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The present experiment was carried out to assess influence and inter-relationships of soil properties in grasslands of three national parks in Madhya Pradesh, Central India. Above ground biomass samples of grass and soil samples were collected during different seasons based on specified measurement protocol by the state forest department. Aboveground biomass of grass showed a characteristic growth pattern throughout the year, increased and achieved maximum biomass at the end of rainy season (September), while started decreasing and attained minimum biomass during pre-summer (March) season. Mean aboveground biomass in the study regions varied from 2.03 (Bandhavgadh National Park) to 5.44 Mg/ha (Kanha National Park) with an average biomass of 3.37 Mg/ha. Biomass showed strong correlation with soil moisture (r=0.69), organic carbon (r=0.77) and electric conductivity (r=0.80) at p=0.05. Correlation between six soil properties showed significant correlation (r=0.90; p=0.01). From this analysis it can be conclude that variation in soil moisture, electric conductivity and organic carbon have direct effect on biophysical properties of grass. [ABSTRACT FROM AUTHOR]

This paper reports results on the LAI Retrieval and Validation Experiment (LRVE) that was conducted for two agricultural areas in Central India during the winter season of 2001–2002. The study aimed at relating field measurements of leaf area index (LAI) to spaceborne Indian Remote Sensing Satellite (IRS) Linear Imaging Self Scanning Sensor-III (LISS-III) data, preparation of site-level LAI maps, and validation of Moderate Resolution Imaging Spectroradiometer (MODIS) 1-km LAI global fields. Measurements of field-level LAI, aerosol optical thickness and water vapor were carried out on the day of LISS-III overpasses. Empirical models based on the site-specific LAI-vegetation index relation were developed and used to generate 23-m resolution LAI maps for two sites (Indore and Bhopal) covering 30 km × 30 km. These LAI images were degraded to 1-km spatial resolution and used for validation of the version 3 and 4 MODIS LAI products (MOD15A2). The results indicate a positive correlation (r = 0.78) between LAI derived from LISS-III data and MODIS data. However an overestimate by a factor of 1.6 to 2.5 in the version 3 MODIS product is observed with root mean square error (RMSE) ranging from 0.20 to 1.26. The factor of overestimation reduces significantly by 50% and RMSE by 40% when version 4 MODIS LAI was analyzed. The improvement in accuracy was observed to be associated with the change in algorithm path adopted for retrieving version 3 and 4 MODIS LAI. Analysis of the MODIS land cover product that is an input in the MODIS LAI retrieval algorithm indicated errors in assigning land cover classes for the study sites, which could be one of the sources of error in MODIS LAI product. [ABSTRACT FROM AUTHOR]