combining both passive and active satellite based microwave sensors has the potential to offer improved estimates of surface
soil moisture at global scale Liu et al., 2011. The blended products have higher spatial and temporal resolutions. The
enhancement of information by combining both passive and active microwave products helps in understanding land surface
atmosphere interactions these regions Liu et al., 2012. One of the approach used practically for combining soil moisture
derive from active and passive microwave datasets is the blending approach. This technique has an added advantage of
improved spatial and temporal soil moisture dataset as compared individually with passive or active soil moisture
product. With the availability of geospatial soil moisture products, a
variety of applications like flood forecasting, drought monitoring and landslide susceptibility monitoring have been
demonstrated. With increasing uncertainties in the rainfall affecting a large proportion of crop area, drought assessment in
the early part of the cropping season remains to be challenging in India. Since physical indicators like soil moisture are more
sensitive to agricultural drought than biological indicators like NDVI during the early part of the crop season, there is a need
to evaluate the soil moisture datasets for near real-time agricultural drought surveillance for this part of the crop
season. 1.5 Research Objective
The major aim of the research is to perform a detailed analysis of ECV soil moisture time series to bringout the soil moisture
dynamics over Indian region through quantitative indicators. Geospatial analysis of soil moisture changes across space and
time, understanding interrelations, detection of drought exposure patterns etc. constitute the scope of the study.
1.5.1 Objectives: 1. To build the database of soil moisture time series generated under ECV production system of ESA and to
generate soil moisture index for spatio-temporal comparisons. 2. To study the changes in soil moisture in response to rainfall
patterns.
3. To study the dynamics of soil moisture during crop seasons and to analyse the changes in soil moisture during drought and
normal years.
4. To carry-out drought exposure analysis based on soil moisture and rainfall variations.
2. DATA SOURCES 2.1 Introduction
Microwave remote sensing measurements of bare soil surfaces are very sensitive to the water content in the surface layer due
to the pronounced increase in the soil dielectric constant with increasing water content. This is the fundamental reason why
any microwave technique, particularly in the low-frequency microwave region from 1 to 10 GHz, offers the opportunity to
measure soil moisture in a relatively direct manner.
For soil moisture studies the most important bands are: L-band
frequency f= 1-2 GHz, wavelength l = 30-15 cm, C-band f = 4-8 GHz, l = 7.5-3.8 cm, and X-band f =8-12 GHz, l = 3.8
– 2.5 cm.
The main objective of the soil moisture data production system is to produce the most complete and most consistent global Soil
Moisture ECV Data Products based on the measurements observations made by imaging microwave instruments
sensors flying on board of earth observation satellites.
There are two principal types of remote sensing, corresponding to the
following types of microwave instruments: a scatterometers and radars which measure the radar backscattering coefficient
σ0 in physical units [dB] or [m2m2], and b radiometers which measure the brightness temperature TB in physical unit
[K]. The generation of the long-term 30+ years soil moisture data set involves three step blending of active and passive soil
moisture datasets.
3. STUDY AREA AND DATA USED 3.1 Study Area
The present research work has been carried out with all India coverage. India is situated north of the equator between 8°4
and 37°6 N latitude and 68°7 and 97°25 E longitude with the total area of 3,166,414 km2. India is geographically blessed
with wide variety of climatic conditions ranging temperate and alpine in the Himalayan north to tropical in the south. The
elevated regions like J K or Himachal Pradesh receive sustained winter snowfall while other parts of the country being
influenced by two seasons of rain southwest and north east. The south west monsoon season from June
– September is considered the prime rainfall contributor, because 75 of
annual rainfall is received during this short span of time. India has diverse rainfall zones, crop growing environments
and cropping pattern. The net cropped area is 140 m ha and about 60 percent of it is directly dependent on rainfall. Kharif is
the principal crop season which corresponds to 4-5 months period starting from June. The country experiences localized
drought in one part or other almost every year. 3.2 Soil Moisture Time Series Data
The ECV production system has three main components - 1 merging the original active microwave products from 1991,
2 merging the original passive microwave products from 1978 and 3 blending the two merged products. All the inputs
are resampled to a common grid of 0.25 degree and scaled to the same dynamic range. Land surface model GLDAS-Noah
estimates of soil moisture with global coverage have been used as reference to develop uniform dynamic range for different
products. 3.3 Rainfall Data
Currently, these historical rainfall data are archived at the National Data Centre NDC, India Meteorological Department
IMD, Pune. IMD’s efforts to make use of all the available
quality rain gauge data over the country to prepare a high resolution daily rainfall dataset for various applications such as
climate variability climate change studies, validation of model rainfall at various scales, hydrological modelling,
drought monitoring etc., development of a new daily gridded rainfall data set over India at a spatial resolution 0.25° X 0.25°
for 110 years 1901-2010 have been discussed.
The data set was prepared using the daily rainfall data from all the rain
gauge stations over the country available in the IMD archive. 3.4 In Situ Soil Moisture Data
This contribution has been peer-reviewed. doi:10.5194isprsarchives-XLI-B7-631-2016
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The International Soil Moisture Network ISMN is an international cooperation to establish and maintain a global in-
situ soil moisture database. This database is an essential means of the geoscientific community for validating and improving
global satellite observations and land surface models. The soil moisture product has been validated with in situ data from a
ground station of International Soil Moisture Network ISMN. The LPRM estimated soil moisture coincides quite well with
the in-situ measurements and the correlation coefficient is 0.7909. In situ measurements are used to evaluate whether the
temporal variations in the original six microwave soil moisture products are preserved in the final blended product.
4. METHODOLOGY
