Presently, unplanned changes of land use have become a major problem. Most land use changes occur without a clear
and logical planning with little attention to their environmental impacts. In last four-decade, urban growth in Delhi has
occurred rapidly in some unwanted direction and destroyed valuable agriculture lands in its surround. Rapid changes in
land use / cover occurring over large areas; remote sensing technology is an essential and useful tool in monitoring of
this area. Monitoring of land use/cover change are increasingly reliant on information derived from remotely sensed data.
Such information provides the data link to other techniques to understand the human processes behind these changes.
Specially, in agricultural area in suburb (or countryside) of a metropolitan city like Delhi. In this paper different change
detection approaches (such as Post classification comparison and spectral change detection techniques) were evaluated
with available images of National Capital Territory of Delhi during 1973 to 2001. These techniques were analyzed
independently, using the concept of well-known procedures to define the best approach/methodology for addressing the
change detection issues in this study.
Aerosol presence reduces sunshine hours and the amount of radiation received.
The extent of reduction in radiation during this extreme event (January-March 1999) was
relatively lower, as the extent of the diffused radiation increases. During this time, the
reduction ranged from 5-12%. The differential response of the crops (wheat, rice and
sugarcane) under changed proportion of direct and diffused radiation due to haze was
seen through using crop simulation models (WTGROWS for wheat, DSSAT for rice and
sugarcane). The growing conditions were optimal. Regions chosen for simulation were
north-west India for wheat, coastal and southern regions for rice and north-eastern,
western and southern regions for sugarcane. Simulation results were obtained in terms of
phenology, biomass and economic yield at harvest. There was slight reduction in the yield
of these three crops due to reduction in the radiation, but coupled weather changes
(lowering of temperature, etc.) due to cloudy condition could benefit the crops through
phenology modifications and other crop process activities, which can some times give
higher yields of crops under the aerosol layer when compared to no haze layer situation.
Diffused radiation is more photo-synthetically active, and this feature has still to be
included in most of the existing crop growth models, as the existing crop models do not
differentiate between direct and diffused radiation. The scope of using remote sensing for
assessing the haze layer (spatial and temporal extent) could be employed in the crop
simulation models for regional impact analysis.
Directional reflectance measurement has been found to be better and more reliable compared to the conventional statistical approach to retrieve plant biophysical parameters as it takes care of its anisotropic nature. Keeping this in view, a field experiment was conducted with the objectives set as (i) to relate canopy biophysical parameters and geometry to its bidirectional reflectance, (ii) to evaluate a canopy reflectance model to best represent the radiative transfer within the canopy for its inversion and (iii) to retrieve crop biophysical parameters through inversion of the model. Two varieties of the mustard crop (Brassica juncea L) were grown with two nitrogen treatments to generate a wide range of Leaf Area Index (LAI) and biomass. The reflectance data obtained at 5nm interval for a range of 400- 1100nm were integrated to IRS LISS -II sensor's four band values using Newton Cotes Integration technique. Biophysical parameters were estimated synchronizing with the bi-directional reflectance measurements. The radiative transfer model PROSAIL was used for its evaluation and to retrieve biophysical parameters mainly LAI and Average Leaf Angle (ALA) through its inversion. Look Up Table (LUT) of BRDF was prepared simulating through PROSAIL model varying only LAI (0.2 interval from 1.2 to 5.4 ) and ALA (5° interval from 40 to 55°) parameters and inversion was done using a merit function and numerical optimization technique given by Press et al., 1986. The derived LAI and ALA values from inversion were well matched with observed one with RMSE 0.521 and 5.57, respectively.
A study was undertaken to validate the Wheat Growth Simulator (WTGROWS) in the farmers' fields of Alipur Block of Delhi and linking satellite derived vegetation index with the simulation model to estimate the wheat yield. Date of sowing, management practices and cultivars varied widely among the study sites. Leaf area index (LAI), phenological development and agronomic management (fertilizers and irrigation) were monitored at regular intervals for the 25 field sites selected in the study area. Above ground biomass and grain yield were recorded at harvest. Using the parameters derived for these sites, WTGROWS was run for each of the individual 25 sites. Crop phenology, temporal course of LAI and grain yield of each site was compared with the actual observations. The simulated and actual LAI temporal profile matched well for sites with different dates of sowing, excepting larger deviation noticed in the later stages of the crop growth. The simulated pre-anthesis duration and total above ground biomass were also correlated well with the observed values being mostly within ±15%. There were large discrepancies in simulated and observed grain yield. A satellite image near anthesis of IRS 1D LISS-3 was acquired for the study area. The sites were identified on the image and their vegetation indices were derived. Average grey value in Infrared (IR) and Red (R) band, Ratio Vegetation Index (RVI), Soil Adjusted Vegetation Index (SAVI) and Normalized Difference Vegetation Index (NDVI) were giving significant relation with measured LAI of 5th February which corresponded to crop anthesis stage. The relation between vegetation indices and LAI was logarithmic in nature. This logarithmic relation was incorporated into the WTGROWS to force the LAI to the equation-derived value at particular growth stage and model yield was computed and compared with actual observations.