Comparison of Vegetation Indices from Two Ground Based Sensors

The best and commonly used ground-based sensor to monitor crop growth, ASD FieldSpecPro Spectroradiometer (Analytical Spectral Devices, Boulder, CO, USA) is a passive sensor, which can be used under adequate light condition. However, now-a-days active sensors such as GreenSeeker? (GS) handheld crop response (Trimble Agriculture division, USA) are used for monitoring crop growth and are flexible in terms of timeliness and illumination conditions besides being cheaper than the ASD. Before its wide use, the suitability and accuracy of GS should be assessed by comparing the NDVI measured by this instrument with that by ASD, under diverse wheat growing conditions of India. Keeping this in view, the present experiment was undertaken with the following objectives: (1) to find out the temporal variation of NDVI measured both by ASD and GS treatments, (2) to find out relationship between the NDVI measured through ASD and GS and, (3) to evaluate the suitability of GS for NDVI measurements. It was observed that the numerical value of NDVI as measured by GS was always significantly (P < 0.05) lower than that measured by ASD for all the experiments under study. The NDVI-ASD and NDVI-GS were significantly positively correlated (P < 0.01) with the correlation coefficients being +0.94, +0.88 and +0.87 for irrigation and nitrogen experiment, irrigation and cultivars experiment, and tillage, residue and nitrogen experiments, respectively. Further, the regression equation developed between the NDVI-ASD and NDVI-GS: [NDVI-GS = 1.070 × (NDVI-ASD ? 0.292] can be successfully used to compute the NDVI of ASD from that computed by GS.     

Estimation of Partial Pressure of Carbon Dioxide and Air-Sea Fluxes in Hooghly Estuary Based on In Situ and Satellite Observations

An empirical model is developed and used with remotely sensed predictors: sea surface temperature (SST) and chlorophyll-a concentration (Chl-a), to compute surface water partial pressure of carbon dioxide (pCO_2w) and air-sea fluxes of CO₂ in the Hooghly estuary and its adjacent coastal oceans. In situ observations used here were based on measurements carried out in this region during winter and summer periods in 2008. The estimated pCO_2w compares well with the in situ observations at root mean square error ±18 μatm. In winter, estimated pCO_2w ranges between 320 and 500 μatm with large values (>400 μatm) on the south-western and south-eastern flanks of the coastal domain and lower values (340–375 μatm) on the main-channel. In summer, it remained spatially uniform at 450 μatm. Extrapolation of the results over the study region based on the Moderate Imaging Specroradiometer (MODIS) measured SST and Chl-a suggests that the region is a strong source of atmospheric CO₂ during the summer with net release of 0.095 Tg C year^?1 (equivalent to mean flux of 90 molC m^?2 year^?1) and is a weak source during the winter with net release of 0.006 Tg C yr^?1 (0.5 molC m^?2 year^?1) from the geographical extent of 6000 Km² area.     

Seismic hazard monitoring in Kamchatka and its applications to the M = 6.6 earthquake of 6 October 1987

The earthquake of 6 October 1987 (M = 6.6), which occurred near the Shipunsky Cape, Kamchatka, was the largest crustal event in the vicinity of the main city of Kamchatka — Petropavlovsk-Kamchatsky — during the last three decades. It was followed by numerous aftershocks. This earthquake allowed us to test the effectiveness of the seismic hazard monitoring in Kamchatka, including the seismological, geodetic and hydrogeochemical surveys. The seismic survey provided the location and source nature of the main shock and aftershocks and the seismic environment of the main shock. The geodetic and hydrogeochemical surveys have yielded data on the response to earthquakes of the Earth's surface deformations, water level, and chemical elements concentration in the underground water. As a result, the following data were obtained:

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The earthquake of 6 October had a seismic moment 4–10 E18 Nm, thrust type of faulting and the source volume of 20 × 20 × 10 km³. The maximum intensity was VI–VII (MSK-64 scale) and maximum acceleration 88 cm/s².

Before this event, a relative increase in the number of the upper mantle (depth more than 100 km) moderate magnitude earthquakes during 5 years and a one-year period of seismic quiescence for small shallow earthquakes, were recognized. Significant anomalies in HCO₃ and H₃BO₃ concentrations in the underground waters were observed in the wells a week before the main shock.

     

Simulating the effect of Nitrogen application on Wheat Yield by linking remotely sensed measurements with wtgrows simulation model

A field experiment was conducted on wheat at New Delhi with five treatments of Nitrogen (N) fertilizer application (0, 30, 60, 90 and 120 kgha^-1). Relationship has been established between observed leaf area index (LAI) and remotely sensed vegetation indices. These relationships are inverted and used for predicting LAI from vegetation indices on different days after sowing. The “re-initialization” strategy is implemented in model WTGROWS in which initial conditions of model are changed so that the model simulated LAI match remote sensing predicted LAI. The model performance with re-initialization has been evaluated by comparing the simulated grain yield and total above-ground dry matter (TDM) values with the actual observations. The results show that in-season re-initialization is effective in model course correction by improving the simulated results of yield and TDM for different N treatments even though the model was run with no N stress condition. Model re-initialization at different days shows that the closer is the day of re-initialization to crop anthesis the more effective is model course correction. Also, the treatment showing maximum error in yield simulation without re-initialization shows maximum reduction in error by re-initialization. The approach shows that the remote sensing inputs can substitute for some of the inputs or errors in inputs required by crop models for yield prediction.     

Quantification of suspended solids in Dal lake,Srinagar using remote sensing technology

Indian Remote Sensing satellite (IRS)-1B, Linear Imaging Self Scanner (LISS)-II spectral digital data was analysed to determine the feasibility of quantifying the concentration of suspended solids in the surface water of inland water body, Dal lake, in Srinagar, India. The water samples collected in concurrent with IRS-1B overpass, were analysed to determine the concentration of suspended solids. The results indicate that a positive functional relationship exist between the concentration of suspended solids and the visible wave length bands 1 and 3 and near infrared band 4. It has been observed that as the concentration of suspended solids increase, the spectral response also increases. It is concluded that IRS LISS-H data can be effectively used to quantify suspended sediment concentration in the Dal lake surface water.     

On the Distance Function Between Two Keplerian Elliptic Orbits

The problem of finding critical points of the distance function between two Keplerian elliptic orbits is reduced to the determination of all real roots of a trigonometric polynomial of degree 8. The coefficients of the polynomial are rational functions of orbital parameters. Using computer algebra methods we show that a polynomial of a smaller degree with such properties does not exist. This fact shows that our result cannot be improved and it allows us to construct an optimal algorithm to find the minimal distance between two Keplerian orbits. This revised version was published online in July 2006 with corrections to the Cover Date.     

Evaluation of significant sources influencing the variation of physico-chemical parameters in Port Blair Bay,South Andaman,India by using multivariate statistics

Port Blair is the capital city of Andaman & Nicobar Islands, the union territory of India. More than 50% of the population of these islands lives around Port Blair Bay. Therefore the anthropogenic effects in the bay water were studied for monitoring purpose from seven stations. Physico-chemical parameters of seawater were analyzed in samples collected once in every 3 months for 2 years from seven sampling stations located in Port Blair Bay, South Andaman Island to evaluate the spatial and tidal variation. Cluster analysis and factor analysis were applied to the experimental data in an attempt to understand the sources of variation of physico-chemical parameters. In cluster analysis, the stations Junglighat Bay and Phoenix Bay having high anthropogenic influence formed a separate group. The factors obtained from factor analysis indicated that the parameters responsible for physico-chemical variations are mainly related to land run-off, sewage outfall and tidal flow.