Fuzzy C-Means Algorithm Based on Density Canopy and Manifold Learning

Fuzzy C-Means(FCM)is an effective and widely used clustering algorithm,but there are still some problems.considering the number of clusters must be determined manually,the local optimal solutions is easily influenced by the random selection of initial cluster centers,and the performance of Euclid distance in complex high-dimensional data is poor.To solve the above problems,the improved FCM clustering algorithm based on density Canopy and Manifold learning(DM-FCM)is proposed.First,a density Canopy algorithm based on improved local density is proposed to automatically deter-mine the number of clusters and initial cluster centers,which improves the self-adaptability and stability of the algorithm.Then,considering that high-dimensional data often present a nonlinear structure,the manifold learning method is applied to construct a manifold spatial structure,which preserves the global geometric properties of complex high-dimensional data and improves the clustering effect of the algorithm on complex high-dimensional datasets.Fowlkes-Mallows Index(FMI),the weighted average of homogeneity and completeness(V-measure),Adjusted Mutual Information(AMI),and Adjusted Rand Index(ARI)are used as performance measures of clustering algorithms.The experimental results show that the manifold learning method is the superior distance measure,and the algorithm improves the clustering accuracy and performs superiorly in the clustering of low-dimensional and complex high-dimensional data.

Optimal Operation Strategy Analysis with Scenario Generation Method Based on Principal Component Analysis,Density Canopy,and K-medoids for Integrated Energy Systems

The operation of integrated energy systems(IESs)is confronted with great challenges for increasing penetration rate of renewable energy and growing complexity of energy forms.Scenario generation is one of ordinary methods to alleviate the system uncertainties by extracting several typical scenarios to represent the original high-dimensional data.This paper proposes a novel representative scenario generation method based on the feature extraction of panel data.The original high-dimensional data are represented by an aggregated indicator matrix using principal component analysis to preserve temporal variation.Then,the aggregated indicator matrix is clustered by an algorithm combining density canopy and K-medoids.Together with the proposed scenario generation method,an optimal operation model of IES is established,where the objective is to minimize the annual operation costs considering carbon trading cost.Finally,case studies based on the data of Aachen,Germany in 2019 are performed.The results indicate that the adjusted rand index(ARI)and silhouette coefficient(SC)of the proposed method are 0.6153 and 0.6770,respectively,both higher than the traditional methods,namely K-medoids,K-means++,and density-based spatial clustering of applications with noise(DBSCAN),which means the proposed method has better accuracy.The error between optimal operation results of the IES obtained by the proposed method and all-year time series benchmark value is 0.1%,while the calculation time is reduced from 11029 s to 188 s,which verifies that the proposed method can be used to optimize operation strategy of IES with high efficiency without loss of accuracy.

Factorial analysis on forest canopy density restoration in the burned area of northern Great Xing＇an Mountains, China

The restoration of forest landscape has drawn much attention since thecatastrophic fire took place on the northern slope of Great Xing'an Mountains in 1987. Forest canopydensity, which has close relation to forest productivity, was selected as a key factor to find howmuch the forest quality was changed 13 years after fire, and how fire severity, regeneration way andterrain factors influenced the restoration of forest canopy density, based on forest inventory datain China, and using Kendall Bivariate Correlation Analysis, and Distances Correlation Analysis. Theresults showed that fire severity which was inversely correlated with forest canopy density gradewas an initial factor among all that selected. Regeneration way which did not remarkably affectforest canopy density restoration in short period, may shorten the cycle of forest succession andpromote the forest productivity of conophorium in the future. Among the three terrain factors, theeffect of slope was the strongest, the position on slope was the second and the aspect was the last.

Estimating canopy closure density and above-ground tree biomass using partial least square methods in Chinese boreal forests

Boreal forests play an important role in global environment systems. Understanding boreal forest ecosystem structure and function requires accurate monitoring and estimating of forest canopy and biomass. We used partial least square regression （PLSR） models to relate forest parameters, i.e. canopy closure density and above ground tree biomass, to Landsat ETM＋ data. The established models were optimized according to the variable importance for projection （VIP） criterion and the bootstrap method, and their performance was compared using several statistical indices. All variables selected by the VIP criterion passed the bootstrap test （p〈0.05）. The simplified models without insignificant variables （VIP 〈1） performed as well as the full model but with less computation time. The relative root mean square error （RMSE%） was 29% for canopy closure density, and 58% for above ground tree biomass. We conclude that PLSR can be an effective method for estimating canopy closure density and above ground biomass.

Effects of forest canopy density and epixylic vegetation on nutrient concentrations in decaying logs of a subalpine fir forest

Background:Deadwood and the associated epixylic vegetation influence nutrient cycles in forest ecosystems.Open canopies strongly regulate deadwood decomposition and disrupt epixylic vegetation on logs.However,it is unclear how the forest canopy density and epixylic vegetation growth affect the nutrient concentrations in deadwood.Methods:We measured the concentrations of nitrogen(N),phosphorus(P),potassium(K),calcium(Ca),sodium(Na),magnesium(Mg),and manganese(Mn)in experimentally exposed decaying logs placed in gaps,at the edge of gaps,and under the closed canopy during a four-year decomposition experiment in a Subalpine Faxon fir forest(Abies fargesii var.faxoniana)on the eastern Qinghai-Tibetan Plateau,China.To assess the effect of the epixylic vegetation,we experimentally removed it from half of the logs used in the study.Results:Under open canopy conditions in the gap and at the edge,the concentrations for most of the nutrients in the bark and the highly decayed wood were lower than under the closed canopy.The effect of the epixylic treatment on nutrient concentrations for all but K and Na in barks varied with the decay classes.Significantly lower concentrations of N,P,Ca,and Mn following the removal of epixylic vegetation were observed in the wood of decay class IV.Epixylic vegetation significantly increased most nutrient concentrations for decaying barks and wood under open canopy conditions.In contrast,epixylic vegetation had no or minimal effects under the closed canopy.Conclusions:Forest canopy density and epixylic vegetation significantly alter the nutrient concentrations in decaying logs.Open canopies likely accelerate the rate of nutrient cycling between the epixylic vegetation and decaying logs in subalpine forests.

The Status of Canopy Density and above Ground Biomass along the Northern Coastal Forest Zone of Tanzania

Canopy density and forest biomass estimation are critical for understanding of the carbon cycle, climate change and detecting health status of the forest ecosystems. This study was conducted on the coastal forests reserves in Zanzibar and mainland Tanzania. A systematic sampling design was used to establish a total of 110 temporary sample plots in all study sites. The stratification of the forests was adopted to identify closed forest patches with less anthropogenic effects. The study assessed the forest canopy density and above ground biomass with relative carbon stock for closed forest classes. Jozani Chwaka Bay National Park in Zanzibar recorded higher average canopy densities of 63% followed by Ngezi (46%), Pugu forests (26%) and Kazimzumbwi (16%). However, Ngezi forest had higher forest biomass than all study sites with the overall mean AGB of 138.5 tAGB/ha equivalent to carbon stock of 67.9 tC/ha. Tree species, Bombax rhodognaphala (Msufi mwitu) and Antiaris toxicaria (Mgulele) recorded the highest biomass of 1099 tABG/ha and 703 tAGB/ha (equivalent to 538 tC/ha and (345 tC/ha)) respectively. The study revealed that about 35% of the total closed forest patches at Pugu FR were covered by lower canopy density which accounted about 490 ha. Kazimzumbwi FR was dominated by lower canopy density which represented about 64% of the total forest cover area (1750 ha).

Characterization of Forest Degradation beyond Canopy Cover Change in Mau Forest, Kenya

Monitoring Forest degradation is evidence enough to show a country’s commitment to monitor the forest trend both for national and local decision-making and international reporting processes. Unlike deforestation which is easier to point out, monitoring forest degradation is quite a challenge since there is no universal definition and thus no clear monitoring methods apart from the canopy cover change. This research, therefore, sought to look at the degradation trends in the Mau forest complex between 1995-2020 with the aim of finding out whether monitoring canopy density changes over time and quantifying these changes in terms of biomass loss could be a good approach in monitoring forest degradation. Forest Canopy Density (FCD) model was adopted focusing on using vegetation indices describing biophysical conditions of Vegetation, Shadow and Bareness to monitor changes in canopy density as a parameter for describing forest degradation in the forest blocks of Maasai Mau and Olpusimoru in Mau forest complex. Results indicated how different vegetation indices responded to changes in the vegetation density and eventually changes in the canopy density values which were converted in terms of biomass loss. The forest Canopy Density model proved to be a good tool for monitoring forest degradation since it combines different biophysical indices with different characteristics capturing what is happening below the canopy.

Effect of micro-environmental factors on natural regeneration of Sal (Shorea robusta)

factors viz., soil moisture and light in- tensity are important factors that affect natural regeneration in forests. These factors vary spatially depending on the overhead canopy density of the forest. The present study focused on studying the effect of variation of soil moisture and light intensity on natural regeneration of sal species （Shorea robusta） under different micro-environments due to overhead canopy of varying forest density. Experimental plots of 40m× 40m size were laid under different overhead canopy densities in a small sal forested watershed in the foot hills of Himalayas in Nainital District of Uttarakhand State, India. The plots were monitored on a long term basis for soil moisture at multi depths, light intensity and natural regeneration of sal. The results of the study revealed that the natural regeneration was highest under C1 （up to-0.30） canopy followed by C2 （0.30-0.50）, and C3 （0.50-0.70） canopies. The C3 canopy showed the dying back of sal shoots over 4 years of study. The highest R2 value of linear regression between incremental score of plot regeneration and average soil moisture content was obtained as 0.156 for average soil moisture content during months at 100 cm depth. The R2 value between incremental score of plot regeneration and annual average light intensity was obtained as 0.688 which indicated that the regeneration is largely dependent on the light intensity conditions during the year. The multiple linear regression analysis between the incremental score of regeneration and the average light intensity and average soil moisture content revealed that that about 80% of variation in regeneration is explained by both the factors.

Influence of environmental predispositions on temperate mountain forest damage at different spatial scales during alternating drought and flood periods:case study in Hruby Jeseník Mts.(Czech Republic)

Mountain forests are more prone to environmental predispositions(EPs)than submountain ones.While remote sensing of mountain forests enables instantaneous damage mapping,the investigation of the causes requires field data.However,a local field or regionally modeled environmental characteristics influence remote data evaluation differently.This study focused on the evaluation of EPs effects damaging mountain forests between various spatial resolutions during environmental change.The evaluation was divided into managed and natural forests in the Hruby Jeseník Mts.(Czech Republic;240-1491 m a.s.l.;50.082°N,17.231°E).Damage was assessed through the discrimination analysis of the normalised difference vegetation index(NDVI)by MODIS VI during alternating drought and flood periods 2003-2014.The local environmental influence was assessed using the discrimination function(DF)separability of forest damage in the training sets.The regional influence was assessed through map algebra estimated via the DF and a forest decline spatial model based on EPs from differences between risk growth conditions and biomass fuzzy sets.Management,EPs and soil influenced forest NDVI at different levels.The management afflicted the NDVI more than the EPs.The EPs afflicted the NDVI more than the soil groups.Strong winters and droughts had a greater influence on the NDVI than the flood events,with the winter of 2005/2006 inverting the DF direction,and the 2003 drought increasing differences in managed forest biomass and decreasing differences in natural forest biomasses.More than 50% of declining managed forests in the training sets occurred on Leptosols,Podzols and Histosols.On a regional scale,the soil influence was eliminated by multiple predispositions.The EPs influenced 96% of natural forest and 65% of managed forest,though managed forest damage was more evident.The mountain forest NDVI decline was dependent on both management and risk predispositions.

Compound Planting of Bletilla striata under Forest in the Three Gorges Dam Area

[Objectives] The aim was to study the artificial cultivation of Bletilla striata to realize large scale and standardization planting. [Methods] The comparison tests were conducted on B. striata with different canopy densities of the Magnolia officinalis forests,different compound planting densities and different tending measures and management. [Results] When the stand canopy density was 0. 4-0. 6,the per unit yield of B. striata was 5. 4%,6. 8% higher than that at the canopy density of less than 0. 4 and more than 0. 6,respectively. When the planting density was 30 cm × 30 cm,the per unit yield increased by 16. 1%,12. 0%,13. 1% respectively compared with the planting density of 20 cm × 20 cm,25 cm × 25 cm,35 cm × 35 cm. When B. striata was planted from October to November,the per unit yield was 5. 6% higher than that planted from December to January of the following year,and 21. 3% higher than that from February to March of the second year. When farmyard manure was applied during the cultivation,the per unit yield was 31. 7% and 18. 4% higher than the application of chemical fertilizer and compound fertilizer. When weeding 4 times per year,the per unit yield increased by 240. 1%,137. 0% and 43. 9% respectively from that weeding 1 times,2 times,3 times per year. [Conclusions]When planting B. striata,the stand canopy density of 0. 4-0. 6 could make it receive absolutely shelters and the lighting conditions required for the growth,thereby bringing in high emergence rate,good growth potential and high yield. The best planting effect of B. striata could achieve by planting from October to November with the planting density of 30 cm × 30 cm,which can play the maximum benefit of individual plants. Moreover,weeding 4 times per year combined with the use of farmyard manure can promote the development and growth of tubers,which can greatly improve the yield of B. striata.

Development of a modified thermal humidity index and its application to human thermal comfort of urban vegetation patches

Extremely hot environments can trigger serious health problems.To evaluate the effects of microclimate on thermal comfort,we proposed and validated a modified thermal humidity index(MTHI)that combined air temperature and relative humidity with land surface temperature(LST).MTHI was more sensitive to microclimate changes than the general thermal humidity index that includes only T and RH,and thus the thermal comfort could be better indicated.In an urban riparian buffer study,we estimated the temporal dynamics and spatial distribution of MTHI values for 47 vegetation patches and explored how structural characteristics of patches affect the thermal comfort.The results showed that planting could significantly reduce LST and MTHI.Vegetation patches with complex vertical structures had considerably higher thermal comfort than those with simple structures.Decreasing nearest distance to river or increasing plant abundance could reduce the thermal discomfort.There were significant differences in the structure characteristics between the patches with MTHI<70 and those with MTHI>70,implying the critical thresholds of variations in thermal comfort with patch structure.Given that people always feel uncomfortable during the daytime in July,optimizing the patch structure is essential to improve the microclimate regulation services of an urban landscape.

Droplets deposition and harvest-aid efficacy for UAV application in arid cotton areas in Xinjiang,China

With the development of Unmanned Aerial Vehicle(UAV)sprayers,the application of low-volume spraying of harvest-aid and other agrochemicals to cotton using UAVs is becoming a new agronomic trend worldwide.The effect of spray volume and canopy density for UAV spraying is significant but was rarely studied.In this study,five representative spray volumes were explored to examine the effect of spray volume on deposition and harvest-aid efficacy for cotton using a UAV sprayer.To explore the effect of canopy density,similar tests were carried out in a field located nearby with a lower leaf area index(LAI).A conventional trailer boom sprayer was selected for comparison.Different spray volumes had a significant effect on defoliation,but had no significant effect on boll opening and fiber quality.A higher defoliation rate was achieved in the lower LAI field.The total rate of defoliation using the UAV was inferior to the boom sprayer in the high LAI field for lower deposition and defoliation rate in the lower canopy.Considering the deposition,defoliation rate,and working efficiency,a spray volume of 15.0 L/hm^(2) with an average droplet size of 150μm is recommended for UAV application.