林地变化驱动力研究中逻辑回归模型的应用

林地变化驱动力研究旨在揭示林地变化背后的驱动因素及其作用机制,是动态模拟、预测林地利用变化的前提工作。逻辑回归模型是研究林地变化驱动力的常见方法,但目前还没有学者对此进行系统的梳理。文中对逻辑回归模型在国内外林地变化驱动力研究中的应用进行综述,并提出对未来相关研究的建议; 通过文献分析法、归纳法等研究发现,相较于其他方法逻辑回归模型具有适用于因变量是分类变量的案例、重视空间机制等优势; 提出未来通过逻辑回归模型进行林地变化驱动力研究需要考虑数据的空间自相关性,选用恰当的研究单元、尺度以及变量。     

Definition of priority areas for forest conservation through the ordered weighted averaging method

The general objective of this study was to evaluate the ordered weighted averaging (OWA) method, integrated to a geographic information systems (GIS), in the definition of priority areas for forest conservation in a Brazilian river basin, aiming at to increase the regional biodiversity. We demonstrated how one could obtain a range of alternatives by applying OWA, including the one obtained by the weighted linear combination method and, also the use of the analytic hierarchy process (AHP) to structure the decision problem and to assign the importance to each criterion. The criteria considered important to this study were: proximity to forest patches; proximity among forest patches with larger core area; proximity to surface water; distance from roads; distance from urban areas; and vulnerability to erosion. OWA requires two sets of criteria weights: the weights of relative criterion importance and the order weights. Thus, Participatory Technique was used to define the criteria set and the criterion importance (based in AHP). In order to obtain the second set of weights we considered the influence of each criterion, as well as the importance of each one, on this decision-making process. The sensitivity analysis indicated coherence among the criterion importance weights, the order weights, and the solution. According to this analysis, only the proximity to surface water criterion is not important to identify priority areas for forest conservation. Finally, we can highlight that the OWA method is flexible, easy to be implemented and, mainly, it facilitates a better understanding of the alternative land-use suitability patterns.     

文峪河流域土地利用/覆被变化及其驱动力分析

土地利用/覆被变化对于区域的自然、经济和生态发展有着深刻的影响,土地变化驱动力研究是土地利用/覆被变化的核心问题之一。为了探讨中西部小流域的土地覆被变化特征及其驱动因子组成与驱动方式,以山西省文峪河流域为研究对象,基于RS与GIS平台,分析流域2000—2018年土地利用/覆被变化情况;利用马尔柯夫模型预测未来土地利用结构;选取自然因子、区位建设因子、社会经济因子,利用Logistic回归的建模方法分析流域的土地利用/覆被驱动力。结果表明,流域整体耕地、林地、草地面积有所减少,水域、建设用地、其他用地类型面积增加,不同地类的变化速度、土地转移情况不同,流域整体土地变化速度较快,利用程度提高,有序化程度下降,均匀度增加。预测结果显示,耕地、林地、草地、其他用地面积下降,水域、建设用地面积增加,除耕地、建设用地外,其余地类面积变化较小。自然因子、区位建设因子和社会经济因子对研究区土地利用/覆被变化都具有显著的驱动作用。流域的土地利用/覆被在过去18年间经历了快速、复杂的变化,自然因子对土地变化具有基础性、长远性的影响,短时间尺度上区位建设因子与社会经济因子是影响土地变化的主要驱动力量。     

森林生物量空间知识挖掘方法应用研究——以河南西峡县为例

以河南省重点林业县西峡为研究对象,以2003年森林资源连续清查空间数据库为主要信息源,在地理信息系统软件ArcGIS 9.3、数据挖掘软件Clemintine 12.0支持下,通过空间热点探测、趋势面分析、地理加权回归、C5.0决策分析来进行西峡县森林生物量空间知识挖掘。研究表明:生物量的空间分布与海拔梯度有关,呈现一种从北向南阶梯状逐渐降低的带状分布格局;生物量与平均树高、坡度正相关,与土壤厚度、灯光亮度负相关;C5.0决策分析4个主要输入变量的重要性依次为平均树高(0.30)>灯光亮度(0.24)>坡度(0.23)>土壤厚度(0.22)。     

GIS-based forest fire susceptibility mapping in Iran: a comparison between evidential belief function and binary logistic regression models

The aim of this research was to produce forest fire susceptibility maps (FFSM) based on evidential belief function (EBF) and binary logistic regression (BLR) models in the Minudasht Forests, Golestan Province, Iran. At first, 151 forest fire locations were identified from Moderate-Resolution Imaging Spectero Radiometer data, extensive field surveys, and some reports (collected in year 2010). Out of these locations, 106 (70%) were randomly selected as training data and the remaining 45 (30%) cases were used for the validation goals. In the next step, 15 effective factors such as slope degree, slope aspect, elevation, plan curvature, Topographic Position Index, Topographic Wetness Index, land use, Normalized Difference Vegetation Index, distance to villages, distance to roads, distance to rivers, wind effect, soil texture, annual temperature, and rainfall were extracted from the spatial database. Subsequently, FFSM were prepared using EBF and BLR models, and the results were plotted in ArcGIS. Finally, the receiver operating characteristic curves and area under the curves (AUCs) were constructed for verification purposes. The validation of results showed that the AUC for EBF and BLR models are 0.8193 (81.93%) and 0.7430 (74.30%), respectively. In general, the mentioned results can be applied for land use planning, management and prevention of future fire hazards.     

Spatial heterogeneity of factors influencing forest fires size in northern Mexico

In Mexico, forest fires are strongly influenced by environmental, topographic, and anthropogenic factors. A government-based database covering the period 2000-2011 was used to analyze the spatial heterogeneity of the factors influencing forest fire size in the state of Durango, Mexico. Ordinary least squares and geographically weighted regression models were fit to identify the main factors as well as their spatial influence on fire size. Results indicate that fire size is greatly affected by distance to roads, distance to towns, precipitation, temperature, and a population gravity index. The geographically weighted model was better than the ordinary least squares model. The improvement of the former is due to the influence of factors that were found to be non-stationary. These results suggest that geographic location determines the influence of a factor on fire size. While the models can be greatly improved with additional information, the study suggests the need to adopt fire management policies to more efficiently reduce the effect of anthropogenic factors. These policies may include more training for landowners who use fire for clearing, closure of roads, application of thinning, prescribed burning, and fire breaks in perimeters adjacent to roads.     

Spatial variation and prediction of forest biomass in a heterogeneous landscape

Large areas assessments of forest biomass distribution are a challenge in heterogeneous landscapes, where variations in tree growth and species composition occur over short distances. In this study, we use statistical and geospatial modeling on densely sampled forest biomass data to analyze the relative importance of ecological and physiographic variables as determinants of spatial variation of forest biomass in the environmentally heterogeneous region of the Big Sur, California. We estimated biomass in 280 forest plots (one plot per 2.85 km2) and measured an array of ecological (vegetation community type, distance to edge, amount of surrounding non-forest vegetation, soil properties, fire history) and physiographic drivers (elevation, potential soil moisture and solar radiation, proximity to the coast) of tree growth at each plot location. Our geostatistical analyses revealed that biomass distribution is spatially structured and autocorrelated up to 3.1 km. Regression tree (RT) models showed that both physiographic and ecological factors influenced biomass distribution. Across randomly selected sample densities (sample size 112 to 280), ecological effects of vegetation community type and distance to forest edge, and physiographic effects of elevation, potential soil moisture and solar radiation were the most consistent predictors of biomass. Topographic moisture index and potential solar radiation had a positive effect on biomass, indicating the importance of topographically-mediated energy and moisture on plant growth and biomass accumulation. RT model explained 35% of the variation in biomass and spatially autocorrelated variation were retained in regession residuals. Regression kriging model, developed from RT combined with kriging of regression residuals, was used to map biomass across the Big Sur. This study demonstrates how statistical and geospatial modeling can be used to discriminate the relative importance of physiographic and ecologic effects on forest biomass and develop spatial models to predict and map biomass distribution across a heterogeneous landscape.     

Expansion of traditional land-use and deforestation: a case study of an adat forest in the Kandilo Subwatershed,East Kalimantan,Indonesia

Deforestation issues are more problematic when indigenous(adat) communities,living within a forest,have lived there for many generations.These adat communities,who employ traditional land-use,are frequently accused of encroaching on the forest.To understand existing and future trends in the spatial patterns of the expansion of traditional land-use and deforestation,we conducted a case study in the Kandilo Subwatershed using mixed methods with image interpretation,spatial modelling and sociocultural surveys to examine the interrelationships between physical conditions,community characteristics and traditional land-use expansion.We investigated community characteristics through household interviews,communication with key informants,and discussions with focusgroups.By using an area production model,we were able to analyze the effect of improved farming systems,policy intervention and law enforcement on traditional land-use expansion and deforestation.Based on our examination of a 20-year period of traditional land-use activities in adat forests,the evidence indicated that the steeper the slope of the land and the farther the distance from the village,the lower the rate of deforestation.Our study found that customary law,regulating traditional land-use,played an important role in controlling deforestation and land degradation.We conclude that the integration of land allocation,improved farming practices and enforcement of customary law are effective measures to improve traditional land productivity while avoiding deforestation and land degradation.     

林火发生预报模型研究进展

森林火灾直接影响森林生态环境质量,严重威胁人类生命财产安全,还会造成病虫害频发、群落退化等次生灾害。由于综合考虑了各类影响林火发生的因子,林火发生预报模型是目前预报结果最为准确的林火预报预测方法。文中从林火驱动因子、林火发生预报模型构建、模型检验方法等3个方面综述国内外林火发生预报模型的发展现状和研究成果,讨论各类林火发生预报模型的优缺点,梳理目前研究中存在的问题,对其研究前景进行展望,并结合我国实际情况提出开展更大空间尺度林火预报的研究建议,以期为相关研究和林火管理工作提供参考。     

Landsat-7ETM+遥感影像在三北防护林工程县级森林资源调查中的应用

以甘肃景泰县的八道泉等3个乡镇为研究区,以2000年的Landsat-7ETM+遥感资料(多光谱波段空间分辨率为30m×30m,全色波段为15m×15m)作为信息源,以2000年甘肃景泰县的土地利用及森林资源地面调查数据为参考,分别采用目视解译和人机交互式解译两种方法,对研究区土地利用及森林类型进行了判读分类,并与2000年的地面调查结果对比,对两种解译方法进行了精度分析和综合评价。     

Forest Fire Risk Zone Modeling Using Logistic Regression and GIS: An Iranian Case Study

Forest fires are an important environmental concern worldwide, affecting the soil, forests and human lives. During the process of burning, soil nutrients are depleted and the soil is subsequently more vulnerable to erosion. Nowadays it is necessary to identify the factors influencing the occurrence of fire and fire hazard areas, in order to minimize the frequency of fire and avert damage. Logistic regression was used to study the forest fire risk and identify the most influential factors in the occurrence of forest fires. Climatic variables (temperature and annual precipitation), human factors (distance from streams and farmland) and physiography (land slope and elevation) were considered and their correlation with the occurrence of fires investigated. Results of model validation and sensitivity of various areas to fire were examined with the ROC coefficient and Hosmer–Lemeshow test. The estimated coefficients for the independent variables indicated that the probability of occurrence of fire is negatively related to land slope, site elevation and distance from farmlands, but is positively related to amount of annual precipitation.     

基于1990-2020年综合土地利用动态变化的巩义市城市边缘区空间研究

以郑州市下辖且接壤的巩义市为研究对象,以1990年和2020年两期TM/OLI影像和统计年鉴数据为依据,使用1 km×1 km网格划分样区并提取各样区的综合土地利用动态度数值,借助数学模型分析确定城市边缘区范围,分析巩义市近30年来城市边缘区用地变化特征及扩展机制。结果表明,自然条件是用地扩张的基础因素,政策与经济是边缘区外扩的核心驱动力,交通对扩张具有指向性作用;边缘区内的土地变化主要表现为建设用地急剧增加、农业用地锐减,同时受距离和开发时序影响,用地类型交错复杂,破碎化特征明显。     

Diversity and composition of tropical secondary forests recovering from large-scale clearing: results from the 1990 inventory in Puerto Rico

The extensive recovery from agricultural clearing of Puerto Rican forests over the past half-century provides a good opportunity to study tropical forest recovery on a landscape scale. Using ordination and regression techniques, we analyzed forest inventory data from across Puerto Rico’s moist and wet secondary forests to evaluate their species composition and whether the landscape structure of older forest affected tree species composition of recovering forests at this scale. Our results support conclusions from studies conducted in Puerto Rico at smaller scales and temperate forests at larger scales that timing of abandonment and land use history are of overwhelming importance in determining the species composition of recovering forests. Forest recovery is recent enough in Puerto Rico that previous land use is clearly evident in current species composition, and creates new forest communities. As demonstrated in other work, physical factors such as elevation and substrate co-vary with land use history, so that the species composition of the forest landscape results from the interplay between biophysical and socioeconomic forces over time. Our results also indicate that increasing the distance to the largest forest patches occurring in the landscape 12 years previous had a small negative impact on species richness but not species diversity or community composition. We conclude that land use history has as much influence in species composition as biophysical variables and that, at the scale of this study, there is no large influence of forest landscape structure on species diversity or composition.     

基于ICESat-GLAS波形估测平均树高的研究

以吉林省汪清林业局经营区域为例,基于星载激光雷达ICESat-GLAS回波参数,构建了平均树高回归模型,预估精度为84.05%;利用反距离加权法,对ICESat-GLAS光斑平均树高估测值进行差值运算,得到初始CHM(Canopy Height Model),实现了平均树高空间连续分布制图;再利用坡度校正和3×3移动窗口差分滤波平滑初始CHM,得到研究区平均树高修正CHM,预估精度达到91.52%。研究结果表明,坡度校正和移动窗口差分滤波方法能有效削弱坡度影响,剔除异常点,提高平均树高估测精度。     

国外森林土壤研究现状与趋向

本文就森林土壤分类、立地分类和质量评价、生态系统中养分和水分循环以及林木肥效与生物固氮等问题的研究进展作了简要介绍。     

Deforestation and fragmentation of Chaco dry forest in NW Argentina (1972–2007)

The sustained increase in the global food demand has favoured the recent expansion of industrial agriculture into neotropical dry forest ecosystems, with resulting changes in their extent and spatial configuration. Based on Landsat satellite images, we analyzed changes in forest cover and landscape configuration over an area of 600 by 100 km located in NW Argentina (Tucumán and Salta provinces) in four periods between 1972 and 2007. The study area, one of the most active deforestation frontiers of South American dry forest, was divided into six relatively homogeneous sectors in terms of land property structure and biophysical characteristics. During the study period 1.4 millions hectares of dry forest were cleared. Deforestation started in the 1970s as a result of technological changes and increasing rainfall; continued (with spatial and temporal fluctuations) during the 1980s and 1990s in association to the sustained global demand of soybean, and was accelerated (to ca. 100,000 ha year⁻¹) between 2001 and 2007 following the global increase in commodity prices, and the national peso devaluation. We described the landscape structure using eight landscape indices, summarized as one synthesis value: the Euclidian distance across the seven dimensions from a theoretical non-fragmented situation. In areas with soil limitations deforestation resulted in relatively stable, highly fragmented landscapes. In contrast, the sites with regional coarser-scale limitations (rainfall), deforestation produced a less fragmented landscape where agriculture concentrates in sites with high rainfall. Sites with no limitations for agriculture tend to a largely deforested landscape with few small and poorly connected forest patches. The land properties size seems to influence some indices of fragmentation, but the synthetic index of fragmentation suggests an overall convergence of fragmentation patterns towards a similar configuration across different biophysical and land tenure conditions.     

杉木幼林地水土流失动态研究

杉木幼林地水土流失动态研究＊何贵平陈益泰蔡宏明封剑文关志山关键词杉木、幼林地、水土—养分流失、预测模型杉木（Ｃｕｎｎｉｎｇｈａｍｉａｌａｎｃｅｏｌａｔａ（Ｌａｍｂ．）Ｈｏｏｋ）是我国南方的主要用材树种，常以营造纯林为主，整地方式又以全垦挖大穴或火烧炼...     

大尺度小样本情况下的数据预测方法对比研究

采用反距离加权法(IDW)、协同克里格法(Cokriging)、回归模型法,利用云南省134个县(市)气象站观测数据对全省≥10°积温区域进行预测.结果表明,由于气象站点稀少,用不同的方法结合不同的辅助信息得到的预测结果不同.反距离加权法强调了空间距离尺度的影响,但未能较好地体现云南省局部积温的分布规律;协同克里格法则优于反距离加权法,但在样本数偏少的情况下预测结果会出现明显的凹凸现象;回归模型法预测结果能很好地体现云南省北低南高、西高东低的气温总体变化规律,又能体现峡谷地带中局部干热河谷的特点,是3种方法中效果最好的预测方法.     

A comprehensive insight into the geography of forest cover in Italy: Exploring the importance of socioeconomic local contexts

Forest cover is a key attribute of local communities and affects the spatial organization of any given region. Changes in forest cover are influenced by spatially-varying biophysical and anthropogenic factors mainly associated with urban-rural, coastal-inland and elevation gradients. The present study investigates the relationship between the socioeconomic structure of local communities and selected indicators of forest landscape in Italy, including change in forest area over time (2000 − 2012), using an exploratory multivariate analysis based on principal component analysis, hierarchical clustering and discriminant analysis. We assess the importance of socio-spatial structures, economic dynamics and demographic patterns in the geography of forest cover, expansion and loss, considering 149 statistical indicators that are used to evaluate the multiple dimensions of sustainable development. The results point to agriculture, income, education and labour market indicators as a key predictors of contexts with high forest cover and moderate changes in forest area (both gain and loss) from those with low forest cover and marked changes in forest area. High forest cover in rural districts was spatially associated with local communities featuring depopulation, unemployment, low educational levels and subsistence agriculture. These factors consolidate land abandonment and soil erosion. The highest rate of change in forest area was observed in economically-growing, accessible local contexts with dynamic socio-demographic profiles. Integrated environmental and socioeconomic policies for sustainable development are required to incorporate forest cover and changes in wooded area as pivotal variables and may benefit from a better understanding of the role of local communities in forest management.     

重庆山区不同土地利用下的土壤肥力质量研究

该文旨在揭示重庆市山区小流域不同土地利用方式下的土壤肥力状况,为土壤培肥管理提供依据.以重庆市南川区山区小流域为例,选取3种不同的土地利用方式,共采集样品81个,结合主成分分析法与隶属度函数,分析山区小流域的土壤养分状况与肥力质量水平.结果表明,研究区土壤酸化严重,林地的有机质含量最高,旱地全氮、全磷和速效磷较为丰富,...