LANDAST MSS Data Processing for Measuring Groundwater Level

Abstract

Remote sensing techniques have provided new scientific tools for measurement of specific quantities in natural environment. However, techniques for measuring groundwater level or soil moisture from LANDSAT MSS data are now under development by many groups. We have been conducting feasibility study for measuring groundwater level or soil moisture of Takasu Polder located at estury of Nagara River. Our final purpose is to apply this method for estimating the effects of the rise of groundwater level due to backwater of Estuary Dam now under planning.
As a first step we intended to analyze the relation between LANDSAT image and groundwater level, using 9 LANDSAT scenes and observed groundwater level data at 10 points. At Takasu Polder region, groundwater level is about 50 cm below ground surface, therefore it is not irrational to assume that the groundwater level affects the moisture content of ground surface, and resulting change of the reflection characteristics of ground surface affects the LANDSAT image.
This paper describes some results on processing techniques and regression analysis. Main results obtained up to now can be summarized as follows.
(1) Land use categorization from LANDSAT MSS data can be attained by two seasonal composite data than one seasonal data. Paddy field in the study area was extracted from two seasonal LANDSAT MSS data.
(2) Following regression equation with a correlation coefficient, 0.89, was obtained for the estimation of groundwater level in the case of no vegetation on paddy field.
These coefficients are applied to the LANDSAT data on December 1. 1980. Also, following regression equation with a correlation coefficient, 0.75, in the case of vegetation on paddy field was obtained.
These coefficients are applied to the LANDSAT data on September 8. 1979 and September 2. 1980. Here, ymeans the distance from groundwater level to the ground surface. X₄, X₅, and X₇ are the values in each band of LANDSAT MSS data.