Abstract:Urban tree species provide various essential ecosystem services in cities， such as mediating urban temperature， isolating noise， fixing carbon， and mitigating the urban heat island impact. The quality of these services is influenced by species diversity， tree growth status， and the distribution and composition of trees. Traditionally， data about urban trees has been gathered through field data collection and manual interpretation of remote sensing images. In this study， we evaluate the capacity of using Multispectral Airborne Laser Scanning （ALS） data to classify 24 common urban roadside tree species in Espoo， Finland. We utilized tree crown structure information， intensity features， and spectral information for classification. 8 different machine learning algorithms were used in our study and Extra trees （ET） performed best with an overall accuracy of 71.7% using multispectral LiDAR data， highlighting that combining structural and spectral information in a single frame could enhance classification accuracy. In the future， we will focus on identifying the most important features in species classification and finding algorithms with higher efficiency and accuracy.

Abstract:The water in lunar materials can promote the evolution of lunar geology and environment and provide the necessary conditions for the utilization of lunar resource. Owing to the low resolution of lunar remote sensing methods， it is difficult to obtain direct evidence of water / ice or determine its form of occurrence. Laser Raman spectroscopy can obtain fingerprint information of minerals and water bodies without the need for illumination， sample pretreatment， and non-destructive， providing direct and favorable information regarding the type， distribution range， and content of lunar materials. In this study， Raman spectroscopy was used to detect the water-containing characteristics of typical lunar rocks/minerals and forms such as adsorbed water， ice， crystalline water， and hydroxyl-structured water， and quantitatively analyze the water content. First， a 532 nm laser micro-Raman spectroscopy was used to identify and analyze the water-containing signals of typical lunar minerals and various forms of water in lunar soil simulants. Second， the detection limits of adsorbed water， crystalline water， and hydroxyl-structured water in lunar soil simulants were examined and analyzed， along with the patterns between their content and signal intensity. Finaly， linear regression （LR）， ridge regression （RR）， and partial least squares regression （PLSR） were employed for quantitatively analyze of the contents of three forms of water in the lunar soil simulants. The results show that （1） the characteristic spectral peaks of the four forms of water in the lunar soil simulants can be clearly identified. The peak distribution regions of the lunar soil simulants components and water bodies are located at 100-1700 cm^-1 and 2600-3900 cm^-1， respectively. The characteristic spectral peaks of water are manifested as a combination of broad envelope peaks of hydrogen-bonded OH and sharp peaks of non-hydrogen-bonded OH stretching vibrations in varying proportions. （2） Detection limits of adsorbed water， crystalline water （MgSO₄·7H₂O）， and hydroxyl water （Al₂Si₂O₅（OH）₄） in the lunar soil simulants are 1.3 wt%， 0.8 wt%， and 0.3 wt%， respectively. （3） A linear relationship exists between the intensity of water-containing peaks and the water content in the lunar soil simulants， with root mean square errors of 1.75 wt%， 1.16 wt%， and 1.19 wt% obtained through LR， RR， and PLSR.

Abstract:The sensitivity of the detector is the core technical indicator of the infrared detector. Short-wave infrared detector has low dark current and the sensitivity will be limited by the inherent read-out circuit noise of the detection system. Therefore， it is an effective way to further enhance the sensitivity by introducing internal gain into the detector. Heterogeneous phototransistor takes advantages of high gain， low operating bias， and low excess noise， which provides novel approach for high-sensitive detection. This paper mainly focuses on the simulation design of InGaAs/GaAsSb type-II superlattice short-wave infrared phototransistor， and studies the dependence of the device size on the optoelectronic characteristics. The results show that a higher gain， a lower dark current， and a faster response can be achieved by a smaller base size. Based on the optimization design of size structure， a sensitivity with a noise equivalent photon lower than 10 can be achieved， which provides a new technical approach to achieve high-sensitive heterogeneous phototransistor detector.

Abstract:Space-borne infrared remote sensing images have crucial application value in the fields of environmental monitoring and military reconnaissance. Nonetheless， due to limitations in technologies， atmospheric disturbances， and sensor noise， these images suffer from insufficient resolution and blurred texture details， severely restricting the accuracy of subsequent analysis and processing. To address these issues， a new super-resolution generative adversarial network model is proposed. This model integrates dense connections with the Swin Transformer architecture to achieve effective cross-layer feature transmission and contextual information utilization while enhancing the model"s global feature extraction capabilities. Furthermore， we improve the traditional residual connections with multi-scale channel attention-based feature fusion， allowing the network to more flexibly integrate multi-scale features， thereby enhancing the quality and efficiency of feature fusion. A combined loss function is constructed to comprehensively optimize the performance of the generator. Comparative tests on different datasets demonstrate significant improvements with the proposed algorithm. Additionally， the super-resolved images exhibit higher performance in downstream tasks such as object detection， confirming the effectiveness and application potential of the algorithm in space-borne infrared remote sensing image super-resolution.

Abstract:The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible image. To meet these requirements, an autoencoder-based method for infrared and visible image fusion is proposed. The encoder consists of a base encoder and a detail encoder, designed according to the optimization objective, to extract low-frequency and high-frequency information from the image. This extraction may lead to some information not being captured, so a compensation encoder is proposed to supplement the missing information. Multi-scale decomposition is also employed to extract image features more comprehensively. The decoder combines low-frequency, high-frequency and supplementary information to obtain multi-scale features. Subsequently, the attention strategy and Fusion module are introduced to perform multi-scale fusion for image reconstruction. Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.

Abstract:When extracting coastal zone tidal flats using remote sensing transient images, the influence of tides greatly limits the accuracy of tidal flat spatial distribution extraction. With the purpose of weakening the influence of tides, a method of extracting coastal zone tidal flats by combining time-series Sentinel-2 images and tidal flat index is proposed. First, based on the Sentinel-2 time-series image data, we use the quantize synthesis method to generate high- and low-tide images, and then analyze the spectral reluctance characteristics of different land classes on the high- and low-tide images. A NIR-band tidal flat extraction index that excludes the interference of the tidal transient is constructed. Secondly, the image spectral information and the tidal flat extraction index are input into a machine learning algorithm to realize fast and efficient extraction of the tidal flat. In addition, the study discusses the separability of the tidal flats index and the generalizability of the methodology. The results show that the tidal flat's extraction index constructed in this research had a good separability for tidal flats, the overall accuracy of tidal flats extraction was 93.02%, the Kappa coefficient was 0.86, and the proposed method has good applicability to remote sensing images containing near-infrared bands. This method can realize automatic and rapid tidal flat extraction, and provide data support for the sustainable management and protection of coastal zone resources.

Abstract:In this paper， a linear optimization method（LOM） for the design of terahertz circuits is presented， aimed at enhancing simulation efficacy and reducing the time of the circuit design workflow. This method enables the rapid determination of optimal embedding impedance for diodes across a specific bandwidth to achieve maximum efficiency through harmonic balance simulations. By optimizing the linear matching circuit with the optimal embedding impedance， the method effectively segregates the simulation of the linear segments from the nonlinear segments in the frequency multiplier circuit， substantially increasing the speed of simulations. The design of on-chip linear matching circuits adopts a modular circuit design strategy， incorporating fixed load resistors to simplify the matching challenge. Utilizing this approach， a 340GHz frequency doubler was developed and measured. The results demonstrate that， across a bandwidth of 330GHz to 342GHz， the efficiency of the doubler remains above 10%， with an input power ranging from 98mW to 141mW and an output power exceeding 13mW. Notably， at an input power of 141mW， a peak output power of 21.8mW was achieved at 334GHz， corresponding to an efficiency of 15.8%.

Abstract:The preparation of quantum dot thin films and the accurate determination of optical constants are particularly important in the development and application of their optoelectronic fields. At present， the optical constants of MoTe₂ single-crystal films prepared by mechanical exfoliation and chemical vapor deposition are relatively mature. However， the optical constants of 2H-MoTe₂ quantum dot films are rarely reported. 2H-MoTe₂ quantum dots were prepared by ultrasonic assisted liquid phase exfoliation， and two sizes of 2H-MoTe₂ quantum dots were prepared by changing the type of solvent and ultrasonic order. The optical constants such as refractive index， extinction coefficient and dielectric constant of quantum dot films of two sizes were studied by B-spline model and Tauc-Lorentz model using ellipsometry. The results show that the two sizes of 2H-MoTe₂ quantum dots have similar refractive index， extinction coefficient and a wider spectral absorption in the visible to near infrared band. And compared with MoTe₂ bulk material， it has a lower dielectric constant.

Abstract:The energy received in the mid-infrared (MIR) band at the sensor's aperture includes both reflected solar energy and the emitted energy from Earth's surface. Typically, the reflected solar energy in this band is weak; however, under certain conditions, such as in sun glint regions over the sea surface, the reflected solar energy detected by the MIR channel can be substantial. Currently, the application of sun glints physical models in the MIR band is not well-understood. This study investigates the accuracy of applying different visible light and shortwave infrared sun glint models to the MIR band. The paper selects three models: Breon-Henriot, Ebuchi-Kizu, and Wu, and evaluates the sensitivity of each sun glint model. Subsequently, using four selected MODIS sun glint images as data sources, and combining them with ERA5 reanalysis data matched to satellite data for atmospheric parameter calculations, the solar radiation intensity reflected by the sea surface is computed using the three models. The accuracy of each model is then further validated with an MIR radiation transfer model. The results show that the Breon-Henriot model generally performs best in terms of correlation coefficient and root-mean-square error compared to MODIS measurements. These findings not only extend the application range of sun glint models in the MIR band but also enhance the MIR forward modeling system, providing new theoretical support for MIR radiation transfer and improving the effectiveness and accuracy of MIR remote sensing products in climate change monitoring and sea surface temperature dynamic analysis.

Abstract:The laser altimeter onboard China's Gaofen series satellites is primarily used to provide elevation control points for imagery. During satellite operations, environmental variations can induce laser pointing offsets, which in turn increase the positioning errors of the footprints, thereby directly reducing the elevation accuracy of the control points. This issue is particularly pronounced in complex mountainous terrains. To enhance the reliability of laser altimeter observations from satellites in such regions, this paper proposed a new laser footprint positioning method based on waveform frequency domain matching. This method utilizes high-precision terrain data for waveform simulation and determines the position of the laser footprint by calculating the correlation between the simulated waveform and the waveform received by China's Gaofen series satellite in the frequency domain. Additionally, systematic deviations in laser pointing are derived from the joint computational results of multi-footprint frequency domain matching. Experiments were conducted using in three regions: central Montana, western Wyoming, and eastern Utah in the United States. The results indicate that the standard deviations of footprint planar offset distances, planar true north pinch angles, and equivalent laser pointing deviation angles obtained with this method are all superior to those achieved with the time-domain waveform matching method. The findings underscore the advantages of frequency-domain waveform matching in achieving high-precision footprint localization, thereby providing a robust foundation for enhancing the utility of satellite laser altimeter observations in challenging environments and facilitating the correction of laser altimeter pointing errors.