Klasyfikacja gleb słonych doliny Czuj w Kirgistanie na podstawie wielospektralnych obrazów satelitarnych Landsat TM, Landsat ETM+, TERRA ASTER oraz danych naziemnych
Klasyfikacja gleb słonych doliny Czuj w Kirgistanie na podstawie wielospektralnych obrazów satelitarnych Landsat TM, Landsat ETM+, TERRA ASTER oraz danych naziemnych Classification of salt-affected soils of the Chuy Valley in Kyrgyzstan using multispectral satellite Landsat TM, Landsat ETM+, TERRA ASTER images and ground-collected data
The natural conditions of Kyrgyzstan and consequences of
human-induced processes, such as inappropriate methods of
irrigation, have led to the extension of salt-affected soils.
Extensive areas of irrigated land have been increasingly degraded
by salinization from over-irrigation and other forms of
inadequate agricultural practices. Between 1985 and 1990,
the area of salt-affected soils increased from 666 300 ha to
1170 300 ha (Mamytov, 1995). In recent years salinity processes
have been described as one of the problems of agriculture
in that area. For the last ten years many none-affected soils
of the Chuy Valley have become salinized. According to
Mamytov et al. (1991) the total area of salt-affected soils in
the Chuy Valley exceeds 259.5 thousands ha, which is more
than 42% of the research area.
In this research, an attempt has been made to estimate
soil salinity quantitatively and also spatially by applying remote
sensing techniques. Conventional methods of mapping
salt-affected soils consume a lot of energy, time and money.
Remote sensing enables us to detect and to map salt-affected
soils by using relatively cheap multispectral satellite data
such as Landsat TM, Landsat ETM+ and TERRA ASTER.
The objective of this study is to identify salt-affected soils by
integrating satellite images with ground-collected data. In
order to achieve this goal the best algorithms of an unsupervised and a supervised classifi cation have been chosen using
TNTmips software. The Normalized Difference Vegetation
Index (NDVI) and the Transformed Vegetation Index (TVI)
have been applied to distinguish densely and partly vegetation-
covered soils, which are not salt-affected. To distinguish
areas covered with stone and sands from saline soils the
Salinity Index (SI) has been applied. For the differentiation
of arable land which is not covered with vegetation the brightness
parameter of Tasseled Cap transformation has been used.
All these indices were calculated from satellite images. Finding
an appropriate interpretation scheme for identifying the saltaffected
soils of the Chuy Valley becomes a very important
factor infl uencing the accuracy of the supervised classifi cation.
The temporal change of salinity accumulation is demonstrated
by comparing the classifi cation’s results of the multispectral
satellite images from 1994 to those of 2001. This study
also includes measurements of spectral properties of collected
soil samples for better understanding the difference in classifi
cation accuracy of various types of salt-affected soils.
Spectral refl ectance was registered from the surfaces of saline
and saline-sodic soils using fi eld luminancemeter CIMEL CE
313-21 in the following wavelength bands: 450 nm, 550 nm,
650 nm and 850 nm.
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