Above Ground Forest Phytomass Assessment in Southern Gujarat

Spectral modeling of above ground biomass (AGB) with field data collected in 48 field sites representing moist deciduous forest in Surat district is reported. Models were generated using LISS-III and MODIS data. The plot-wise field data was aggregated to MODIS pixel (250 m) using area weightages of forest/vegetation. The study reports that above ground phytomass varied from 6.13 t/ha to 389.166 t/ha while AGB phytomass estimated using area-weights for sites of 250×250 m, ranged from 5.534 t/ha to 134.082 t/ha. The contribution of bamboo in AGB has been found very high. The analysis indicated that the highest correlation between AGB phytomass and red band (R) of MODIS satellite data of October was (R²=0.7823) and R²=0.6998 with both NDVI of October data as well as NDVI_max. High correlation (R²=0.402) with IR band of February month was also found. The phytomass range obtained by using MODIS data varies from 0.147 t/ha to 182.16 t/ha. The mean biomass is 40.50 t/ha. Total biomass is 31.44 Mt. The mean Carbon density is 19.44 tC/ha in forest areas. The study is validation of region-wise spectral modeling approach that will be adopted for mapping vegetation carbon pool of the India under National Carbon Project of ISRO-Geosphere Biosphere Programme.     

Retrieval of wheat leaf area index using price approach based on inversion of canopy reflectance model

This paper reports estimation of the Leaf Area Index (LAI) of wheat crop from IRS-LISS-III data using Price (1993) approach. Empirical approach for LAI estimation with different NDVI estimation procedures viz. radiance, apparent reflectance and dark object subtraction (DOS) based atmospheric correction were also evaluated. Validation of LAI retrieval and NDVI normalizations were carried out using field level measurements of crop LAI and spectral property using canopy analyzer and spectro-radiometer, respectively over selected fields in Bhopal District, Madhya Pradesh. It was observed that empirical relations are sensitive to the NDVI estimation approach and DOS method performed better as compared to other two approaches. It was also observed that LAI estimation from Price algorithm is sensitive to the crop attenuation coefficients. Crop specific attenuation coefficients reported in literature for Indian cultivars gave higher accuracy. The root mean square (RMS) error of 0.77 for LAI estimation was achieved using above described approach.     

Extreme rainfall event of July 25–27, 2005 over Mumbai, West Coast, India

Extreme localised rainfall events are part of monsoon system occurring every year. Satellite data (TRMM and other geostationary satellites) together with ground observations will be useful in providing spatial and temporal variability of atmospheric changes. The short and long term variability is required for better understanding of the local and regional climatic conditions through detailed modelling. Such information will play a key role in real time data analysis and dissemination system to the disaster management groups in the country to minimize losses due to these extreme rainfall events.     

Sub-surface water regime related to landform studies through satellite images

Based on the visual interpretation of satellite (Landsat) false colour composite imagery, the entire Haryana State is divided into eleven landform units. Seven major landform units are studied in details with respect to water table fluctuation, ground water quantum and draft. The studies reveal that usable recharge and draft per unit area are maximum in case of area of water seepage and periodic flooding followed by Yamuna and Ghaggar flood plain and upper alluvial plains with occasional sand dunes. The minimum recharge and draft are observed in case of dune areas.     

Delineating salt-affected soils in the ganges plain by digital analysis of landsat data

A study has been conducted to determine the feasibility of delineating salt-affected soils using computer-aided analysis of Landsat-1 data in an area of the Ganges Plain. The multispectral scanner data have been obtained on 2nd December 1972 Landsat pass. Both supervised and unsupervised classification techniques are used. Four spectral classes of salt-affected soils have been separated. The results indicate that Landsat data can be successfully used for differentiating salt-affected soils.     

Demarcation of spatial extension of kandi (piedmont) area in bist doab (Punjab) through analysis of landsat imagery

The analysis of Landsat imagery has enabled to demarcate the exact limits of the Piedmont Zone (Kandi Area) an important geomorphic unit of the Bist Doab. The study reveals that this Piedmont has the shape of a large fan and covers aboutone third of the total area of Bist Doab.     

Delineating ravinous areas on aerial photographs and satellite Imagery-A comparative study

Extensive areas along Yamuna, Chambal and their tributaries in Uttar Pradesh, Rajasthan and Madhya Pradesh have been severely eroded forming ravines of various depths. These areas offer great potential for the development of agriculture and forestry after reclamation. In order that they are reclaimed and managed properly, precise data on their nature and extent are needed. Morphometric analysis of ravine lands along Chambal and Kunwari rivers near Bhind, Madhya Presdesh has been carried out using 1:25,000 scale aerial photographs. Landsat imagery for the same area has been interpreted to find out the relative recognition of morphometric units earlier interpreted on air photos. It was observed that while aerial photographs provide data regarding depth, width, slope and frequency distribution of ravines at a greater detail, Landsat imagery helps in delineation of broad reclamative groupings which would be useful for Large Area Planning (LAP). A multistage approach involving the use of both air photos and satellite imagery seems to be the possible answer for preparing a Ravine Map of India.     

The effect of synoptic-scale advection on the performance of the Priestley-Taylor evaporation formula

Measurements of the appropriate parameters for the calculation of the latent heat flux over a black spruce forest in northern Quebec were carried out in August, 1980. Values of the Priestley-Taylor parameter, , were derived by exploiting the Bowen-ratio-energy-balance (BREB) technique. Derived values of are then related to synoptic-scale warm air advection, derived from surface synoptic charts and tephigrams of the planetary boundary layer. It is found that when warm air advection is present, > 1.26, especially when the surface is wet. When advection enhancement is removed, however, values of approach unity. A new approach to calculating the latent heat flux, when warm air advection is present, is therefore proposed.     

Impact of surface meteorological observations on RAMS forecast of monsoon weather systems over the Indian region

Summary An attempt has been made to study the impact of surface meteorological observations on the Regional Atmospheric Modelling System (RAMS) simulation of a monsoon depression and two low pressure systems. The surface observations are blended with the GEWEX Asian Monsoon Experiment (GAME) gridded analyses for these cases. In one set of experiments the model is run in 12 hour nudging mode initially and then in forecast mode using GAME gridded data without incorporating surface observations. In another set of experiments surface data are incorporated to enhance the signature of the systems in the large scale GAME analyses and nudging is applied initially for twelve hours. Subsequently the model is run in forecast mode to see the temporal and spatial evolution of different meteorological features associated with the systems. It is found that inclusion of the surface data has in general enhanced the signature of the systems in the analysis and subsequently shows improvement in the forecast of sea-level pressure, geopotential, wind field, etc. and the associated forecast of heavy rainfall, in particular. To make a quantitative comparison of the predicted rainfall with the observed one, equitable threat score and bias are calculated for different threshold values of rainfall. It is clearly noted that inclusion of surface data has improved the precipitation forecast over the Indian land mass as indicated by the equitable threat score and bias for all the threshold rainfall categories.