@inbook {KNZ00626,
	title = {A landscape perspective of patterns and processes in tallgrass prairie},
	booktitle = {Grassland Dynamics: Long-Term Ecological Research in Tallgrass Prairie},
	year = {1998},
	pages = {265 -279},
	publisher = {Oxford University Press},
	organization = {Oxford University Press},
	address = {New York},
	keywords = {LTER-KNZ, tallgrass prairie},
	author = {J. M. Briggs and Nellis, M.D. and Turner, C.L. and Henebry, G.M. and Su, H.},
	editor = {Alan K. Knapp and J. M. Briggs and D.C. Hartnett and Scott. L. Collins}
}
@article {KNZ00570,
	title = {Detecting spatial and temporal patterns of aboveground production in a tallgrass prairie using remotely-sensed data},
	year = {1996},
	pages = {2361 -2365},
	abstract = {Spatial and temporal patterns of aboveground production in a tallgrass prairie ecosystem constitute one of the important spatial components associated with ecological processes and biophysical resources (e.g., water and nutrients). This study addresses the effects of disturbance, topography, and climate on the spatial and temporal patterns of North American tallgrass prairie at a landscape level by using high resolution satellite data. Spatial heterogeneity (SH) derived from the satellite data was related to the impacts of the disturbance of fire and grazing, topographical gradient, and amount of precipitation during the growing season. The result suggests that ecological processes and biophysical resources can be quantified with high resolution satellite data for tallgrass prairie management},
	keywords = {LTER-KNZ, tallgrass prairie},
	doi = {10.1109/IGARSS.1996.516987},
	author = {Su, H. and J. M. Briggs and Alan K. Knapp and John M. Blair and Krummel, J.R.}
}
@proceedings {KNZ00496,
	title = {Observing spatial structure in the Flint Hills using AVHRR biweekly composites of maximum NDVI},
	year = {1995},
	pages = {143 -151},
	keywords = {LTER-KNZ},
	author = {Henebry, G.M. and Su, H.},
	editor = {D.C. Hartnett}
}
@inbook {KNZ00435,
	title = {Development and refinement of the Konza Prairie LTER Research Information Management Program},
	booktitle = {Environmental Information Management and Analysis: Ecosystem to Global Scales},
	year = {1994},
	pages = {87 -100},
	publisher = {Taylor and Francis Ltd},
	organization = {Taylor and Francis Ltd},
	address = {London},
	keywords = {LTER-KNZ},
	author = {J. M. Briggs and Su, H.},
	editor = {Michener, W.K. and Brunt, J.W. and Stafford, S.G.}
}
@inbook {KNZ00469,
	title = {Effects of topography and fire on spatial and temporal distribution of soil moisture in a tallgrass prairie},
	booktitle = {Time Domain Reflectometry in Environmental, Infrastructure and Mining Applications},
	year = {1994},
	pages = {154 -162},
	publisher = {United States Department of Interior Bureau of Mines},
	organization = {United States Department of Interior Bureau of Mines},
	keywords = {LTER-KNZ, tallgrass prairie},
	author = {Su, H. and Alan K. Knapp and J. M. Briggs}
}
@article {KNZ00407,
	title = {Using landscape trajectories to assess the effects of radiometric rectification},
	journal = {International Journal of Remote Sensing},
	volume = {14},
	year = {1993},
	pages = {2417 -2423},
	abstract = {We demonstrate a simple procedure, landscape trajectories, for quantifying the effects of radiometric correction on image characteristics. Eleven Landsat Thematic Mapper (TM) images of tallgrass prairie spanning 1987 and 1988 were radiometrically rectified to a common date using a {\textquoteleft}pseudoinvariant features in real space{\textquoteright} method (Schott et ai 1988). The Normalized Difference Vegetation Index (NDVI) was calculated for each raw and corrected image. Four watersheds within the study area were subset and the images were decomposed into spectral intensity (SI), spatial eterogeneity (SH), and spatial dependence (SD) components. Time-ordered vectors in SI-SH-SD space described landscape trajectories. Vector lengths along trajectories were calculated and integrated. Differences between measures on raw and corrected images may be attributable to climatic forcings, time of season, time since fire, and watershed topography. The correction procedure changed SI most and SD least. While the rectification procedure was linear with respect to the entire scene, specific watersheds exhibited nonlinear responses to radiometric rectification.},
	keywords = {LTER-KNZ},
	doi = {10.1080/01431169308954046},
	author = {Henebry, G.M. and Su, H.}
}
@article {KNZ00297,
	title = {Separability of soils in a tallgrass prairie using SPOT and DEM Data},
	journal = {Remote Sensing of the Environment},
	volume = {32},
	year = {1990},
	pages = {10 -17},
	abstract = {<p>A sufficient transformation technique is important in using computer-aided soil pattern recognition to interpret soils in soil surveys. This study was conducted using the Systeme Probatoire d\&$\#$39;Observation de la Terre (SPOT) satellite images and Digital Elevation Model (DEM) data to seperate five major sils in a tallgrass prairie near Manhattan, Kansas. The high resolution SPOT satellite im;ages were integrated with DEM data. the soils were sampled and classified using conventional soil survey procedures to extract the important soil features from SPOT and DEM data. A pairwise transformed divergence analysis was also conducted to evaluate the several aanonical variables in order to sufficiently separate the soils. Consequently, two canonical variables derived from training samples were selected. Our results suggest that canonically transformed data were superior to combined SPOT and DEM data. High resolution SPOT images and DEM data can be used to aid secondd- order soil surveys in grasslands</p>},
	keywords = {LTER-KNZ, tallgrass prairie},
	doi = {10.1016/0034-4257(90)90027-J},
	author = {Su, H. and Kanemasu, E.T. and Ransom, M.D. and Yang, S.}
}
@article {KNZ00256,
	title = {Detecting soil information on a native prairie using Landsat TM and SPOT satellite data},
	journal = {Soil Science Society of America Journal},
	volume = {53},
	year = {1989},
	pages = {1479 -1483},
	abstract = {<p>Computer pattern recoginiton techniques were used to discriminate soil information from the Landsat Thematic Mapper (TM) and the French Systeme Probatoire d\&$\#$39;Observation de le Terre (SPOT) satellite data on a native prairie near Manahttan, KS. Digital Elevation Model (DEM) data were merged to Landsat TM and SPOT data to delineate soil mapping units within the study area. Soil mapping units from a conventional soil survey were compared with a classified soil spectral map obtained from Landsat TM or SPOT, and DEM derived elevation, slope, and aspect data, using an overall accuracy assessment. The overall accuracy of soil spectral classesfrom TM and SPOT data were merged. A higher average accuracy for soil mapping units was obtained with a low frequency filtering transformation of the data. For Landsat TM data, Band 5 (middle infrared, 1.55-1.75 {\ae}m) was most useful for soil information extraction, and a higher overall accuracy was obtained in the dormant season compared with the accuracy in the growing season. The overall accuracy (about 57\%) from SPOT data was slightly higher than the accuracy (about 53\%) from Landsat TM at a similar wavelength range. Our results indicate that high resolution Landsat TM and SPOT satellite data can be used to aid second-order soil surveys in areas where the dominant land use is rangeland</p>},
	keywords = {LTER-KNZ},
	doi = {10.2136/sssaj1989.03615995005300050030x},
	author = {Su, H. and Ransom, M.D. and Kanemasu, E.T.}
}
@mastersthesis {KNZ00210,
	title = {Detecting soil information on the Konza Prairie using high resolution satellite data},
	volume = {MS Thesis},
	year = {1988},
	pages = {1 -109},
	school = {Kansas State University},
	type = {M.S. Thesis},
	address = {Manhattan, KS},
	keywords = {LTER-KNZ},
	author = {Su, H.}
}
