scholarly journals Spectral Reflectance of Wheat Residue during Decomposition and Remotely Sensed Estimates of Residue Cover

2010 ◽  
Vol 2 (2) ◽  
pp. 416-431 ◽  
Author(s):  
Craig S. Daughtry ◽  
Guy Serbin ◽  
James Reeves ◽  
Paul Doraiswamy ◽  
Earle Raymond Hunt
Author(s):  
Mark Jakubauskas ◽  
Kevin Price

Remotely sensed multispectral data collected from satellites provide a systematic, synoptic ability to assess conditions over large areas on a regular basis. Early use of this satellite data for land cover mapping was based on spectral differences of cover types, with little integration of ancillary data such as soils or topographic information (Iverson et al. 1990). In recent years, concurrent with trends toward integrating remotely sensed and ancillary data for improved classification accuracy (Cibula and Nyquist 1987; Frank 1988), there has been increasing interest in utilizing remotely sensed data for extracting biophysically important variables, relating observed spectral reflectance to leaf area index, biomass, net primary productivity, and vegetation moisture content (Waring et al. 1986; Hobbs and Mooney 1990). The concept of using remotely sensed spectral data to map and monitor the progress of succession within forests and other environments has not been extensively explored. However, the capability to map and predict successional stages of forest habitat types on a landscape to regional scale has important implications for animal habitat management, assessment of insect infestation susceptibility, prediction of fire behavior, and evaluation of plant and animal species diversity. Ecological models based on established successional change rates and trends permit the prediction of future environmental conditions, landscape patterns, and the propagation and effects of disturbances across these landscapes (Hall et al. 1988; Romme 1982). Despain (1990) provides two examples where information on habitat and cover types is important for park management purposes: the cumulative effects model for grizzly bears; and the prediction, assessment, and management of mountain pine beetle outbreaks in conifer forests. Accurate mapping of habitat and cover types can provide information on the distribution and pattern of specific plant communities important to animal species for food, cover, and breeding ground (Knight and Wallace 1989). The ability to map and predict successional stages of forest habitat types has implications for prediction of fire behavior and spread. Previous studies (Despain 1990; Romme and Despain 1989; Romme 1982; Taylor 1969) have noted the relationship between forest age and fire susceptibility. Older stands are comparatively more flammable than younger stands due to fuel accumulations on the ground and in the canopy, and have a higher propensity to propagate and sustain extensive crown fires. Spatial patterns of cover types may also be important, with a highly fragmented landscape mosaic providing natural firebreaks under typical weather conditions. Consequently, as Despain (1990) has noted, the ability to map forest habitat and cover types is of importance for estimation of fire intensity and spread. The use of a single habitat type provides a logical unit for environmental stratification of the study site. Since a habitat type integrates vegetation, climate, topography, and soils (Pfister and Amo 1980), using a single habitat type forces a restriction to selective ranges in climate, topography, and soils types. These constrictions will minimize the effects of abiotic variation on the recorded spectral reflectance, allowing analysis of spectral variation to be concentrated on the changes in biotic factors associated with succession.


2008 ◽  
Vol 17 (4) ◽  
pp. 527 ◽  
Author(s):  
David L. Verbyla ◽  
Eric S. Kasischke ◽  
Elizabeth E. Hoy

The maximum solar elevation is typically less than 50 degrees in the Alaskan boreal region and solar elevation varies substantially during the growing season. Because of the relatively low solar elevation at boreal latitudes, the effect of topography on spectral reflectance can influence fire severity indices derived from remotely sensed data. We used Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) data to test the effect of changing solar elevation and topography on the Normalized Burn Ratio (NBR) and the differenced Normalized Burn Ratio (dNBR). When a time series of unburned pixels from black spruce forests was examined, we found that NBR values consistently decreased from June through September. At the stand level, dNBR-derived values from similar unburned and burned black spruce stands were substantially higher from September imagery relative to July or August imagery. Within the Boundary burn, we found mean post-fire NBR to consistently vary owing to topographic control of potential solar radiation. To minimise spectral response due to topographic control of vegetation and fire severity, we computed a dNBR using images from August and September immediately after a June–July wildfire. There was a negative bias in remotely sensed fire severity estimates as potential solar radiation decreased owing to topography. Thus fire severity would be underestimated for stands in valley bottoms dominated by topographic shading or on steep north-facing slopes oriented away from incoming solar radiation. This is especially important because highly flammable black spruce stands typically occur on such sites. We demonstrate the effect of changing pre- and post-fire image dates on fire severity estimates by using a fixed NBR threshold defining ‘high severity’. The actual fire severity was constant, but owing to changes in phenology and solar elevation, ‘high severity’ pixels within a burn ranged from 56 to 76%. Because spectral reflectance values vary substantially as solar elevation and plant phenology change, the use of reflectance-based indices to assess trends in burn severity across regions or years may be especially difficult in high-latitude areas such as the Alaskan boreal forest.


Author(s):  
Clayton Blodgett ◽  
Mark Jakubauskas

Satellite remotely sensed multispectral data provides a systematic, synoptic means for broad-area spatially-explicit estimation of biophysically important variables. By using ground measurements of biotic properties to calibrate remotely sensed multispectral data, vegetation properties measured at sample points can be extrapolated across a large geographic region (Graetz, 1990). Biophysical variables derived by this empirical method may include the successional state of the vegetation, or an intrinsic property of the vegetation, such as biomass, leaf area index, cover, or moisture content (Jensen, 1983; Waring et al., 1986; Spanner et al., 1984; Graetz, 1990). Spatially-explicit estimation of forest biophysical factors at landscape to regional scales has applications in forest management and ecology, including insect infestation susceptability, forest fire behavior, and estimating plant and animal species habitat and diveristy. Our previous research examined relationships -- between forest structure, successional state, and spectral reflectance characteristics. Results indicated that decreases in visible and middle-infrared spectral reflectance are related to the age and development of a coniferous forest stand. Spectral reflectance changes are rapid during the initial stages of stand regeneration, but the rate of change slows as the stand progresses into later successional stages (Blodgett and Jakubauskas, 1996; Jakubauskas, 1996). Our ongoing objectives are to develop methods for estimation of forest biophysical parameters from satellite remotely sensed data and to compare Yellowstone and Teton coniferous forests in terms of forest structure and successional pattern. Forest stands sampled in 1995 in Grand Teton National Park are 500 - 1000 meters lower in elevation than the Yellowstone sites (sampled 1992-1994), and subject to different temperature and precipitation regimes. Sampling in 1995 was directed at increasing our database of lodgepole-dominated forest stands in the Greater Yellowstone Area.


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