A GPS-Supported Gravity Survey in the Amazon of Ecuador

The growing importance and effectiveness of the Global Positioning System (GPS) in positioning geophysical surveys is now well established. In Ecuador's Amazon basin the use of GPS was the determining factor in the successful completion of a gravity survey carried out in 1994. Over 500 gravity stations, spaced from 1 to 5 km apart and positioned by GPS, were collected in the jungle environment in the country's southeast, where the preexisting data, of variable and unknown quality, were mostly confined to areas along the major rivers. This station densification, which includes the reoccupation of selected points, contributed to increase the gravity coverage; it also allowed us to evaluate and correct 1100 preexisting data points in the area, so that the different surveys can be merged. The composite data set is used for a geologic analysis of the study area, where previously unknown structures are discovered. ? 1999 John Wiley & Sons, Inc.     

Preparation of volume table of SAL (Shorea robusta) - an approach using satellite data

Sal (Shorea robusta) is an important forest tree species in north and north-eastern India. Large-scale plantations of this species have been raised there under taungya and coppice system of management. The conventional volume table prepared for high sal forest is referred to infer the volume of production of this species. Earlier workers have used aerial remote sensing data to develop volume tables of this species. In the present study a volume table for sal is developed based on remotely sensed satellite data using a regression technique. A two-step method was developed to estimate mean tree volume from satellite data. In step 1, mean crown diameter — an intermediate variable - was estimated from satellite data. In step 2, the estimated mean crown diameter was used to estimate the mean tree volume. Addition of age of the crop as an independent variable improved the predictive ability of the regression equation.     

Late Cretaceous-Cenozoic history of the Lake Baikal depression and formation of its unique biodiversity

Independent methods of geological and molecular-biological chronologies have made it possible to define generally corresponding stages in the geological and biological evolution of the environments and communities of Lake Baikal since the Late Cretaceous, i.e., during the last 70 myr. All the abiotic elements drastically changed during geological evolution, with destruction of existing and formation of new natural complexes. Nevertheless, some specific zones retained relicts of former settings. The resulting present-day natural complex includes elements of different ages and geneses. Similar to different natural zones of the present-day Earth, which are populated by different biocoenoses, stages in the development of abiotic elements are also characterized by different faunal and floral assemblages. Some taxa were replaced by others, and the resulting aqueous biota of Lake Baikal includes different-age and ecologically different elements. The oldest groups of Baikal organisms appeared approximately 70 Ma ago, although the largest proportion of the lake biota started forming 4–3 Ma ago in response to the most drastic changes in the abiotic elements of the environment. The youngest taxa appeared 1.8 to 0.15 Ma ago, i.e., during the period when superdeep lake environments and mountainous glaciations were developing. The chronological coincidence of main stages in development of abiotic and biotic elements of the nature indicates their relationships. Particular transformations of abiotic elements and the probable mechanism of their influence on the evolution of living communities are also considered.     

Peculiarities of surface air temperature variations over the Far East regions in 1976–2005

Peculiarities are investigated of the air temperature variation tendencies at some stations of the Far East in 1976–2005. The estimate of linear trend equation coefficients is computed according to the air temperature observation data using the least squares method. It is demonstrated that the air temperature trend in northern regions possesses a small probability at small values of residual variability. In the southern regions, the trend significance increases for almost all seasons at small values of residual variability. At midlatitude stations, the trend significance in January and February decreases considerably due to the large values of residual variability.     

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.