Nonsupervised classification by clustering has been shown to be a very important tool in the analysis of satellite remote senSing data. However, clustering algorithms which use Euclidean distance as a measure of similarity are highly sensitive to scaling differences among the variables which participate in the clustering process. Since the Landsat MSS spectral bands have different ranges and di...

In this paper, the authors describe and implement an algorithm to perform a supervised classification into Landsat MSS satellite images. The Maximum Likelihood Classification method is used to generate raster digital thematic maps by means of a supervised clustering. The clustering method has been proved in Landsat MSS images of different regions of Mexico to detect several training data relate...

, A number of image a n a l y s i s t a s k s r e q u i r e t h e r e g i s t r a t i o n of a s u r f a c e model w i t h an image. I n t h e case o f s a t e l l i t e images, t h e s u r f a c e model may be a map o r d i g i t a l t e r r a i n model i n t h e form o f surface e l e v a t i o n s on a g r i d o f p o i n t s. We develop here an a f f i n e transformation between coordinates...

LANDSAT-l and -2 multispectral scanner (MSS) data from six overpass dates (April 2, May 17, June 4, July 10, October 17. and December 10, 1975) showed that MSS digital data for bare soil. cloud tops. and cloud shadows followed a highly predictable linear relation (soil background line) for MSS bands 5 and 7 (r2 = 0.974). Increasing vegetation development. documented by leaf area index measureme...

ABSTRACf The National Agricultural Statistics Service used LANDSAT multispectral scanner (MSS) data to aid regression estimates of acreage for major crops during 1980-1987. Future LANDSAT satellites will not have the MSS scanner, but will have a thematic mapper (TM) scanner. TM data is more expensive to purchase and process for large areas because of its higher spatial and spectral resolution. ...

this research was performed to evaluate the potentials of landsat mss data for map-ping land features in arid zones of southeastern esfahan, iran. databases of the area were formed using all available relevant maps and reports which were supported by fieldwork. a supervised image classification approach was used and thirty-two training areas were applied. separability of the spectral classes wa...

The aim of this project was to determine the accuracy of using simple digital image processing techniques to map riverine water bodies with Landsat 5 TM data. This paper quantifies the classification accuracy of single band density slicing of Landsat 5 TM data to delineate water bodies on riverine floodplains. The results of these analyses are then compared to a 6-band maximum likelihood classi...

The launch of the Landsat-4 satellite in July 1982 provided the first full coverage from space of the .4-12 ~m spectrum of the earth scene. In addition to the green, red, and near IR bands of the MSS, the TM provides a band in the blue, two in the middle IR, and one thermal IR. The paper describes spectral class analysis of coincident MSS and TM data to evaluate the contribution of the addition...