To address the significant measurement errors caused by vehicle vibration in traditional reference-beam laser Doppler velocimeters (LDV), this paper proposes and investigates a vehicle-mounted laser Doppler velocimeter with asymmetric oblique incidence. The system emits two laser beams toward the ground at different incident angles, thereby forming a set of asymmetric oblique-incidence measurement beams. By constructing a system of Doppler frequency equations, changes in the incident angles can be determined, effectively suppressing errors induced by vehicle vibration. Experimental results show that the measurement system features a simple structure, high reliability, and good adaptability to vehicle-mounted environments, with a velocity measurement accuracy better than 0.32% of the measured value. These advantages make it highly suitable for meeting the demands of high-precision vehicle-mounted integrated navigation systems.

Module partition is a fundamental task in the modular design of complex products. With the increasing adoption of graph-theoretic representations, community detection has become a common strategy for deriving module structures from product networks. However, the intricate coupling among complex product components and the existence of bus components conflicting with the partitioning logic often lead to unreasonable partitioning schemes. To mitigate this issue, an iterative module partition method is proposed by integrating structural entropy with the Louvain algorithm, where modularity is used as the optimization objective. Initial modules are first obtained via the Louvain algorithm. Bus components are then characterized quantitatively by evaluating the changes in modularity and structural entropy when a component is separated from its original community and treated as an independent module. Through iterative identification and adjustment, bus components unsuitable for internal modules can be detected, and the resulting partition scheme derived from community detection becomes more rational. A motorcycle engine case study is used to demonstrate the effectiveness and feasibility of the proposed method.

The balance between carbon stocks (CS) and carbon emissions (CE) is crucial for optimizing regional ecosystem management and enhancing ecosystem carbon sink capacity. Taking the main urban area of Chongqing (MUAC) as the study area, this study integrated the InVEST model, carbon emission coefficient method, CS-CE ratio (CSER), hotspot analysis, and spatial flow field strength model to investigate the spatial mismatch characteristics of CS and CE and their flows patterns from 2000 to 2020. The results showed the following: (1) The average CS declined steadily from 328.63 t to 313.76 t, with high-CS areas coinciding with high-altitude regions. The CE exhibited an inverted U-shaped trend over time, with an overall upward tendency. And high-CE areas were mainly concentrated in the midwestern and northern parts of MUAC. (2) The CSER exhibited a decreasing trend, with the deficit area expanding by 8.3

Traditionally, the transmittance analysis of a beam passing through an optical chopper is based on the assumption of a top-hat beam. However, most practical laser sources emit Gaussian beams. This paper establishes a complete theoretical model for the transmittance of a Gaussian beam passing through a multi-circular-aperture chopper, in which the luminous flux contributions of all apertures are considered simultaneously. An analytical transmittance expression is derived by using the Marcum Q function, which avoids cumbersome two-dimensional numerical integration and improves computational efficiency significantly. Two dimensionless characteristic parameters dominating the transmittance behavior are identified: c1 = w/R (the ratio of the beam radius to the offset distance between the beam center and the chopper rotation center) and c2 = w/ra (the ratio of the beam radius to the aperture radius). Based on the proposed model, the influences of the aperture number N and dimensionless parameters c1 and c2 on the period, waveform shape, and modulation depth of the transmittance curve are simulated and analyzed systematically. The results show that the modulation frequency increases linearly with N, while c1 and c2 dominate the waveform smoothness and spectral distribution. This research provides accurate theoretical support for the structural design, parameter optimization, and engineering application of circular-aperture choppers, and has important reference value for improving the modulation performance of optical systems.

Regarding the contradiction between high resolution and complex structure in traditional laser self-mixing measurement systems, the co-axial dual-wavelength solid-state laser self-mixing technology was proposed and studied. LD pumped the Nd:YVO4 crystal and doubled the frequency to generate two wavelengths laser of 1064nm and 532nm, and a co-axial dual-wavelength laser self-mixing measurement system was constructed. A 90° phase difference of the two wavelengths was produced by adjusting the angle of incidence of the parallel glass plate. As a result, a set of orthogonal signals was built to distinguish the direction of the displacement for the target. The results of experiment show that the measuring system can adapt to different vibration waveform and the frequency measurement upper limit can be reached by 7kHz. With a peak-to-peak average error below 10 nm, a minimum reconstructable displacement of less than 10 nm, and a short-term resolution better than 2 nm, the system demonstrates high precision in displacement measurement.

Under the background of "double carbon，" it is of great significance to study the land use change in Shandong Province to maintain the security of the ecosystem and build a sustainable ecological network. Based on the analysis of land use data in 2010 and 2020， this study coupled the SD-PLUS model to simulate the land use evolution in 2030 and 2060 under three scenarios in CMIP6： low emission sustainable development scenario （SSP119）， medium emission baseline scenario （SSP245）， and high emission extreme scenario （SSP585）， and we then extracted the land use pattern. The InVEST model was used to evaluate the habitat quality， and the MSPA model and MCR model were further combined to construct the ecosystem network of Shandong Province. The results show that： ① From 2010 to 2020 （historical period）， land use was dominated by cultivated land but continued to decrease， with the dual-core expansion of construction land， the slight growth of forest land and water area， and the continuous reduction of grassland and unused land. From 2020 to 2060 （the future period）， under the SSP119 scenario， the cultivated land area will decrease to 64.01 %， the construction land will increase to 25.37 %， the forest land and water area will increase， and the grassland and unused land area will decrease. Under the SSP585 scenario， the decrease of cultivated land was the largest， and the proportion of construction land was the highest in the three scenarios. ② Changes in habitat quality： In the historical period， the pattern of "high in the east and low in the west" was presented， and the contribution of cultivated land was > 60 %. Under the SSP119 scenario in the future period， the high-value areas of mountainous and coastal areas in the central and western regions will be optimized， and the contribution of forest habitat will be the most obvious. Under the SSP245 scenario， the habitat in southwest Shandong Province and the Yellow River Delta was degraded and partially fragmented. Under the SSP585 scenario， the habitat quality in the plain area was degraded in a large area， and the contribution of various habitats decreased. ③ Ecological network construction： From 2010 to 2020， the ecological source area developed into the "East-Central-South" three poles， and the ecological network was gradually optimized. In the future， under the SSP119 scenario， the mountainous areas of central Shandong Province and Jiaodong Peninsula will form a dense network， and the corridors will be interwoven and connected. Under the SSP245 scenario， a buffer zone appears in the northwestern Shandong Plain， and the secondary corridor expands， but the Jiaoji Economic Belt is still dominated by the primary corridor. In the context of SSP585， the ecological source is fragmented， and the first-level corridor along Jiaoji is the core， and there are only sparse low-level corridors in southwestern Shandong Province.

Coastal ecosystem services (ESs) exhibit obvious sea-land gradient characteristics. However, their specific patterns and evolutionary mechanisms remain unclear. Therefore, we developed an analytical framework integrating this gradient perspective. In the case of the Yellow River Delta, we systematically revealed the sea-land gradient evolution pattern of ESs from multiple dimensions, including spatiotemporal trends, multi-scenario responses, interrelationships, and interaction mechanisms. Key findings include: (1) From 1980 to 2050, coastal areas exhibit higher ESs stability than inland zones. The water yield (WY) persistently increases by 20.10% of the study area, whereas habitat quality (HQ) degrades in 45.98% of inland regions. (2) ESs display distinct spatial patterns across the sea-land gradient. HQ declines with increasing distance from the coastline. Other ESs display fluctuating patterns, with poorer performance in nearshore areas (0-5 km). (3) Trade-offs dominate WY-HQ and WY-carbon storage (CS), while synergies prevail among other ESs. (4) Spatially, ESs interactions exhibit high heterogeneity and a clear sea-land gradient variation. (5) When the distance from the coastline is also considered, the influence of factors is significantly enhanced. This study provides a forward-looking research framework for coastal risk management by revealing the complex dynamics and underlying mechanisms of ESs under the influence of sea-land interactions.

Achieving reliable and precise vehicle positioning is paramount for modern autonomous systems, yet it remains a formidable challenge in Global Navigation Satellite Systems (GNSS)-denied environments, especially when relying on ubiquitous low-cost Micro-Electro-Mechanical Systems (MEMS) Inertial Measurement Units (IMUs). This paper introduces a solution that enhances MEMS IMU capabilities by integrating two symmetrically mounted dual-beam Laser Doppler Velocimeters (LDVs). Our core innovation lies in leveraging two specialized Long Short-Term Memory (LSTM) networks that robustly regress the vehicle’s yaw and lateral velocities by effectively fusing both LDV and IMU outputs. To further elevate system accuracy, we propose an LDV outlier handling strategy and a method for LSTM prediction reliability detection designed to mitigate the adverse effects of anomalous network outputs. The vehicle velocities from the LDVs, augmented by our LSTM-derived yaw and lateral velocities, are then fused with MEMS IMU data within a Lie group-based Kalman filter. Experimental validation through two rigorous test sets demonstrates that our method significantly reduces system positioning errors under prolonged GNSS-denied conditions, outperforming existing LDV-based methods. This work underscores the potential of combining precise LDV measurements with the predictive power of deep learning and a robust Lie group-based data fusion strategy for accurate and reliable autonomous vehicle localization.

Constructing ecological networks (ENs) is an effective measure to mitigate the conflict between urban development and ecological conservation. However, existing simulating methods lack adequate consideration of human ecological demands and the spatial scale differences between these demands and natural ecological processes. This might lead to issues such as incomplete ecological process cycles or structural mismatches being overlooked during ENs simulations. To address these gaps, this study proposed an urban multi-scale nested ENs simulating framework that integrates human ecological demands with natural ecological processes. The framework first simulated an ENs focused on natural ecological process cycles at a global scale (GS). Then, it simulated an ENs centered on human ecological needs within the core urban areas at local scale (LS). Finally, it nested these multi-scale ENs by using cross-scale ecological supply sources as connecting points. This framework was applied to simulate spatio-temporal pattern changes in ENs of Jinan City, a core city in downstream of the Yellow River in China, aiming to mitigate cross-scale ecological conflicts between human–nature interactions under the background of urbanization. The study’s findings revealed that the area of demand sources increased by 8.56 times over 20 years. the area of cross-scale supply sources decreased by 15 km2 relative to 2000, and the deterioration in connectivity was more pronounced in GS compared to LS, with a decline of approximately 13.8%. These changes indicate the presence of incomplete ecological process cycles and structural mismatches across the multi-scale boundaries within the study area, which have been worsening annually. We recommend optimizing Jinan City’s multi-scale ecological network through three key strategies: rectifying internal structural mismatches, protecting core ecological areas, and aligning regional ecological demands. Implementing these strategies could significantly improve the network structure, reduce cross-scale mismatches, and enhance ecological connectivity by about 9%. This study highlights the importance of addressing structural mismatches and promoting complete ecological cycles in urban multi-scale ENs simulating, providing valuable insights for formulating urban multi-scale ecological conservation and restoration policies.

The strapdown inertial navigation system (SINS) and pitch-independent laser Doppler velocimeter (PI-LDV) integration represents a traditional navigation architecture. However, its effectiveness in obtaining precise altitude measurements remains constrained by the PI-LDV's inherent limitation of providing only one-dimensional velocity information. This study addresses this limitation by using the optical path structure of the PI-LDV to construct a frame capable of providing two-dimensional velocity information. To achieve this objective, two innovative integration methods are proposed: a SINS/PI-LDV loosely coupled integration method and a SINS/PI-LDV tightly coupled integration method, both of which consider the influence of potential laser beam fluctuations. Furthermore, a displacement increment measurement model is developed for the SINS/PI-LDV integrated navigation system to maximize the utilization efficiency of PI-LDV measurements while reducing the impact of sensor noise and outliers. The effectiveness of the proposed methods is rigorously validated through a comprehensive series of experimental tests, including: 1) extended-duration, long-distance tests using high-precision inertial measurement units (IMUs); 2) short-duration, limitedrange evaluations using high-precision IMUs; and 3) two additional long-distance verification experiments using both high-precision and medium-precision IMUs. Experimental results demonstrate that the proposed method significantly outperforms traditional methods, particularly in height accuracy. Notably, the performance advantages become more pronounced when implementing the SINS/PI-LDV integrated navigation system with medium-precision IMUs, suggesting enhanced practical applicability in cost-sensitive applications.

Strapdown inertial navigation systems (SINS) integrated with two-dimensional laser Doppler velocimeters (2D-LDVs) present a promising autonomous navigation solution for land vehicles, particularly in GNSS-denied environments. However, their performance is often degraded by vehicle sideslip and outliers in 2D-LDV measurements. This paper addresses these challenges by proposing a novel fault-tolerant SINS/Dual-2D-LDV tightly coupled integration scheme. In this scheme, two 2D-LDVs are integrated with SINS to create a redundant measurement model. This model utilizes the raw measurements from both LDVs along with the vehicle’s lateral zero-velocity constraint. To handle anomalies, a fault detection method based on the Local Outlier Factor (LOF) is introduced to identify measurement outliers and violations of the zero-velocity constraint. An adaptive filter, whose gain is dynamically adjusted by the LOF value, is then employed to mitigate the impact of these anomalies on the integrated navigation solution. The effectiveness and robustness of the proposed method are validated through two sets of long-distance vehicle experiments. Results demonstrate that the proposed scheme achieves superior positioning accuracy in both horizontal and vertical directions compared to traditional approaches. Furthermore, the LOF-based fault detection method proves to be more sensitive and effective in identifying anomalies than the traditional residual chi-squared detection method, enhancing the overall reliability of the system.

Urbanization has significantly impacted ecological connectivity, making the optimization of ecological networks (ENs) crucial. However, many existing strategies focus on overall network structure and overlook the spatial concentration of local ecological processes flow (EPF), limiting the effectiveness of ecological planning. This study proposes a novel EN optimization framework based on urban–rural gradient spatial zoning to enhance connectivity from the perspective of EPF. The framework divides areas outside the core urban zone (CUZ) into the urban fringe zone (UFZ), urban–rural interface zone (UIZ), and natural rural zone (NRZ), applying tailored optimization strategies in each zone. These strategies include increasing corridor redundancy, reducing corridor resistance, and expanding corridor width to alleviate EPF concentration. Using Jinan, a mega-city in China’s Yellow River Basin, as a case study, this study simulated EN changes over 20 years and validated the framework’s effectiveness. Optimization validation showed that increasing ecological land in low-flow corridors to 65% in the UIZ and expanding NRZ corridors to 5 km improved connectivity by 6.3%, addressing seven pinch points and three barrier points. This study highlights the importance of optimizing ENs via urban–rural zoning to support sustainable development and ecological protection policies.

Carbon storage (CS) of terrestrial ecosystems is strongly associated with space utilization changes. However, effects of urban spatial planning on the spatio-temporal heterogeneity of production-living-ecological land (PLEL) and CS remain unclear. To bridge this gap, we developed a new PGIP framework that combines PLEL theory, gradient analysis, the InVEST model, and the PLUS model. This integrated approach offers a comprehensive tool for assessing and simulating how urban planning influences CS. We applied this framework in Jinan, China, where we defined four urban gradient zones to examine the gradient differentiation of PLEL and CS. By integrating dynamic driving factors and urban spatial planning, the PLEL and CS in 2030 were simulated under different scenarios. Results revealed significant gradient-based variations in PLEL between 1980 and 2020. The urban living land (ULL) within 10 km of the city center increased by 117.60%. The CS has decreased by 8.14 × 10⁶ t, and the spatial heterogeneity of CS in the southeastern gradient zone was the strongest. More than 50% of the rise in CS resulted from the shift of rural living land to cultivated production land (CPL), while over 41% of the decrease in CS was caused by the conversion of CPL to ULL. By 2030, urban spatial planning is projected to significantly affect CS pattern, especially in downtown, far suburban, and southeastern gradient zone. Compared with unconstrained development scenario, under spatial planning-guided scenario, high-value clusters of CS will increase by 14.86 km2, while low-value clusters will decrease by 3.99 km2. This study provides a spatially explicit, policy-relevant framework for understanding and planning CS across urban-rural gradients, integrating planning scenarios and mechanistic insights to support low-carbon land use strategies.

The changes in landscape patterns induced by human activities such as the urban expansion and resource exploitation during the process of urbanization significantly affects habitat quality. However, there are insufficient studies on the spatial heterogeneity of landscape pattern changes and habitat quality and their spatiotemporal influencing mechanism, which hampers the optimization of regional land spatial layout and the formulation of ecological protection policies. Therefore, an analytical framework coupling the InVEST model, Geodetector and spatial statistical model was proposed in this study. Then, the impact mechanisms of landscape pattern changes on habitat quality and its spatial spillover effects were explored in Jinan, a typical city in the lower reaches of the Yellow River Basin, for the years 2000, 2010 and 2020. The results indicate that over the 20year period, Jinan experienced high dynamic changes in land use and land cover (LULC), leading to an increasingly fragmented landscape. Consequently, the spatial heterogeneity of habitat quality has been progressively enhanced, exhibiting an unbalanced spatial distribution with higher values in the south and lower values in the north. However, the gap between improvement and degradation ratios has narrowed by threefold over the 20 years. Expansion of mining land, fragmentation of woodland landscapes, and decrease in patch diversity were identified as the dominant factors causing the decline in habitat quality, while the restoration of water bodies and woodland landscapes, along with the recovery of patch diversity were the core reasons for promoting habitat quality improvement. Additionally, the spatial spillover range of landscape pattern changes on habitat quality improvement and degradation is similar (about 1200 m), but the spatial spillover intensity of degradation is significantly stronger than that of improvement, about twice as much. This study can provide a scientific support for urban spatial structure planning, ecological resource deployment and ecological restoration efforts.

The theory analysis of the interference fringe for the dual beam system is currently based on the ordinary Gaussian beam model where the velocity measured by dual beam LDV is v =λ fd/ (2sinα0 ) . αo is the half intersection angle between two intersecting laser beams. And the direction of the velocity is along the normal of the bisector of the optical axis of two output beams ( y axis) after focused by the positive lens. This study establishes two interference fringe models for the dual beam LDV based on the ordinary Gaussian beam and off-axis Gaussian beam model, respectively. In Model one and Model two, the velocity of the particles running through the measurement volume is v model1 = λfd/(sinα1+ sinα2 and V model2 = λfd/(2tanα0) , respectively, where α1 is the angle between optical axis of one output beam and the positive lens, and α2 is the angle between optical axis of other output beam and the positive lens. Two models indicate that when the distances between the optical axis of two input parallel beams and the positive lens is not equal, there is an angle between the distributing direction of the interference fringe and y axis.

The water track laser Doppler velocimeter (WTLDV) reported by our group recently emits laser to sense the moving velocity of the carrier in forward direction relative to water in underwater environment. And SINS/WTLDV integrated navigation system is a promising underwater navigation system with high concealment and autonomy. In this study, a calibration system for WTLDV combining the pitch independent laser Doppler velocimeter (PILDV) and the towing tank is presented to obtain the velocity measurement accuracy of WTLDV in water. The heading angle of PILDV mounted on the cart should be calibrated firstly using the distance observation-based method. The three main contributions of uncertainty in the calibration system are discussed. The expanded uncertainty of the calibration system is less than 0.11%. one hundred times measurement by PILDV under the same set velocity of the cart indicate that the towing velocity of the cart is unstable so that the set velocity of the cart cannot be used to calibrate WTLDV. The calibration results show that the relative measurement error of WTLDV is less than 2.5% with expanded uncertainty of less than 0.11% in the velocity range of 1m/s to 2m/s. The proposed calibration system can be used in the calibration process for WTLDV, as well as other current profiling sensors, such as the impeller current meter, electromagnetic log and DVL.

Doppler velocity log (DVL) is usually employed to suppress the divergency of the Strapdown Inertial Navigation System (SINS) in underwater navigation, which is not concealable due to high transmittance for acoustic wave in the water. To conduct underwater navigation task with high concealment, a differential laser Doppler velocimeter (LDV) working at water track mode is integrated with SINS in this paper. The developed LDV measures the advance velocity of the underwater carrier with respect to the surrounding water in underwater navigation scenario with advantages of high concealment, high real-time performance, high update rate, light weight, and small dimension. A dynamic river test was conducted to validate the underwater navigation performance of SINS/LDV integrated system. The experimental results show that during the voyage of 4493s and 5271.8 m, the maximum horizontal positioning errors of the proposed SINS/LDV integrated underwater navigation system is 27.8 m and the relative position error is less than 0.6% with respect to total distance. Therefore, the water track LDV is practical to aid SINS in underwater navigation environment.

ObjectiveRecently, the South China Sea has been facing a crisis of depleted fishery resources, primarily due to the impacts of illegal, unreported, and unregulated fishing activities, as well as overfishing. Accurately understanding the fishing activity intensity in the South China Sea holds significant implications for the sustainable management of fisheries resources.MethodsLeveraging the automatic identification system trajectory data from 2018, this paper employs spatial statistical methods and fishing effort indicators to comparatively analyze the spatial variations in fishing intensity between Chinese and Vietnamese fishing vessels.ResultThe results of this study show that (1) in 2018, the total fishing effort of Chinese fishing vessels in the South China Sea was 7.65 times that of Vietnamese vessels, but during China's South China Sea fishing moratorium, the fishing effort exerted by Vietnamese vessels surpassed that of China and (2) the top 10 ports in China and Vietnam support approximately 30% and 55.13% of their respective fishing intensities in the South China Sea.ConclusionThe study highlights significant variations in fishing intensity between Chinese and Vietnamese vessels and the substantial support provided by major ports. These findings offer valuable insights for fisheries resource monitoring and maritime spatial planning, contributing to the sustainable management of the South China Sea's fisheries resources. Impact statement This study sheds light on fishing by Chinese and Vietnamese vessels during the South China Sea fishing ban and the intensity of fishing by vessels supported by ports along the South China Sea. By understanding these patterns, we can better manage fishery resources in the South China Sea and ensure sustainable fishing.

The ecological supply-demand mismatch resulting from rapid urbanization stands as a core challenge affecting regional sustainability. This study constructed ecological supply-demand networks from the perspective of the circulation of ecological processes flow within regions, and proposed a novel supply-demand relationships evaluation index system. The case study results of six typical cities in the 'Upstream-Midstream-Downstream' of the Yellow River Basin demonstrate that our proposed evaluation index system can more accurately reveal the dynamic interaction of ecological resources within the urban area and the degree of supply-demand mismatch. Additionally, we found that the supply-demand relationship in upstream cities is better than that in midstream and downstream cities, with downstream cities exhibiting the worst performance. Furthermore, over the past 20 years, the supply-demand relationships of all six cities have consistently deteriorated, with the maximum decline reaching 39.8 %. Social development factors have driven imbalance changes in ecological resource allocation and spatial connectivity between the supply and demand sides, serving as a key factor in driving the deterioration of urban ecological supply-demand relationships. Lastly, this study proposes a partitioned protection strategy adaptable to both the basin and individual cities. This study holds significant importance for optimizing the allocation of ecological supply-demand resources and protecting ecosystems in different watershed segments.