On the Evolution of Orbits in a Photo-Gravitational Circular Three-Body Problem: The Inner Problem     

Dobroslavskiy  A. V.  Krasilnikov  P. S. 《Astronomy Letters》2021,47(5):345-356

Astronomy Letters - We consider the spatial restricted circular three-body problem in the nonresonant case. The massless body (satellite) is assumed to have a large sail area and, therefore, the...  相似文献   

Pliocene–Holocene Alkali-Basaltoid Volcanism of the Tsushima Basin of the Sea of Japan: New Geochemical and Geodynamic Data     

Emelyanova  T. A.  Lelikov  E. P.  Pugachev  A. A. 《Oceanology》2020,60(2):236-247

Oceanology - Abstract—The paper contains original data on the rock-forming and rare element compositions in the Pliocene–Holocene alkaline basaltoids of the Tsushima Basin Sea of Japan,...  相似文献   

Effect of microstructure on stress–strain and pore-pressure response of sabarmati sand under the influence of mica     

P. Seethalakshmi 《Geomechanics and Geoengineering》2020,15(2):123-139

ABSTRACT

Micaceous soil is believed to be detrimental for civil engineering constructions due to the effect of high compressibility, low compacted density and low shear strength. Individual mica particle has numerous intact mica flakes foliated over each other making it flexible upon loading and rebound upon unloading due to its low hardness and resilient nature. Hence, micaceous soils with mica content more than 10% are considered undesirable for highway pavements, embankments and railway track constructions. When platy mica particles are sufficiently numerous to interact with spherical sand particles, bridging and ordering phenomena are augmented within the soil mass creating unique sand-mica particle orientation (MS microstructure) unlike sand-sand particle orientation (PS microstructure). The current experimental research was conducted to evaluate the variation in stress–strain, pore pressure and effective stress path response of Sabarmati sand under the influence of mica (sand with 30% mica and pure sand) with MS and PS microstructure respectively. Effect of particle crushing on stress–strain and pore pressure response was also studied on Sabarmati sand with MS and PS microstructure. Distinctive macroscopic response was observed in Sabarmati sand with MS microstructure under the influence of mica as well as mica particle crushing.  相似文献   

Mineral Composition of Manganese Crusts from Belyaevskii Volcano (Sea of Japan)     

Volokhin  Yu. G.  Khanchuk  A. I.  Mikhailik  P. E.  Mikhailik  E. V. 《Doklady Earth Sciences》2020,491(2):214-219

Doklady Earth Sciences - The polygenic mineral composition of Mn crusts from Belyaevskii Volcano of the Central Basin of the Sea of Japan is determined. The crusts are found for the first time to...  相似文献   

On the accuracy of the GPS L2 observable for ionospheric monitoring     

Anthony M. McCaffrey  P. T. Jayachandran  Richard B. Langley  Jean-Marie Sleewaegen 《GPS Solutions》2018,22(1):23

The introduction of the unencrypted global positioning system (GPS) L2 civil (L2C) signal has the potential to improve measurements made with the L2 frequency, an important observable in GPS-based ionospheric research and monitoring. Recent work has shown significant differences between the legacy L2P(Y) and L2C-derived total electron content rate of change index (ROTI). This difference is observed between L2P(Y) and L2C-derived ROTI with certain receiver models and between zero-baseline receiver pairs. We discuss the likely cause for these differences: L1-aided tracking used to track both the L2P(Y) and L2C signals. We also present L2C data that are confirmed to be from tracking independent of L1. Using the ionospheric-free linear combination, we show that the independently tracked carrier phase dynamics are significantly more accurate than the L1-aided observables. This result is confirmed by comparing the behavior of the L2C and L2P(Y) carrier phase observables upon a sudden antenna rotation.  相似文献   

Subsidence in the Kathmandu Basin,before and after the 2015 Mw 7.8 Gorkha Earthquake,Nepal Revealed from Small Baseline Subset-DInSAR Analysis     

Suresh Krishnan P.V.  Jungkyo Jung 《地理信息系统科学与遥感》2018,55(4):604-621

Land subsidence in densely urbanized areas is a global problem that is primarily caused by excessive groundwater withdrawal. The Kathmandu Basin is one such area where subsidence due to groundwater depletion has been a major problem in recent years. Moreover, on 25 April 2015, this basin experienced large crustal movements caused by the Gorkha earthquake (Mw 7.8). Consequently, the effects of earthquake-induced deformation could affect the temporal and spatial nature of anthropogenic subsidence in the basin. However, this effect has not yet been fully studied. In this paper, we applied the SBAS-DInSAR technique to estimate the spatiotemporal displacement of land subsidence in the Kathmandu Basin before and after the Gorkha earthquake, using 16 ALOS-1 Phased Array L-band Synthetic Aperture Radar (PALSAR) images during the pre-seismic period and 26 Sentinel-1 A/B SAR images during the pre- and post-seismic periods. The results showed that the mean subsidence rate in the central part of the basin was about ?8.2 cm/year before the earthquake. The spatial extents of the subsiding areas were well-correlated with the spatial distributions of the compressible clay layers in the basin. We infer from time-series InSAR analysis that subsidence in the Kathmandu basin could be associated with fluvio-lacustrine (clay) deposits and local hydrogeological conditions. However, after the mainshock, the subsidence rate significantly increased to ?15 and ?12 cm/year during early post-seismic (108 days) and post-seismic (2015–2016) period, respectively. Based on a spatial analysis of the subsidence rate map, the entire basin uplifted during the co-seismic period has started to subside and become stable during the early-post-seismic period. This is because of the elastic rebound of co-seismic deformation. However, interestingly, the localized areas show increased subsidence rates during both the early-post- and post-seismic periods. Therefore, we believe that the large co-seismic deformation experienced in this basin might induce the local subsidence to increase in rate, caused by oscillations of the water table level in the clay layer.  相似文献   

GIScience research at the 2018 Esri International User Conference          下载免费PDF全文

John P. Wilson 《Transactions in GIS》2018,22(3):637-639

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Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands,USA   总被引：1，自引：0，他引：1  

Stephen P. Boyte  Bruce K. Wylie  Matthew B. Rigge  Devendra Dahal 《地理信息系统科学与遥感》2018,55(3):376-399

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R² values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.  相似文献   

Comparison of Vegetation Indices from Two Ground Based Sensors     

S. Pradhan  V. K. Sehgal  K. K. Bandyopadhyay  R. N. Sahoo  P. Panigrahi  C. M. Parihar  S. L. Jat 《Journal of the Indian Society of Remote Sensing》2018,46(2):321-326

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.  相似文献   

A Stochastic Approach to Estimate Distribution of Built-Up Area in Regions with Thick Tree Cover     

Bimal Puthuvayi  P. P. Anilkumar 《Journal of the Indian Society of Remote Sensing》2018,46(1):145-155

Buildings and other human-made constructions have been accepted as an indicator of human habitation and are identified as built-up area. Identification of built-up area in a region and its subsequent measurement is a key step in many fields of studies like urban planning, environmental studies, and population demography. Remote sensing techniques utilising medium resolution images (e.g. LISS III, Landsat) are extensively used for the extraction of the built-up area as high-resolution images are expensive, and its processing is difficult. Extraction of built land use from medium resolution images poses a challenge in regions like Western-Ghats, North-East regions of India, and countries in tropical region, due to the thick evergreen tree cover. The spectral signature of individual houses with a small footprint are easily overpowered by the overlapping tree canopy in a medium resolution image when the buildings are not clustered. Kerala is a typical case for this scenario. The research presented here proposes a stochastic-dasymetric process to aid in the built-up area recognition process by taking Kerala as a case study. The method utilises a set of ancillary information to derive a probability surface. The ancillary information used here includes distance from road junctions, distance from road network, population density, built-up space visible in the LISS III image, the population of the region, and the household size. The methodology employs logistic regression and Monte Carlo simulation in two sub processes. The algorithm estimates the built-up area expected in the region and distributes the estimated built-up area among pixels according to the probability estimated from the ancillary information. The output of the algorithm has two components. The first component is an example scenario of the built-up area distribution. The second component is a probability surface, where the value of each pixel denotes the probability of that pixel to have a significant built-up area within it. The algorithm is validated for regions in Kerala and found to be significant. The model correctly predicted the built-up pixel count count over a validation grid of 900 m in 95.2% of the cases. The algorithm is implemented using Python and ArcGIS.  相似文献