01730nas a2200169 4500008004100000245007900041210006900120300001300189490000700202520115500209653002201364100001701386700001601403700001701419700001901436856010501455 1986 eng d00aAssessing grassland biophysical characteristics from spectral measurements0 aAssessing grassland biophysical characteristics from spectral me a141 -1520 v203 a

Remote sensing offers a potential alternative to tedious hand sampling as a means of monitoring vegetation condition and estimating productivity over large areas of grasslands. This sutdy was conducted to assess the use of spectral reflectance measurements in estimating grass canopy leaf area index (LAI) and total above ground green phytomass. Spectral reflectance measurements were made on a tallgrass prairie during 1983 and 1984 with two multiband radiometers. Green leaf-area index and dry matter accumulations (green above-ground phytomass) were measured on the area monitored by the radiometer. Three indices-near infrared to red ratio, greenness, and normalized difference-were computed from spectral reflectance data. The direct relationships between these special reflectance indices and grass biophysical parameters (LAI and phytomass) were site-dependent and year-specific. Indirect methods of estimating LAI and phytomass from estimates of absorbed, phytosynthetically active radiation, based on measurements of grass canopy spectral reflectance, were found to be more consistent across treatments for the two years of this study

10atallgrass prairie1 aWeiser, R.L.1 aAsrar, G.A.1 aMiller, G.P.1 aKanemasu, E.T. uhttp://knz.lternet.edu/content/assessing-grassland-biophysical-characteristics-spectral-measurements01689nas a2200181 4500008004100000245010200041210006900143300001300212490000700225520104000232653002201272100001601294700001701310700001801327700001901345700001801364856012501382 1986 eng d00aDistinguishing among tallgrass prairie cover types from measurements of multispectral reflectance0 aDistinguishing among tallgrass prairie cover types from measurem a159 -1690 v193 a

The heterogeneity in surface cover caused by management practices or natural events complicates monitoring the conditions of grasslands and asseessing their productivity by remote sensing techniques. Statistical procedures were sought that would allow different grassland surface cover types (bare soil,senescent vegetation, and green vegetation) to be distinguished by using measurements of grassland multispectral reflectance. Two procedures, discriminant functions and canonical discriminant analysis, were found suitable for achieving this objective. Linear classification functions and canonical variables were derived, which distinguish between the three cover types. A comparison between two sensor systems, a Barnes multiband radiometer and an Exotech radiometer that simulates the Landsatthematic mapper (TM) and multispectral scanner (MSS) bands, respectively, showed that the separability among the three cover types was substantially improved by the additional and improved spectral features of the Barnes radiometer

10atallgrass prairie1 aAsrar, G.A.1 aWeiser, R.L.1 aJohnson, D.E.1 aKanemasu, E.T.1 aKilleen, J.M. uhttp://knz.lternet.edu/content/distinguishing-among-tallgrass-prairie-cover-types-measurements-multispectral-reflectance01772nas a2200169 4500008004100000245009300041210006900134300001100203490001000214520117100224653002201395100001601417700001901433700001701452700001701469856011601486 1986 eng d00aLight interception and leaf area estimates from measurements of grass canopy reflectance0 aLight interception and leaf area estimates from measurements of  a76 -820 vGE-243 a

Grassland is a major component of the Earth's available land. The vast area and remoteness of this ecosystem makes it difficult to assess its condition and monitor productivity by traditional methods. Remote sensing potentially offers a rapid nondestructive approach for monitoring such ecosystems. A study was carried out in a tallgrass prairie site near Manhattan, Kansas, during the 1983 and 1984 seasons to investigate the feasibility of estimating light interception and green leaf area index (LAI) from measurements of canopy multispectral reflectance. Greenness (Gn) index was found to be strongly correlated with intercepted photosynthetically active radiation (PAR). Two methods, a direct regression (RGR) and an indirect approach (IND), were used to estimate LAI form Gn index. The LAI values estimated by RGR method were consistently lower than the measured ones; however, good agreement was obtained between the LAI values estimated by IND method and the measured LAI. This suggests that Gn transformation of canopy spectral reflectance is more closely related to the fraction of intercepted PAR by green foliage than the quantity of green LAI

10atallgrass prairie1 aAsrar, G.A.1 aKanemasu, E.T.1 aMiller, G.P.1 aWeiser, R.L. uhttp://knz.lternet.edu/content/light-interception-and-leaf-area-estimates-measurements-grass-canopy-reflectance