Estimation of recent glacial variations in baspa basin using remote sensing technique

The Himalayas has one of the largest concentrations of glaciers outside the Polar Regions. Various reports suggest that significant number of mountain glaciers is shrinking due to climatic variations. Monitoring of these glaciers is important to assess future availability of water resources in the Himalayan region. However, Himalayan glaciers are normally difficult to monitor due to the rugged, mountainous terrain. Therefore, images of Indian Remote Sensing Satellite were used to monitor glaciers in the Baspa basin. Investigations have shown the presence of 30 glaciers in the basin, with areal extent of 167 km2. Out of these, 19 glaciers, with areal extent of 140 km² were selected to estimate retreat. Investigation suggests that almost all glaciers are retreating in the study basin and overall 19% deglaciation has been observed from 1962 to 2001. In general, altitude distribution appears to have significant influence on glacial retreat. Glaciers located around 5000 m altitude range are showing 24% loss as compared to 14% by glaciers located in altitude range higher than 5400 m. In addition, mean altitude of glacier terminus is shifted upward by 88 m, i.e. from 4482 to 4570 m in last 39 years. The glacial volumes were estimated using regression relationship between area and depth. The investigations have suggested that 19.10 km³ of glacial water stored in the 19 glaciers in 1962, has been reduced to 14.71 km³ in 2001, respectively, an overall loss of 23 percent in a period between 1962 and 2001. These investigations suggest that all glaciers in the Baspa Basin are reducing and in long term, such reducing trend can create scarcity of water in the region.     

Towards Real‐Time Geodemographics: Clustering Algorithm Performance for Large Multidimensional Spatial Databases

Geodemographic classifications provide discrete indicators of the social, economic and demographic characteristics of people living within small geographic areas. They have hitherto been regarded as products, which are the final “best” outcome that can be achieved using available data and algorithms. However, reduction in computational cost, increased network bandwidths and increasingly accessible spatial data infrastructures have together created the potential for the creation of classifications in near real time within distributed online environments. Yet paramount to the creation of truly real time geodemographic classifications is the ability for software to process and efficiency cluster large multidimensional spatial databases within a timescale that is consistent with online user interaction. To this end, this article evaluates the computational efficiency of a number of clustering algorithms with a view to creating geodemographic classifications “on the fly” at a range of different geographic scales.     

Hyper Redundancy for Accuracy Enhancement in Automated Close Range Photogrammetry

A generic network design in close range photogrammetry is one where optimal multi-ray intersection geometry is obtained with as few camera stations as practicable. Hyper redundancy is a concept whereby, once the generic network is in place, many additional images are recorded, with the beneficial impact upon object point precision being equivalent to the presence of multiple exposures at each camera position within the generic network. The effective number of images per station within a hyper redundant network might well be in the range of 10 to 20 or more. As is apparent when it is considered that a hyper redundant network may comprise hundreds of images, the concept is only applicable in practice to fully automatic vision metrology systems, where it proves to be a very effective means of enhancing measurement accuracy at the cost of minimal additional work in the image recording phase. This paper briefly reviews the network design and accuracy aspects of hyper redundancy and illustrates the technique by way of the photogrammetric measurement of surface deformation of a radio telescope of 26 m diameter. This project required an object point measurement accuracy of σ  = 0·065 mm, or 1/400 000 of the diameter of the reflector.     

Spatial patterns of sub-tidal seagrasses and their tissue nutrients in the Torres Strait,northern Australia: Implications for management

The distribution and nutritional profiles of sub-tidal seagrasses from the Torres Strait were surveyed and mapped across an area of 31,000 km². Benthic sediment composition, water depth, seagrass species type and nutrients were sampled at 168 points selected in a stratified representative pattern. Eleven species of seagrass were present at 56 (33.3%) of the sample points. Halophila spinulosa, Halophila ovalis, Cymodocea serrulata and Syringodium isoetifolium were the most common species and these were nutrient profiled. Sub-tidal seagrass distribution (and associated seagrass nutrient concentrations) was generally confined to northern-central and south-western regions of the survey area (<longitude 142.60), where mean water depth was relatively shallow (approximately 13 m below MSL) and where sediments were comprised primarily muddy sand to gravelly sand. Seagrass nitrogen and starch content, the most important nutrients for marine herbivores, were significantly correlated with species and with the plant component (above or below ground). For all seagrass species, the above-ground component (shoots and leaves) possessed greater nitrogen concentrations than the below-ground component (roots and rhizomes), which possessed greater starch concentrations. S. isoetifolium had the highest total nitrogen concentrations (1.40±0.05% DW). However, it also had higher fibre concentrations (38.2±0.68% DW) relative to the other four species. H. ovalis possessed the highest starch concentrations (2.76±0.12% DW) and highest digestibility (83.24±0.66% DW) as well as the lowest fibre (27.2±0.66% DW). The high relative abundance (found at 55% of the sites that had seagrass) and nutrient quality characteristics of H. ovalis make it an important source of energy to marine herbivores that forage sub-tidally in the Torres Strait. There were two regions in Torres Strait (north-central and south-western) where sub-tidal seagrass meadows were prevalent and of relatively higher nutritional value. This spatial and nutritional information can be used by local agencies to manage and to protect the ecological, economic and cultural values of the sub-tidal seagrass ecosystems and associated fisheries of the Torres Strait.     

Effectiveness of a market-based instrument for the allocation of water in a tropical river environment

The seasonal nature of Australia’s tropical rivers means that connected groundwater aquifers are an important source of both consumptive and non-consumptive water, particularly during the dry season. The management of these common pool groundwater resources is one of the predominant water issues facing northern Australia. A national program of water reform stipulates the expansion of water trading as a key instrument for water allocation. The effectiveness of new institutional arrangements such as water markets will be determined mostly by how well they coordinate with local environmental requirements, local institutions and local norms. This paper describes a novel application of combined field work, institutional analysis, experimental economics and agent-based modeling to the analysis of a potential water market in the Katherine region of the Northern Territory, Australia. The effectiveness of different versions of the policy instrument is assessed in light of local conditions. Instruments that enable personal relationships and local institutions and norms to play a role in water management are found to be more effective in terms of both farming income and environmental impact.     

Optical water type discrimination and tuning remote sensing band-ratio algorithms: Application to retrieval of chlorophyll and Kd(490) in the Irish and Celtic Seas

This paper assesses the feasibility of applying remote sensing algorithms based on blue/green reflectance ratios to Case 2 waters. Two algorithms from the SeaDAS (NASA) image processing package, OC4v4 for surface chlorophyll concentration, Chl, and K(490) for the attenuation coefficient for downward irradiance at 490 nm, K_d(490), were investigated using an extensive set of observations from the Irish and Celtic Seas. In situ data from a profiling radiometer were used as inputs for the algorithms to avoid uncertainties in atmospheric correction procedures, and direct measurements of Chl and K_d490 and were used for validation purposes. The standard versions of the algorithms performed poorly: OC4v4 generally overestimated Chl (with a very low coefficient of determination), and K(490) progressively underestimated K_d490 for values greater than 0.3 m⁻¹. A two-step procedure for level 2 product generation was therefore devised in which the numerical coefficients of OC4v4 and K(490) were tuned for the two optical water types known to occur most frequently in this region (McKee, D., Cunningham, A., 2006. Identification and characterisation of two optical water types in the Irish Sea from in situ inherent optical properties and seawater constituents. Estuarine, Coastal and Shelf Science 68, 305–316) by statistical regression on a data set of 102 stations from the Irish and Celtic Seas. The water types were distinguished by the magnitude of their normalised water leaving radiance signals at 665 nm, nL_w(665), and appropriate versions of the tuned algorithms applied to each water type. When this procedure was tested on an independent data set of 19 stations from the Bristol Channel, Chl values were recovered with an RMS error of 0.36 mg m⁻³ and K_d(490) values with an RMS error of 0.095 m⁻¹. The identification of water types from water-leaving radiance signals, and the application of band-ratio algorithms tuned for specific water types, may therefore provide a simple means of improving the quality of remote sensing products in optically complex shelf seas.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models: An Empirical Validation of ISWRidge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models： An Empirical Validation of ISW-Ridge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p<0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to check the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height (X1) and potential energy (X2) significantly impact (p<0.0001) the amplitude-based reflected rate; the P-values for the deviance and Pearson are all >0.05 (0.2839, 0.3438, respectively). That is, the goodness-of-fit between ridge height (X1) and potential energy (X2) can further predict parameters under the scenario of the best parsimonious model.Investigation of 6 predictive powers (R2, Max-rescaled R2, Somers'D, Gamma, Tau-a, and c, respectively) indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Long‐term temporal and spatial patterns in bioeroding sponge distribution at the Abrolhos Bank,Brazil, Southwestern Atlantic

Bioeroding sponges belong to the most dominant bioeroders, significantly contributing to the erosion of coral reefs. Some species are tolerant or even benefit from environmental conditions such as ocean warming, acidification, and eutrophication. In consequence, increases in sponge bioerosion have been observed on some coral reefs over the last decades. The Abrolhos Bank is the largest coral reef system in the South Atlantic. It has been affected by sedimentation, eutrophication, overfishing, and climate change, mainly affecting coastal reefs, and at lesser intensity outer ones as well. This study aimed to describe spatial and temporal patterns in bioeroding sponge distribution in carbonate substrates in the Abrolhos Bank. Photo‐quadrats were used to compare bioeroding sponge abundance between two shallow reefs: a coastal, Pedra de Leste (PL), and an outer reef, Parcel dos Abrolhos (PAB). Each individual was delimitated over the substrate by determining the sponge surface through a line connecting the outermost papillae. The study was conducted over 6 years in 2008–2009 and 2013–2016. Four species of bioeroding sponges were identified: Cliona carteri Ridley, 1881, C. delitrix Pang, 1973, C. cf. schmidtii Ridley, 1881, and Siphonodictyon coralliphagum Rützler, 1971. The distribution and abundance of species varied between the inner and outer reefs and across the years, and displayed certain selectivity for the calcareous substrates recorded. Crustose coralline algae (CCA) were the main substrate excavated by the most abundant bioeroding species, C. carteri, and represented 70% of the substrate types occupied by this sponge (CCA, coral overgrown by CCA and plain coral). The highest abundance of bioeroding sponges observed in photo‐quadrats was 21.3 individuals/m² at the outer reefs (PAB) in 2014. The abundances or areal extents of bioeroding sponges were up to 10 times greater on the outer reefs than on the coastal ones, where sedimentation is higher and more strongly influenced by siliciclastic material. Moreover, a higher herbivorous fish biomass has been reported on outer reefs which could also influence the higher abundance of bioeroding sponges in outer reefs. During the study period of 6 years, an increase in bioeroding sponge abundance was observed at the outer reefs (PAB), with the sea surface temperature increase. As CCA have an important role in reefal cementation and carbonate production in the Abrolhos reefs, a bioerosion impact might be expected, in particular, on the outer reefs.