Abstract
Drought is a recurrent phenomenon in Jharkhand. It affects the livelihoods of the majority of its people, particularly tribals and dalits living in rural areas. Twelve of the 24 districts of the state, covering 43% of the total land area, are covered under the Drought Prone Areas Programme (DPAP). Hunger and starvation deaths are reported almost every year. Vegetation moisture content is one of the key parameters in drought monitoring, agricultural modelling and forest health mapping. In this paper the three different approaches is described using Advanced Spaceborne Thermal Emission & Reflection Radiometer (ASTER) data for measuring the vegetation moisture content in a part of Palamu Commissionaire of Jharkhand state, which is prone to severe drought. ASTER thermal data was used to calculate land surface temperature using Normalized Differential Vegetation Index (NDVI) emissivity correction method. Reflective bands are used to determine NDVI, Modified Soil Adjustment Vegetation Index (MSAVI) & Normalised Differential Water Index (NDWI). The three different vegetation moisture estimation methods namely MSAVI – LST (land surface temperature) feature space identification, NDWI & Vegetation Dryness Index (VDI) is applied to determine the vegetation moisture level. The results of three methods were classified and final moisture content map was produced. The result was validated using rainfall data of study area. This study indicates that by proper pre-processing of ASTER data, it can be used to estimate the land surface temperature and vegetation moisture content and can be used for drought prediction.
Highlights
Periods of persistent abnormally dry weather known as droughts, can produce a serious agricultural, ecological and hydrological imbalance
The Modified Soil Adjustment Vegetation Index (MSAVI) created from Advanced Spaceborne Thermal Emission & Reflection Radiometer (ASTER) VNIR image was used as Vegetation Index and Land surface kinetic temperature calculated from ASTER TIR image was used as Land Surface Temperature (LST) [16]
This paper explores the relationship between LST and different vegetation index to measure the moisture content within the vegetations in drought prone area of Jharkhand state during the early summer season
Summary
Periods of persistent abnormally dry weather known as droughts, can produce a serious agricultural, ecological and hydrological imbalance. Drought harshness depends upon the degree of moisture deficiency, duration and the size of the affected area [1]. Remote sensing is widely used to monitor and predict vegetation characteristics for sustainable development. Imaging spectrometry has great potential for monitoring vegetation type and biophysical characteristics [2]. Vegetation reflectance spectra are often quite informative, containing information on the vegetation chlorophyll absorption bands in the visible region, the sustained high reflectance in the near infrared band, and the effects of plant water absorption in the middle infrared region. Normalized Differential Vegetation Index (NDVI) is used to measure the forest health. It measures the chlorophyll content within the vegetation [3].
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