Comparison of Deep Underwater Measurements and Radar Observations of Rainfall

Deep-water acoustical measurements of rainfall are compared to high-resolution ground radar observations for the first time. The measurements of underwater ambient sound were made from a subsurface mooring near Methoni, Greece, in 2004. The acoustical measurements were at 60-, 200-, 1000-, and 2000-m depths. Simultaneous ground-based polarimetric -band radar observations were made over the acoustic mooring. Comparisons show acoustic detection of rain events and storm structure that are in agreement with the radar observations. Results from a comparison between the underwater sound pressure level at different depths and the observed radar reflectivities are presented.     

High-Resolution Forecast Models of Water Vapor Over Mountains: Comparison With MERIS and Meteosat Data

Propagation delay due to variable tropospheric water vapor (WV) is one of the most intractable problems for radar interferometry, particularly over mountains. The WV field can be simulated by an atmospheric model, and the difference between the two fields is used to correct the radar interferogram. Here, we report our use of the U.K. Met Office Unified Model in a nested mode to produce high-resolution forecast fields for the 3-km-high Mount Etna volcano. The simulated precipitable-water field is validated against that retrieved from the Medium-Resolution Imaging Spectrometer (MERIS) radiometer on the Envisat satellite, which has a resolution of 300 m. Two case studies, one from winter (November 24, 2004) and one from summer (June 25, 2005), show that the mismatch between the model and the MERIS fields ( rms = 1.1 and 1.6 mm, respectively) is small. One of the main potential sources of error in the models is the timing of the WV field simulation. We show that long-wavelength upper tropospheric troughs of low WV could be identified in both the model output and Meteosat WV imagery for the November 24, 2004 case and used to choose the best time of model output.     

Testing satellite and ground thermal imaging of low-temperature fumarolic fields: The dormant Nisyros Volcano (Greece)

The Nisyros Volcano (Greece) was monitored by satellite and ground thermal imaging during the period 2000–2002. Three night-scheduled Landsat-7 ETM⁺ thermal (band 6) images of Nisyros Island were processed to obtain land surface temperature. Ground temperature data were also collected during one of the satellite overpasses. Processed results involving orthorectification and 3-D atmospheric correction clearly show the existence of a thermal anomaly inside the Nisyros Caldera. This anomaly is associated mainly with the largest hydrothermal craters and has land surface temperatures 5–10 °C warmer than its surroundings. The ground temperature generally increased by about 4 °C inside the main crater over the period 2000–2002. Ground thermal images of the hydrothermal Stephanos Crater were also collected in 2002 using a portable thermal infrared camera. These images were calibrated to ground temperature data and orthorectified. A difference of about 0–2 °C was observed between the ground thermal images and the ground temperature data. The overall study demonstrates that satellite remote sensing of low-temperature fumarolic fields within calderas can provide a reliable long-term monitoring tool of dormant volcanoes that have the potential to reactivate. Similarly, a portable thermo-imager can easily be deployed for real-time monitoring using telemetric data transfer. The operational costs for both systems are relatively low for an early warning system.     

Skyline-based registration of 3D laser scans

Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-free registration methods are required. Based on the existence of skyline features, this paper proposes a novel method. The skyline features are extracted from panoramic 3D scans and encoded as strings enabling the use of string matching for merging the scans. Initial results of the proposed method in the old city center of Bremen are pre-sented.     

Evaluating a thermal image sharpening model over a mixed agricultural landscape in India

Fine spatial resolution (e.g., <300 m) thermal data are needed regularly to characterise the temporal pattern of surface moisture status, water stress, and to forecast agriculture drought and famine. However, current optical sensors do not provide frequent thermal data at a fine spatial resolution. The TsHARP model provides a possibility to generate fine spatial resolution thermal data from coarse spatial resolution (≥1 km) data on the basis of an anticipated inverse linear relationship between the normalised difference vegetation index (NDVI) at fine spatial resolution and land surface temperature at coarse spatial resolution. The current study utilised the TsHARP model over a mixed agricultural landscape in the northern part of India. Five variants of the model were analysed, including the original model, for their efficiency. Those five variants were the global model (original); the resolution-adjusted global model; the piecewise regression model; the stratified model; and the local model. The models were first evaluated using Advanced Space-borne Thermal Emission Reflection Radiometer (ASTER) thermal data (90 m) aggregated to the following spatial resolutions: 180 m, 270 m, 450 m, 630 m, 810 m and 990 m. Although sharpening was undertaken for spatial resolutions from 990 m to 90 m, root mean square error (RMSE) of <2 K could, on average, be achieved only for 990–270 m in the ASTER data. The RMSE of the sharpened images at 270 m, using ASTER data, from the global, resolution-adjusted global, piecewise regression, stratification and local models were 1.91, 1.89, 1.96, 1.91, 1.70 K, respectively. The global model, resolution-adjusted global model and local model yielded higher accuracy, and were applied to sharpen MODIS thermal data (1 km) to the target spatial resolutions. Aggregated ASTER thermal data were considered as a reference at the respective target spatial resolutions to assess the prediction results from MODIS data. The RMSE of the predicted sharpened image from MODIS using the global, resolution-adjusted global and local models at 250 m were 3.08, 2.92 and 1.98 K, respectively. The local model consistently led to more accurate sharpened predictions by comparison to other variants.     

Remote sensing study of granulitic terrain in parts of Gujarat and Rajasthan

The geology of northwestern part of Indian peninsula is considered to be important due to complete preservation of rocks from Archaean to Upper Proterozoic. Further, these rocks have served as ideal host of varieties of economic minerals. The present work is an attempt to study the structurally deformed granulitic terrain in parts of Gujarat and Rajasthan in light of remote sensing. The study area falls under Sirohi, Banas Kantha and Sabar Kantha districts of Rajasthan and Gujarat. Remote sensing technique is utilized for the understanding of structural geology and deciphering the shear pattern. The methods adopted in this study include generation of False Color Composite (FCC) of satellite data, interpretation of lineaments from FCC and study the drainage pattern, structural basin delineation, profiling, and field mapping. It is observed that the area has undergone extensive deformation. There are two major sets of lineaments interpreted in the granulitic terrain such as WNW-ESE and NE-SW directions. Majority of the WNW-ESE lineaments are brittle in nature and N-S, NE-SW trending lineaments are ductile in nature. Overall the study area bifurcated into seven structural basins comprises of basic granulites, calc granulites and pelitic granulites.     

Application of S-SEBI model for crop evapotranspiration using Landsat-8 data over parts of North India

Estimation and monitoring of crop evapotranspiration (ET_c) or consumptive water use over large-area holds the key to irrigation management plans and regional drought preparedness. The objective of this study was to estimate ET_c by applying the simplified-surface energy balance index (S-SEBI) model to Landsat-8 data for the 2014–2015 period in parts of North India. An average ET_c was estimated 2.72 and 2.47 in mm day^?1 with 0.22, 0.18 standard deviation and 0.11, 0.07 standard error for Kharif and Rabi crops, respectively. On validation part, a close relationship was observed between S-SEBI derived and scintillometer observed evaporative fraction with 0.85 correlation coefficient and 0.86 agreement index. The statistical analysis also endorses the results accuracy and reliability with 0.026 and 0.602, relative root-mean square errors and model efficiency for wheat crop, respectively. The study showed that normalized difference vegetation index and LST are closely related and serve as a proxy for qualitative representation of ET_c.     

Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67 km²) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed “hotspots” of high erosion of up to 16 t ha⁻¹ a⁻¹. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.     

Kinematic precise point positioning at remote marine platforms

Precise kinematic differential positioning using the global positioning system (GPS) at a marine platform usually requires a relatively short distance (e.g. <500 km) to a land-based reference station. As an alternative, precise point positioning (PPP) is normally considered free from this limiting requirement. However, due to the prerequisite of network-based satellite products, PPP at a remote marine platform may still be affected by its distance to the reference network. Hence, this paper investigates this scenario by configuring rings of reference stations with different radii centered on a to-be-positioned marine platform. Particularly, we applied ambiguity resolution at a single station to PPP by estimating uncalibrated phase delays (UPDs). We used three rings of reference stations centered on a vessel, with radii of roughly 900, 2,000 and 3,600 km, to determine satellite clocks and UPDs independently. For comparison, we also performed differential positioning based on a single reference station with baseline lengths of about 400, 1,700 and 2,800 km. We demonstrate that, despite the increasing ring-network radius to a few 1,000 km, the overall change in accuracy of the satellite clocks that are used at the vessel is smaller than 0.02 ns, and the RMS values of differences between the three sets of narrow-lane UPD estimates are around 0.05 cycles only. Moreover, the kinematic positioning accuracy of PPP is affected by the increasing ring-network radius, but can still achieve several centimeters after ambiguity resolution when the vessel is over a few 1,000 km away from the ring network, showing better performance than that of differential positioning. Therefore, we propose that ambiguity-fixed PPP can be used at remote marine platforms that support precise oceanographic and geophysical applications in open oceans.     

Contribution of new AAM data source to δLOD excitation

Data sets of the changes of the length of day (ΔLOD) measured by space geodetic techniques and of the atmospheric angular momentum (AAM) derived from global meteorological data by the National Meteorological Center (NMC) and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) are used to reanalyze and study the excitations of ΔLOD, and to examine and compare the contribution of each AAM series to ΔLOD. The main results are as follows. 1. The AAM reanalyzed with the assimilated global meteorological data by NCEP/NCAR are more accurate and have lower noise than the original AAM derived by NMC. The NCEP/NCAR-based AAM is more consistent with the changes of the length-of-day series. 2. The NCEP reanalysed AAM data may better explain the non-tidal LOD variations on intraseasonal to interannual time scales, especially on the quasi-biennial time scale. The atmosphere cannot, however, explain all LOD variations; other excitation sources are possible. 3. The effects of atmosphere on the estimated values of tides for ΔLOD components up to a month are weak. The preliminary results of the annual and semiannual tides can be estimated after removing the effects of atmosphere from ΔLOD. Received: 27 May 1998 / Accepted: 22 March 1999