Landsat Multispectral Data Research Articles

Snow Surface Measurements from Digital Landsat MSS Data

The snow cover is an important parameter for water run-off prediction in high mountain areas. At present its seasonal changes can be monitored regularly by satellite. The paper presents a new method for a more accurate classification of snow from multispectral Landsat data with the aid of a digital terrain model (DTM). A reflectance map derived from the DTM was used to register the Landsat data onto the map applying the cross-correlation function. The DTM makes the independent evaluation of snow possible with respect to elevation, exposure and slope angle. For areas with climatologically similar conditions, it becomes possible to extrapolate the snow cover of the total catchment area supposed to be partially obscured by clouds from a small “cloud free” zone.

Delineation of soil associations for a part of tamil nadu by digital processing of landsat multispectral data

The utility of Landsat multispectral data for small scale soil mapping has been demonstrated in this study. The scene used for the study has path-row number 153-054 of Landsat-1 dated 26th February, 1973 covering parts of Ramnad, Tirunelveli and Kanyakumari districts of Tamil Nadu. Associations of sub groups have been delineated on 1 : 250,000 scale using computer-aided multispectrcl data analysis system (M-DAS). Soil map prepared using the computer has been found to be camparable with the soil map prepared by conventional methods at the same scale. Apart from the soil associations, other land use/land cover classes like water bodies forest/scrub/hiliy areas, crcps etc. were also categorised in the colour coded soil map.

A comparison of two methods for classifying forestland†

Two methods of developing land-cover classifications using Landsat multispectral data were compared. The first method, called P-1, uses a semi-automated approach to develop training statistics which characterize the land-cover types. The second, called multicluster blocks, depends more on analyst interaction to produce the training statistics used by the classifier. The results showed that P-1 performed as well as the multicluster-blocks approach on a mountainous study area in southwestern Colorado. These results may interest any resource discipline which has available to it ground-checked or photointerpreted information. P-1 can use this information directly to output a land-cover classification with little analyst interaction.

Chemical whitings and chlorophyll distributions in the Great Lakes as viewed by Landsat

A chemical precipitation of calcium carbonate, or whiting, was first observed by satellite in Lake Michigan during August 1973. Since that initial observation similar events have been noted in Lakes Michigan, Erie, and Ontario with imagery from LANDSAT, SKYLAB, and NOAA satellites. By the use of LANDSAT multispectral data together with NOAA thermal infrared data, we have observed that whitings occur several meters below the lake surface in relatively warm water. They are most vividly displayed during and after periods of upwelling. As the epilimnetic waters become supersaturated with Ca ++ ions during summer, a triggering mechanism (presumably biological or physical) initiates the whiting, which then may continue for several months. At present, the effects on the biota of the euphotic zone when this milky cloud is present in the upper layers are poorly understood. However, scientists engaged in Great Lakes' circulation studies are taking advantage of “nature's free dye tracers” to better understand currents in the lakes.

A Landsat digital image rectification system

DIRS is a digital image rectification system for the geometric correction of Landsat multispectral scanner digital image data. DIRS removes spatial distortions from the data and brings it into conformance with the universal transverse mercator (UTM) map projection. Scene data in the form of landmarks or ground control points (GCP's) are used to drive the geometric correction algorithms. The system offers extensive capabilities for “shade printing” to aid in the determination of GCP's. Affine, two-dimensional least squares polynominal and spacecraft attitude modeling techniques for geometric mapping are provided. Entire scenes or selected quadrilaterals may be rectified. Resampling through nearest neighbor or cubic convolution at user designated intervals is available. The output products are in the form of digital tape in band-interleaved, single-band, or CCT format in a rotated UTM projection. The system was designed and implemented on large-scale IBM 360 computers with at least 300–500 kbytes of memory for user application programs and five 9-track tapes plus direct access storage.

Use of Satellite Data in Urban Hydrologic Models

The study investigates the use of computer-aided analysis of LANDSAT multispectral data in estimating percentage of imperviousness and associated land uses needed in urban hydrologic modeling. An interactive computer was used to delineate seven land use classifications in the 132-sq mi (342-sq km) Maryland portion of the Anacostia River Basin from LANDSAT data. The land-use distributions compared favorably with those of an earlier study which obtained the same information through analysis of aerial photographs having a scale of 1:4800. The LANDSAT data were used to estimate the basin imperviousness as 25.1% while the aerial photographic study had given 23.5%. Comparisons between the photographic and LANDSAT imperviousness estimates are made for subareas within the Anacostia Basin as small as 0.14 sq mi (0.36 sq km). Approximately 94 man-days were required to complete the land-use analysis using the aerial photographs while less than 4 man-days were required to accomplish similar tasks using the LANDSAT data.