Aboveground biomass (AGB) is vital for assessing productivity and carbon storage. The area-based approach (ABA) and individual tree approach (ITA) are commonly used in remote sensing for AGB estimation, but their combined application remains underexplored. This study introduced a practical method that combined ABA and ITA using airborne laser scanning (ALS) data to estimate AGB of natural secondary forests of northeastern China. The results demonstrated that combining ABA and ITA features significantly enhanced AGB estimation accuracy. CNN achieved the highest accuracy and substantially improved compared to using ABA features alone. Among ITA features, tree height-related features were the most influential, and combining multiple types of ITA features proved to be more successful than using a single type. Therefore, using CNN based on ABA and all selected ITA features is recommended in practical applications. This method simplifies the complex ITA process and can be applied for large-scale, efficient forest inventory, sustainable forest management, and precise forest monitoring and protection in the future.

Northeast China is rich in forest resources and is one of China's most crucial forest resource areas. Due to environmental changes and human impacts, long-term monitoring of the fractional vegetation cover (FVC) in Northeast China is necessary. This study investigated the vegetation dynamics in Northeast China from 1986 to 2021 using the FVC based on kernel normalized difference vegetation index (kNDVI), and analyzed the influence of human activities on FVC. In the past 36 years, the FVC in Northeast China showed a fluctuating upward trend with high spatial heterogeneity. The mountain areas are the key regions with high vegetation coverage. However, the area with increased FVC accounted for 66.7% of Northeast China, most in densely populated areas with low FVC. In general, Northeast China experienced a high growth in FVC in the 36 years, suggesting that the effects of ecological construction and vegetation regeneration were noteworthy.

Abstract The original online fountain codes discard a large number of symbols that do not meet the requirements at the decoder. To improve channel utilization, this article proposes a new online fountain code. In the completion phase, the proposed code improves the receiving rules of encoded symbols, that is, the encoded symbols discarded in the original online fountain codes are selectively cached. Moreover, an optimal degree selection strategy of encoded symbols is obtained in the proposed scheme. The valid degree range of the proposed strategy is also analyzed, leading to an upper bound of cached events which eventually limits the number of feedbacks. The theoretical analysis and simulation results reveal that the proposed scheme outperforms two state‐of‐the‐art online fountain codes in terms of overhead factors, number of feedback transmissions, and encoding/decoding efficiency.

Individual tree crown delineation (ITCD), which includes treetop detection and/or tree crown delineation, plays a significant role in modern forest resources management and precise forestry. Recent years, amount of ITCD algorithms have been proposed based on passive and active remotely sensed data. However, since there is no standardized accuracy assessment procedure for ITCD, it is extremely difficult to compare ITCD algorithms unless multiple approaches are tested on a single study area using the same datasets and accuracy metrics. This study proposes a standard accuracy assessment procedure on both plot and individual tree levels, and develops an accuracy assessment tool for ITCD studies, including treetop detection and crown delineation procedures. The tool provides a scientific and efficient approach for accuracy assessment of ITCD.

This paper introduces a novel link-based ranking algorithm based on a model of focused Web surfers. FocusedRank is described and compared to implementations of PageRank and Topic-Sensitive PageRank. We report a user study that measures the relevance and precision of each approach. FocusedRank gives superior relevancy over PageRank, while significantly reducing the computational complexity compared to the Topic-Senstivice PageRank.

The next generation wireless network is an overlay network, in which AAA (authentication, authorization and accounting) is performed across domains. The current IETF AAA architecture causes long authentication delays during handoffs. In this paper, we propose a new network trust model to simplify the key management among networks. Based on this, a protocol is designed to shorten the delays.