Image vectorization aims to convert raster images to vector ones, allowing for easy scaling and editing. Existing works mainly rely on preset parameters (i.e., a fixed number of paths and control points), ignoring the complexity of the image and posing significant challenges to practical applications. We demonstrate that such an assumption is often incorrect, as the preset paths or control points may be neither essential nor enough to achieve accurate and editable vectorization results. Based on this key insight, in this paper, we propose AdaVec, an efficient image vectorization method with adaptive parametrization, where the paths and control points can be adjusted dynamically based on the complexity of the input raster image. In particular, we first decompose the input raster image into a set of pure-colored layers that are aligned with human perception. For each layer with varying shape complexity, we propose a novel allocation mechanism to adaptively adjust the control point distribution. We further adopt a differentiable rendering process to compose and optimize the shape and color parameters of each layer iteratively. Extensive experiments demonstrate that AdaVec outperforms the baselines qualitatively and quantitatively, in terms of computational efficiency, vectorization accuracy, and editing flexibility.

Spatiotemporal continuous fractional snow cover(FSC) dataset is needed as an important input for the study of large-scale hydrological, meteorological and climate research. But optical data often have gap due to cloud cover. The widely used Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover dataset uses an eight-day composite approach to remove cloud effects, but it cannot meet the requirement of monitoring snow cover, a parameter with high temporal and spatial variability. This paper uses multiple endmember spectral mixture analysis (MESMA) algorithm to retrieve FSC from geostationary satellite (FY-4A and Himawari-8) and polar-orbiting satellite (MODIS) data; Then geostationary satellite retrieve results are used to fill the MODIS cloud cover pixels, which can reduce the cloud cover from 50% to 15%; Finally, the daily FSC product is obtained by using Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) algorithm. Landsat-8/OLI data processed by the MESMA algorithm is determined as “ground truth” to validate this product. The result shows that the accuracy of the daily cloud-free FSC product is high with the root mean square error is 0.1-0.15.

Many algorithms and products for snow cover have been developed. We built a high spatial and temporal resolution validation data set, which can be used as a unified standard for the validation of existing snow products. In recent years, Sentinel-2 MSI has been widely used because of its higher spatial and temporal resolution. In this study, we applied the linear spectral mixture analysis to Sentinel-2 MSI to obtain the fractional snow cover products, then we explored whether the Sentinel-2 MSI FSC products can meet the accuracy requirements with GF-2 data. The results show that the accuracy of Sentinel-2 MSI FSC can meet the requirements. Finally, we use Sentinel-2 MSI FSC to validate the MODAGE product.

The moderate resolution imaging spectroradiometer (MODIS) snow algorithm has been used to generate global fractional snow cover (FSC) at a pixel size of 500 m using a linear regression relationship (called “FRA6T”) between FSC and the normalized difference snow index (NDSI). However, the linear relationship is problematic because of the considerable NDSI variation in nonsnow conditions. In this letter, we propose a universal ratio snow index (URSI), which is the ratio of the visible reflectance and the sum of the near infrared and shortwave infrared reflectances. It is called “universal” because it has weak sensitivity under snow-free ground conditions and, therefore, can improve the stability of the linear snow index methodology. A comparison between NDSI and URSI with regard to estimate FSC using the linear snow index methodology is carried out for the Tibetan Plateau. The scatter plots of MODIS NDSI/URSI and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) FSC indicate that a linear relationship can be assumed for both NDSI and URSI for barren land conditions and is more appropriate for URSI than it is for NDSI in forested areas. Validation efforts show that the linear relationship using URSI (designated “FracURSI”) achieves fewer errors in FSC estimation compared with the developed NDSI method (“FracNDSI”), particularly for forested areas and for moderate FSC values. Averaged over all comparisons, the root-mean-square error (RMSE) of FSC estimates for FRA6T is 0.13, and for FracNDSI is 0.12, whereas FracURSI RMSE is 0.11.

Many algorithms and products for snow cover have been developed. Then a unified set of “ground truth” data is important to validate snow cover products. In this study, Landsat-8/OLI data processed by linear unmixing algorithm was determined as “ground truth” to validate the moderate resolution snow products. In order to evaluate the cloud removing effect of the daily fractional snow cover (FSC) dataset of MODIS over High Asia, we use the MOD10A1 FSC product which is calculated by recommended equations as the before cloud removing data, then the Landsat-8/OLI FSC was used to validate both of the MODIS data. The results show that when the percentage of cloud pixels is less than 10%, the binary accuracy can reach 0.85 or more, the mean absolute error is less than 0.25, and the root mean square error is less than 0.35. These results suggest that the product has high credibility, despite there is still a small amount of cloud in the product.

High-resolution soil moisture dataset is important for studying cold and humid temperate forest climates, estimating forest carbon emissions and storage, and identifying the influence of water circulation and global change in Genhe area. Leaf Area Index (LAI) is an important vegetation biophysical variable and has been widely used for analysis of the vegetation biomass, land-surface process simulation, and many other global change studies. This paper based on LAI from Global LAnd Surface Satellite (GLASS), microwave polarization difference index (MPDI) from Soil Moisture Active Passive (SMAP) L band Brightness Temperature (TB), and synthetic Land Surface Temperature (LST) from combine AMSR-2 TB and MODIS LST data proposed a downscaling method for SMAP L3 soil moisture product. Using the multiple linear regression method, we obtained 1km spatial resolution of soil moisture data in Genhe area. The results showed that downscaling SMAP soil moisture can present more details than before with low errors.

Land surface freeze/thaw (FT) state is important for identifying the variable of carbon-nitrogen, water and energy cycling and soil erosion. The Soil Moisture Active Passive (SMAP) mission produces global and northern hemispheric daily landscape FT dataset [1] at a spatial resolution of 36 km from L-band radiometer. Parameterized discriminant function algorithm (PDFA) [2] detect landscape FT state from Advanced Microwave Scanning Radiometer 2 (AMSR2) observations. In this study, we use the in-situ soil temperature to validate the SMAP global FT dataset (36 km) and PDFA-based AMSR2 FT dataset (0.25°). Performance evaluation are obtained from two regions at northern hemispheric located in the China. The evaluation results show that overall accuracies usually greater than 85% for SMAP global FT dataset at Genhe (GH) region, but lower than 70% at Saihanba (SHB) region. AMSR2 FT dataset have accuracies that always higher than 85% at both regions.

Snow depth (SD) and snow water equivalent (SWE) are significant parameters in climate and hydrologic models. Successful estimation of SD (SWE) can improve the accuracy of snowmelt-runoff predictions and the management of water supplies. Currently, passive microwave (PMW) remote sensing is the most efficient way to monitor SD on global and regional scales; however, there are many challenges for accurate SD estimation. In this study, a new spatial dynamic method is developed by introducing random forest (RF) model, AMSR-2 TB and other auxiliary data. The main objective of this work is to produce long term SD dataset with the dynamic method using the Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager/Sounder (SSMI/S) which span from 1987 to present. Through evaluation and analysis, the RF method performs better than traditional linear-fitting model. However, it tends to overestimate SD in shallow snow cover areas. Now, a preliminary spatial dynamic method (pixel-based model) is developed. For further work, the evaluation will be conducted to assess the feasibility of SD reconstruction. Moreover, to address overestimation over shallow snow areas, the snow depletion curve (SDC) incorporating SD and fractional snow cover (FSC) is expected to improve SD retrievals.

Several intrusion detection techniques (IDTs) proposed for mobile ad hoc networks rely on each node passively monitoring the data forwarding by its next hop. This paper presents quantitative evaluations of false positives and their impact on monitoring-based intrusion detection for ad hoc networks. Experimental results show that, even for a simple three-node configuration, an actual ad hoc network suffers from high false positives; these results are validated by Markov and probabilistic models. However, this false positive problem cannot be observed by simulating the same network using popular ad hoc network simulators, such as ns-2, OPNET or Glomosim. To remedy this, a probabilistic noise generator model is implemented in the Glomosim simulator. With this revised noise model, the simulated network exhibits the aggregate false positive behavior similar to that of the experimental testbed. Simulations of larger (50-node) ad hoc networks indicate that monitoring-based intrusion detection has very high false positives. These false positives can reduce the network performance or increase the overhead. In a simple monitoring-based system where no secondary and more accurate methods are used, the false positives impact the network performance in two ways: reduced throughput in normal networks without attackers and inability to mitigate the effect of attacks in networks with attackers.

Abstract Route falsification attacks are easy to launch in mobile ad hoc networks with on demand routing protocols that employ network‐wide flooding of control packets for route discoveries. To mitigate such attacks, we propose ap‐hop crosscheck mechanism, which requires nodesp,p ≥ 2, hops apart to authenticate and verify route reply packets using pairwise shared keys. This mechanism can detect route falsification by non‐colluding malicious nodes on‐the‐fly; furthermore, it can identify a group of at mostp+1 nodes that contain the malicious nodes that caused the route falsification. Unlike intrusion detection techniques, which require extensive monitoring and sampling, the proposed crosscheck mechanism is light‐weight and fast and hence can be used to augment the existing secure routing protocols and improve intrusion detection capability. We implement a two‐hopcrosscheck for an on demand ad hoc network routing protocol. Using simulations, we show that the two‐hopcrosscheck mitigates attacks by multiple malicious nodes with negligible impact on performance. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract Colluding malicious insider nodes with no special hardware capability can use packet encapsulation and tunneling to create bogus shortcuts (in‐band wormholes) in routing paths and influence data traffic to flow through them. This is a particularly hard attack using which even a handful of malicious nodes can conduct data traffic analysis of packets or disrupt connections by dropping packets when needed. Simulation analysis shows that a disproportionately large amount of traffic goes through routes with wormholes even when a secure routing protocol (SRP) such as Ariadne is used. To mitigate such attacks and augment existing on demand SRPs, distributed packet filtering techniques based on statistical profiling of control packet propagation speeds are proposed. These techniques do not require network‐wide synchronized clocks or new packet transmissions and need only simple computations by the sources or the destinations of the connections. The proposed packet filters together with Ariadne are implemented in the Glomosim simulator and their effectiveness is evaluated. The simulation results indicate that the proposed packet filters can reduce the in‐band wormhole creation and their usage by a factor of 2‐‐10. Also, the false alarm rates of the proposed techniques are very low and have little impact on normal network throughput, making them practical for mobilead hocnetworks. Copyright © 2008 John Wiley & Sons, Ltd.

Several intrusion detection techniques proposed for mobile ad hoc networks rely on each node passively monitoring the data forwarding by its next hop. This paper presents quantitative evaluations of false positives and their impact on monitoring based intrusion detection for ad hoc networks. Experimental results show that even for a simple 3-node configuration, an actual ad hoc network suffers from high false positives; these results are validated by a Markov model. However, this false positive problem cannot be observed by simulating the same network using popular ad hoc network simulators such as ns- 2, OPNET or Glomosim with default noise models. To remedy this, a probabilistic noise generator model is incorporated in the Glomosim simulator. With this revised noise model, the simulated network exhibits the aggregate false positive behavior similar to that of the experimental testbed. Simulations of larger (50- node) ad hoc networks indicate that a monitoring based intrusion detection has very high false positives which impact its ability to mitigate the attacks.

Wormhole attacks, in which colluding attackers with out-of-band communication links record packets (or bits) at one location and replay at another, cause far away nodes to consider themselves as neighbors to one another. Such attacks can ruin the routing and communication capabilities of mobile ad hoc networks. This paper presents NEVO, in which nodes passively monitor (overhear) the forwarding of broadcast type packets by their neighbors and use the send and overhear times of transmissions of these packets, to mitigate these wormhole attacks. NEVO does not require synchronized clocks, special hardware support, or any special capability. NEVO can detect almost all instances of wormhole attacks and is virtually independent of the routing protocol used. NEVO is simple to implement - requires mostly network layer software changes, has low overhead, and is very robust. NEVO is implemented in the Glomosim simulator and its performance is evaluated. Simulation results show that NEVO effectively mitigates wormhole attacks (no data packets were sent through the wormholes in the simulated networks) and has low impact in normal with low to moderate traffic loads.

Abstract Radio frequency identification (RFID) systems are very effective for identifying objects. Existing published works focus on designing efficient collision resolution protocols for the tag identification problem in RFID systems with passive RFID tags. However, advances in low‐cost and low‐power sensing technologies will make active RFID tags more popular and affordable in the near future. In multiple object identification systems with active tags, the tags are designed for extremely low‐cost large‐scale applications such that battery replacement is not feasible. This imposes a critical energy‐constraint on the communication protocols used in these systems. In this paper, we analyze energy consumption and identification times for several protocols. The objective is to decrease energy consumption of tags by reducing both the total identification time and the total active time. Copyright © 2007 John Wiley & Sons, Ltd.

Colluding malicious insider nodes with no special hardware capability can use packet encapsulation and tunnelling to create bogus short-cuts (in-band wormholes) in routing paths and influence data traffic to flow through them. This is a particularly hard attack using which even a handful of malicious nodes can conduct traffic analysis of packets or disrupt connections by dropping packets when needed. Using simulations we show that a disproportionately large amount of traffic goes through routes with wormholes even when a secure routing protocol such as Ariadne is used. To mitigate this, we propose distributed techniques based on the propagation speeds of requests and statistical profiling; they do not require network-wide synchronized clocks, do not impose any additional control packet overhead, and need only simple computations by the sources or destinations of connections. We implemented our techniques in Ariadne and evaluated their effectiveness using the Glomosim simulator. Our results indicate that in-band wormhole creation and usage can be reduced by a factor of 2-10. Also, the false alarm rates of the proposed techniques are very low and have little impact on normal network operation, making them practical for MANETs.

Network simulators such as NS-2, Glomosim, and OPNET are extensively used to validate and evaluate the performance of network protocols for mobile ad hoc networks (MANETs). For accurate simulations, realistic signal propagation and noise models should be used to simulate the radio channels in MANETs. A significant amount of emphasis is put on the correctness of signal propagation, while the ambient noise (due to external sources) is modeled as a constant noise. Based on the noise levels measured in a wireless ad hoc network testbed, we present two analytical models to describe the noise levels in a real network: a generalized extreme value (GEV) random process model and a Markov chain model. We incorporate GEV noise model in the Glomosim network simulator and show that it impacts the network performance significantly.

Route falsification attacks are easy to launch in mobile ad hoc networks with on demand routing protocols that employ network-wide flooding of control packets for route discoveries. To mitigate this attack, we propose a p-hop crosscheck mechanism that requires nodes p, p ≥ 2, hops apart to authenticate and verify route reply packets using pair-wise shared keys. The crosscheck can detect route falsification by non-colluding malicious nodes on-the-fly; furthermore, it can identify a group of at most p+1 nodes that contain the malicious nodes that caused the route falsification. Unlike intrusion detection techniques, which require extensive monitoring and sampling, the proposed crosscheck mechanism is light-weight and fast. Therefore, the proposed crosscheck mechanism can be used to augment the existing secure routing protocols and improve intrusion detection capability. We implemented 2-hop crosscheck for AODV in the Glomosim simulator. Using simulations, we show that 2-hop crosscheck mitigates attacks by multiple malicious nodes with negligible performance impact.

Radio frequency identification (RFID) systems are very effective for identifying objects. In multiple object identification systems with active tags, the tags are designed for extremely low-cost large-scale applications such that battery replacement is not feasible. This imposes a critical energy-constraint on the communication protocols used in these systems. In this paper, we analyze energy consumption and identification times for several protocols. The objective is to decrease energy consumption of tags by reducing both total identification time and total active time.

In this paper, we present a new online algorithm for dynamically routing bandwidth guaranteed label switched paths (LSPs). LSP set-up requests are represented in terms of a pair of ingress and egress routers as well as its bandwidth requirement, and arrive one by one. There is no a priori knowledge regarding future LSP set-up requests and their characteristics. Our proposed algorithm considers not only the importance of critical links, but also the degree of their importance to routing possible future LSP set-up requests by characterizing their normalized bandwidth contribution to routing future LSP demands. Moreover, link residual bandwidth information, i.e., the link's capability of routing future LSPs, is also incorporated. Simulation results show that our proposed algorithm performs better than the best known bandwidth guaranteed routing algorithm, the minimum interference routing algorithm, in terms of LSP rejection rate under both static and dynamic LSP set-up request arrivals.