Remote Targets Recognition Based on Adaptive Weighting Feature Dictionaries and Joint Sparse Representations

With the improvement in resolution, more and more useful information is contained in the space of remote sensing images, which makes the processing of remote sensing data become more complex, and it is easy to cause the curse of dimensionality and the poor recognition effect. In this paper, a remote target recognition approach named AJRC is proposed, which uses joint feature dictionary for sparse representation based on different feature information for adaptive weighting. Firstly, the features of the images are extracted to calculate the contribution weight of each eigenvalue in sparse representation, and each eigenvalue contribution weight is calculated in sparse representation. Through the adaptive method, the contribution ability of each feature value in sparse representation is strengthened, and new atoms are formed to construct feature dictionary, which makes the dictionary more discriminative. Then, the common features of each category image and the private features of a single image are extracted from the feature vector, and a joint dictionary is formed to represent the test image sparse and recognize the output of the target. Aiming at the problem that the target visual contrast difference, the low resolution and the rotation of the target with different angles, the experiment is carried out by different feature extraction methods. At the same time, we use the PCA method to reduce the feature dictionary in order to avoid dimensionality. Experiments show that compared with the existing SRC method and JSM method, this method has better recognition rate.     

Future wave climate over the west-European shelf seas

In this paper, we investigate changes in the wave climate of the west-European shelf seas under global warming scenarios. In particular, climate change wind fields corresponding to the present (control) time-slice 1961–2000 and the future (scenario) time-slice 2061–2100 are used to drive a wave generation model to produce equivalent control and scenario wave climate. Yearly and seasonal statistics of the scenario wave climates are compared individually to the corresponding control wave climate to identify relative changes of statistical significance between present and future extreme and prevailing wave heights. Using global, regional and linked global–regional wind forcing over a set of nested computational domains, this paper further demonstrates the sensitivity of the results to the resolution and coverage of the forcing. It suggests that the use of combined forcing from linked global and regional climate models of typical resolution and coverage is a good option for the investigation of relative wave changes in the region of interest of this study. Coarse resolution global forcing alone leads to very similar results over regions that are highly exposed to the Atlantic Ocean. In contrast, fine resolution regional forcing alone is shown to be insufficient for exploring wave climate changes over the western European waters because of its limited coverage. Results obtained with the combined global–regional wind forcing showed some consistency between scenarios. In general, it was shown that mean and extreme wave heights will increase in the future only in winter and only in the southwest of UK and west of France, north of about 44–45° N. Otherwise, wave heights are projected to decrease, especially in summer. Nevertheless, this decrease is dominated by local wind waves whilst swell is found to increase. Only in spring do both swell and local wind waves decrease in average height.     

Ambiguity resolved precise point positioning with GPS and BeiDou

This paper focuses on the contribution of the global positioning system (GPS) and BeiDou navigation satellite system (BDS) observations to precise point positioning (PPP) ambiguity resolution (AR). A GPS + BDS fractional cycle bias (FCB) estimation method and a PPP AR model were developed using integrated GPS and BDS observations. For FCB estimation, the GPS + BDS combined PPP float solutions of the globally distributed IGS MGEX were first performed. When integrating GPS observations, the BDS ambiguities can be precisely estimated with less than four tracked BDS satellites. The FCBs of both GPS and BDS satellites can then be estimated from these precise ambiguities. For the GPS + BDS combined AR, one GPS and one BDS IGSO or MEO satellite were first chosen as the reference satellite for GPS and BDS, respectively, to form inner-system single-differenced ambiguities. The single-differenced GPS and BDS ambiguities were then fused by partial ambiguity resolution to increase the possibility of fixing a subset of decorrelated ambiguities with high confidence. To verify the correctness of the FCB estimation and the effectiveness of the GPS + BDS PPP AR, data recorded from about 75 IGS MGEX stations during the period of DOY 123-151 (May 3 to May 31) in 2015 were used for validation. Data were processed with three strategies: BDS-only AR, GPS-only AR and GPS + BDS AR. Numerous experimental results show that the time to first fix (TTFF) is longer than 6 h for the BDS AR in general and that the fixing rate is usually less than 35 % for both static and kinematic PPP. An average TTFF of 21.7 min and 33.6 min together with a fixing rate of 98.6 and 97.0 % in static and kinematic PPP, respectively, can be achieved for GPS-only ambiguity fixing. For the combined GPS + BDS AR, the average TTFF can be shortened to 16.9 min and 24.6 min and the fixing rate can be increased to 99.5 and 99.0 % in static and kinematic PPP, respectively. Results also show that GPS + BDS PPP AR outperforms single-system PPP AR in terms of convergence time and position accuracy.     

Response of the uppermost mantle to Indo-Eurasian collisional tectonics

The rheological law for the power law creep field of peridotite suggested by Chopra and Paterson (1981, 1984) is combined with theoretically modelled thermal and stress perturbations for continent-continent collisions (Bird et al., 1975; Bird, 1978a) to determine the effect of such collisions on the uppermost mantle below the zone of convergence. The model predicts a change from continental to oceanic geotherms during the oceanic subduction phase, followed by a rapid rise in differential stress during the collisional phase.These perturbations, when combined, cause a cyclical change in the steady state flow of the uppermost mantle ending with a re-equilibration of thermal and stress regimes. The thermal re-equilibration proceeds at a much slower rate, with a suggested total re-equilibration period of about 100 m.y. after collision has ceased. The combination of the flow law with the model predicts that the perturbations in the mantle are limited in depth with no changes in mantle behavior below about 100 km.     

Evaluating relationships between soil chemical properties and vegetation cover at different slope aspects in a reclaimed dump

Conducting research about the relationships between soil chemical properties and vegetation coverage at different slope aspects is especially important in reconstructed ecosystems of vulnerable ecological regions. This study was conducted in the first reclaimed dump within the Pingshuo mining area of Shanxi Province, China, to analyze patterns of soil chemical properties (soil organic matter (SOM), soil total nitrogen (STN), soil available phosphorus (SAP) and soil available potassium (SAp) and vegetation coverage (NDVI) and their correlations at different slope aspects. In the reclaimed dump, 26 quadrats were established along four slope aspects (i.e., shady, semi-shady, sunny and semi-sunny slopes). There was no significant difference in SOM or STN among different slope aspects, while SAP differed between shady slopes compared to semi-shady, sunny and semi-sunny slopes; SAP differed significantly between semi-shady and semi-sunny slopes. The NDVI of semi-sunny slopes differed significantly from that of the other three aspects. There was variation in the relationships between NDVI and soil chemical properties, depending on the slope aspects. The logarithm of SOM and NDVI was related linearly on shady and semi-shady slopes, while NDVI was inversely related to the natural logarithm of the logarithm of SOM on sunny and semi-sunny slopes. STN and NDVI had a first-order function relationship on shady and semi-shady slopes, yet a quadratic function relationship on sunny and semi-sunny slopes. The relationships between SAP and NDVI were inverse on all types of slopes. On shady and semi-shady slopes, NDVI had a quadratic relationship with the logarithm of SAp, but it was well fitted by using a cubic function on sunny and semi-sunny slopes. The sensitivity coefficients of soil chemical properties and NDVI were different, and soil chemical properties changed differently depending on changes in NDVI at different slope aspects.     

Process-based forward numerical ecological modeling for carbonate sedimentary basins

Nowadays, numerical modeling is a common tool used in the study of sedimentary basins, since it allows to quantify the processes simulated and to determine interactions among them. One of such programs is SIMSAFADIM-CLASTIC, a 3D forward-model process-based code to simulate the sedimentation in a marine basin at a geological time scale. It models the fluid flow, siliciclastic transport and sedimentation, and carbonate production. In this article, we present the last improvements in the carbonate production model, in particular about the usage of Generalized Lotka-Volterra equations that include logistic growth and interaction among species. Logistic growth is constrained by environmental parameters such as water depth, energy of the medium, and depositional profile. The environmental parameters are converted to factors and combined into one single environmental value to model the evolution of species. The interaction among species is quantified using the community matrix that captures the beneficial or detrimental effects of the presence of each species on the other. A theoretical example of a carbonate ramp is computed to show the interaction among carbonate and siliciclastic sediment, the effect of environmental parameters to the modeled species associations, and the interaction among these species associations. The distribution of the modeled species associations in the theoretical example presented is compared with the carbonate Oligocene-Miocene Asmari Formation in Iran and the Miocene Ragusa Platform in Italy.     

Contribution of a Dense Population of the Brittle Star <Emphasis Type="Italic">Acrocnida brachiata</Emphasis> (Montagu) to the Biogeochemical Fluxes of CO<Subscript>2</Subscript> in a Temperate Coastal Ecosystem

The production of organic matter and calcium carbonate by a dense population of the brittle star Acrocnida brachiata (Echinodermata) was calculated using demographic structure, population density, and relations between the size (disk diameter) and the ash-free dry weight (AFDW) or the calcimass. During a 2-year survey in the Bay of Seine (Eastern English Channel, France), organic production varied from 29 to 50 g_AFDW m⁻² year⁻¹ and CaCO₃ production from 69 to 104 g_CaCO3 m⁻² year⁻¹. Respiration was estimated between 1.7 and 2.0 mol_CO2 m⁻² year⁻¹. Using the molar ratio (ψ) of CO₂ released: CaCO₃ precipitated, this biogenic precipitation of calcium carbonate would result in an additional release between 0.5 and 0.7 mol_CO2 m⁻² year⁻¹ that represented 23% and 26% of total CO₂ fluxes (sum of calcification and respiration). The results of the present study suggest that calcification in temperate shallow environments should be considered as a significant source of CO₂ to seawater and thus a potential source of CO₂ to the atmosphere, emphasizing the important role of the biomineralization (estimated here) and dissolution (endoskeletons of dead individuals) in the carbon budget of temperate coastal ecosystems.     

Atlanta’s urban heat island under extreme heat conditions and potential mitigation strategies

The urban heat island (UHI), together with summertime heat waves, foster’s biophysical hazards such as heat stress, air pollution, and associated public health problems. Mitigation strategies such as increased vegetative cover and higher albedo surface materials have been proposed. Atlanta, Georgia, is often affected by extreme heat, and has recently been investigated to better understand its heat island and related weather modifications. The objectives of this research were to (1) characterize temporal variations in the magnitude of UHI around Metro Atlanta area, (2) identify climatological attributes of the UHI under extremely high temperature conditions during Atlanta’s summer (June, July, and August) period, and (3) conduct theoretical numerical simulations to quantify the first-order effects of proposed mitigation strategies. Over the period 1984–2007, the climatological mean UHI magnitude for Atlanta-Athens and Athens-Monticello was 1.31 and 1.71°C, respectively. There were statistically significant minimum temperature trends of 0.70°C per decade at Athens and −1.79°C per decade at Monticello while Atlanta’s minimum temperature remained unchanged. The largest (smallest) UHI magnitudes were in spring (summer) and may be coupled to cloud-radiative cycles. Heat waves in Atlanta occurred during 50% of the years spanning 1984–2007 and were exclusively summertime phenomena. The mean number of heat wave events in Atlanta during a given heat wave year was 1.83. On average, Atlanta heat waves lasted 14.18 days, although there was quite a bit of variability (standard deviation of 9.89). The mean maximum temperature during Atlanta’s heat waves was 35.85°C. The Atlanta-Athens UHI was not statistically larger during a heat wave although the Atlanta-Monticello UHI was. Model simulations captured daytime and nocturnal UHIs under heat wave conditions. Sensitivity results suggested that a 100% increase in Atlanta’s surface vegetation or a tripling of its albedo effectively reduced UHI surface temperature. However, from a mitigation and technological standpoint, there is low feasibility of tripling albedo in the foreseeable future. Increased vegetation seems to be a more likely choice for mitigating surface temperature.     

Climate change influences on pollinator,forest, and farm interactions across a climate gradient

Improved cookstoves have been identified in Mexico as a key opportunity to advance sustainable local development priorities in disadvantaged regions while mitigating climate change. This paper reviews the Patsari Cookstove Project initiated in 2003 by an NGO, Interdisciplinary Group on Appropriate Rural Technology (GIRA). The project applied an interdisciplinary and participative user-centered approach to disseminate improved cookstoves in rural Mexico, with a special focus on indigenous and poor rural communities. To date, GIRA and the Patsari Network have disseminated thousands of stoves using a “training to trainers” model. Benefits from the project include tangible improvements in users’ health, as well as savings in time and money expended on fuelwood procurement and use. The project has also documented substantive environmental benefits from significant mitigation of greenhouse gas (GHG) emissions associated with traditional open fires. To sustain scaling up efforts over the long-term, two networks have been created: The Patsari Network, which includes several organizations promoting Patsari stoves for household users, and the Tsiri Network, which supports local food security and the empowerment of indigenous women through the promotion of institutional cookstoves. Through appropriately designed and implemented local interventions, the project demonstrates that the goals of advancing sustainable local development in rural areas and climate change mitigation may not be contradictory, and may in fact reinforce one another.