping in urban areas using 5m-spatial resolution IRS-1C imagery , 2000 .

[21]  C. Small.  High spatial resolution spectral mixture analysis of urban reflectance , 2003 .

[22]  Robin Wall Kimmerer,et al.  Native knowledge for native ecosystems. , 2000 .

[23]  E. Mcpherson,et al.  A Benefit-Cost Analysis of Ten Street Tree Species in Modesto, California, U.S. , 2003, Arboriculture & Urban Forestry.

[24]  C. Lo,et al.  Using a time series of satellite imagery to detect land use and land cover changes in the Atlanta, Georgia metropolitan area , 2002 .

[25]  R. Rowntree.  Ecology of the urban forest: Introduction to part III , 1988 .

[26]  Pol Coppin,et al.  Review ArticleDigital change detection methods in ecosystem monitoring: a review , 2004 .

[27]  Eyal Ben-Dor,et al.  A spectral based recognition of the urban environment using the visible and near-infrared spectral region (0.4-1.1 µm). A case study over Tel-Aviv, Israel , 2001 .

[28]  R. Rowntree.  Ecology of the urban forest—Introduction to part II , 1984 .

[29]  James L. Regens,et al.  Predicting the urbanization of pine and mixed forests in Saint Tammany Parish, Louisiana , 2000 .

[30]  Th. Toutin,et al.  DSM generation and evaluation from QuickBird stereo imagery with 3D physical modelling , 2004 .

[31]  David J. Nowak,et al.  Compensatory Value of Urban Trees in the United States , 2002, Arboriculture & Urban Forestry.

[32]  S. Running,et al.  Numerical Terradynamic Simulation Group 12-1988 Rapid Estimation of Coniferous Forest Leaf Area Index Using a Portable Integrating Radiometer , 2018 .

[33]  Yun Zhang,et al.  Texture-Integrated Classification of Urban Treed Areas in High-Resolution Color-Infrared Imagery , 2001 .

[34]  R. A. Sanders.  Some determinants of urban forest structure , 1984 .

[35]  M. Duggin,et al.  A temporal analysis of urban forest carbon storage using remote sensing , 2006 .

[36]  J. Dwyer,et al.  Sustaining Urban Forests , 2003, Arboriculture & Urban Forestry.

[37]  George Xian,et al.  An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data , 2006 .

[38]  Robert L Anderson,et al.  Changing forests and forest management policy in relation to dealing with forest diseases. , 2003, Phytopathology.

[39]  E. McPherson.  Monitoring urban forest health , 1993, Environmental monitoring and assessment.

[40]  Paul F. Hopkins,et al.  Urban cover mapping using digital, high-spatial resolution aerial imagery , 2001, Urban Ecosystems.

[41]  P. Gong,et al.  Assessment of multi-resolution and multi-sensor data for urban surface temperature retrieval , 2006 .

[42]  Bert Guindon,et al.  Landsat urban mapping based on a combined spectral–spatial methodology , 2004 .

[43]  Y. Ouma,et al.  On the optimization and selection of wavelet texture for feature extraction from high‐resolution satellite imagery with application towards urban‐tree delineation , 2006 .

[44]  E. Mcpherson,et al.  Quantifying urban forest structure, function, and value: the Chicago Urban Forest Climate Project , 1995, Urban Ecosystems.

[45]  D. Quattrochi,et al.  Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect , 1997 .

[46]  H. Flint.  Plants Showing Tolerance of Urban Stress , 1985 .

[47]  P. Dare.  Shadow Analysis in High-Resolution Satellite Imagery of Urban Areas , 2005 .

[48]  Louis R. Iverson,et al.  Urban forest cover of the Chicago region and its relation to household density and income , 2000, Urban Ecosystems.

[49]  Hermann Kaufmann,et al.  Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data , 2003 .

[50]  A. Luckman,et al.  Mapping urban change in the UK using satellite radar interferometry , 2003 .

[51]  B. Law,et al.  A selection of forest condition indicators for monitoring , 1992, Environmental monitoring and assessment.

[52]  Chris T. Kiranoudis,et al.  A Multidisciplinary Decision Support System for Forest Fire Crisis Management , 2004, Environmental management.

[53]  Chad Hendrix,et al.  A Comparison of Urban Mapping Methods Using High-Resolution Digital Imagery , 2003 .

[54]  S. Ustin,et al.  Using AVIRIS data and multiple-masking techniques to map urban forest tree species , 2004 .

[55]  D. Maktav,et al.  Remote sensing of urban areas , 2005 .

[56]  Olga Rigina,et al.  Detection of Forest Decline in Monchegorsk Area , 1998 .

[57]  David M. Rizzo,et al.  Sudden Oak Death , 2003 .

[58]  Kevin E. Percy,et al.  Forest Health in North America: Some perspectives on Actual and Potential Roles of Climate and Air Pollution , 1999 .

[59]  Jay O'Laughlin,et al.  Defining and Measuring Forest Health , 1994 .