Land-cover classification of China: integrated analysis of AVHRR imagery and geophysical data

Over last two decades, numerous studies have used remotely sensed data from the Advanced Very High Resolution Radiometer (AVHRR) sensors to map land use and land cover at large spatial scales, but achieved only limited success. In this paper, we employed an approach that combines both AVHRR images and geophysical datasets (e.g. climate, elevation). Three geophysical datasets are used in this study: annual mean temperature, annual precipitation, and elevation. We first divide China into nine bio-climatic regions, using the long-term mean climate data. For each of nine regions, the three geophysical data layers are stacked together with AVHRR data and AVHRR-derived vegetation index (Normalized Difference Vegetation Index) data, and the resultant multi-source datasets were then analysed to generate land-cover maps for individual regions, using supervised classification algorithms. The nine land-cover maps for individual regions were assembled together for China. The existing land-cover dataset derived from Landsat Thematic Mapper (TM) images was used to assess the accuracy of the classification that is based on AVHRR and geophysical data. Accuracy of individual regions varies from 73% to 89%, with an overall accuracy of 81% for China. The results showed that the methodology used in this study is, in general, feasible for large-scale land-cover mapping in China.

Semisupervised Dimensionality Reduction and Classification Through Virtual Label Regression

Semisupervised dimensionality reduction has been attracting much attention as it not only utilizes both labeled and unlabeled data simultaneously, but also works well in the situation of out-of-sample. This paper proposes an effective approach of semisupervised dimensionality reduction through label propagation and label regression. Different from previous efforts, the new approach propagates the label information from labeled to unlabeled data with a well-designed mechanism of random walks, in which outliers are effectively detected and the obtained virtual labels of unlabeled data can be well encoded in a weighted regression model. These virtual labels are thereafter regressed with a linear model to calculate the projection matrix for dimensionality reduction. By this means, when the manifold or the clustering assumption of data is satisfied, the labels of labeled data can be correctly propagated to the unlabeled data; and thus, the proposed approach utilizes the labeled and the unlabeled data more effectively than previous work. Experimental results are carried out upon several databases, and the advantage of the new approach is well demonstrated.

Discriminative Orthogonal Neighborhood-Preserving Projections for Classification

Orthogonal neighborhood-preserving projection (ONPP) is a recently developed orthogonal linear algorithm for overcoming the out-of-sample problem existing in the well-known manifold learning algorithm, i.e., locally linear embedding. It has been shown that ONPP is a strong analyzer of high-dimensional data. However, when applied to classification problems in a supervised setting, ONPP only focuses on the intraclass geometrical information while ignores the interaction of samples from different classes. To enhance the performance of ONPP in classification, a new algorithm termed discriminative ONPP (DONPP) is proposed in this paper. DONPP 1) takes into account both intraclass and interclass geometries; 2) considers the neighborhood information of interclass relationships; and 3) follows the orthogonality property of ONPP. Furthermore, DONPP is extended to the semisupervised case, i.e., semisupervised DONPP (SDONPP). This uses unlabeled samples to improve the classification accuracy of the original DONPP. Empirical studies demonstrate the effectiveness of both DONPP and SDONPP.

Biologically Inspired Features for Scene Classification in Video Surveillance

Inspired by human visual cognition mechanism, this paper first presents a scene classification method based on an improved standard model feature. Compared with state-of-the-art efforts in scene classification, the newly proposed method is more robust, more selective, and of lower complexity. These advantages are demonstrated by two sets of experiments on both our own database and standard public ones. Furthermore, occlusion and disorder problems in scene classification in video surveillance are also first studied in this paper.

Order-Order Transition of C -> sdG -> sL -> S in ABC Triblock Copolymer Thin Film Induced by Solvent Vapor

The morphology transition of polystyrene-block-poly(butadiene)-block-poly(2-vinylpyridine) (SBV) triblock thin film induced in benzene vapor showing weak selectivity for PS is investigated. The order-order transitions (OOT) in the sequence of core-shell cylinders (C), sphere in 'diblock gyroid' (sdG), sphere in lamella (sL) and sphere (S) are observed. The projection along (111) direction in Gyroid phase (sdG(111)) is found to epitaxially grow from C(001) in the film.

Bump-Surface Multicompartment Micelles from a Linear ABC Triblock Copolymer: A Combination Study by Experiment and Computer Simulation

Novel bump-surface multicompartment micelles formed by a linear amphiphilic ABC triblock copolymer via self-assembly in selective solvent were successfully observed both in simulation and experiment. The results revealed that the block A forms the most inner core, and the blocks B and C form the inner and outer layers, respectively, and the bumps were formed by block A and more likely to be born on curving surfaces. Moreover, the micelle shape could be controlled by changing the solvent selectivity of the blocks A and B. Spherical, cylindrical, and discoidal micelles with bumpy surfaces were obtained both in experiment and simulation.

Simulation Study of Aggregate Morphologies Formed by ABC Linear Triblock Copolymers in a Selective Solvent Through the Self-Consistent Field Theory

The effect of the hydrophobic properties of blocks B and C on the aggregate morphologies formed by ABC linear triblock copolymers in selective solvent was studied through the self-consistent field theory. Five typical micelles, such as core-shell-corona, hamburger-like, segmented-wormlike, were obtained by changing the hydrophobic properties of blocks B and C. The simulation results indicate that the shape and size of micelle are basically controlled by the hydrophobic degree of the middle block B, whereas the type of micelle is mainly determined by the hydrophobic degree of the end block C.

Formation of Two Kinds of Hexagonally Arranged Structures in ABC Triblock Copolymer Thin Films Induced by a Strongly Selective Solvent Vapor

An order-order transition (OOT) in the sequence of a hexagonally arranged core-shell cylinder to a double-hexagonally arranged dot in polystyrene-block-poly(butadiene)-block-poly(2-vinylpyridine) (SBV) triblock copolymer thin films is reported to be induced upon exposure to a solvent vapor that: is strongly selective for the two end blocks. These two kinds of hexagonally arranged structures could form when the film thickness is 44, 3.23, and 223 nm. When the film thickness is decreased to 13 nm, the ordered structure is absent. The sizes of the cylinder structures formed with the same annealing time in films of different thickness are compared to address the effects of film thickness on the phase structure. The mechanism is analyzed from the total surface area of the blocks and the effective interaction parameter in the solvent vapor.

Tethered diblock copolymer chains on platelets prepared by semicrystalline ABC triblock copolymers in toluene with trace amounts of water

Lamellar platelets of triblock copolymers grown in dilute toluene solution with trace amounts of water can be used as templates for tethered diblock copolymer chain preparation and analysis. Polystyrene-bpoly(2-vinylpyridine)-b-poly(ethylene oxide) (PS-b-P2VP-b-PEO) with two different block fractions were used as model templates to generate tethered P2VP-b-PS chains on the platelet basal surfaces. In toluene solution the aggregation states of PS-b-P2VP-b-PEO were sensitive to the water content in the solution. For toluene with trace amount of water, spherical micelles were formed in the early stage and large square platelets would gradually grow from these spherical micelles. The hydrogen bonding between water and EO units was responsible for the formation of micelles and subsequent square platelets in the solution. Tethered P2VP-b-PS chains on basal surface of PEO platelets could be regarded as diblock copolymer brushes and the density (or: 0.086-0.36) and height (d: 3.5-14.3 nm) of these tethered chains could be easily modulated by changing the crystallization condition and/ or the molecular weight of each block. The tethered P2VP-b-PS chains were responsive to different solvent vapor.

Formation of ordered microphase-separated pattern during spin coating of ABC triblock copolymer

In this paper, the authors have systematically studied the microphase separation and crystallization during spin coating of an ABC triblock copolymer, polystyrene-b-poly(2-vinylpyridine)-b-poly(ethylene oxide) (PS-b-P2VP-b-PEO). The microphase separation of PS-b-P2VP-b-PEO and the crystallization of PEO blocks can be modulated by the types of the solvent and the substrate, the spinning speed, and the copolymer concentration. Ordered microphase-separated pattern, where PEO and P2VP blocks adsorbed to the substrate and PS blocks protrusions formed hexagonal dots above the P2VP domains, can only be obtained when PS-b-P2VP-b-PEO is dissolved in N,N-dimethylformamide and the films are spin coated onto the polar substrate, silicon wafers or mica. The mechanism of the formation of regular pattern by microphase separation is found to be mainly related to the inducement of the substrate (middle block P2VP wetting the polar substrate), the quick vanishment of the solvent during the early stage of the spin coating, and the slow evaporation of the remaining solvent during the subsequent stage. On the other hand, the probability of the crystallization of PEO blocks during spin coating decreases with the reduced film thickness. When the film thickness reaches a certain value (3.0 nm), the extensive crystallization of PEO is effectively prohibited and ordered microphase-separated pattern over large areas can be routinely prepared.

Self-assembly of polypeptide-containing ABC-type triblock copolymers in aqueous solution and its pH dependence

Self-assembling of novel biodegradable ABC-type triblock copolymer poly(ethylene glycol)-poly(L-lactide)-poly(L-glutamic acid) (PEG-PLLA-PLGA) is studied. In aqueous media, it self-assembles into a spherical micelle with the hydrophobic PLLA segment in the core and the two hydrophilic segments PEG and PLGA in the shell. With the lengths of PEG and PLLA blocks fixed, the diameter of the micelles depends on the length of the PLGA block and on the volume ratio of H2O/dimethylformamide (DMF) in the media. When the PLGA block is long enough, morphology of the self-assembly is pH-dependent. It assembles into the spherical micelle in aqueous media at pH 4.5 and into the connected rod at or below pH 3.2. The critical micelle concentration (cmc) of the copolymer changes accordingly with decreasing solution pH. Both aggregation states can convert to each other at the proper pH value. This reversibility is ascribed to the dissociation and neutralization of the COOH groups in the LGA residues. When the PLGA block is short compared to the PEG or PLLA block, it assembles only into the spherical micelle at various pH values.

Comparing the morphology and phase diagram of H-shaped ABC block copolymers and linear ABC block copolymers

By using a combinatorial screening method based on the self-consistent field theory (SCFT) for polymers, we have investigated the morphology of H-shaped ABC block copolymers (A(2)BC(2)) and compared them with those of the linear ABC block copolymers. By changing the ratios of the volume fractions of two A arms and two C arms, one can obtain block copolymers with different architectures ranging from linear block copolymer to H-shaped block copolymer. By systematically varying the volume fractions of block A, B, and C, the triangle phase diagrams of the H-shaped ABC block copolymer with equal interactions among the three species are constructed. In this study, we find four different morphologies ( lamellar phase ( LAM), hexagonal lattice phase ( HEX), core-shell hexagonal lattice phase (CSH), and two interpenetrating tetragonal lattice (TET2)). Furthermore, the order-order transitions driven by architectural change are discussed.

Synthesis and characterization of ABC ternary segregated H-shaped copolymers

The synthesis of a novel ABC ternary segregated H-shaped copolymer is described, of which a central poly(ethylene glycol) (PEG) chain is terminated on both sides by polystyrene (PS) and poly(tert-butylacrylate) (PtBA) chains. The synthetic procedure involves functionalization of PEG by 2-bromosuccinic anhydride followed by esterification of 1,6-hexanediol, which gives its ends the bifunctional nature that allows sequential growth of two PS, then two PtBA arms via atom transfer radical polymerization (ATRP). The resulting segregated H-shaped copolymers were characterization by NMR spectroscopy and gel permeation chromatography (GPC). All these copolymers were affirmed to have well-defined structures and narrow molecular weight distributions.

A Monte Carlo simulation for the micellization of ABC 3-miktoarm star terpolymers in a selective solvent

We have used Monte Carlo simulation to study the micellization of ABC 3-miktoarm star terpolymers in a selective solvent (good to A segment, bad to B and C segments). The simulation results reveal that the self-assembled morphology is determined by the block length, molecular architecture, terpolymer concentration and insolubility of insoluble block in the solvent. In dilute solution, symmetric terpolymers (N-B = N-C = 30) tend to aggregate into a novel wormlike pearl-necklace structure linked by an alternating arrangement of B and C spheres, whereas the asymmetric terpolymers (NB = 10, NC = 50) are likely to aggregate into spherical or cylindrical micelles (formed by C blocks) connected with some small B spheres, when the concentration of terpolymer is relatively low (chain number is 100). However, when the concentration of terpolymer is relatively high (chain number is 250), the symmetric terpolymers tend to aggregate into a netlike structure linked by an alternation of B and C spheres, whereas the asymmetric terpolymers are likely to aggregate into wormlike micelles (formed by C blocks) connected with some of small spheres (formed by B blocks). Moreover, when the insolubility of insoluble block in the solvent is weak, the insoluble blocks aggregate into some incompact micelles.

Classification of valence changes of trivalent rare earth ions in alkaline earth borates using artificial neural networks

The investigations of classification on the valence changes from RE3+ to RE2+ (RE = Eu, Sm, Yb, Tm) in host compounds of alkaline earth berate were performed using artificial neural networks (ANNs). For comparison, the common methods of pattern recognition, such as SIMCA, KNN, Fisher discriminant analysis and stepwise discriminant analysis were adopted. A learning set consisting of 24 host compounds and a test set consisting of 12 host compounds were characterized by eight crystal structure parameters. These parameters were reduced from 8 to 4 by leaps and bounds algorithm. The recognition rates from 87.5 to 95.8% and prediction capabilities from 75.0 to 91.7% were obtained. The results provided by ANN method were better than that achieved by the other four methods. (C) 1999 Elsevier Science B.V. All rights reserved.