Land Cover Change and Associated Trends in Surface Reflectivity and Vegetation Index in Southwest Kansas: 1972-1992

Abstract Land cover is an important component of the earth system. Human induced surface alteration can affect earth systems directly, through loss or degradation of ecosystems, or indirectly through impact on the climate and biogeochemical cycles necessary to sustain life on earth. The significance of the earth's surface has made land use/land cover change an important issue in global change research. Alteration of land cover occurs at a variety of spatial scales, but as with many environmental change issues, the impacts of surface changes are often conceptualized at the global scale. In this study, we investigate the effects of land cover change on total reflected radiation and the Normalized Difference Vegetation Index (NDVI) in a 10,000 km2 local area in the High Plains of southwestern Kansas. Landsat MSS data from five years of record within the twenty‐year period 1973 to 1992 were classified into cool season crop, warm season crop, and pasture/prairie. Mean values of summer reflectance and NDVI from each cover type and for the study area as a whole were then analyzed for systematic change over the study period. Both reflectivity and vegetation index increased during the study period, although causes for the increase appear to be different. Results suggest that changes in mean surface reflectance in the study site are strongly influenced by land cover change, whereas changes in NDVI are more closely linked to 50‐day antecedent precipitation.

[1]  James W. Merchant,et al.  An assessment of AVHRR/NDVI-ecoclimatological relations in Nebraska, U.S.A. , 1997 .

[2]  C. Tucker,et al.  Tropical Deforestation and Habitat Fragmentation in the Amazon: Satellite Data from 1978 to 1988 , 1993, Science.

[3]  D. E. Kromm,et al.  Groundwater Exploitation in the High Plains , 1992 .

[4]  A. Henderson-Sellers,et al.  Possible climatic impacts of land cover transformations, with particular emphasis on tropical deforestation , 1984 .

[5]  A. Kuchler.  A New Vegetation Map of Kansas , 1974 .

[6]  P. Crutzen,et al.  Biomass Burning in the Tropics: Impact on Atmospheric Chemistry and Biogeochemical Cycles , 1990, Science.

[7]  William J. Volchok,et al.  Radiometric scene normalization using pseudoinvariant features , 1988 .

[8]  R. Kates,et al.  Global Change in Local Places , 1998 .

[9]  Douglas G. Goodin,et al.  Mesoscale Satellite Bioclimatology , 2000 .

[10]  S. E. White.  Ogallala Oases: Water Use, Population Redistribution, and Policy Implications in the High Plains of Western Kansas, 1980–1990 , 1994 .

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

[12]  K. Price,et al.  Natural resource capability of CRP lands as Grasslands in Southwest Kansas: A remote sensing and GIS perspective , 1996 .

[13]  N. Rosenberg,et al.  Climate of the Great Plains Region of The United States , 1987 .

[14]  J. L. Barker,et al.  Landsat MSS and TM post-calibration dynamic ranges , 1986 .

[15]  J. Monteith,et al.  Boundary Layer Climates. , 1979 .

[16]  J. Hudson.  A DIAMOND ANNIVERSARY , 1979 .

[17]  R. Jackson.  Total reflected solar radiation calculated from multi-band sensor data , 1984 .

[18]  P. Derfler,et al.  The United States Department of Agriculture , 1872, Nature.

[19]  C. Woodcock,et al.  Classification and Change Detection Using Landsat TM Data: When and How to Correct Atmospheric Effects? , 2001 .

[20]  Douglas G. Goodin,et al.  Mapping the surface radiation budget and net radiation in a sand hills wetland using a combined modeling/ remote sensing method and Landsat thematic Mapper Imagery , 1995 .

[21]  E. Schanda,et al.  Remote sensing of the environment , 1978, Naturwissenschaften.

[22]  B. Turner.  The Earth as Transformed by Human Action , 1988 .

[23]  Clyde Young Kramer,et al.  Extension of multiple range tests to group means with unequal numbers of replications , 1956 .

[24]  P. Chavez.  An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data , 1988 .

[25]  G. Fischer,et al.  Land-use and land-cover change. Science/research plan , 1995 .

[26]  Edwin T. Engman,et al.  Status of remote sensing algorithms for estimation of land surface state parameters , 1995 .

[27]  Thomas D. Frank,et al.  The Effect of Change in Vegetation Cover and Erosion Patterns on Albedo and Texture of Landsat Images in a Semiarid Environment , 1984 .

[28]  Liping Di,et al.  Modelling relationships between NDVI and precipitation during vegetative growth cycles , 1994 .

[29]  Samuel N. Goward,et al.  Deriving surface albedo measurements from narrow band satellite data , 1987 .

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

[31]  John A. Richards,et al.  Remote Sensing Digital Image Analysis: An Introduction , 1999 .

[32]  C. J. Robinove,et al.  Computation with physical values from Landsat digital data , 1982 .

[33]  Kevin P. Price,et al.  Mapping conservation reserve program (CRP) grasslands using multi‐seasonal thematic mapper imagery , 1998 .

[34]  K. Goïta,et al.  Land surface climatology and land cover change monitoring since 1973 over a north‐Sahelian zone (Ansongo ‐ Mali) using landsat data , 1993 .

[35]  M. Iqbal.  An introduction to solar radiation , 1983 .