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1.
以2005—2020年遥感影像为数据源,采用像元二分法计算得到雅安市植被覆盖度,并结合DEM和气象数据,通过趋势分析、地理探测器和变异指数分析了不同海拔带、坡度带、坡向、降水和气温下植被覆盖度的时空变化特征和波动程度,探讨了影响植被覆盖度的主要因子。结果表明:(1)雅安市2005—2020年植被覆盖度一直呈上升趋势,且植被覆盖度较高;(2)植被覆盖度波动小,受外界环境影响小,植被生态环境稳定;(3)植被覆盖度整体得到改善的面积比例远大于退化;(4)海拔对植被覆盖度变化的解释力最强,交互作用以非线性增强为主,其中海拔和坡度的叠加作用最大。  相似文献   

2.
斯里兰卡亚洲象栖息地是全球重要的亚洲象保护区,象群分布密度约为其他地区的10倍,但由于生境破碎与丧失以及人象冲突等原因导致亚洲象数量急剧下降。对斯里兰卡亚洲象栖息地的生境质量监测与评估能够为亚洲象及其栖息地的保护政策制定与规划提供理论依据,并在全球物种多样性保护中具有重要意义。为评估斯里兰卡亚洲象栖息地的生境质量,综合考虑亚洲象栖息地需求以及影响亚洲象栖息地的关键要素,应用InVEST-HQ模型来估算生境质量指数,同时分析亚洲象栖息地生境质量在海拔梯度及植被覆盖梯度上的分布状况;随后引入空间自相关分析方法在像元尺度上探讨亚洲象栖息地生境质量的空间分布模式与时间演化过程,进而分析栖息地内不同保护区和气候分区的生境质量所存在的空间分异特征。研究结果表明:在空间分布上,斯里兰卡亚洲象栖息地生境质量具有高度聚集性,空间异常值不显著。生境质量高值区主要集中在中低海拔、植被覆盖情况较好、保护区范围密集的区域;生境质量低值区集中于耕地面积大、海拔偏高的区域。在梯度分布上,斯里兰卡亚洲象栖息地生境质量对海拔和植被覆盖度均具有显著线性相关关系,且在较低海拔和较高植被覆盖度梯度上存在聚集现象。在区域尺度上,斯里兰卡亚洲象栖息地生境质量存在显著的地域差异性。栖息地内自然保护区的生境质量明显高于非自然保护区,其中严格自然保护区的生境质量相对较高;热带雨林气候带的生境质量高值聚类大于其余气候分区,而热带疏林草原气候带与热带季风气候带生境质量受到季节性降水的影响较大,高值像元占比偏少。在时间尺度上,斯里兰卡亚洲象栖息地的生境质量总体呈现先降低后趋于平缓的态势。1995年—2010年,生境质量高值聚类占比明显减少,低值聚类占比缓慢上升;2010年—2020年生境质量低值占比有小幅度下降,高值聚类逐渐增加,生境质量逐渐稳定并呈缓慢上升的趋势。  相似文献   

3.
综合考虑大气降水-植被生长-海拔相互作用等多元成因,以新疆地区2001—2019年的MODIS数据、TRMM降水数据以及该地区数字高程模型(digital elevation model,DEM)数据为遥感数据源,计算降水集中指数(precipitation concentration index,PCI)、温度植被干...  相似文献   

4.
稀疏植被净初级生产力时空变化及气象因素关系分析   总被引:1,自引:0,他引:1  
本文探讨了2001-2018年古尔班通古特沙漠植被NPP时空格局,基于改进的CASA模型,采用空间分析、相关性分析及地理探测器模型等方法,揭示了研究区NPP气候驱动因子及其影响。结果表明:①古尔班通古特沙漠近18年植被NPP变化总体呈现波动增加趋势,增速为0.56 gC· a-1,NPP均值为46.90 gC· m-2· a-1;②2001-2018年,年均NPP整体呈西低东高、北低南高的空间分布格局,但从动态上而言,基本呈现沙漠腹地较稳定、四周较活跃的格局;③古尔班通古特沙漠植被NPP主要受降水因子的影响,与降水、气温因子均呈正相关关系,从各因子驱动力分析而言,降水因子(0.614 4)为限制荒漠植被生长的主导因素。  相似文献   

5.
高光谱吸收特征参数反演草地光合有效辐射吸收率   总被引:1,自引:0,他引:1  
在植被光合有效辐射吸收率(FAPAR)遥感估算中被广泛采用的植被指数法,其估算精度往往受到"红波段吸收峰"峰值点光谱反射率易饱和特征的影响。考虑到高光谱吸收特征参数能较好地诠释地物光谱吸收特征的细节信息,基于微分法与包络线去除法研发"高光谱曲线特征吸收峰自动识别法"识别对FAPAR敏感的特征吸收峰,再结合连续统去除法以及光谱吸收指数(SAI)提取FAPAR的高光谱吸收特征参数,构建估算天然草地冠层水平FAPAR的高光谱吸收特征参数模型。结果表明:(1)天然草地冠层FAPAR与高光谱吸收特征参数具有很好的相关性,其中,"红波段吸收峰"SAI对FAPAR变化最为敏感,在植被覆盖度较高时,其饱和性相比"红波段吸收峰"峰值点反射率与归一化植被(NDVI)值有较大的提升。(2)以"红波段吸收峰"SAI为变量的对数方程为FAPAR的最佳估算模型,在植被覆盖度处于中与高时,其FAPAR预测精度比NDVI模型有不同程度的提高。研究采用的高光谱吸收特征参数一定程度上弥补了部分植被指数因饱和问题在估算FAPAR时的不足,可作为植被FAPAR反演的新参数,适用于中、高覆盖度的天然草地FAPAR监测。  相似文献   

6.
基于RS与GIS技术的泸定县植被空间分布分析   总被引:2,自引:0,他引:2  
杨晏立  何政伟  管磊  张雪峰 《测绘工程》2010,19(5):49-52,56
以四川省泸定县为分析研究区域,综合运用遥感图像处理技术与GIS空间分析技术,用ETM+遥感影像获取归一化植被指数(NDVI)信息并反演植被覆盖度,用地形图等高线生成数字高程模型(DEM)并提取地形因子。借助叠合分析法,讨论植被覆盖度与海拔高度、坡度、坡度变率、坡向、坡向变率5种地形因子的空间关系,得到泸定县关于地形因子的各等级植被空间分布特征。分析对地植物学中高山峡谷地区植被的地形格局分布规律研究与生态环境的评价与改良都具有重要的参考价值。  相似文献   

7.
为分析山东省植被覆盖度变化及其与降水量、温度等气候因子变化的相关性,该文采用2005—2015年的NDVI、降水量和温度数据,利用重心模型和相关系数法,进行了植被覆盖度与降水、温度的月动态变化和季度动态变化分析。研究结果显示,在2005—2015年的10年间,山东省植被覆盖度在整体上呈现增长趋势,植被覆盖度与气候因子无论是在月动态变化还是季动态变化都表现出不同程度的正相关性,植被NDVI的季度走向与降水和温度的季动态变化趋势几乎一致,并且温度对植被生长的影响大于降水对植被生长的影响。研究验证了植被覆盖度的变化与气候因子的变化有一定的关系。  相似文献   

8.
近30年来渭河流域植被与气候变化互影响模式的探寻分析   总被引:2,自引:0,他引:2  
基于1982-2006年间的GIMMS NDVI和2001-2013年的MODIS NDVI数据对渭河流域30年来植被NDVI的年际变化和空间分布特征进行了分析,并结合研究区内的气象数据探讨了植被NDVI与气候因子的相互影响关系。研究显示,近32年间渭河流域植被NDVI整体呈上升趋势,且空间差异显著,主要表现为流域西北地区的黄土丘陵沟壑区及北部的黄土高原区NDVI较低,植被覆盖较差;流域南部的秦岭山区、关中平原区等地植被生长状况较好。流域气温和降水呈现缓慢增长趋势。植被NDVI与年均气温整体上表现为负相关,与年降水量间呈正相关。总体上,降水是渭河流域植被生长的主要影响因子。  相似文献   

9.
《遥感学报》2023,(11):2467-2483
人类活动、极端气候、物种入侵等事件导致植物的生物多样性丧失加剧,生物多样性保护迫切需要快速准确地收集陆地植物多样性信息。高光谱遥感的出现,为大空间尺度上的植物多样性研究提供了技术基础,为群落和景观水平的生物多样性相关理论的验证提供了契机。本文简要回顾了近年来高光谱遥感技术的发展及其在植物多样性研究中的应用。重点介绍了两类高光谱遥感反演多样性的手段,即直接反演和间接反演。直接反演手段以光谱变异假说为理论基础,从光谱曲线特征入手直接建立光谱信息与植物多样性的关系;间接反演手段则通过植被指数将光谱信息关联植物多样性,或通过定量反演功能性状计算功能多样性指标,进而实现植物多样性的间接估测。论文进一步结合实例,论述了高光谱遥感技术在大尺度生物多样性相关研究中的应用,如物种入侵监测、物种分布及多样性格局制图、生物多样性与生态系统功能关系研究。最后分析了高光谱遥感技术在生态研究应用中的局限性。随着多源遥感技术的发展日渐成熟,高光谱遥感技术与地面通量监测、激光雷达、计算机可视化等其他技术的协同应用可能是在生物多样性研究领域中一个新的发展方向。  相似文献   

10.
针对内蒙古不同生态区植被长势时空变化及其对气候变化的响应差异问题,本文基于MODIS遥感数据构建植被长势指数(GI)模型,结合研究区气温降水数据,利用相关分析法研究了该区植被长势对不同气候因子响应的时空差异特征.结果表明:内蒙古近17a生长季植被GI整体呈上升趋势,森林生态区和草原生态区植被长势平稳,荒漠草原生态区植被长势较好;生长季植被GI均值在空间上呈南高北低的分布特征,植被长势整体由好到差表现为荒漠草原生态区>森林生态区>草原生态区;植被长势与气温呈负相关关系、与降水呈正相关关系;森林生态区植被长势受气温和降水共同影响,草原生态区和荒漠草原生态区植被长势主要受降水影响;大部分地区表现为受非气候因子驱动.  相似文献   

11.
12.
Landscape ecology, inter alia, addresses the question as to how altered landscape patterns affect the distribution, persistence, and abundance of a species. Landscape ecology plays an important role in integrating the different scales of biodiversity from habitat patch to biome level. Satellite remote sensing technology with multi-sensor capabilities offers multi-scale information on landscape composition and configuration. Advances in geospatial analytical tools and spatial statistics have improved the capability to quantify spatial heterogeneity. Globally, landscape level characterization of biodiversity has become an important discipline of science. Considering the vast extent, heterogeneity, and ecological and economic importance of forest landscapes, significant efforts have been made in India during the past decade to strengthen landscape level biodiversity characterization. The generic frame work of studies comprises preparation of national databases providing information on composition and configuration of different landscapes using multi-scale remote sensing techniques, understanding the landscape patterns using geospatial models to elicit disturbance and diversity patterns and application of this information for bioprospecting and conservation purposes. Studies on hierarchical linkage of multi-scale information to study the processes of change, landscape function, dynamics of habitat fragmentation, invasion, development of network of conservation areas based on the understanding of multi-species responses to landscape mosaics, macro-ecological studies to understand environment and species richness, habitat and species transitions and losses, landscape level solutions to adaptation and mitigation strategies to climate change are a few of the future challenges. The paper presents the current experiences and, analyses in conjunction with international scenario and identifies future challenges of Indian landscape level biodiversity studies.  相似文献   

13.
Abstract

The aim of this study is to investigate the potential of Sentinel-2 imagery for the identification and determination of forest patches of particular interest, with respect to ecosystem integrity and biodiversity and to produce a relevant biodiversity map, based on Simpson’s diversity index in Taxiarchis university research forest, Chalkidiki, North Greece. The research is based on OBIA being developed on to bi-temporal summer and winter Sentinel-2 imagery. Fuzzy rules, which are based on topographic factors, such as terrain elevation and slope for the distribution of each tree species, derived from expert knowledge and field observations, were used to improve the accuracy of tree species classification. Finally, Simpson’s diversity index for forest tree species, was calculated and mapped, constituting a relative indicator for biodiversity for forest ecosystem organisms (fungi, insects, birds, reptiles, mammals) and carrying implications for the identification of patches prone to disturbance or that should be prioritized for conservation.  相似文献   

14.
多房棘球绦虫(Echinococcus multilocularis)的幼虫期导致罕见而致命的肝病即人类的泡型包虫病(HAE)。绦虫在狐狸(或狗类)与一些小型哺乳类动物之间以寄生虫-寄主的方式进行循环传播。中国中部一些地区的人类泡型包虫病属于地方流行病,在部分乡村的发生概率达到15%。本文研究如何利用遥感数据并基于地区景观特性获取该流行病清晰地空间危害分布图。遥感数据分析的结果显示,人类居住地附近的草地或灌木是HAE传播的一个主要危险区域,从空间分布上看,这些区域是小型哺乳动物等中间寄主的聚集处。  相似文献   

15.
李强  张景发  罗毅  焦其松 《遥感学报》2019,23(4):785-795
2017年8月8日发生的7.0级九寨沟地震诱发九寨沟熊猫海附近产生大量的滑坡体,造成道路阻塞,严重影响地震应急救援进度。为快速准确地识别滑坡分布范围,本文在深入分析滑坡遥感影像特征的基础上,引入面向对象分析方法,实现了基于无人机影像的震后滑坡体的自动识别。通过多尺度分割算法获取滑坡多层次影像对象,利用SEaTH算法自动构建每一层次特征规则集,实现基于不同层次分析的滑坡体自动识别。分析滑坡体在地形、活动断层等因子中的空间分布特征,为地震滑坡预测与危险性评价奠定基础。与人工目视解译结果相比较,基于面向对象的滑坡自动识别方法提取精度可达94.8%,Kappa系数为0.827,在电脑配置相同的情况下,自动识别方法的效率是人工目视解译效率的一倍。空间分布特征分析表明,地震滑坡的空间分布与斜坡坡度、地形起伏度呈正相关关系,与地表粗糙度存在负相关关系,研究区滑坡体分布存在明显的断层效应。  相似文献   

16.
Amongst many ongoing initiatives to preserve biodiversity, the Millennium Ecosystem Assessment again shows the importance to slow down the loss of biological diversity. However, there is still a gap in the overview of global patterns of species distributions. This paper reviews how remote sensing has been used to assess terrestrial faunal diversity, with emphasis on proxies and methodologies, while exploring prospective challenges for the conservation and sustainable use of biodiversity. We grouped and discussed papers dealing with the faunal taxa mammals, birds, reptiles, amphibians, and invertebrates into five classes of surrogates of animal diversity: (1) habitat suitability, (2) photosynthetic productivity, (3) multi-temporal patterns, (4) structural properties of habitat, and (5) forage quality. It is concluded that the most promising approach for the assessment, monitoring, prediction, and conservation of faunal diversity appears to be the synergy of remote sensing products and auxiliary data with ecological biodiversity models, and a subsequent validation of the results using traditional observation techniques.  相似文献   

17.
Species richness, or simply the number of species in a given area, is commonly used as an important indicator of biological diversity. Spatial variability in species richness has been postulated to depend upon environmental factors such as climate and climatic variability, which in turn may affect net primary productivity. The Advanced Very High Resolution Radiometer (AVHRR) derived Normalized Difference Vegetation Index (NDVI) has been shown to be correlated with climatic variables including rainfall, actual evapotranspiration and net primary productivity. To determine factors favoring high species richness, we examined the relationship between interannual NDVI variables and species richness of birds at a quarter degree scale (55 × 55 km). Results revealed a strong positive correlation between species richness and maximum average NDVI. Conversely, species richness showed negative correlation with standard deviation of maximum NDVI and the coefficient of variation. Though these relationships are indirect, they apparently operate through the green vegetation cover. Understanding such relationships can help in mapping and monitoring biological diversity, as well as in estimating changes in species richness in response to global climatic change.  相似文献   

18.
Modelling the empirical relationships between habitat quality and species distribution patterns is the first step to understanding human impacts on biodiversity. It is important to build on this understanding to develop a broader conceptual appreciation of the influence of surrounding landscape structure on local habitat quality, across multiple spatial scales. Traditional models which report that ‘habitat amount’ in the landscape is sufficient to explain patterns of biodiversity, irrespective of habitat configuration or spatial variation in habitat quality at edges, implicitly treat each unit of habitat as interchangeable and ignore the high degree of interdependence between spatial components of land-use change. Here, we test the contrasting hypothesis, that local habitat units are not interchangeable in their habitat attributes, but are instead dependent on variation in surrounding habitat structure at both patch- and landscape levels. As the statistical approaches needed to implement such hierarchical causal models are observation-intensive, we utilise very high resolution (VHR) Earth Observation (EO) images to rapidly generate fine-grained measures of habitat patch internal heterogeneities over large spatial extents. We use linear mixed-effects models to test whether these remotely-sensed proxies for habitat quality were influenced by surrounding patch or landscape structure. The results demonstrate the significant influence of surrounding patch and landscape context on local habitat quality. They further indicate that such an influence can be direct, when a landscape variable alone influences the habitat structure variable, and/or indirect when the landscape and patch attributes have a conjoined effect on the response variable. We conclude that a substantial degree of interaction among spatial configuration effects is likely to be the norm in determining the ecological consequences of habitat fragmentation, thus corroborating the notion of the spatial context dependence of habitat quality.  相似文献   

19.
Estimates of forest aboveground biomass are fundamental for carbon monitoring and accounting; delivering information at very high spatial resolution is especially valuable for local management, conservation and selective logging purposes. In tropical areas, hosting large biomass and biodiversity resources which are often threatened by unsustainable anthropogenic pressures, frequent forest resources monitoring is needed. Lidar is a powerful tool to estimate aboveground biomass at fine resolution; however its application in tropical forests has been limited, with high variability in the accuracy of results. Lidar pulses scan the forest vertical profile, and can provide structure information which is also linked to biodiversity. In the last decade the remote sensing of biodiversity has received great attention, but few studies focused on the use of lidar for assessing tree species richness in tropical forests.This research aims at estimating aboveground biomass and tree species richness using discrete return airborne lidar in Ghana forests. We tested an advanced statistical technique, Multivariate Adaptive Regression Splines (MARS), which does not require assumptions on data distribution or on the relationships between variables, being suitable for studying ecological variables.We compared the MARS regression results with those obtained by multilinear regression and found that both algorithms were effective, but MARS provided higher accuracy either for biomass (R2 = 0.72) and species richness (R2 = 0.64). We also noted strong correlation between biodiversity and biomass field values. Even if the forest areas under analysis are limited in extent and represent peculiar ecosystems, the preliminary indications produced by our study suggest that instrument such as lidar, specifically useful for pinpointing forest structure, can also be exploited as a support for tree species richness assessment.  相似文献   

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