The fine structure of the geomagnetic field

It was shown in our previous works that the dipole part of the geomagnetic field direction is mainly represented by the 1200-yr variation. According to some indications, the residual of the dipole part of the field, the so-called δ variation, may be classified as standing waves. Average values of δ are calculated for each hemisphere. In this work, the difference values equal to the δ variations for each territory minus δ averages over hemispheres (western or eastern) are calculated. The resulting values, fine structure (FS) variations, characterize the FS of the geomagnetic field. The study of the activity of the FS variations and specific features of their N-S and E-W behavior and the comparative analysis of dynamic characteristics (activity and rate) give grounds to classify the FS variations (as well as the δ variations) as standing waves of the nondipole field.     

Accuracy Assessment of Digital Elevation Model Generated by SAR Stereoscopic Technique Using COSMO-Skymed Data

Radargrammetry technique using the stereoscopic synthetic aperture radar (SAR) images is used for the generation of a digital elevation model (DEM) of a region requires only the amplitude images. SAR stereoscopic technique is analogous to the stereo-photogrammetric technique where the optical stereoscopic images are used for DEM generation. While the advantages of the SAR images are their indifference to atmospheric transparency and solar illumination conditions, the side-looking geometry of the SAR increases the complexity in the SAR stereo analysis. The availability of high spatial and temporal resolution SAR data in recent years has facilitated generation of high-resolution DEM with greater vertical accuracy using radargrammetric technique. In the present study, attempt has been made to generate the DEM of Dehra Dun region, India, from the COSMO-Skymed X-band SAR data-pair acquired at 8 days interval through the radargrammetry technique. Here, radargrammetric orientation approach has been adopted to generate the DEM and various issues and processing steps with the radargrammetry technique have been discussed. The DEM was validated with ground measured elevation values using a differential global positioning system and the root-mean-square error of the DEM was found as 7.3 m. The DEM was compared with the reference DEM of the study area generated from the Cartosat-1 stereo data with a model accuracy of 4 m.     

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.