摘要:

The objective of this study was to use Landsat-MSS digital data converted for the mapping of suspended sediments (SS) in the Krishna Bay Estuary. The relation between Landsat-MSS radiance values for all four bands and measured values of suspended solid concentrations were quantified using simple linear and multiple regression equations. An optimum and best fitted equation was chosen based on the percentage error of estimation, Chi2values and simplicity of the model. This calibrated regression model was then applied to map the SS(mgl−1) concentration for the entire study area. It is shown that Landsat-MSS data can be used successfully to quantify suspended sediment concentrations in this geographical area and possibly in other areas which have similar environmental and climatic conditions, if the regression equation is tested using an independent data set.

ISSN:0143-1161    

DOI:10.1080/01431169308954030

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

A vegetation index and radiative surface temperature were derived from NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) data for the Seattle, WA region from 28 June through 4 July 1991. The vegetation index and surface temperature values were computed for locations of weather observation stations within the region and compared to observed minimum air temperatures. These comparisons were used to evaluate the use of AVHRR data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). AVHRR derived normalized difference vegetation index (NDVI) and radiant surface temperature data from a one week composite product were both related significantly to observed minimum temperatures, however, the vegetation index accounted for a greater amount of the spatial variation observed in mean minimum temperatures. The difference in the NDVI between urban and rural regions appears to be an indicator of the difference in surface properties (i.e., evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures.

ISSN:0143-1161    

DOI:10.1080/01431169308954031

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor

摘要:

A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3·55-3·95 μm channel was used with the two reflective channels 0·58-0·68 μm and 0·725-1·-1 μm to run a Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. In addition, the relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse spatial resolution data for global studies.

ISSN:0143-1161    

DOI:10.1080/01431169308954032

出版商:Taylor & Francis Group    

年代:1993

数据来源: Taylor