4 - Central Institute of Brackishwater Aquaculture

Nattonal Workshopcum-Training on Bidnformatia and Information Management in Aquaculture
Trans Gangetic Plain of the country using time series satellite data available in
public domain. New techniques were developed to discriminate different crops,
cropping pattern using these products. Even if the potential of this data was
found to discriminate early, timely and late sown crop in a region. The cropping
system analysis has provided valuable inputs for crop diversification and
intensification planning. Same work was also carried out by Dept of Space form
whole state Punjab and West Bengal. While implementing the same, long-term
sustainability and cropping system performance as well as feasibility of applying
the precision farming concept need to be appropriately addressed. The cropping
system analysis needs to be extended to national level to maximize the
agricultural productivity.
3.6 Crop Parameter Retrieval and Prioritization for Intervention
Understanding and predicting crop phenology and canopy development is
important for many reasons including improving the efficacy of management
practices and increasing accuracy of simulation models and decision support
systems. Biophysical parameters such as leaf area index (LAI), fraction of
absorbed photosynthetic active radiation (FAPAR), fraction vegetation cover
(NC), chlorophyll content, canopy height, roughness etc. have been identified as
the most important physical properties of the terrestrial surface due to their
specific roles in biosphere-atmosphere interactions, and they play unique role in
global climate change studies. The knowledge of canopy biophysical variables
and agrometeorology is of prime interest in many applications and can be used
as inputs to crop growth and yield simulation models. The role of remote sensing
in retrieval of some of these parameters could be explained in terms of
parameters that can be obtained from Earth observing satellite data. The
parameters of interest amenable to remote sensing based assessment are
grouped under three groups: (i) crop phenology (emergence, greening, peak
vegetative stage, senescence, length of growing season); (ii) biophysical
parameters (LAI, fAPAR, FVC, chlorophyll content, canopy roughness etc.); and
(iii) Agrometeorological parameters (Albedo, surface temperature, soil moisture
etc.). IARI experiment has been successfully conducted to retrieve Leaf Area
Index (LAI), chlorophyll (Cab) and moisture content (Cw) of wheat crop at
regional scale in Trans Gangetic Plain from free available MODIS data products
using physical process based radiative transfer model and developed a composite
crop health index based on LAI, chlorophyll and moisture content of the crop for
better site specific crop management practices.
3.7 Water and Nutrient Management
Nutrient and water stress management is another area where remote sensing
data has been potential used in country and abroad. Detecting nutrient stresses
using remote sensing and combining data in a GIs can help in site-specific
applications of fertilizers and soil amendments such as lime, manure, compost,
gypsum, and sulfur, which in turn would increase fertilizer use efficiency and
reduce nutrient losses. In semi-arid and arid tropics, precision technologies can
help growers in scheduling irrigation more profitably by varying the timing,
amounts and placement of water. For example, drip irrigation, coupled with
information from remotely sensed stress conditions (e.g., canopy-air
temperature difference), can increase the effective use of applied water thereby
reducing runoff and deep percolation.