The Sustainable Development Science Satellite-1 (SDGSAT-1) is a new-generation night-light satellite equipped with an advanced Glimmer Imager (GLI) sensor capable of acquiring multispectral, high-resolution night-time light (NTL) images. It has been widely applied to various fields, yield valuable insights in supporting human activity monitoring and sustainable development research. However, the Level 4A GLI images still suffer from spatial misalignment issues, including seam misalignment between the images captured by different cameras in the same scene; registration errors between images and basic geographic information data (i.e. OpenStreetMap road networks) and spatial inconsistencies between the panchromatic (Pan) and RGB bands. The existing studies mainly relied on manual registration or algorithms to mitigate misalignment effects, lacking efficient and systematic solutions. To effectively address this issue, in this work, an automatic geometric registration algorithm called road-guided image registration (RGIR), which uses the OSM road network as a spatial reference. Ground control points (GCPs) are selected via a three-step process: point match, line match and precise match. The RGIR algorithm could achieve high-precision registration and effectively correct the three typical spatial misalignment problems commonly found in GLI images. The experimental results demonstrated that RGIR can achieve sub-pixel accuracy across various scenarios and exhibits strong robustness. Overall, our work provides a workable technical approach to solving the existing spatial misalignment problem in GLI images, laying a solid foundation for its reliable application in multi-temporal analyses and large-scale sustainable development analyses.

Full-waveform hyperspectral LiDAR (HSL) generates comprehensive hyperspectral waveforms for scenes to reveal the shape and spectral heterogeneity of multiple natural targets. Nevertheless, current waveform processing methods are primarily designed for single-wavelength LiDAR systems, resulting in a shortage of methods tailored for full-waveform HSL data processing and in a restriction to further quantitative applications for HSL. This study is designed to extract targets’ physical and spectral characteristics by integrating spectral-dimension features into the HSL waveform processing. The core idea of the method involves a rigorous processing technique consisting of parameter initialization, parameter optimization, and re-optimization over calculating the median (M) after ranking central locations of natural target echoes (Rclonte). The medians in the re-optimization step serve as the reference parameter sets for supplementing the hidden or weak components at some wavelengths for HSL. Two groups of datasets, the simulated and measured datasets, were utilized to evaluate the component detection ability of the proposed Rclonte-M method. The results suggest that the Rclonte-M method demonstrates excellent component detection performance on both simulated and measured data, outperforming the multispectral waveform decomposition (MSWD) method. The HSL system designed by us owns an overall ranging error of about 7 cm for adjacent components, with the relative neighbor distance error (RNDE) limited to 0.160. Besides, spectra retrieval results from HSL easily distinguish the natural targets along the laser path. This study enriches the full-waveform HSL data processing algorithm library and could be considered in other full-waveform HSL systems and the simulated airborne or space-borne HSL waveforms. Codes are freely available on https://github.com/Jie-Bai/Rclonte-M-TGRS.

Recent years have witnessed the emergence and ongoing proliferation of dynamic adaptive streaming over HTTP (DASH1), which reuses web servers with HTTP communication instead of relying on RTSP/RTP/RTCP-based media server and promises to be capable of automatically tuning to bandwidth dynamics. Aware of its excellent performance, the third generation partnership project (3GPP) long term evolution (LTE) has adopted DASH (with specific codecs and operating modes) for use over mobile wireless networks in order to realize ubiquitous multimedia delivery. In a multi-user multiple-input-multiple-output (MU-MIMO) LTE system, spatial multiplexing gain can be achieved by making sure the transmitter to deliver distinct data streams to multiple receivers simultaneously, which provides the choices to opportunistically schedule the preferred receivers each time for a common time-frequency resource. In such a system, one of the major challenges to enhance DASH performance is to design an effective scheduler that can fully enjoy the benefit of spatial reuse as well as guaranteeing satisfactory video services for all users. To this end, in this paper, we propose a utility maximization framework (UMF) for DASH application delivered over MU-MIMO LTE downlinks. In particular, we characterize DASH performance by a combined utility function in terms of average video rate, playback buffer status, and battery energy state. Correspondingly, we develop a utility-based scheduler that selects multiple user equipments (UEs) to share each common network resource under the consideration of precoding-based MU-MIMO links in order to maximize system-wide DASH performance. We prove the NP-hardness of the scheduling problem and propose a priority search algorithm to provide time-efficient solution. We further incorporate novel rate adaptation on the application layer for the scheduled UEs to dynamically set the requested encoding bitrates to explore the balance between agile responsiveness and shifting smoothness. Extensive system-level simulations with realistic video trace validate the effectiveness of our framework in terms of rate adaptability, playback buffer depletion percentage, and battery energy saving.

Most crop classification work use the ground reference data to training the classifier; but sometimes, the ground reference data cannot be obtained. In this paper, we tried to use the NDVI time series obtained during 2006 and 2013 to classify crop types in 2014 at 30 m spatial resolution. The experiment was conducted in Southeast Kansas, USA. Firstly, we extracted the NDVI time series using ground reference data between 2006 and 2013 from MODIS NDVI time series. Then, the composed Landsat NDVI data were transformed to MODIS NDVI using the linear correlation between the two data sets. Next, Random Forest (RF) was employed to classify crop types at 30 m resolution. The result showed that this procedure could accurately identify the major crops in the study area as the overall accuracy was 92.22% and the Kappa coefficient was 0.8758. In addition, two subsets of the study area showed that the result obtained in this study was similar to that of Crop Data Layer (CDL) provided by National Agricultural Statistics Service (NASS). Thus, the method proposed in this study could be an alternative way for crop classification when ground reference data cannot be acquired.

Providing well-satisfactory multi-party video conferencing service is remarkably challenging, which demands not only high bandwidth but also low latency. Current commercial implementations typically use one or multiple multipoint control units (MCUs) as the central points for distributing video bit-streams to all participants in the conferencing session. Such MCU-based solution has limited control on quality of service (QoS), which may cause large delay, single-point malfunction and communication bottleneck for entire system. Recent years have witnessed the emergence of a new paradigm in networking, software defined networking (SDN), which advocates separating data plane and control plane, making network switches in the data plane simple packet forwarding devices and leaving a logically centralized controller to manipulate network behaviors. SDN provides the flexibility of changing underlying infrastructure and makes it possible to radically provide service/flow-aware QoS guarantee. In this paper, we propose a novel architecture for multi-party video conferencing by utilizing SDN-enabled multicasting, where SDN controller helps media controller to buildup multicast trees for video flows originated at video parties. To realize the architecture, we correspondingly propose a novel multicast construction and packing method, in which multiple source-based multicast trees are constructed and integrated to maximize system-wide utility while guaranteeing an end-to-end delay bound. Extensive simulations demonstrate that it could provide better video delivery compared to the conventional MCU-based solution in terms of video rate and delay in both sparsely and densely distributed networks.

Recent years have witnessed the emergence and ongoing proliferation of dynamic adaptive streaming over HTTP (DASH1), which reuses web servers with HTTP communication instead of relying on RTP-based media server and promises to be capable of automatically tuning to bandwidth dynamics. The third generation partnership project (3GPP) long term evolution (LTE) has adopted DASH for use in order to realize ubiquitous multimedia delivery. In a multi-user multiple-input-multiple-output (MU-MIMO) LTE system, spatial multiplexing gain can be achieved by making the transmitter deliver distinct data streams to multiple receivers simultaneously, which provides choices to schedule preferred receivers for a common resource. In such a system, one of the major challenges to enhance adaptive HTTP streaming performance is to design an effective scheduler that can fully enjoy the benefit of spatial reuse as well as guaranteeing satisfactory video services for all users. To this end, we propose a utility maximization framework (UMF) for DASH application over MU-MIMO LTE downlinks. In particular, we characterize DASH performance by a combined utility function in terms of average video rate, playback buffer status, and battery energy state. Correspondingly, we develop a utility-based scheduler that selects multiple user equipments (UEs) to share each common network resource under the consideration of precoding-based MU-MIMO in order to maximize system-wide DASH performance. Specifically, we propose a priority search algorithm to provide time-efficient solution to the scheduling problem. We further incorporate novel rate adaptation on the application layer for scheduled UEs to dynamically set the requested video encoding bitrates. Extensive system-level simulations validate the effectiveness of UMF in terms of rate adaptability, playback buffer depletion percentage and battery energy consumption.

Intra-flow network coding (NC) is an innovative technique that has potential to improve multicast performance in wireless mesh networks (WMNs) by allowing intermediate forwarding nodes (FNs) to use coding and overhearing to reduce the number of required transmissions. However the benefits of the NC technology are limited unless there are protocols to exploit its capabilities. The existing intra-flow NC-based multicast protocols are all based upon the conventional end-to-end transport principle. By such a principle, intermediate FNs are unable to accurately determine the minimum number of coded packets they should transmit in order to ensure successful data delivery to the destinations, and hence redundant packets can be injected into the network, leading to performance degradation. Furthermore, the existing protocols cannot handle the bandwidth heterogeneity of multicast receivers very well. We argue that a receiver-driven hop-by-hop transport approach is more suitable for intra-flow NC and these two techniques can create synergy by enabling cooperation among the FNs. In this paper we propose HopCaster, a novel protocol that incorporates intra-flow NC with hop-by-hop transport to achieve high-throughput reliable multicast and to solve the heterogeneous receiver issue. It completely eliminates the need for estimating the number of coded packets to be transmitted by a FN and avoids transmission of redundant packets, as well as simplifies multicast management and congestion control. Moreover, HopCaster employs a cross-layer rate adaptation mechanism that optimizes radio transmission rate in hop-by-hop multicast by taking into consideration next-hop node population changes. Our evaluations show that HopCaster outperforms the existing NC-based reliable multicast protocol.

Data redundancy elimination (DRE), also known as data de-duplication, reduces the data amount to be transferred or stored by identifying and eliminating both intra-object and inter-object duplicated data elements. It is one of the key content delivery acceleration techniques over wide area networks (WANs) to reduce delivery latency and bandwidth consumptions by reducing the amount of data to be transferred. Deploying DRE at the end hosts maximizes the bandwidth savings and latency reductions, because the amount of content sent to the destination hosts is minimized. However, standard DRE used to identify redundant content chunks is very expensive in terms of memory and processing capability especially on resource constrained hosts. By analyzing the web application traffic traces, we find out that some types of contents have more redundant contents than others. Thus, it is possible to apply DRE selectively and opportunistically on those contents with more redundant data elements than other content types to save the memory and processing resources at the hosts. In this paper, we propose content-type based selective DRE (SDRE), which deploys DRE selectively on the contents which have the most opportunities for redundant content identification. We explore the benefits of deploying SDRE on smartphone traffic traces. The results show that SDRE can achieve almost the same bandwidth savings as that of standard DRE with less computation and smaller memory.

Owing to the imminent fixed mobile convergence, Internet applications are frequently accessed through mobile nodes. However, service delivery latency is too high to satisfy user expectations. In this paper, we design a new TCP algorithm, TCP-ME (Mobile Edge), to accelerate the service delivery in mobile networks. Considering the QoS (Quality of Service) mechanisms of mobile networks, TCP-ME is designed to differentiate the packet loss caused by wireless errors, traffic conditioning of mobile core networks, and Internet congestion, as well as to react to the packet loss accordingly. To detect wireless errors, we mark the ACK (Acknowledge) packets in the uplink direction at the base station, and the marking threshold is a function of the instantaneous downlink queue length and the number of consecutive HARQ retransmissions. We modify the ECN mechanism with deterministic marking to detect Internet congestion. The packet loss caused by traffic conditioners of mobile networks is detected by whether the incoming DUPACK is marked or not. TCP-ME adapts the inter-packet interval when the packet loss is caused by wireless errors or the admission control mechanism. If the packet loss is due to Internet congestion, TCP-ME applies the TCP-New Reno's congestion window adaptation algorithm. Simulation results show that TCP-ME can speed up web service response time in mobile networks by about 80%.

Transmission Control Protocol (TCP) slow start degrades TCP performance under conditions of long-distance and high end-to-end latency, i.e., inherent characteristics of wide area networks (WANs). In this paper, we propose a new TCP slow start algorithm for WANs, called Adaptive Fast Start (AFStart), which incorporates an inline available bandwidth measurement over TCP technique into TCP slow start to set the slow start threshold adaptively and adjusts the congestion window intelligently. The performance of AFStart is evaluated through simulations using the dumb-bell topology and parking-lot topology by applying AFStart to Fast TCP. The simulation results show that AFStart can ramp up the congestion window from its initial value to the slow start threshold more quickly and smoothly than standard slow start, and AFStart achieves higher network link utilization and TCP throughput during the slow start than Fast TCP.

A new GPP/NPP model driven by the satellite SAR data was introduced in this paper. It was based on the light use efficiency theory and was referred to the MODIS model for the value of the maximum light use efficiency of different vegetation types. The model was testified in the HEIHE area with ENVISAT-SAR data and showed its feasibility to estimate GPP/NPP. Firstly, the driving factors such as PAR, T_scalar, W_scalar were calculated based on the algorithm and meteorological observation data. Then, the LUT algorithm using the MIMICS model was introduced and validated for its effectiveness to estimate LAI. Finally, the GPP was obtained based on the model and compared with the ground flux observation and MODIS product. The results reveal a potential possibility that the satellite SAR data could be used for the GPP/NPP estimation.

Recently, a new paradigm for cognitive radio networks has been advocated, where primary users (PUs) recruit some secondary users (SUs) to cooperatively relay the primary traffic. However, all existing work on such cooperative cognitive radio networks (CCRNs) operate in the temporal domain. The PU needs to give out a dedicated portion of channel access time to the SUs for transmitting the secondary data in exchange for the SUs' cooperation, which limits the performance of both PUs and SUs. On the other hand, Multiple Input Multiple Output (MIMO) enables transmission of multiple independent data streams and suppression of interference via beam-forming in the spatial domain over MIMO antenna elements to provide significant performance gains. Researches have not yet explored how to take advantage of the MIMO technique in CCRNs. In this paper, we propose a novel MIMO-CCRN framework, which enables the SUs to utilize the capability provided by the MIMO to cooperatively relay the traffic for the PUs while concurrently accessing the same channel to transmit their own traffic. We design the MIMO-CCRN architecture by considering both the temporal and spatial domains to improve spectrum efficiency. Further we provide theoretical analysis for the primary and secondary transmission rate under MIMO cooperation and then formulate an optimization model based on a Stackelberg game to maximize the utilities of PUs and SUs. Evaluation results show that both primary and secondary users achieve higher utility by leveraging MIMO spatial cooperation in MIMO-CCRN than with conventional schemes.

emerging technologies such as orthogonal frequency division multiplexing (OFDM) and multiple in multiple out (MIMO) has significantly increased the bandwidth of a wireless channel. A potential application of these technologies is to distribute digital video content over wireless in a home environment. However, video streaming is bandwidth demanding, and the number of interference free wireless channels is limited, selecting the best operating channel is critical to guarantee the quality of viewer's experience. We study the feasibility of transmitting video over WLANs in a multi-dwelling unit environment; design a centralized channel selection algorithm that satisfies each client's demand, at the same time, takes the fairness and residual bandwidth into consideration. We use directed edge-weighted graph to model the interference between different basic service systems and classify APs into cooperative APs and non cooperative APs. Our simulation results show that using existing 802.11a channels, a feasible channel allocation scheme for video streaming over WLANs in a dense deployment can be found in most cases.

Orthogonal frequency-division multiple access (OFDMA) exploits the frequency selective property of a wireless communication channel by allocating subchannels to individual users. Conventional multicast systems, however, suffer from diversified channel conditions among users. The main contribution of this paper is to maximize the multicast rate of one multicast session while being fair among users and build a general framework for resource allocation for multi multicast sessions. By assuming availability of channel state information, we study resource allocation in a multicast OFDMA system. We first study one multicast session system and solve the resource allocation problem in two steps. We first propose a novel subchannel allocation algorithm by allocating each subchannel to a group of users in the multicast session based on their subchannels gains. Second, a bit loading algorithm is also proposed. We further study multiple multicast transmission systems and propose a greedy algorithm for resource allocation to achieve proportional fairness among sessions. Finally, we numerically show that proposed algorithms outperform conventional multicast schemes and previous works for one multicast scenario and conventional multicast schemes for multi multicast scenario.

In multi-hop infrastructure wireless mesh networks (WMNs), the association mechanism, by which a client station (STA) affiliates with a mesh access point (MAP), and the routing algorithm, through which MAPs form a multi-hop backhaul for relaying STAs' traffic, determine a two-tier logical topology. Apparently the STA-MAP association mechanism and the backhaul routing impact the available bandwidth that can be allocated to each STA. In this paper, we formulate a joint optimization problem of STA-MAP association, backhaul routing and bandwidth allocation. Our rigorous framework maximizes the network throughput while guaranteeing network-wide fairness among STAs, taking into account the bandwidth constraints of both access and backhaul links, as well as the wireless interference. We then develop approximation algorithms for efficiently solving the joint optimization problem. A method to decouple topology construction and bandwidth allocation is proposed to simplify the optimization problem under integral association and single- path routing, which is NP hard in the original formulation. We also use the clique approximation to alleviate the complexity for constructing the wireless interference constraints. Furthermore a scheduling algorithm is proposed, which coordinates channel access to provide bandwidth guarantee and can recover certain performance loss due to the clique approximation. Our evaluation demonstrates that constructing a good logical topology can improve throughput while enhancing fairness, and our algorithms can achieve performance close to the optimal solution to the joint association, routing and bandwidth allocation problem.

In a wireless mesh network, a client station needs to associate with a mesh access point for network access. Conventional association mechanisms assume a high-speed backhaul and only the access link being the bottleneck. This assumption holds for most WLANs, but in wireless mesh networks traffic could be bottlenecked either by the access link or by the bandwidth-limited wireless backhaul. In this paper, we propose an association mechanism for wireless mesh networks to improve stations' end- to-end communication performance with the Internet. A station makes its association decision by jointly considering the quality of the access link between the station and the candidate mesh access point as well as the cost of the multi-hop path from the mesh access point to the gateway. In addition, we design two access link metrics, Contention Aware Expected Transmission Time (CAETT) and Load Aware Expected Transmission Time (LAETT). The main strength of CAETT is incorporating the impact of 802.11 MAC layer contention on the bandwidth sharing among the multi-rate stations. LAETT further captures the traffic load. We evaluate the performance of our system through simulations and demonstrate that the proposed joint association mechanism with the CAETT/LAETT metric can significantly improve the end-to-end performance for wireless mesh networks by up to 60%.

We report the design, implementation and evaluation of Merged Hybrid ARQ with staggered FEC (MHARQ) system for video multicast over wireless LANs. MHARQ combines the advantages of receiver-driven staggered FEC and hybrid ARQ schemes to compensate the large dynamic range of WLAN channels and to achieve high reliability, scalability and wireless bandwidth efficiency for video multicast. The FEC packets generated by a cross-packet FEC code are divided into multiple streams according to the pre-configured overhead and are transmitted in different multiple IP multicast groups. Certain FEC streams are delayed from the original video stream. The receivers dynamically join/leave the FEC multicast groups based on the channel conditions. For efficient utilization of WLAN bandwidth, FEC data for a multicast group would not be transmitted by the APs in wireless networks if no receiver joins this group. The time shift between the video stream and the FEC streams introduces temporal diversity and compensates for the client join delay and handoff interruption. In addition, when delayed FEC packets are not enough to recover the lost packets, the receivers can send a hybrid ARQ request to the video server. We design a channel estimation algorithm for a receiver to dynamically determine the delayed FEC multicast groups to join and/or send ARQ NACK to request for retransmission. Using the ORBIT radio grid testbed, we have investigated the performance of the proposed MHARQ system with various numbers of users per AP and different number of APs per video server. It is demonstrated via real system implementation on ORBIT that MHARQ improves wireless bandwidth efficiency and scalability for reliable video multicast, compared with existing reliable multicast schemes.

Streaming video over wireless mesh networks is an attractive and challenging technology. It is important to select an appropriate metric in the routing algorithm to improve the video delivery quality. In this paper, we report the design, implementation, and evaluation of a prototype for video streaming over a wireless mesh network. In order to select the best path dynamically to improve the multimedia performance, Ad Hoc On-Demand Distance Vector (AODV) routing protocol is enhanced with a new radio and bandwidth aware routing metric, better route request/reply message process rules and periodic route refreshment and maintenance. A metric quantization method is also proposed to maintain the route stability while achieving quick response to the network dynamics. In addition, we implemented a proxy function in the mesh access point so that the stations can access the mesh through the access point without any modification to themselves. Using the prototype, we prove the concept that our approach can significantly improve the video quality over the traditional AODV routing protocol in a real system implementation.

We report the implementation experience and experimental evaluation of a staggered adaptive forward error correction (FEC) system for video multicast over wireless LANs. In the system, the parity packets generated by a cross-packet FEC code are transmitted at a time delay from the original video packets, i.e. staggercasting video stream and FEC stream in different multicast groups. The delay provides temporal diversity to improve the robustness of video multicast, especially to enable the clients to correct burst packet loss using FEC and to achieve seamless handoff. A wireless client dynamically joins the FEC multicast groups based upon its channel conditions and handoff events. We have implemented the system including the streaming server and client proxy. A novel software architecture is designed to integrate the FEC functionality in the clients without requirement for changing the existing video player software. We conduct extensive experiments to investigate the impact of FEC overhead and the delay between the video stream and FEC stream to the video quality under different interference levels and mobile handoff durations. The efficacy of staggered adaptive FEC system on improving video multicast quality is demonstrated in real system implementation.

Network embedded FEC (NEF) can greatly improve the quality of service for real-time applications in p2p and proxy-based overlay networks [H. Radha and Mingquan Wu, September 2004]. Under NEF, FEC encoders and decoders (codecs) are placed in selected intermediate nodes of an overlay network The NEF codecs detect and recover lost packets, within FEC blocks at earlier stages before these blocks arrive at deeper intermediate nodes or at the final leaf nodes. This approach significantly reduces the probability of receiving undecodable FEC blocks. In many multi-hop wireless networks (such as ad hoc networks), end systems also act as routers to forward packets; higher layer functions such as FEC can then be implemented within the intermediate nodes of a multi-hop wireless network. In this paper, we analysis and compare the performance of NEF and end-to-end FEC in a multi-hop wireless channel for packet-loss recovery. We consider Markov erasure channels with memory, and hence, we present a new (and a rather simple and elegant) method for evaluating any desired loss/recovery probability measure for the Gilbert channel model. Consequently, the impact of the loss burst length on the performance of NEF and end-to-end FEC over multi-hop wireless channels are thoroughly analyzed and presented.

Network embedded forward error correction (NEF) framework is a paradigm shift from a conventional approach of providing forward error correction (FEC) only on an end-to-end basis. Previous work on NEF has shown promise in greatly improving the decodable probability, message throughput and video quality available to the end receiver. However the utility of NEF for video applications in presence of packet loss correlation has not been evaluated as yet. In practice, packet losses are often correlated and occur in bursts. The distortion in video can be sensitive to the bursty nature of the losses. Thus in this paper we analyze the performance of NEF within random multicast distribution trees that exhibit losses-with-memory over their branches. We utilized the Gilbert model for packet losses over each link. We quantify the performance improvement of NEF over conventional end-to-end FEC in terms of improvement in video quality in presence of packet loss correlation. Embedding NEF codecs can impact the sensitivity of video quality to packet loss correlation. We explicitly evaluate as to how NEF can alter the dependence of video quality on packet loss burstiness. Finally we show that in addition to an average improvement in video quality, NEF can improve the performance in terms of quality guarantees also.