Factors affecting the remotely sensed response of coniferous forest plantations

Remote sensing of forest biophysical properties has concentrated upon forest sites with a wide range of green vegetation amount and thereby leaf area index and canopy cover. However, coniferous forest plantations, an important forest type in Europe, are managed to maintain a large amount of green vegetation with little spatial variation. Therefore, the strength of the remotely sensed signal will, it is hypothesized, be determined more by the structure of this forest than by its cover. Airborne Thematic Mapper (ATM) and SPOT-1 HRV data were used to determine the effects of this structural variation on the remotely sensed response of a coniferous forest plantation in the United Kingdom. Red and near infrared radiance were strongly and negatively correlated with a range of structural properties and with the age of the stands but weakly correlated with canopy cover. A composite variable, related to the volume of the canopy, accounted for over 75% of the variation in near infrared radiance. A simple model that related forest structural variables to the remotely sensed response was used to understand and explain this response from a coniferous forest plantation.

[1]  Tiit Nilson,et al.  A forest canopy reflectance model and a test case , 1991 .

[2]  S. Running,et al.  The seasonality of AVHRR data of temperate coniferous forests - Relationship with leaf area index , 1990 .

[3]  Gautam Badhwar,et al.  Spectral Characterization of Biophysical Characterstics in a Boreal Forest: Relationship between Thematic Mapper Band Reflectance and Leaf Area Index for Aspen , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[4]  F. Bonn,et al.  Evaluation and correction of viewing angle effects on satellite measurements of bidirectional reflectance , 1985 .

[5]  P. M. Teillet,et al.  Image correction for radiometric effects in remote sensing , 1986 .

[6]  J. Townshend,et al.  African Land-Cover Classification Using Satellite Data , 1985, Science.

[7]  C. Wessman,et al.  Remote sensing of canopy chemistry and nitrogen cycling in temperate forest ecosystems , 1988, Nature.

[8]  C. Justice,et al.  Analysis of the phenology of global vegetation using meteorological satellite data , 1985 .

[9]  R. Williams Intermediate Statistics for Geographers and Earth Scientists , 1986 .

[10]  Gautam D. Badhwar,et al.  Satellite-derived leaf-area-index and vegetation maps as input to global carbon cycle models-a hierarchical approach , 1986 .

[11]  Ramakrishna R. Nemani,et al.  Mapping regional forest evapotranspiration and photosynthesis by coupling satellite data with ecosystem simulation , 1989 .

[12]  Jennifer L. Dungan,et al.  Seasonal LAI in slash pine estimated with landsat TM , 1992 .

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

[14]  S. Running,et al.  A general model of forest ecosystem processes for regional applications I. Hydrologic balance, canopy gas exchange and primary production processes , 1988 .

[15]  Steven W. Running,et al.  Remote sensing of temperate coniferous forest leaf area index The influence of canopy closure, understory vegetation and background reflectance , 1990 .

[16]  M. Butera,et al.  A Correlation and Regression Analysis of Percent Canopy Closure Versus TMS Spectral Response for Selected Forest Sites in the San Juan National Forest, Colorado , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[17]  R. Webster,et al.  The relation between reflected radiation and yield on the Broadbalk winter wheat experiment , 1990 .

[18]  J. C. Price An update on visible and near infrared calibration of satellite instruments , 1988 .

[19]  S. Running,et al.  Remote Sensing of Coniferous Forest Leaf Area , 1986 .

[20]  P. Sellers Canopy reflectance, photosynthesis and transpiration , 1985 .

[21]  Stanley R. Herwitz,et al.  Thematic mapper detection of changes in the leaf area of closed canopy pine plantations in Central Massachusetts , 1989 .

[22]  W. Ripple,et al.  A preliminary comparison of Landsat Thematic Mapper and SPOT-1 HRV multispectral data for estimating coniferous forest volume , 1991 .

[23]  C. Tucker Asymptotic nature of grass canopy spectral reflectance. , 1977, Applied optics.

[24]  J. D. Ovington,et al.  Dry-matter Production by Pinus sylvestris L. , 1957 .

[25]  S. Running,et al.  Relationship of thematic mapper simulator data to leaf area index , 1987 .

[26]  F. M. Danson,et al.  Spatial Resolution For Remote Sensing Of Forest Plantations , 1988, International Geoscience and Remote Sensing Symposium, 'Remote Sensing: Moving Toward the 21st Century'..

[27]  Atmospheric effects on the remote sensing estimation of forest leaf area index , 1985 .

[28]  Michael Spanner,et al.  Analysis of Forest Structure Using Thematic Mapper Simulator Data , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[29]  Russell G. Congalton,et al.  Using thematic mapper imagery to examine forest understory , 1990 .

[30]  P. Chavez Use of the variable gain settings on SPOT , 1989 .

[31]  P. Curran Multispectral remote sensing of vegetation amount , 1980 .