High Spatial Resolution Remotely Sensed Data for Ecosystem Characterization

Abstract Characterization of ecosystem structure, diversity, and function is increasingly desired at finer spatial and temporal scales than have been derived in the past. Many ecological applications require detailed data representing large spatial extents, but these data are often unavailable or are impractical to gather using field-based techniques. Remote sensing offers an option for collecting data that can represent broad spatial extents with detailed attribute characterizations. Remotely sensed data are also appropriate for use in studies across spatial scales, in conjunction with field-collected data. This article presents the pertinent technical aspects of remote sensing for images at high spatial resolution (i.e., with a pixel size of 16 square meters or less), existing and future options for the processing and analysis of remotely sensed data, and attributes that can be estimated with these data for forest ecosystems.

[1]  Janet Franklin,et al.  Thematic mapper analysis of coniferous forest structure and composition , 1986 .

[2]  Alan H. Strahler,et al.  On the nature of models in remote sensing , 1986 .

[3]  C. Field,et al.  A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency , 1992 .

[4]  J. Chen,et al.  Defining leaf area index for non‐flat leaves , 1992 .

[5]  S. Franklin,et al.  Empirical relations between digital SPOT HRV and CASI spectral response and lodgepole pine (Pinus contorta) forest stand parameters , 1993 .

[6]  G. Carter Ratios of leaf reflectances in narrow wavebands as indicators of plant stress , 1994 .

[7]  Gregory J. McDermid,et al.  Forest structural damage analysis using image semivariance , 1994 .

[8]  P. Gong,et al.  Remote Sensing of Seasonal Leaf Area Index Across the Oregon Transect , 1994 .

[9]  R. Fournier,et al.  Remote sensing and the measurement of geographical entities in a forested environment. 2. The optimal spatial resolution , 1994 .

[10]  D. Leckie,et al.  Data Processing and Analysis for MIFUCAM: A Trial of MEIS Imagery for Forest Inventory Mapping , 1995 .

[11]  Remote sensing for forest ecosystem characterization: a review. , 1995 .

[12]  L. F. Riley,et al.  Criteria and indicators of sustainable forest management in Canada , 1995 .

[13]  Ruiliang Pu,et al.  Coniferous forest leaf area index estimation along the Oregon transect using compact airborne spectrographic imager data , 1995 .

[14]  F. Gougeon Comparison of Possible Multispectral Classification Schemes for Tree Crowns Individually Delineatedon High Spatial Resolution MEIS Images , 1995 .

[15]  Richard A. Fournier,et al.  A catalogue of potential spatial discriminators for high spatial resolution digital images of individual crowns , 1995 .

[16]  F. Gougeon A Crown-Following Approach to the Automatic Delineation of Individual Tree Crowns in High Spatial Resolution Aerial Images , 1995 .

[17]  W. Cohen,et al.  Estimating the age and structure of forests in a multi-ownership landscape of western Oregon, U.S.A. , 1995 .

[18]  I. Filella,et al.  Reflectance assessment of mite effects on apple trees , 1995 .

[19]  F. Gemmell,et al.  Effects of forest cover, terrain, and scale on timber volume estimation with Thematic Mapper data in a rocky mountain site , 1995 .

[20]  Influence of aerial film spectral sensitivity and texture on interpreting images of forest species composition , 1996 .

[21]  S. Franklin,et al.  High Spatial Resolution Optical Image Texture for Improved Estimation of Forest Stand Leaf Area Index , 1996 .

[22]  M. Wulder,et al.  Mission planning for operational data acquisition campaigns with the {sup casi} , 1996 .

[23]  P. Meyera,et al.  Semi-automated procedures for tree species identification in high spatial resolution data from digitized colour infrared-aerial photography , 1996 .

[24]  C. Stone The role of psyllids (Hemiptera: Psyllidae) and bell miners (Manorina melanophrys) in canopy dieback of Sydney blue gum (Eucalyptus saligna Sm.) , 1996 .

[25]  Geoffrey J. Hay,et al.  An object-specific image-texture analysis of H-resolution forest imagery☆ , 1996 .

[26]  Yonghe Wang,et al.  Canada’s Forest Biomass Resources: Deriving Estimates from Canada’s Forest Inventory , 1997 .

[27]  Jerry F. Franklin,et al.  Creating a forestry for the 21st century : the science of ecosystem management , 1997 .

[28]  W. Kurz,et al.  Comprehensive assessment of carbon stocks and fluxes in a Boreal-Cordilleran forest management unit , 1997 .

[29]  B. St-Onge Automated forest structure mapping from high resolution imagery based on directional semivariogram estimates , 1997 .

[30]  B. Guindon,et al.  Computer-Based Aerial Image Understanding: A Review and Assessment of its Application to Planimetric Information Extraction from Very High Resolution Satellite Images , 1997 .

[31]  Paul J. Curran,et al.  Remote sensing the biochemical composition of a slash pine canopy , 1997, IEEE Trans. Geosci. Remote. Sens..

[32]  T. M. Lillesand,et al.  Estimating the leaf area index of North Central Wisconsin forests using the landsat thematic mapper , 1997 .

[33]  George Alan Blackburn,et al.  An ecological survey of deciduous woodlands using airborne remote sensing and geographical information systems (GIS). , 1997 .

[34]  Michael A. Wulder,et al.  Optical remote-sensing techniques for the assessment of forest inventory and biophysical parameters , 1998 .

[35]  R. Hall,et al.  Hierarchical image classification and extraction of forest species composition and crown closure from airborne multispectral images , 1998 .

[36]  Stephen J. McGregor,et al.  An integrated geographic information system approach for modeling the suitability of conifer habitat in an alpine environment , 1998 .

[37]  S. Franklin,et al.  Aerial Image Texture Information in the Estimation of Northern Deciduous and Mixed Wood Forest Leaf Area Index (LAI) , 1998 .

[38]  Guangxing Wang,et al.  The calibration of digitized aerial photographs for forest stratification , 1998 .

[39]  A. Cutini,et al.  Estimation of leaf area index with the Li-Cor LAI 2000 in deciduous forests , 1998 .

[40]  Karin S. Fassnacht,et al.  Relationships between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites , 1999 .

[41]  J. P. Kimmins Biodiversity, Beauty and the "Beast": Are beautiful forests sustainable, are sustainable forests beautiful, and is "small" always ecologically desirable? , 1999 .

[42]  J. Beaubien,et al.  Linking ecophysiology and forest productivity: An overview of the ECOLEAP project , 1999 .

[43]  W. Cohen,et al.  Surface lidar remote sensing of basal area and biomass in deciduous forests of eastern Maryland, USA , 1999 .

[44]  Emmanuel P. Baltsavias,et al.  On the performance of photogrammetric scanners , 1999 .

[45]  David L. Glackin,et al.  Civil, Commercial, and International Remote Sensing Systems and Geoprocessing , 1999 .

[46]  Charles L. Walthall,et al.  Compact Airborne Spectrographic Imager (CASI) used for mapping biophysical parameters of boreal forests , 1999 .

[47]  Werner A. Kurz,et al.  A 70-YEAR RETROSPECTIVE ANALYSIS OF CARBON FLUXES IN THE CANADIAN FOREST SECTOR , 1999 .

[48]  Sandra A. Brown,et al.  Spatial distribution of biomass in forests of the eastern USA , 1999 .

[49]  Baoxin Hu,et al.  Retrieval of Leaf Area Index and Canopy Closure from CASI Data over the BOREAS Flux Tower Sites , 2000 .

[50]  P. Wolf,et al.  Elements of Photogrammetry(with Applications in GIS) , 2000 .

[51]  Aerial photography in the next decade. , 2000 .

[52]  D. Donoghue Remote sensing: sensors and applications , 2000 .

[53]  Douglas J. King,et al.  Modelling Deciduous Forest Ice Storm Damage Using Aerial CIR Imagery and Hemispheric Photography , 2000 .

[54]  Philip J. Howarth,et al.  High Spatial Resolution Remote Sensing Data for Forest Ecosystem Classification: An Examination of Spatial Scale , 2000 .

[55]  R. Hall,et al.  Incorporating texture into classification of forest species composition from airborne multispectral images , 2000 .

[56]  Pablo J. Zarco-Tejada,et al.  Chlorophyll Fluorescence Effects on Vegetation Apparent Reflectance: I. Leaf-Level Measurements and Model Simulation , 2000 .

[57]  Richard A. Fournier,et al.  Spatial implementation of models in forestry. , 2000 .

[58]  R. Youngs "A right smart little jolt": loss of the chestnut and a way of life. , 2000 .

[59]  W. Cohen,et al.  An evaluation of alternate remote sensing products for forest inventory, monitoring, and mapping of Douglas-fir forests in western Oregon , 2001 .

[60]  S. Phinn,et al.  Integrating High and Moderate Spatial Resolution Image Data to Estimate Forest Age Structure , 2001 .

[61]  W. Cohen,et al.  Modelling forest cover attributes as continuous variables in a regional context with Thematic Mapper data , 2001 .

[62]  S. Franklin,et al.  Texture analysis of IKONOS panchromatic data for Douglas-fir forest age class separability in British Columbia , 2001 .

[63]  Steven E. Franklin,et al.  Texture analysis of IKONOS panchromatic data for Douglas-fir forest age class separability in British Columbia , 2001 .

[64]  S. Franklin Remote Sensing for Sustainable Forest Management , 2001 .

[65]  P. Curran Imaging spectrometry for ecological applications , 2001 .

[66]  Trisalyn A. Nelson,et al.  Spatial resolution implications of digitizing aerial photography for environmental applications , 2001 .

[67]  Mary Ann Fajvan,et al.  A Comparison of Multispectral and Multitemporal Information in High Spatial Resolution Imagery for Classification of Individual Tree Species in a Temperate Hardwood Forest , 2001 .

[68]  R. Fernandes,et al.  A multi-scale approach to mapping effective Leaf Area Index in Boreal Picea mariana stands using high spatial resolution CASI imagery , 2002 .

[69]  Steven E. Franklin,et al.  Multi‐layer Forest Stand Discrimination with Spatial Co‐occurrence Texture Analysis of High Spatial Detail Airborne Imagery , 2002 .

[70]  K. Olaf Niemann,et al.  Error reduction methods for local maximum filtering of high spatial resolution imagery for locating trees , 2002 .

[71]  S. Franklin,et al.  Classification of wetland habitat and vegetation communities using multi-temporal Ikonos imagery in southern Saskatchewan , 2002 .

[72]  Fabio Maselli,et al.  Analysis of Multitemporal NDVI Data for Crop Yield Forecasting in the Sahel , 2002 .

[73]  W. Andrew Marcus,et al.  Mapping of stream microhabitats with high spatial resolution hyperspectral imagery , 2002, J. Geogr. Syst..

[74]  W. Cohen,et al.  Lidar Remote Sensing for Ecosystem Studies , 2002 .

[75]  Ron Graham,et al.  Digital Aerial Survey: Theory and Practice , 2002 .

[76]  K. Olaf Niemann,et al.  Spatial statistical techniques for aggregating point objects extracted from high spatial resolution remotely sensed imagery , 2002, J. Geogr. Syst..

[77]  Peter J. Mumby,et al.  Mapping marine environments with IKONOS imagery: enhanced spatial resolution can deliver greater thematic accuracy , 2002 .

[78]  S. Leblanc,et al.  Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements , 2002 .

[79]  David B. Lobell,et al.  Per-Pixel Analysis of Forest Structure , 2003 .

[80]  M. Fladeland,et al.  Remote sensing for biodiversity science and conservation , 2003 .

[81]  Paul Aplin,et al.  Remote sensing: base mapping , 2003 .

[82]  S. Franklin,et al.  Remote sensing of forest environments : concepts and case studies , 2003 .

[83]  R. Hall The Roles of Aerial Photographs in Forestry Remote Sensing Image Analysis , 2003 .

[84]  J. Kerr,et al.  From space to species: ecological applications for remote sensing , 2003 .

[85]  Joseph D. White,et al.  Modeling Forest Productivity Using Data Acquired Through Remote Sensing , 2003 .

[86]  G. G Wright,et al.  Reducing the cost of multi-spectral remote sensing: combining near-infrared video imagery with colour aerial photography , 2003 .

[87]  Richard A. Fournier,et al.  Indirect Measurement of Forest Canopy Structure from In Situ Optical Sensors , 2003 .

[88]  Christine Stone,et al.  Chlorophyll content in eucalypt vegetation at the leaf and canopy scales as derived from high resolution spectral data. , 2003, Tree physiology.

[89]  Josée Lévesque,et al.  Spatial analysis of radiometric fractions from high-resolution multispectral imagery for modelling individual tree crown and forest canopy structure and health , 2003 .

[90]  Ronald J. Hall,et al.  Ground and remote estimation of leaf area index in Rocky Mountain forest stands, Kananaskis, Alberta , 2003 .

[91]  M. Flood,et al.  LiDAR remote sensing of forest structure , 2003 .

[92]  W. Cohen,et al.  Selection of Remotely Sensed Data , 2003 .

[93]  S. Franklin,et al.  Geostatistical and texture analysis of airborne-acquired images used in forest classification , 2004 .

[94]  D. Turner,et al.  Integrating Remote Sensing and Ecosystem Process Models for Landscape- to Regional-Scale Analysis of the Carbon Cycle , 2004 .

[95]  Michael D. Jennings,et al.  Gap analysis: concepts, methods, and recent results* , 2004, Landscape Ecology.

[96]  W. Cohen,et al.  Landsat's Role in Ecological Applications of Remote Sensing , 2004 .

[97]  Daniel G. Cole Manual of Aerial Survey: Primary Data Acquisition , 2004 .

[98]  D. Roberts,et al.  Using Imaging Spectroscopy to Study Ecosystem Processes and Properties , 2004 .

[99]  B. Law,et al.  Forest Attributes from Radar Interferometric Structure and Its Fusion with Optical Remote Sensing , 2004 .

[100]  Maosheng Zhao,et al.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .

[101]  N. Coops,et al.  Prediction of the spatial distribution and relative abundance of ground-dwelling mammals using remote sensing imagery and simulation models , 2002, Landscape Ecology.