Exploring the Forest Cover Changes and Influential Factors of Dongsithouane National Production Forest Area, Savannakhet Province, Lao PDR

The Dongsithouane National Production Forest (DNPF) is one of the largest natural forest areas in Savannakhet, Lao PDR, which has been a vital support for the local community’s livelihood, Recently, significant changes in land use and land cover (LULC) have been observed in this area, leading to a reduction of natural forests. There were two separate methods of this study: firstly, to identify LULC changes across three different periods, spectral imagery from the Landsat 5 Thematic Mapper (TM) for the years 2001 and 2011, and the Landsat 8 Operational Land Imager (OLI) for 2021 were used as the primary data sources. The satellite images were preprocessed for various forest classes, including pretreatment of the top of atmosphere reflectance by using QGIS software’s semi-automatic classification plug-in (SCP), and ArcGIS was used for post-classification. A supervised classification approach was applied to the satellite images from 2001, 2011, and 2021 to generate diverse maps of LULC. Secondly, a household survey dataset was used to investigate influential factors. Approximately 220 households were interviewed in order to collect socio-economic information (including data on population growth, increased business activities, location of the area, agriculture land expansion, and need for settlement land). Household survey data was analyzed by using SPSS. Descriptive statistics, including frequency distributions and percentages, were applied to observe characteristics. Additionally, a binary logistic regression model was used to analyze the socioeconomic factors related to LULC change in DNPF. Key findings indicated a decline in natural forest areas within the study site. Specifically, both dry dipterocarp forest (−11.35%) and mixed deciduous forest (−0.18%) decreased from 2001 to 2021. The overall accuracy of the LULC maps was 94%, 86%, and 89% for the years 2001, 2011, and 2021 respectively. In contrast, agricultural land increased significantly by 155.70%, while built-up land, and water bodies increased by 65.54% and 35.33%, respectively. The results also highlighted a significant increase in construction land, up to 65.54%. Furthermore, the study found a correlation between agricultural expansion and a reduction of forest areas, along with an increase in built-up land along the forest areas’ boundaries. Timber exploitation and charcoal production also contributed to the decline in forest cover. The logistic regression model identified significant determinants of LULC change, including the area’s location, agricultural land expansion, increased business activity, and the need for settlement land. These factors have influenced the management of DNPF. Urgent sustainable management practices and actions, including forest ecosystem protection, village agricultural zoning, water source and watershed protection and public awareness, are required to preserve the forest areas of DNPF.

NUMERICAL SIMULATION OF THE INFLUENCE OF VEGETATION COVER FACTOR ON BOUNDARY LAYER CLIMATE IN SEMI-ARID REGION

A numerical model has been developed for simulating land-surface processes and atmospheric boundary layer climate of vegetation and desert in semi-arid region.Dynamically,thermal and hydrological processes take place in the atmospheric boundary layer.Vegetation and surface layer of soil are included in the soil-vegetation-atmosphere coupled system,in which,vegetation is considered as a horizontally uniform layer,soil is divided into 13 layers and the horizontal differences of variables in the system are neglected.The influence of local boundary layer climate by vegetation cover factor is simulated with the coupled model in the semi-arid region of Northwest China (around 38°N,105°E).Results indicate that due to significant differences of water and energy budgets in vegetation and desert region,the air is colder and wetter over the vegetation and correspondingly an obvious local circulation in the lower atmosphere is formed. Simulating results also show that maximum updraft and downdraft occur around the vegetation-desert marginal area,where the dynamical and thermodynamical properties of PBL (Planetary Boundary Layer) are uncontinuous.It is stronger at daytime,weaker and reverse at nighttime.In the simulation,the moisture inversion phenomena are analyzed.Finally.the influences of vegetation cover factor exchange on local boundary layer climate are simulated.The simulating results bring to light that water may be conserved and improved by developing tree planting and afforestation,and improving cover factor of vegetation in local ecoenvironment,and this is an important way of transforming local climate in arid and semi-arid area.Results indicate that the coupled model can be used to study the soil-vegetation-atmosphere interaction and local boundary layer climate.

Analysis of PM2.5 concentrations in Heilongjiang Province associated with forest cover and other factors

Atmospheric particulate matter(PM2.5) seriously influences air quality. It is considered one of the main environmental triggers for lung and heart diseases. Air pollutants can be adsorbed by forest. In this study we investigated the effect of forest cover on urban PM2.5 concentrations in 12 cities in Heilongjiang Province,China. The forest cover in each city was constant throughout the study period. The average daily concentration of PM2.5 in 12 cities was below 75 lg/m^3 during the non-heating period but exceeded this level during heating period. Furthermore, there were more moderate pollution days in six cities. This indicated that forests had the ability to reduce the concentration of PM2.5 but the main cause of air pollution was excessive human interference and artificial heating in winter. We classified the 12 cities according to the average PM2.5 concentrations. The relationship between PM2.5 concentrations and forest cover was obtained by integrating forest cover, land area,heated areas and number of vehicles in cities. Finally,considering the complexity of PM2.5 formation and based on the theory of random forestry, we selected six cities and analyzed their meteorological and air pollutant data. The main factors affecting PM2.5 concentrations were PM10,NO_2, CO and SO_2 in air pollutants while meteorological factors were secondary.

Correlation between Climate Factors and Vegetation Cover in Qinghai Province, China

The Qinghai Province, situated in the northwest of China, is experiencing a continuous warming which is approximately three times more than the rate of global warming. This ongoing warming has a direct connection to vegetation cover, with significant societal and economic impacts in this region. In the present study, we investigate the correlation between climate change and vegetation cover in Qinghai Province. Analysis shows that in the Qinghai Province, order of NDVI is highest in summer followed by autumn, spring and winter. By calculating the average annual and seasonal-NDVI values, it is deduced that the main type of vegetation cover in the Qinghai Province has an upward trend at the rate of 0.013/10a, 0.016/10a, 0.035/10a and 0.058/10a for annual, winter, spring and summer, respectively. While a downward trend at a rate of 0.056/10a is present in autumn-NDVI. At the 0.01% significance level, a significant positive relationship of winter-NDVI with mean winter precipitation and temperature is revealed. Mean NDVI of spring and autumn show a significant positive relationship with respective seasonal mean precipitation. However, a significant difference is present between mean summer-NDVI and mean summer precipitation. Furthermore, mean NDVI of summer and autumn has a significant negative relationship with respective seasonal mean temperature.

Change of Vegetation Cover and Its Relationships with Climatic Factors in Large-area Eucalyptus Introduced Region of Yunnan

Taking Lancang County as a study area with a large area of eucalyptus introduction in Yunnan, spatiotemporal change characteristics of vegetation cover, as well as the relationships between Enhanced Vegetation Index（EVl） and climatic factors （temperature and precipitation） were analyzed by using the data of MODIS-EVI from 2005 to 2010. The results indicated that： （1） The vegetation cover was overall good, and the annual average values of EVl were greater than 0.395 and showed a slow increasing trend from 2005 to 2010 in study area; the monthly average values of EVl ranged from 0.296 to 0.538, and seasonal variability was obvious. Monthly average values of EVl usually fell to the lowest level in February and March, and reached the peak in July and August. From the perspective of space, average EVl over the years significantly varied in different towns of Lancang County. During 2005 -2010, in 92.534% area of total, vegetation coverage change were not obvious; in 7.25% area of total, vegeta- tion becoming better; only in 0.02% area of total, vegetation cover were getting worse. （2） Monthly average values of EVl were significantly correlated with monthly average rainfall in Lancang County. The maxima of monthly average EVI and rainfall appeared in August on summer, while the minima of monthly average EVl and rainfall appeared in February and January on winter respectively. （3） Monthly average EVl was somewhat relative with monthly average temperature. The maxima of monthly average EVl and temperature appeared in June and August respectively, while the minima appeared in January and February respectively.

Land Use/Land Cover Dynamics and Anthropogenic Driving Factors in Lake Baringo Catchment, Rift Valley, Kenya

Anthropogenic activities have altered land cover in Lake Baringo Catchment contributing to increased erosion and sediment transport into water bodies. The study aims at analyzing the spatial and temporal Land Use and Land Cover Changes (LULCC) changes from 1988 to 2018 and to identify the main driving forces. GIS and Remote Sensing techniques, interviews and field observations were used to analyze the changes and drivers of LULCC from 1988-2018. The satellite imagery was selected from SPOT Image for the years 1988, 1998, 2008 and 2018. Environment for Visualizing Images (ENVI 5.3) was used to perform image analysis and classification. The catchment was classified into six major LULC classes which are water bodies, settlement, rangeland, vegetation, farmland and bare land. The results revealed that, between the years 1988-1998, and 1998-2008, water bodies decreased by 2.77% and 0.76% respectively. However, during the years 2008-2018, water body coverage increased by 1.87%. Forest cover steadily increased from 1988-2018. From 1988-1998, 1998-2008 and 2008-2018, farmland was increased by 21.11%, 3.21% and 1.7% while rangeland decreased continuously between the years 1988-1998, 1998-2008 and 2008-2018 in the order 15.14%, 4.13% and 3.74% respectively. Similarly, bare land also reduced by 1.75%, 1.04% and 0.99% between the years 1988-1998, 1998-2008 and 2008-2018 respectively. The findings attributed LULCC to rapid population growth, deforestation, poor farming practices and overstocking. The results will provide valuable information to the relevant stakeholders to formulate evidence-based land use management strategies in order to achieve ecological integrity.

Analysis on the Climatic Change Characteristics of the Snow Cover Days and Its Influence Factors in Suzhou during Recent 50 Years

[Objective] The research aimed to study climatic variation characteristics of snow cover days and its influence factors in Suzhou of Anhui Province during recent 50 years. [Method] According to annual snow cover days and correlated data in Suzhou during 1961-2010, by using linear trend method, accumulative anomaly and complete correlation coefficient method, etc., the climatic variation characteristics of snow cover days and its influence factors in Suzhou were analyzed. [Result] In recent 50 years, the snow cover period in Suzhou presented shortened trend. Except days of snow cover (≥20 cm), the annual snow cover days at each thickness all showed varying degrees of decrease trend. The annual snow cover days had wavy decline trend, and the decline amplitude was 0.84 d/10 a. From the 1960s to prior period of the 1970s, the annual snow cover days presented increase trend. From middle and later periods of the 1970s to middle period of the 1980s, the snow cover days was less and gradually increased from later period of the 1980s to the early 1990s. From middle period of the 1990s to 2003, it entered into less snow period again. From 2004 to now, it presented oscillation of snowy and less-snow alternating. The main climatic factor which affected annual snow cover days in Suzhou was average temperature. The second one was average surface temperature. [Conclusion] The research provided theoretical basis for analyzing climate variation in Suzhou under the background of global climate warming.

Binding Number and Fractional k-Factors of Graphs

In this paper, we consider the relationship between the binding number and the existence of fractional k-factors of graphs. The binding number of G is defined by Woodall as bind(G)=min{ | NG(X) || X |:∅≠X⊆V(G) }. It is proved that a graph G has a fractional 1-factor if bind(G)≥1and has a fractional k-factor if bind(G)≥k−1k. Furthermore, it is showed that both results are best possible in some sense.

Estimation of USLE crop and management factor values for crop rotation systems in China

Soil erosion on cropland is a major source of environmental problems in China ranging from the losses of a non-renewable resource and of nutrients at the source to contamination of downstream areas. Regional soil loss assessments using the Universal Soil Loss Equation (USLE) would supply a scientiifc basis for soil conservation planning. However, a lack of in-formation on the cover and management (C) factor for cropland, one of the most important factors in the USLE, has limited accurate regional assessments in China due to the large number of crops grown and their complicated rotation systems. In this study, single crop soil loss ratios (SLRs) were col ected and quantiifed for 10 primary crops from past studies or re-ports. The mean annual C values for 88 crop rotation systems in 12 cropping system regions were estimated based on the combined effects of single crop SLRs and the percentage of annual rainfal erosivity (R) during the corresponding periods for each system. The C values in different cropping system regions were compared and discussed. The results indicated that the SLRs of the 10 primary crops ranged from 0.15 to 0.74. The mean annual C value for al 88 crop rotation systems was 0.34, with a standard deviation of 0.12. The mean C values in the single, double and triple cropping zones were 0.37, 0.36 and 0.28, respectively, and the C value in the triple zone was signiifcantly different from those in single and double zones. The C values of dryland crop systems exhibited signiifcant differences in the single and triple cropping system regions but the differences in the double regions were not signiifcant. This study is the ifrst report of the C values of crop rotation systems in China at the national scale. It wil provide necessary and practical parameters for accurately assessing regional soil losses from cropland to guide soil conservation plans and to optimize crop rotation systems.

Study of thermal properties of supraglacial debris and degree-day factors on Lirung Glacier,Nepal

The extensive debris that covers glaciers in the ablation zone of the Himalayan region plays an important part in regulating ablation rates and water availability for the downstream region. The melt rate of ice is determined by the amount of heat conducted through debris material lying over the ice. This study presents the vertical temperature gradients, thermal properties in terms of thermal diffusivity and thermal conductivity, and positive degree-day factors for the debris-covered portion of Lirung Glacier in Langtang Valley, Nepal Himalaya using field-based measurements from three different seasons.Field measurements include debris temperatures at different debris thicknesses, air temperature, and ice melt during the monsoon(2013), winter(2013), and pre-monsoon(2014) seasons. We used a thermal equation to estimate thermal diffusivity and thermal conductivity, and degree-day factors(DDF) were calculated from cumulative positive temperature and ice melt of the measurement period. Our analysis of debris temperature profiles at different depths of debris show the daily linear gradients of-20.81 °C/m, 4.05 °C/m, and-7.79 °C/m in the monsoon, winter, and pre-monsoon seasons, respectively. The values of thermal diffusivity and thermal conductivity in the monsoon season were 10 times greater than in the winter season. The large difference in these values is attributed to surface temperature and moisture content within the debris. Similarly, we found higher values of DDFs at thinner debris for the pre-monsoon season than in the monsoon season although we observed less melting during the pre-monsoon season. This is attributed to higher cumulative temperature during the monsoon season than in the pre-monsoon season. Our study advances our understanding of heat conductivity through debris material in different seasons, which supports estimating ice melt and discharge from glacierized river basins with debris-covered glaciers in the Himalayan region.

SOME CONDITIONS FOR f-COVERED GRAPHS

A graph G is f-covered if each edge of G belongs to an f-factor. Some sufficient conditions for a graph to be f-covered are given.Katerinis'and Bermond's results are generalized.

Minimizing N_20 fluxes from full-scale municipal solid waste landfill with properly selected cover soil

Municipal solid waste landfills emit nitrous oxide （N2O） gas. Assuming that the soil cover is the primary N2O source from landfills, this study tested, during a four-year project, the hypothesis that the proper use of chosen soils with fine texture minimizes N2O emissions. A full-scale sanitary landfill, a full-scale bioreactor landfill and a cell planted with Nerium indicum or Festuca arundinacea Schreb, at the Hangzhou Tianziling landfill in Hangzhou City were the test sites. The N2O emission rates from all test sites were considerably lower than those reported in the published reports. Specifically, the N2O emission rate was dependent on soil water content and nitrate concentrations in the cover soil. The effects of leachate recirculation and irrigation were minimal. Properly chosen cover soils applied to the landfills reduced N2O flux.

Investigation of Vegetation Cover Change in Sudan by Using Modis Data

The aim of this research paper is to investigate the land cover changes in Sudan during the period 2001-2013 by using the MODIS data and to identify climatic factors influencing the land cover. SPSS v 17 software was used to investigate the correlation of climatic factors with vegetation cover;also ArcGIS v 10.2 software was used to analyze the NDVI data. The results indicate that the monthly average time scale, NDVI value curve distribution during the year, July to October as the center to both sides of decreasing vegetation cover in other months. In the spatial distribution of mean NDVI in Sudan, a high value was found in the southern part. On the other hand, a low value of vegetation cover was found in northern part. NDVI spaces mean presenting features values: autumn followed by summer then winter. By calculation of average annual and seasonal-NDVI values, it was deduced that the main vegetation cover type was increasing in winter and summer seasons at the rates of 0.014/10a and 0.008/10a, respectively. While winter-NDVI was decreasing the rate of 0.001/10a and 0.026/10a in autumn and on the annual scale, respectively. Annual NDVI showed a significant degradation (area = 12705.7 km2, 0.5% of total area) in the middle and eastern parts and significant improvement (area = 22485.4 km2, 0.9 % of the total area) in the southern part of the country due to the increase in precipitation and decrease in temperature. Mean summer and autumn-NDVI showed a significant difference 0.01% significance level with mean summer and autumn precipitation (correlation coefficients = 0.955 and 0.953, respectively). While there was a significantly negative relationship between mean summer and autumn-NDVI with mean summer and autumn temperature at 0.01% significance level (correlation coefficients = −0.270 and −0.820, respectively).

On the ｛P_2,P_3｝-Factor of Cubic Graphs

Ler G = （ V, E） be a finite simple graph and Pn denote the path of order n. A spanning subgraph F is called a { P2, P3 }-factor of G if each component of F is isomorphic to P2 or P3. With the path-covering method, it is proved that any connected cubic graph with at least 5 vertices has a { P2, P3 }-factor F such that｜P3（F）｜P2（F）｜, where P2（F） and P3（F） denote the set of components of P2 and P3 in F, respectively.

Retrospective Analysis of Land Cover and Use Dynamics in Gilgel Abbay Watershed by Using GIS and Remote Sensing Techniques, Northwestern Ethiopia

This study was aimed at examining land cover changes for the last 35 years and its causative factors in Gilgel Abbay watershed by using GIS and remote sensing, survey and population data. The land use and cover changes study will help to apply the appropriate land use. The land cover/use status for the years 1973, 1986, 1995 and 2008 were examined using land sat images. The changes in different land cover units such as forest, wood and bush lands, grass, wetlands and water bodies, and farm and settlements were analyzed. Population change, tenure, poverty and lack of market and credit facilities in the watershed area were analyzed as causes of land cover changes. The results of the study have shown that during the last 35 years forest, grass lands, wetlands and lake areas were converted to farm and settlement areas. There was rapid increase of population with growth rates of 4.9% and 3.5% (1984-1994 and 1994-2007), respectively per annum which caused more land cover changes.

(g,f)-FACTORS WITH SPECIAL PROPERTIES IN BIPARTITE (mg,mf)-GRAPHS

Let G be a bipartite graph and g and f be two positive integer-valued functions defined on vertex set V(G) of G such that g(x)≤f(x).In this paper,some sufficient conditions related to the connectivity and edge-connectivity for a bipartite (mg,mf)-graph to have a (g,f)-factor with special properties are obtained and some previous results are generalized.Furthermore,the new results are proved to be the best possible.

Variations and Influence of Cloud Cover in Heze Region in Recent 52 Years

Based on the data of cloud cover, precipitation, temperature, sunshine hours and relative humidity from nine ground meteorological stations in Heze region in the southwest of Shandong Province from 1961 to 2012, changes of total and low cloud cover and its relationship with climatic factors associated in the southwest of Shandong Province in recent 52 years were analyzed. The results showed that average total cloud cover in- creased by 0.89%/10 a, but average low cloud cover decreased by 1.1%/10 a in Heze region in recent 52 years. The positive correlation between the average total cloud cover and temperature in autumn and winter was obvious, that is, when cloud cover increased by 10%, the average temper- ature increased by 0.48 ~C in autumn and increased by 0.83~（3 in winter. The average low. cloud cover negatively correlated with the average tam- perature in each season, and the negative correlation was very significant in spring. When cloud cover increased by 10%, the average temperature decreased by 1.49 ~C. The positive correlation between the average cloud cover and average precipitation was significant. The annual precipitation increased by 148.1 mm when annual mean total cloud cover increased by 10%. When seasonal mean cloud cover increased by 10%, the precipita- tion increased by 48.4, 107.1,55.4 and 12.2 mm in spring, summer, autumn and winter respectively. The annual average total cloud cover and low cloud cover had significantly positive correlation with 〉~0.1, ~〉1.0, ~〉10 and ~〉25 mm precipitation days respectively. The sunshine hours were seriously influenced by cloud cover, and when cloud cover increased by 10%, the sunshine hours decreased by 54.5 h in spring, 134.2 h in sum- mer, 154.3 h in autumn and 60.6 h in winter. The total cloud cover significantly positively correlated with relative humidity in summer and autumn, and when cloud cover increased by 10%, the relative humidity increased by 3.3% in summer and 4.1% in autumn.

基于LUCC的生态系统服务价值时空演变——以祁连山区域为例

分析祁连山区域生态系统服务价值的时空变化特征,可为该区土地高效开发利用、生态恢复与保护机制的构建提供数据支撑。基于1980年、1990年、2000年、2010年和2020年的土地利用数据,运用改进的当量因子定量评估祁连山区域不同历史时期的生态系统服务价值,结合空间自相关及GIS空间统计方法,探究研究区不同乡镇的地均生态系统服务价值时空变化特征。结果表明:1)1980-2020年,研究区主要土地类型为未利用地、草地、林地、耕地,总覆盖率在93%以上。其中林地和未利用地面积减少,建设用地动态度变化最大。2)1980-2020年,祁连山区域生态系统服务总价值增加了170.8285×10^(8)元,其中草地、林地和水域的生态服务价值占78%,水文调节和气候调节的生态服务价值占60.14%。3)地均生态系统服务价值的空间正相关性较明显,空间集聚程度较高。高值聚集区有由增加向减少转变的趋势,低值聚集区逐年增加。4)1980-2010年,祁连山区域南部生态系统服务价值高于北部,北部生态系统服务价值在2010年后有增加趋势,但研究区南北间生态系统服务价值还未达到均衡和稳定。

地质灾害易发性评价因子分级的AIFFC算法优化

针对地质灾害易发性评价因子分级数不确定的问题,引入自适应膨胀因子模糊覆盖分级方法(fuzzy cover approach for clustering based on adaptive inflation factor,AIFFC)对易发性评价因子分级进行优化。以湖南省湘乡市为研究区,提取了坡度、坡向、高程、年平均降雨量、归一化植被指数、道路、断层、岩性和土地利用9类评价因子,运用AIFFC及自然断点法(natural breakpoint classification,NBC)对连续型因子进行分级,并分别代入加权信息量模型和随机森林模型,获取研究区易发性区划图。采用单因子分级结果精度、灾积比分析和易发性分区结果对AIFFC分级法的优越性进行检验,结果表明:各因子采用AIFFC算法分级的AUC值均高于自然断点法;基于AIFFC的随机森林模型及加权信息量模型的高易发区灾积比分别提升了56.3%、74.6%,低易发区灾积比分别降低了48%、58.1%,AUC值分别提升了7.6%、2.7%。采用AIFFC分级方法优化了地质灾害易发性评价因子分级,显著提高了地质灾害易发性评价的合理性。