Insights from i-Tree Eco-efficiency Assessment Management of Urban Trees in Oxford,UK

In the era of stock development following the acceleration of urbanization,the revitalization of urban green space has assumed an increasingly significant role.Consequently,the management of urban trees has emerged as a critical focus of urban governance,contributing to the enhancement of livability in human settlements.This study offers a comprehensive analysis of the urban tree management system in Oxford,UK,identifying that its primary objective is to optimize and maintain a harmonious balance between human activities and the natural environment through the implementation of high-quality planting practices.The system emphasizes enhanced management practices and establishes a robust framework for the development of targeted policies and management regulations,utilizing i-Tree eco-efficiency assessment and real-time feedback mechanisms.China’s urban tree management is in its nascent stages,and there is an urgent need for the development of urban green space.By adopting the refined management assessment methodologies employed for urban trees in Oxford,UK,it is possible to enhance the ecological value of urban trees,which represent a significant green resource within cities,and contribute to the creation of more livable urban spaces.

Development of Trees Management System Using Radial Basis Function Neural Network for Rain Forecast

Agriculture and farming are mainly dependent on weather especially in Malaysia as it received heavy rainfall throughout the years. An efficient crop or tree management system with a weather forecast needed for suitable planning of farming operation. Radial Basis Function Neural Network (RBFNN) algorithm was used in this study to predict rainfall and the main focus of this study is to analyze the factor that affects the performance of neural model. This study found that the model works better the more hidden nodes and the optimum learning rate is 0.01 with the RMSE 49% and the percentage accuracy is 57%. Besides that, it is found that the meteorology data also affect the model performance. Future research can be conducted to improve the rainfall forecast of this study and improve the tree management system.

Structure and species composition of tree stands on verges and slopes along a major highway in Hong Kong

Arboricultural research focusing on transport land use was lacking in Hong Kong.Some highway slopes were registered in the Systematic Identification of Maintenance Responsibility of Slopes in the Territory(SIMAR),abbreviated as SIMAR slopes.We aimed to analyze patterns in the structure and species composition of the tree stock along a highway in Hong Kong and examined how a slope registration system could help explain the characteristics of urban forests.The 53 slopes and 52 verges along San Tin Highway,Hong Kong were randomly selected.The trees on each slope and verge were collectively sampled as a tree stand.Six variables,namely tree abundance,species richness,maximum tree height,Shannon-Wiener diversity,Simpson's dominance,and Pielou's evenness were measured for each stand.In addition,a limited visual tree risk assessment was performed.The 7,209 trees in 23 species were recorded.Species richness was low,ranging from one to eight species per stand.SIMAR and non-SIMAR slopes were compared.SIMAR slopes had significantly higher species richness,diversity,evenness but lower dominance,with mean difference of 1.41 species,0.17,0.17 and-0.28respectively.SIMAR slopes were associated with lower tree risk rating.When training regression models,boosting as an ensemble method arbitrarily raised the explanatory power and the predictive accuracy of some models.Slope height,length,angle and area could be significant predictors of the biodiversity-related variables.Future research can sample more habitat characteristics related to the structure and species composition of slopes and verges which were important components of urban forestry.

An Updatable and Revocable Decentralized Identity Management Scheme Based on Blockchain

We study the decentralized identity management mechanism based on blockchain.Finally,we propose an updatable and revocable decentralized identity management scheme DIURS.In the scheme,we construct the DID management tree,which is a dynamic chameleon authentication tree essentially by using the chameleon hash function.We design algorithms in detail from four stages:sys-tem initialization,identity creation,identity update and revocation,and identity verification.We make the DID documents on the blockchain editable successfully and realize the update and revocation of DIDs.Then,we observe that DIURS can meet the structural stability and irreversibility requirements.The time of identity search and update is milliseconds.The length of the identity authentication path is short.There is no need to save the historical version of DID documents.These results indicate that DIURS is not only safe and reliable but also performs well and achieves functional optimization.