North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer

Spectral vegetation index measurements derived from remotely sensed observations show great promise as a means to improve knowledge of land vegetation patterns. The daily, global observations acquired by the Advanced Very High Resolution Radiometer, a sensor on the current series of U.S. National Oceanic and Atmospheric Administration meteorological satellites, may be particularly well suited for global studies of vegetation. Preliminary results from analysis of North American observations, extending from April to November 1982, show that the vegetation index patterns observed correspond to the known seasonality of North American natural and cultivated vegetation. Integration of the observations over the growing season produced measurements that are related to net primary productivity patterns of the major North American natural vegetation formations. Regions of intense cultivation were observed as anomalous areas in the integrated growing season measurements. These anomalies can be explained by contrasts between cultivation practices and natural vegetation phenology. Major new information on seasonality, annual extent and interannual variability of vegetation photosynthetic activity at continental and global scales can be derived from these satellite observations.

[1]  L. Holdridge Determination of World Plant Formations From Simple Climatic Data. , 1947, Science.

[2]  E. Odum Fundamentals of ecology , 1972 .

[3]  Ernest Habinowicz,et al.  Man's Role in Changing the Face of the Earth , 1955, Nature.

[4]  R. Colwell Determining the prevalence of certain cereal crop diseases by means of aerial photography , 1956 .

[5]  Man's Role in Changing the Face of the Earth , 1958 .

[6]  Victor Ernest Shelford,et al.  The ecology of North America , 1964 .

[7]  A. W. Küchler Potential Natural Vegetation of the Conterminous United States , 1965 .

[8]  D. Harris,et al.  Potential Natural Vegetation of the Conterminous United States , 1965 .

[9]  D. M. Gates,et al.  Spectral Properties of Plants , 1965 .

[10]  G. Czeplak,et al.  Some aspects of the seasonal variation of carbon dioxide and ozone , 1968 .

[11]  J. Mather,et al.  THE ROLE OF CLIMATE IN THE DISTRIBUTION OF VEGETATION , 1968 .

[12]  Istituto geografico De Agostini World atlas of agriculture , 1969 .

[13]  E. B. Knipling Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation , 1970 .

[14]  I. Hiscock Communities and Ecosystems , 1970, The Yale Journal of Biology and Medicine.

[15]  S. Idso,et al.  Light relations in plant canopies. , 1970, Applied optics.

[16]  A. J. Hawley,et al.  Remote Sensing: With Special Reference to Agriculture and Forestry , 1971 .

[17]  G. Suits The calculation of the directional reflectance of a vegetative canopy , 1971 .

[18]  J. Weinman,et al.  Penetration of Solar Irradiances Through the Atmosphere and Plant Canopies , 1972 .

[19]  J. A. Schell,et al.  Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation. [Great Plains Corridor] , 1973 .

[20]  Gene E. Likens,et al.  Primary production: The biosphere and man , 1973 .

[21]  H. Lieth Phenology and Seasonality Modeling , 1974, Ecological Studies.

[22]  J. Colwell Vegetation canopy reflectance , 1974 .

[23]  Raoul Lemeur,et al.  A critical review of light models for estimating the shortwave radiation regime of plant canopies , 1974 .

[24]  D. Deering Measuring forage production of grazing units from Landsat MSS data , 1975 .

[25]  D. M. Sharpe Methods of Assessing the Primary Production of Regions , 1975 .

[26]  R. Kauth,et al.  The tasselled cap - A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat , 1976 .

[27]  A. J. Richardsons,et al.  DISTINGUISHING VEGETATION FROM SOIL BACKGROUND INFORMATION , 1977 .

[28]  M. F. Baumgardner,et al.  Detection of the Green and Brown Wave in Hardwood Canopy Covers Using Multidate, Multispectral Data from LANDSAT-11 , 1977 .

[29]  J. Monteith Climate and the efficiency of crop production in Britain , 1977 .

[30]  G. Likens,et al.  The biota and the world carbon budget. , 1978, Science.

[31]  N. Bunnik The multispectral reflectance of shortwave radiation by agricultural crops in relation with their morphological and optical properties , 1978 .

[32]  D. Thompson,et al.  Using Landsat digital data to detect moisture stress , 1979 .

[33]  R. Waring,et al.  Evergreen Coniferous Forests of the Pacific Northwest , 1979, Science.

[34]  P. Ketner,et al.  Terrestrial primary production and phytomass , 1979 .

[35]  C. Tucker Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[36]  The LACIE Symposium--Proceedings of Technical Sessions. , 1980 .

[37]  C. J. Tucker,et al.  Spectral assessment of soybean leaf area and leaf biomass , 1980 .

[38]  John D. Hesketh,et al.  Predicting Photosynthesis For Ecosystem Models , 1980 .

[39]  Vern C. Vanderbilt,et al.  Spectral-agronomic relationships of corn, soybean and wheat canopies , 1981 .

[40]  C. Tucker,et al.  Remote Sensing of Total Dry-Matter Accumulation in Winter Wheat , 1981 .

[41]  A gradient model of vegetation and climate utilizing NOAA satellite imagery. Phase 1: Texas transect , 1981 .

[42]  J. Hansen,et al.  Climate Impact of Increasing Atmospheric Carbon Dioxide , 1981, Science.

[43]  James P. Ormsby,et al.  Classification of Simulated And Actual NOAA-6 AVHRR Data for Hydrologic Land-Surface Feature Definition , 1982, IEEE Transactions on Geoscience and Remote Sensing.

[44]  J. Shukla,et al.  Influence of Land-Surface Evapotranspiration on the Earth's Climate , 1982, Science.

[45]  J. Norwine,et al.  Vegetation classification based on Advanced Very High Resolution Radiometer /AVHRR/ satellite imagery , 1983 .

[46]  C. Tucker,et al.  Satellite remote sensing of total dry matter production in the Senegalese Sahel , 1983 .

[47]  E. Matthews Global Vegetation and Land Use: New High-Resolution Data Bases for Climate Studies , 1983 .

[48]  M. Steven,et al.  Estimation of sugar beet productivity from reflection in the red and infrared spectral bands , 1983 .

[49]  Renewable resource inventories for monitoring changes and trends , 1983 .

[50]  G. Russell,et al.  Three‐dimensional tracer model study of atmospheric CO2: Response to seasonal exchanges with the terrestrial biosphere , 1983 .

[51]  J. Hatfield,et al.  Remote sensing estimators of potential and actual crop yield , 1983 .

[52]  R. Jackson Spectral indices in N-Space , 1983 .

[53]  Marvin E. Bauer,et al.  Spectral estimates of solar radiation intercepted by corn canopies. , 1983 .

[54]  P. J. Curran,et al.  Multispectral remote sensing for the estimation of green leaf area index , 1983, Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences.

[55]  C. Perry,et al.  Functional equivalence of spectral vegetation indices , 1984 .

[56]  B. Holben,et al.  Red and near-infrared sensor response to off-nadiir viewing , 1984 .

[57]  G. Asrar,et al.  Estimating Absorbed Photosynthetic Radiation and Leaf Area Index from Spectral Reflectance in Wheat1 , 1984 .

[58]  J. D. Tarpley,et al.  Global vegetation indices from the NOAA-7 meteorological satellite , 1984 .

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

[60]  A. Kuchler Potential natural vegetation , 1985 .

[61]  Compton J. Tucker,et al.  Satellite remote sensing of total herbaceous biomass production in the Senegalese Sahel - 1980-1984 , 1985 .

[62]  Compton J. Tucker,et al.  The potential of satellite remote sensing of ecological conditions for survey and forecasting desert-locust activity , 1985 .

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

[64]  K. Kidwell NOAA polar orbiter data (TIROS-N, NOAA-6, NOAA-7, NOAA-8, NOAA-9, and NOAA-10) users guide , 1986 .