Assessing grassland biophysical characteristics from spectral measurements

Weiser, Russell L.; Asrar, Ghassem; Miller, George P.; Kanemasu, E. T.

doi:10.1016/0034-4257(86)90019-2

Cited by 77 publications

(28 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In tallgrass prairie, amounts of litter and standing dead vegetation are strongly influenced by both topography and management practices. These factors interact to significantly alter canopy spectral reflectance characteristics and NDVI Weiser et al 1986;Asrar et al 1989;Turner et al 1992). Distinguishing burned versus unburned areas improved the accuracy of our landscape-scale estimates of gas fluxes.…”

Section: Discussionmentioning

confidence: 93%

Plant productivity and nitrogen gas fluxes in a tallgrass prairie landscape

Groffman

Turner

1995

Landscape Ecol

View full text Add to dashboard Cite

We explored relationships between plant productivity and annual fluxes of nitrogen (N2) and nitrous oxide (N20) in a tallgrass prairie landscape in central Kansas. Our objective was to develop predictive relationships between these variables that could be used in conjunction with remote sensing information on plant productivity to produce large-area estimates of N gas fluxes. Our hypothesis was that there are inherent relationships between plant productivity and N gas fluxes in tallgrass prairie because both are controlled by water and N availability. The research was carried out as part of a multi-investigator project, the First ISLSCP Field Experiment (FIFE, ISLSCP --International Satellite Land Surface Climatology Program), directed toward the use of remote sensing to characterize land-atmosphere interactions. Fluxes of N 2 (denitrification) and N20 were measured using soil core techniques. Estimates of annual flux were produced by temporal extrapolation of measured rates. Annual aboveground net primary productivity (ANPP) was estimated from measurements of the maximum standing crop of plant biomass. There were strong relationships between ANPP and N gas fluxes, and between a satellite remote sensing-based index of plant productivity (normalized difference vegetation index, NDVI) and gas fluxes. We used these relationships to convert images of NDVI into images of N gas fluxes for one 83 ha watershed and for the entire 15 by 15 km FIFE site. These images were used to compute mean landscape gas fluxes (0.62 g N m -2 y-I for N 2, 0.66 g N m -2 y-1 for N20 ) and total N gas production for the two areas. Our flux and production values are useful for comparison with values produced by simulation models and site-specific studies, and for assessing the significance of N gas production to ecosystem and landscape scale processes related to nutrient cycling, water quality and atmospheric chemistry.

show abstract

Section: Discussionmentioning

confidence: 93%

Plant productivity and nitrogen gas fluxes in a tallgrass prairie landscape

Groffman

Turner

1995

Landscape Ecol

View full text Add to dashboard Cite

show abstract

“…In order to further enhance the representation of vegetation we extracted the Normalized Difference Vegetation Index. Additionally we tested several band ratios that provide unique information and subtle spectral reflectance differences between surface materials (Southworth, 2004;Weiser, Asrar, Miller, & Kanemasu, 1986); we used five of them in our model (band 4/band 3; band 7/band 2; band 3/band 2; (band 2−band 6)/ (band 2 + band 6); TC.GVI/band 6). We also derived auxiliary variables (elevation and slope) from the Global Land Survey Digital Elevation Model (GLSDEM) as they helped in discriminating between bare and sparsely vegetated areas.…”

Section: Predictor Variablesmentioning

confidence: 99%

Land cover of Greece, 2010: a semi-automated classification using random forests

2015

View full text Add to dashboard Cite

Information about land cover (LC) and land use is fundamental in various areas of research regarding the Earth's surface. However, field campaigns are costly and time consuming while existing data sets have strong limitations. Classification of LC by remote sensing, although considered a technically and methodologically challenging task, can facilitate mapping initiatives at various scales. This study suggests an efficient and robust methodology of LC classification with minimal user requirements. The study site is Greece which faces a lack of up to date LC maps at national scale. In this context we employed Landsat imagery, open source software and the random forest classification algorithm to produce a high resolution national LC map for 2010. The algorithm was trained semi-automatically, extracting information from available data sets. The results are promising, achieving an overall accuracy of 83%. The methodology presented minimizes many obstacles that lead to data deficiencies and can act as a baseline for future LC mapping initiatives. ARTICLE HISTORY

show abstract

“…The normalized difference vegetation index (NDVI) has been shown to be related to plant canopy variables, which also relate to ET. Ritchie & Burnett (1971), Wiegand et al (1979), Holben et al (1980), Tucker (1979), and Weiser et al (1986) have shown a relationship between NDVI and green leaf area index (LAI), photosyntheticaliy active biomass, and percentage green cover for grass, soybean and corn canopies. The LAI has been related to ET by Stern (1965) for safflower and by Hinkle et al (1984) for corn and soybeans.…”

Section: Introductionmentioning

confidence: 98%

Evapotranspiration estimation using a normalized difference vegetation index transformation of satellite data

Seevers¹,

Ottmann²

1994

Hydrological Sciences Journal

View full text Add to dashboard Cite

Evapotranspiration of irrigated crops on two irrigation service areas along the lower Colorado River was estimated using a normalized difference vegetation index of satellite data. A procedure was developed which equated the index to crop coefficients. Evapotranspiration estimates for fields for three dates of thematic mapper data were highly correlated with ground estimates. Service area estimates using thematic mapper and Advanced Very High Resolution Radiometer data agreed well with estimates based on US Geological Survey gauging station data.

show abstract

Assessing grassland biophysical characteristics from spectral measurements

Cited by 77 publications

References 33 publications

Plant productivity and nitrogen gas fluxes in a tallgrass prairie landscape

Plant productivity and nitrogen gas fluxes in a tallgrass prairie landscape

Land cover of Greece, 2010: a semi-automated classification using random forests

Evapotranspiration estimation using a normalized difference vegetation index transformation of satellite data

Contact Info

Product

Resources

About