Monitoring forest dynamics in Africa during 2000- 2020 using a remotely sensed fractional tree cover dataset

Africa is covered with extensive woodlands,savannas and rainforests.The tree cover of these biomes has been undergoing substantial changes in recent decades.However,the dynamics of forests in Africa are currently unclear,particularly in the woodlands and savanna areas covered by sparse trees.Here,we assessed the spatio-temporal trend of African forests from 2000 to 2020,using a 250-m resolution fractional tree cover product that can capture the variation of forest density in the widespread mixed vegetation landscapes of the continent.The tree cover trends,interannual change and hotspots of forest gain and loss were evaluated.Results showed that the African forest area increased at a rate of 3.59 million ha/year over the study period,reaching 589 million ha in 2020.Considerable forest gain and loss both occurred in Africa.The net change rate in woodlands’forest area was the fastest(2.28 million ha/year),followed by rainforests(0.80 million ha/year)and savannas(0.34 million ha/year).Hotspots of forest gain were concentrated in the north belt of woodlands and savannas,while forest loss primarily clustered in East and South Africa.This work would help African countries to monitor forest change and promote forest management to achieve the Sustainable Development Goals.

Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error

We developed a global,30-m resolution dataset of percent tree cover by rescaling the 250-m MOderate-resolution Imaging Spectroradiometer(MODIS)Vegetation Continuous Fields(VCF)Tree Cover layer using circa-2000 and 2005 Landsat images,incorporating the MODIS Cropland Layer to improve accuracy in agricultural areas.Resulting Landsat-based estimates maintained consistency with the MODIS VCF in both epochs(RMSE=8.6%in 2000 and 11.9%in 2005),but showed improved accuracy in agricultural areas and increased discrimination of small forest patches.Against lidar measurements,the Landsat-based estimates exhibited accuracy slightly less than that of the MODIS VCF(RMSE=16.8%for MODIS-based vs.17.4%for Landsat-based estimates),but RMSE of Landsat estimates was 3.3 percentage points lower than that of the MODIS data in an agricultural region.The Landsat data retained the saturation artifact of the MODIS VCF at greater than or equal to 80%tree cover but showed greater potential for removal of errors through calibration to lidar,with post-calibration RMSE of 9.4%compared to 13.5%in MODIS estimates.Provided for free download at the Global Land Cover Facility(GLCF)website(www.landcover.org),the 30-m resolution GLCF tree cover dataset is the highest-resolution multi=temporal depiction of Earth’s tree cover available to the Earth science community.

Geospatial Analysis of Urban Heat Island Effects and Tree Equity

In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.

Integrating TM and Ancillary Geographical Data with Classification Trees for Land Cover Classification of Marsh Area

The main objective of this research is to determine the capacity of land cover classification combining spec- tral and textural features of Landsat TM imagery with ancillary geographical data in wetlands of the Sanjiang Plain, Heilongjiang Province, China. Semi-variograms and Z-test value were calculated to assess the separability of grey-level co-occurrence texture measures to maximize the difference between land cover types. The degree of spatial autocorrelation showed that window sizes of 3×3 pixels and 11×11 pixels were most appropriate for Landsat TM im- age texture calculations. The texture analysis showed that co-occurrence entropy, dissimilarity, and variance texture measures, derived from the Landsat TM spectrum bands and vegetation indices provided the most significant statistical differentiation between land cover types. Subsequently, a Classification and Regression Tree (CART) algorithm was applied to three different combinations of predictors: 1) TM imagery alone (TM-only); 2) TM imagery plus image texture (TM+TXT model); and 3) all predictors including TM imagery, image texture and additional ancillary GIS in- formation (TM+TXT+GIS model). Compared with traditional Maximum Likelihood Classification (MLC) supervised classification, three classification trees predictive models reduced the overall error rate significantly. Image texture measures and ancillary geographical variables depressed the speckle noise effectively and reduced classification error rate of marsh obviously. For classification trees model making use of all available predictors, omission error rate was 12.90% and commission error rate was 10.99% for marsh. The developed method is portable, relatively easy to im- plement and should be applicable in other settings and over larger extents.

An Assessment of Snow Cover Duration Variability Among Three Basins of Songhua River in Northeast China Using Binary Decision Tree

The dynamics of snow cover differs greatly from basin to basin in the Songhua River of Northeast China, which is attributable to the differences in the topographic shift as well as changes in the vegetation and climate since the hydrological year(HY) 2003. Daily and flexible multi-day combinations from the HY 2003 to 2014 were produced using Moderate Resolution Imaging Spectroradiometer(MODIS) from Terra and Aqua remote sensing satellites for the snow cover products in the three basins including the Nenjiang River Basin(NJ), Downstream Songhua River Basin(SD) and Upstream Songhua River Basin(SU). Snow cover duration(SCD) was derived from flexible multiday combination each year. The results showed that SCD was significantly associated with elevation, and higher SCD values were found out in the mountainous areas. Further, the average SCDs of NJ, SU and SD basins were 69.43, 98.14 and 88.84 d with an annual growth of 1.36, 2.04 and 2.71 d, respectively. Binary decision tree was used to analyze the nonlinear relationships between SCD and six impact factors, which were successfully applied to simulate the spatial distribution of depth and water equivalent of snow. The impact factors included three topographic factors(elevation, aspect and slope), two climatic factors(precipitation and air temperature) and one vegetation index(Normalized Difference Vegetation Index, NDVI). By treating yearly SCD values as dependent variables and six climatic factors as independent variables, six binary decision trees were built through the combination classification and regression tree(CART) with and without the consideration of climate effect. The results from the model show that elevation, precipitation and air temperature are the three most influential factors, among which air temperature is the most important and ranks first in two of the three studied basins. It is suggested that SCD in the mountainous areas might be more sensitive to climate warming, since precipitation and air temperature are the major factors controlling the persistence of snow cover in the mountainous areas.

A basal area increment model for individual trees in mixed continuous cover forests in Iranian Caspian forests

The aim of this study was to develop and test a new basal area growth model in mixed species continuous cover forests in northern Iran.Weanalyzed 421 core samples from 6 main species in the forest area to develop our growth model.In each plot,we measured variables such as total tree height(m),diameter at breast height(DBH)(cm)and basal area of larger trees as cumulative basal areas of trees(GCUM)ofDBH[5 cm.The empirical data were analyzed using regression analysis.There was a statistically significant nonlinear function between the annual basal area increment,as the dependent variable,and the basal area of the individual trees and competition as explanatory variables.Reference area from the largest trees,was circular plot with area of 0.1 ha.GCUM was estimated for trees of DBH>5 cm.Furthermore,we investigated the dependencies of diameter growth of different species on stand density at different levels of competition,and diameter development of individual trees through time.The results indicate that competition caused by larger neighborhood trees has a negative effect on growth.In addition,the maximum diameter increment is affected by competition level.Therefore,the maximum diameter increment of species occurs when the trees are about 35–40 cm in dense-forest(40 to 0 m^2 per ha)and when the trees are about 60 to 70 cm in very dense forest(60 to 0 m^2 per ha)which is more likely to Caspian natural forests with high level density due to uneven-aged composition of stands.

基于覆盖树的自适应均值漂移聚类算法

为解决均值漂移聚类算法聚类效果依赖于带宽参数的主观选取,以及处理密度变化大的数据集时聚类结果精确度问题,提出一种基于覆盖树的自适应均值漂移聚类算法MSCT(MeanShift based on Cover-Tree)。构建一个覆盖树数据集,在计算漂移向量过程中结合覆盖树数据集获得新的漂移向量结果KnnShift,在不同数据密度分布的数据集上都能自适应产生带宽参数,所有数据点完成漂移过程后获得聚类结果。实验结果表明,MSCT算法的聚类效果整体上优于MS、DBSCAN等算法。

一种适用于大图的k步可达性查询算法

k步可达查询用于在给定的有向无环图(Directed Acyclic Graph,DAG)中回答两点之间是否存在长度不超过k的路径。针对现有方法的索引规模大、查询处理效率低的问题,提出了一种构建在大图上的基于树覆盖的倍增索引来提高索引查询效率,并结合GRAIL算法和改进的FELINE算法对本身就不可达查询点对进行剪枝。基于19个真实的数据集进行了实验测试,并将所提算法与现有算法在构建索引大小、索引时间、查询时间3个指标上进行了实验对比。实验结果验证了所提算法的高效性。

基于三参数阈值分割的露天矿山土地遥感分类方法

传统的单机遥感影像处理模式效率低,难以满足对全球任意地区矿山土地覆被快速分类的需求。本文基于遥感云计算平台,开发了三参数阈值分割分类方法,并选取全球9处露天矿山完成了验证。结果表明:1)NDVI、NDWI和NDBI 3个遥感指数是矿山土地覆被的敏感性指标,可有效区分矿山土地覆被类型;2)基于遥感云计算平台和三参数阈值分割方法可以实现全球任意矿山的土地覆被快速分类,三参数阈值分割方法的总体精度高于监督分类的总体精度;3)三参数阈值分割方法分类结果的边界清晰,分类准确度的排序为裸土>森林>水体>裸岩>灌草,分割阈值对不同地球气候带的矿山具有适应性。总体来看,该方法可以有效实现不同地区矿山土地覆被的快速分类,为实现全球矿山土地覆被整体监测提供一种新的方法。

基于FP-tree目录分割自适应算法

研究面向顾客的商业智能目录分割问题,要求顾客对收到的目录至少有兴趣度t,并评估满足最小兴趣度的顾客数量.为优化评估效果,构建频繁模式树结构FP-tree存储顾客数据库,给出MCC-CS算法解决目录分割问题,该算法使用树深度遍历法选择目录产品.经验证,该算法能够获得更好的商业目标.

Effects of stand characteristics on tree species richness in and around a conservation area of northeast Bangladesh

We investigated the effect of tree cover,forest patch and disturbances on tree species richness in a highly diverse conservation area of northeast Bangladesh.A systematic sampling protocol was adopted and 80 sub-plots from twenty five 1 ha plots were used for the vegetation survey.Linear regression analysis was performed to understand the effect of patch area,disturbances and tree cover on tree species richness.Ordination using Redundancy analysis(RDA) and Non-metric Multi Dimensional Scaling(NMDS) were also performed to explore the tree species compositional similarities along the stand characteristics gradient and locations of the sample plots.Our study revealed that,forest patch size has greater influence on species richness.Areas with medium level of disturbances have shown greater species richness.In constrained ordination the selected explanatory variables regulated the richness of common species.Our findings can be useful for better forest management and restoration of landscapes of conservation needs using ecologically important species.

Periodic Bifurcations in Descendant Trees of Finite <i>p</i>-Groups

Theoretical background and an implementation of the p-group generation algorithm by Newman and O’Brien are used to provide computational evidence of a new type of periodically repeating patterns in pruned descendant trees of finite p-groups.

Overview of priorities,threats,and challenges to biodiversity conservation in the southern Philippines

Human activities have severely impacted on many species and ecosystems.Thus,understanding the local biodiversity situation is crucial for implementing effective biodiversity conservation interventions.Mindanao in the southern Philippines is home to various unique species,particularly in its pristine ecosystems.However,the available biodiversity data for many terrestrial vertebrates and key areas remain incomplete.To address this issue,we synthesized published literature related to biodiversity from 2000 to 2022 in Mindanao.Moreover,this analysis used four key terrestrial vertebrates(amphibians,reptiles,birds,and mammals)in Mindanao as research objects.According to our findings,there was a significant and positive correlation between the number of biodiversity studies and species recorded.In terms of species richness,birds were the most recorded group(n=334 spp.),followed by reptiles(n=108 spp.),mammals(n=70 spp.),and amphibians(n=52 spp.).We also found that the number of endemic and threatened species varies geographically and across taxonomic groups.Yet,we discovered a significant disparity in the information available on biodiversity in different provinces of Mindanao.For example,the western provinces of Mindanao have had no record of biodiversity for more than two decades.Furthermore,we found that the changes in tree cover loss were consistent with biodiversity records,but this correlation is only significant for birds.Finally,we highlighted some critical threats and challenges to biodiversity,including deforestation,agricultural expansion,mining,and their impact on biodiversity conservation in Mindanao.Our findings suggested that biodiversity conservation should focus not only on areas with high levels of biodiversity but also on areas lacking biodiversity information.To do this,we call for strengthening collaboration among various institutions and digitizing and centralizing of information related to biodiversity.By gaining a deeper understanding of biodiversity in Mindanao,we can better and sustainably protect critical ecosystems in this region from the increasing threats posed by human activities.

Which trees should be removed in thinning treatments?

Background： In economically optimal management, trees that are removed in a thinning treatment should be selected on the basis of their value, relative value increment and the effect of removal on the growth of remaining trees. Large valuable trees with decreased value increment should be removed, especially when they overtop smaller trees. Methods： This study optimized the tree selection rule in the thinning treatments of continuous cover managemen when the aim is to maximize the profitability of forest management. The weights of three criteria （stem value, relative value increment and effect of removal on the competition of remaining trees） were optimized together with thinning intervals. Results and conclusions： The results confirmed the hypothesis that optimal thinning involves removing predominantly large trees. Increasing stumpage value, decreasing relative value increment, and increasing competitive influence increased the likelihood that removal is optimal decision. However, if the spatial distribution of trees is irregular, it is optimal to leave large trees in sparse places and remove somewhat smaller trees from dense places. However, the benefit of optimal thinning, as compared to diameter limit cutting is not usually large in pure one-species stands. On the contrary, removing the smallest trees from the stand may lead to significant （30-40 %） reductions in the net present value of harvest incomes.

Rubber Tree Distribution Mapping in Northeast Thailand

In many parts of mainland Southeast Asia rubber plantations are expanding rapidly in areas where the crop was not historically found. Monitoring and mapping the distribution of rubber trees in the region is necessary for developing a better understanding of the consequences of land-cover and land-use change on carbon and water cycles. In this study, we conducted rubber tree growth mapping in Northeast Thailand using Landsat 5 TM data. A Mahalanobis typicality method was used to identify different age rubber trees. Landsat 5 TM 30 m non-thermal reflective bands, NDVI and tasseled cap transformation components were selected as the model input metrics. The validation was carried out using provincial level agricultural statistical data on the rubber tree growth area. At regional (Northeast Thailand) and provincial scales, the estimates of mature and middle-age rubber stands produced from 30 m Landsat 5 TM data compared well (high statistical significance) with the provincial rubber tree growth statistical data.

ZS70-2高效植树机的设计与研制

随着我国西部土地荒漠化问题日趋严重,植树造林、提高森林覆盖率迫在眉睫。为此,针对南疆的土地特点,研发了一种针对荒漠化土壤的ZS70-2高效植树机,并对机架、开沟装置、覆土镇压装置等关键部件进行设计分析与建模,利用ANSYS软件对开沟装置中犁刀进行静力学分析,得出其最大应力和应变位置。该植树机集开沟、投苗、覆土镇压等作业于一体,结构简单、工作可靠,作业生产效率≥2.5 hm^(2)/h,可实现大面积连续植树作业,在节省人力物力的同时,大大提高了植树作业效率。

LIMSUP DEVIATIONS ON TREES

The vertices of an infinite locally finite tree T are labelled by a collection of i.i.d. real random variables {Xσ}σ∈T which defines a tree indexed walk Xr. We introduce and study theoscillations of the walk:where Φ(n) is an increasing sequence of positive numbers. We prove that for each $ belonging to a certain class of sequences of different orders, there are ξ 's depending on Φ such that 0 < OSCΦ(ξ) <∞. Exact Hausdorff dimension of the set of such ξ's is calculated. An application is given to study the local variation of Brownian motion. A general limsup deviation problem on trees is also studied.

HY-1C/DCZI多光谱影像云覆盖与耀斑区域绿潮自动提取方法研究

针对多光谱影像受云、雾、太阳耀斑等因素的影响,难以实现高精度的绿潮自动提取的问题,本文以我国的HY-1C/D卫星CZI载荷多光谱影像为数据源,采用数据挖掘技术,通过探索绿潮区域与非绿潮区域的光谱分布差异,提出一种适用于HY-1C/DCZI影像的高精度、全自动绿潮提取方法。首先,分析有云区域和无云区域样本的光谱差异,给出厚云去除规则;其次,选取绿潮和非绿潮区域的样本,采用决策树算法生成绿潮提取规则;然后,针对薄云和厚云边界区域常常会出现误检绿潮的问题,设计了5种错误类别修正策略。为验证方法的有效性,收集2021年黄海区域绿潮暴发周期内的25景HY-1C/D CZI影像,开展绿潮自动检测实验。结果表明,与传统的NDVI方法、VB-FAH方法等指数方法以及ResNet50、U-Net等深度学习方法相比,本文方法在准确度、Kappa系数、F1-Score和MIoU等指标上均优于其他方法,而且能够实现在厚云、薄云、无云、云斑和耀斑区域复杂情况下的绿潮的高精度自动提取。

树的零度与路覆盖数的关系

图的零度是指图G的邻接矩阵A(G)零空间的维度,亦等于其零特征值的重数,用η(G)表示.图的路覆盖是指图G中一组顶点不相交的诱导路的集合,使G的每个顶点都是其中一条路的顶点,G的路覆盖数是指G的最小路覆盖,用ρ(G)表示.2021年Wang给出了图G的零度与路覆盖数的关系:η(G)≤ρ(G),本文刻画了所有满足η(G)=ρ(G)的树.

汽油发动机前盖异响分析研究

本文主要对发动机前盖异响问题进行了研究。通过对发动机零部件结构的深入分析,结合红叉质量工具的应用,得出了前盖异响的主要原因和次要原因,并找到了零部件本体引起异响的尺寸及其后续的控制要求,为生产线解决零部件尺寸问题提供了方法和思路,达到了快速响应问题解决的目的,也为工厂提高产品质量做出了贡献。