As an intermediate step between raw remote sensing data and digital urban maps, remote sensing data classification has been a challenging and long-standing research problem in the community of remote ...sensing. In this work, an effective classification method is proposed for classifying high-resolution remote sensing data over urban areas. Starting from high resolution multi-spectral images and 3D geometry data, our method proceeds in three main stages: feature extraction, classification, and classified result refinement. First, we extract color, vegetation index and texture features from the multi-spectral image and compute the height, elevation texture and differential morphological profile (DMP) features from the 3D geometry data. Then in the classification stage, multiple random forest (RF) classifiers are trained separately, then combined to form a RF ensemble to estimate each sample’s category probabilities. Finally the probabilities along with the feature importance indicator outputted by RF ensemble are used to construct a fully connected conditional random field (FCCRF) graph model, by which the classification results are refined through mean-field based statistical inference. Experiments on the ISPRS Semantic Labeling Contest dataset show that our proposed 3-stage method achieves 86.9% overall accuracy on the test data.
The kilometer square array (KM2A) of the large high altitude air shower observatory (LHAASO) aims at surveying the northern γ-ray sky at energies above 10 TeV with unprecedented sensitivity. γ-ray ...observations have long been one of the most powerful tools for dark matter searches, as, e.g., high-energy γ rays could be produced by the decays of heavy dark matter particles. In this Letter, we present the first dark matter analysis with LHAASO-KM2A, using the first 340 days of data from 1/2-KM2A and 230 days of data from 3/4-KM2A. Several regions of interest are used to search for a signal and account for the residual cosmic-ray background after γ/hadron separation. We find no excess of dark matter signals, and thus place some of the strongest γ-ray constraints on the lifetime of heavy dark matter particles with mass between 10^{5} and 10^{9} GeV. Our results with LHAASO are robust, and have important implications for dark matter interpretations of the diffuse astrophysical high-energy neutrino emission.
Phase constituents and properties of MCrAlY coating alloys play a crucial role in determining the performance of MCrAlY stand-alone overlay coatings and thermal barrier coating systems. Recent ...advances in computer modeling including access to involved thermodynamic databases make it possible to predict phase stabilities in these alloy systems. This article investigates the phase stabilities of a NiCrAlY coating alloy containing Re both experimentally and thermodynamically. The addition of Re promotes the formation of the Cr-rich α-phase that owns low coefficient of thermal expansion (CTE), and thereby decreases the CTE of the NiCrAlYRe coating alloy. In addition, the martensitic transformation of the B2 β-NiAl phase is investigated. This transformation has an important influence on the microhardness of the β-NiAl phase.
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