Dimidiate Pixel Model Research Articles

Human Activity Influences on Vegetation Cover Changes in Beijing, China, from 2000 to 2015

For centuries, the rapid development of human society has already made human activity the dominant factor in the terrestrial ecosystem. As the city of greatest importance in China, the capital Beijing has experienced eco-environmental changes with unprecedented economic and population growth during the past few decades. To better understand the ecological transition and its correlations in Beijing, Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) images were used to investigate vegetation coverage changes using a dimidiate pixel model. Piecewise linear regression, bivariate-partial correlation analysis, and factor analysis were applied to the probing of the relationship between vegetation coverage changes and climatic/human-induced factors. The results showed that from 2000 to 2005, 2005 to 2010, and 2010 to 2015, Beijing experienced both restoration (6.33%, 10.08%, and 12.81%, respectively) and degradation (13.62%, 9.35%, and 9.49%, respectively). The correlation analysis results between climate and vegetation changes demonstrated that from 2000 to 2015, both the multi-year annual mean temperature (r = −0.819, p < 0.01) and the multi-year annual mean precipitation (r = 0.653, p < 0.05) had a significantly correlated relationship with vegetation change. The Beijing-Tianjin Sandstorm Source Control Project (BTSSCP) has shown beneficial spatial effects on vegetation restoration; the total effectiveness in conservation areas (84.94 in 2000–2010) was much better than non-BTSSCP areas (34.34 in 2000–2010). The most contributory socioeconomic factors were the population (contribution = 54.356%) and gross domestic product (GDP) (contribution = 30.677%). The population showed a significantly negative correlation with the overall vegetation coverage (r = −0.684, p < 0.05). The GDP was significantly negatively correlated with vegetation in Tongzhou, Daxing, Central city, Fangshan, Shunyi, and Changping (r = −0.601, p < 0.01), while positively related in Huairou, Miyun, Pinggu, Mentougou and Yanqing (r = 0.614, p < 0.01). These findings confirm that human activity is a very significant factor in impacting and explaining vegetation changes, and that some socioeconomic influences on vegetation coverage are highly spatially heterogeneous, based on the context of different areas.

Dynamics of Fractional Vegetation Coverage and Its Relationship with Climate and Human Activities in Inner Mongolia, China

Long-term remote sensing normalized difference vegetation index (NDVI) datasets have been widely used in monitoring vegetation changes. In this study, the NASA Global Inventory Modeling and Mapping Studies (GIMMS) NDVI3g dataset was used as the data source, and the dimidiate pixel model, intensity analysis, and residual analysis were used to analyze the changes of vegetation coverage in Inner Mongolia—from 1982 to 2010—and their relationships with climate and human activities. This study also explored vegetation changes in Inner Mongolia with respect to natural factors and human activities. The results showed that the estimated vegetation coverage exhibited a high correlation (0.836) with the actual measured values. The increased vegetation coverage area (49.2% of the total area) was larger than the decreased area (43.3%) from the 1980s to the 1990s, whereas the decreased area (57.1%) was larger than the increased area (35.6%) from the 1990s to the early 21st century. This finding indicates that vegetation growth in the 1990s was better than that in the other two decades. Intensity analysis revealed that changes in the average annual rate from the 1990s to the early 21st century were relatively faster than those in the 1980s–1990s. During the 1980s–1990s, the gain of high vegetation coverage areas was active, and the loss was dormant; in contrast, the gain and loss of low vegetation coverage areas were both dormant. In the 1990s to the early 21st century, the gains of high and low vegetation coverage areas were both dormant, whereas the losses were active. During the study period, areas of low vegetation coverage were converted into ones with higher coverage, and areas of high vegetation coverage were converted into ones with lower coverage. The vegetation coverage exhibited a good correlation (R2 = 0.60) with precipitation, and the positively correlated area was larger than the negatively correlated area. Human activities not only promote the vegetation coverage, but also have a destructive effect on vegetation, and the promotion effect during 1982 to 2000 was larger than from 2001 to 2010, while, the destructive effect was larger from 2000 to 2010.

SOC storage and potential of grasslands from 2000 to 2012 in central and eastern Inner Mongolia, China

Grassland ecosystem is an important component of the terrestrial carbon cycle system. Clear comprehension of soil organic carbon (SOC) storage and potential of grasslands is very important for the effective management of grassland ecosystems. Grasslands in Inner Mongolia have undergone evident impacts from human activities and natural factors in recent decades. To explore the changes of carbon sequestration capacity of grasslands from 2000 to 2012, we carried out studies on the estimation of SOC storage and potential of grasslands in central and eastern Inner Mongolia, China based on field investigations and MODIS image data. First, we calculated vegetation cover using the dimidiate pixel model based on MODIS-EVI images. Following field investigations of aboveground biomass and plant height, we used a grassland quality evaluation model to get the grassland evaluation index, which is typically used to represent grassland quality. Second, a correlation regression model was established between grassland evaluation index and SOC density. Finally, by this regression model, we calculated the SOC storage and potential of the studied grasslands. Results indicated that SOC storage increased with fluctuations in the study area, and the annual changes varied among different sub-regions. The SOC storage of grasslands in 2012 increased by 0.51×1012 kg C compared to that in 2000. The average carbon sequestration rate was 0.04×1012 kg C/a. The slope of the values of SOC storage showed that SOC storage exhibited an overall increase since 2000, particularly for the grasslands of Hulun Buir city and Xilin Gol League, where the typical grassland type was mainly distributed. Taking the SOC storage under the best grassland quality between 2000 and 2012 as a reference, this study predicted that the SOC potential of grasslands in central and eastern Inner Mongolia in 2012 is 1.38×1012 kg C. This study will contribute to researches on related methods and fundamental database, as well as provide a reference for the protection of grassland ecosystems and the formulation of local policies on sustainable grassland development.

Quantifying the Impact of NDVIsoil Determination Methods and NDVIsoil Variability on the Estimation of Fractional Vegetation Cover in Northeast China

Fractional vegetation cover (FVC) is one of the most critical parameters in monitoring vegetation status. Accurate estimates of FVC are crucial to the use in land surface models. The dimidiate pixel model is the most widely used method for retrieval of FVC. The normalized difference vegetation index (NDVI) of bare soil endmember (NDVIsoil) is usually assumed to be invariant without taking into account the spatial variability of soil backgrounds. Two NDVIsoil determining methods were compared for estimating FVC. The first method used an invariant NDVIsoil for the Northeast China. The second method used the historical minimum NDVI along with information on soil types to estimate NDVIsoil for each soil type. We quantified the influence of variations of NDVIsoil derived from the second method on FVC estimation for each soil type and compared the differences in FVC estimated by these two methods. Analysis shows that the uncertainty in FVC estimation introduced by NDVIsoil variability can exceed 0.1 (root mean square error—RMSE), with the largest errors occurring in vegetation types with low NDVI. NDVIsoil with higher variation causes greater uncertainty on FVC. The difference between the two versions of FVC in Northeast China, is about 0.07 with an RMSE of 0.07. Validation using fine-resolution FVC reference maps shows that the second approach yields better estimates of FVC than using an invariant NDVIsoil value. The accuracy of FVC estimates is improved from 0.1 to 0.07 (RMSE), on average, in the croplands and from 0.04 to 0.03 in the grasslands. Soil backgrounds have impacts not only on NDVIsoil but also on other VIsoil. Further focus will be the selection of optimal vegetation indices and the modeling of the relationships between VIsoil and soil properties for predicting VIsoil.

调水工程输水管道建设对地表植被格局的影响——以南水北调河北省易县段为例

PDF HTML阅读 XML下载 导出引用 引用提醒 调水工程输水管道建设对地表植被格局的影响——以南水北调河北省易县段为例 DOI: 10.5846/stxb201504080718 作者: 作者单位: 中国科学院生态环境研究中心城市与区域生态国家重点实验室,中国科学院生态环境研究中心城市与区域生态国家重点实验室,中国科学院生态环境研究中心城市与区域生态国家重点实验室,中国科学院生态环境研究中心城市与区域生态国家重点实验室,中国科学院生态环境研究中心城市与区域生态国家重点实验室,中国科学院生态环境研究中心城市与区域生态国家重点实验室 作者简介: 通讯作者: 中图分类号: 基金项目: 环保公益性行业科研专项（201209029-3） Effects of water transfer project construction on vegetation patterns Author: Affiliation: State Key of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences,,,,,State Key of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:随着生态环境不断恶化，水资源紧缺已成为全球性的环境问题，跨流域调水工程是保障区域水资源合理配置，保证区域生态安全、区域经济和社会可持续发展的重要措施之一。但是调水工程会不可避免的对施工建设区的生态系统带来人为干扰，对施工建设的地表植被格局产生影响。以南水北调中线一期工程河北省易县段大型输水管道工程建设区作为研究对象，选取了施工建设前（2000年）、施工建设期（2008年）和施工建设后（2013年）3个不同时间段的遥感影像数据，通过解译施工建设区地表植被类型的变化，采用象元二分法提取植被覆盖度，比较不同时期植被覆盖格局和土地利用格局的动态变化，探讨了输水管道建设对周边生态系统影响的范围和特点。研究表明：施工建设前、中、后期管道沿线土地利用类型有较大变化；随着输水管道的建设，人为干扰逐渐增强，施工作业带成为该区域的主要建设用地，并造成了弃置用地和土地裸露，减少了耕地和草地的面积。同时，输水管道建设施工对研究区内植被覆盖度产生了明显的影响，总体上呈现出先减少后增加的趋势。管道建设期对沿线植被、土壤生态系统影响明显，其范围主要在管道施工作业带中心两侧各100 m；在这个区域以外，影响强度大幅降低。 Abstract:Development of human society depends greatly on the utilization of water resources, with a corresponding deterioration of the ecological environment. Water shortages have become a global environmental problem. Inter-basin water transfer projects can improve the existing patterns of land and water resources, to achieve a rational allocation of water resources to facilitate sustainable social, economic, and environmental development. However, inter-basin water transfer projects will inevitably bring about adverse ecological effects, such as the deterioration of water quality, the loss of biogeographical integrity, frequent and drastic alterations of hydrological regimes, the loss of endemic biotas, etc. Therefore, specific objective appraisals are necessary, before embarking on such projects. The South-North Water Transfer Project is a multi-decade infrastructural mega-project in China; it is the largest of its kind in the world. In the present study, Yi County, which is located in the vicinity of the Middle Route of the South-North Water Transfer Project in Hebei Province, was selected as the subject of study. Through the interpretation of remote sensing images, three land use types in three different construction stages (pre-construction period, construction period, and post-construction period) were selected, and the dimidiate pixel model was used to extract vegetation coverage. The impacts of corridor type projects on landscape structure in surrounding areas can be analyzed by buffer analysis. The present study used four kinds of buffers, namely the 100 m range, 500 m range, 1000 m range, and 3000 m range. In addition, the canal, which was within the 100 m range was a key study area. The present study analyzed the dynamic changes of vegetation coverage, land use patterns, and the relative change rates of vegetation coverage with different buffers. The results show that the Inter-basin water transfer project:directly changed the composition and structure of the ecological system along the construction area; transformed the ecological system from its natural condition to one showing anthropogenic effects. This last finding is the main factor that influenced the dynamics of the ecological system in the area under study. The land use types along the canal varied within different stages of construction. With construction of the canal, inevitably, human interference gradually increased. In addition, the introduction of a relatively large construction site in the region, resulted in increased land areas either laid bare or used for waste disposal, and reduced farmlands and grasslands. The degree of fragmentation was increased, and there was a reduction in ecological function of the regional ecosystem. The construction of the canal had significant effects on vegetation coverage, over three periods of study, showing an increasing trend after first being reduced. During the pre-construction period, vegetation coverage in the 100 m range was significantly higher than it was in other buffers, but significantly lower than it was in the control plot. During the construction period, vegetation coverage in all buffers was significantly lower than it was in the control plot with the lowest coverage recorded in the 100 m range. After almost four years of recovery, vegetation coverage in the 100 m range increased considerably, attaining levels recorded in the 500 m range, but remained significantly lower than that observed in the control plot. The rate of relative change in vegetation coverage in the 100 m range decreased from 0.71 to 0.68 during the period of construction, then rebounded to 0.71 in the post-construction period, to attain the same rate as was recorded during pre-construction. The scope of main influence was the construction area within the range of 100 m; beyond which, the strength of ecological impact was greatly reduced. 参考文献 相似文献 引证文献

基于多时相Landsat5/8影像的岷江汶川-都江堰段植被覆盖动态监测

PDF HTML阅读 XML下载 导出引用 引用提醒 基于多时相Landsat5/8影像的岷江汶川-都江堰段植被覆盖动态监测 DOI: 10.5846/stxb201409051756 作者: 作者单位: 西南土地资源评价与监测教育部重点实验室,西南土地资源评价与监测教育部重点实验室,西南土地资源评价与监测教育部重点实验室,西南土地资源评价与监测教育部重点实验室,西南土地资源评价与监测教育部重点实验室 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金资助项目(41371125) Dynamic monitoring of fractional vegetation cover along Minjiang River from Wenchuan County to Dujiangyan City using multi-temporal landsat 5 and 8 images Author: Affiliation: Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Chengdu,Sichuan,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Chengdu,Sichuan,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Chengdu,Sichuan,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Chengdu,Sichuan,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Chengdu,Sichuan Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:植被覆盖度是衡量地表植被状况和指示生态环境变化的一个重要指标。基于像元二分模型,利用Landsat5/8遥感影像和DEM数据,对岷江汶川-都江堰段植被覆盖动态变化进行了监测,并结合高程、坡度和坡向数据,分析了汶川地震前后植被受损与恢复的空间动态格局变化。研究表明:植被覆盖总体良好,大部分区域的植被覆盖度均在中、高度以上,空间格局上呈现由汶川县东部、都江堰市西北部的龙门山区向两侧减少的总体趋势;地震造成植被受损面积达63808.7 hm2,且集中分布于海拔567-4331 m、坡度26-51°的范围以及东坡、北坡、南坡和西坡;震后5a,植被恢复面积17786.47 hm2,主要分布在海拔576-2180 m与3256-3793 m、坡度小于9°和26-51°以及东坡、东南坡和和南坡;高程和坡度对植被损毁与恢复的影响明显高于坡向。 Abstract:The terrestrial ecosystem plays an important role in maintaining the structure, function, and environment of earth systems, and therefore, human survival. Fractional vegetation cover (FVC) is an important indicator of ecological changes in the environment, and an important spatial parameter of land surface vegetation status for various ecological models. It is very important to estimate the changes and patterns of FVC within the fragile ecological system of the Minjiang River, which is located in a transition zone between the Tibetan Plateau and Sichuan basin. FVC information in the arid valley of the Minjiang River was extracted from remote sensing data, DEM, and GIS technology following the dimidiate pixel model. The differentiation characteristics of the spatial and temporal dynamic patterns of FVC, vegetation damage caused by the Wenchuan earthquake, vegetation restoration, elevation, slope, and aspect were also quantitatively studied. The results showed that:(1) the vegetation coverage was generally good during the study period; there were variations in levels of FVC, and the FVC in most areas was above medium and high levels. The overall spatial pattern showed reduced FVC on either side of the Longmen Mountains, in eastern Wenchuan County, and northwestern Dujiangyan City. The FVC change tended to increase first, then decrease with increasing elevation rendering. Above the lower levels, FVC was mainly distributed at elevations of 4331-4869 m, where the FVC decreased with increasing slope. More than 24% of the vegetation coverage was distributed in the area where the slope was less than 9°; there was little or no vegetation coverage in areas where the slope was greater than 51°. The FVC also changed according to aspect. It was mainly distributed on the eastern, western, and southern slopes. (2) The area of vegetation damage caused by the Wenchuan earthquake was 63808.7 hm2. Severe damage to vegetation occurred mainly within the range of 567-4331 m elevation, on slopes of 26-51°, with eastern, northern, southern, or western aspects. (3) After five years of natural regeneration, 17786.47 hm2 of the destroyed areas were recovered. The recovered vegetation area occurred mainly across elevation ranges of 567-2180 m and 3256-3793 m, on slopes of <9° or 26-51°, and eastern, southeastern, and southern aspects. (4) The results also showed that elevation and slope had significantly larger effects than aspect on vegetation damage or restoration. Although there was a certain correlation between the vegetation damage and restoration, the change patterns were complicated. The results provided very useful information for decision-making and policy-planning in the region of the Minjiang River, from Wenchuan County to Dujiangyan City, after the Wenchuan earthquake. Although the natural vegetation recovery is a slow process, some of the areas with earthquake-induced damage can be restored to their original condition through natural succession. Human intervention may not be a good way to address natural vegetation recovery in this area. Thus, vegetation restoration mainly involves closing the areas to promote natural vegetation restoration, or adopting artificial forestation to restore vegetation in a small area. 参考文献 相似文献 引证文献

Investigating natural drivers of vegetation coverage variation using MODIS imagery in Qinghai, China

The climatically sensitive Qinghai province of China has been recognized as a hotspot for studies on the feedbacks of terrestrial ecosystems to global climate change. Thus, investigating vegetation coverage and its natural drivers in Qinghai is an important focus of ecosystem research. On the basis of Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time series data, we estimated the vegetation coverage in this region using the dimidiate pixel model. Trend analyses, correlations between meteorological parameters, changes in vegetation coverage, and the temporal and spatial relationships between soil texture and vegetation coverage were used to investigate the possible drivers of vegetation coverage variations. The results indicated that the reduction of vegetation coverage slowed down in the period from 2000 to 2012. Annual mean temperature was the main climatic driver of the total extremely low and low vegetation coverage areas in Qinghai, followed by the precipitation anomalies. The extremely low and low vegetation coverage areas were mainly distributed in regions with a mean annual relative air humidity of <40% and the spatial distributions of these two area types differentiated along the 200-mm rainfall contours. The total extremely low and low vegetation coverage areas were mainly characterized by sandy clay loam soil, followed by loamy sand and sandy soil. Regions with sandy loam or loam soil have the greatest risk of vegetation coverage reductions. Knowledge of vegetation coverage variation and its natural drivers in the ecologically fragile region of Qinghai can provide scientific support for managing environmental change and desertification.

Research on Vegetation Coverage Change in Sheng Jin Lake Wetland of Anhui Province

The vegetation coverage in different areas was calculated based on remote sensing images (TM images) in 1986, 2002 and 2011 by employing the method of dimidiate pixel model in Sheng Jin Lake of Anhui province. The vegetation fraction maps of different periods were generated to analyze the temporal change of the vegetation fraction of the Sheng Jin Lake area. The results showed that the vegetation fraction changed greatly from 1986 to 2011. The average vegetation fraction increased from 57.02 to 60.30 %, the medium vegetation coverage continued to increase. The vegetation coverage decreased sharply from 1986 to 2002, and then increased slightly, from 2002 to 2011. The vegetation coverage presented the trend of degradation to recovery. The proportion of the experimental area affected by this trend was larger, which played a considerable role in the environmental quality. In the future, ecological environmental construction should be considered in the experimental area, because of the increasing environment problem in recent decades.

Fractional vegetation cover estimation in northern China and its change analysis

The aim of this study is to analyze the spatial- temporal pattern and change of fractional vegetation cover( FVC) in northern China since 2000. FVC of northern China from 2000 to 2012 was estimated using dimidiate pixel model based on the normalized difference vegetation index( NDVI) calculated by MODIS spectral reflectance data. The FVC change trends and characteristics of the study area during the 13 years were analyzed. The inner annual FVC change trend in northern China indicated that the maximum FVC generally appeared in July or August,which was consistent with the vegetation growth season. The maximum annual FVC showed a slightly increase trend in the whole study area,and the annual increase rate was 0. 2%. However,the spatial distribution of maximum annual FVC change trend had great differences. The typical regions of the Three- North Shelter Forest Region such as Northeast China,North China and Loess Plateau region had an obviously increase in maximum annual FVC.

基于中高分辨率遥感的植被覆盖度时相变换方法

PDF HTML阅读 XML下载 导出引用 引用提醒 基于中高分辨率遥感的植被覆盖度时相变换方法 DOI: 10.5846/stxb201305020904 作者: 作者单位: 黄河中下游数字地理技术教育部重点实验室,中国科学院遥感与数字地球研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 中国科学院知识创新工程重大项目(KZCX1-YW-08-03);水利部-官厅密云水库上游水土保持遥感监测二期工程(HW-STBC2004-03);中国博士后科学基金资助项目(20100470994) A temporal transformation method of fractional vegetation cover derived from high and moderate resolution remote sensing data Author: Affiliation: Institute of Remote Sensing Applications,Chinese Academy of Sciences,Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:植被覆盖度是衡量地表植被状况、指示生态环境变化的一个重要指标,也是许多学科的重要参数。传统的测量方法难以获取时间连续的面状数据,且耗时、耗力,很难大范围推广。遥感估算方法虽然可以弥补传统方法的不足,但由于云覆盖等天气条件的影响,获得同一时相覆盖整个研究区的遥感影像非常困难,时相的差异必然导致研究结果产生误差。针对植被覆盖度这一重要生态参数,结合低分辨率遥感数据的时间优势和中高分辨率遥感数据的空间优势,提出一种时相变换方法,将源于中高分辨率影像的植被覆盖度变换到研究需要的时相上。首先,利用像元二分模型计算MODIS尺度的时间序列植被覆盖度,并利用已经获得的SPOT影像计算其获取时相上的植被覆盖度;其次,利用土地利用图划分植被覆盖类型,并利用MODIS数据和土地利用数据之间的空间对应关系制作MODIS像元内各类植被覆盖的面积百分比数据;再次,利用面积百分比数据提取各类植被覆盖的纯像元,结合MODIS植被覆盖度时间序列,从而提取各类植被覆盖纯像元的植被覆盖度时间序列曲线;最后利用像元分解的方法提取MODIS像元内各类植被覆盖组分的植被覆盖度的变化规律,将其应用到该组分对应位置上SPOT像元的植被覆盖度上,从而将其变换到所需要的时相上。在密云水库上游进行试验,将覆盖研究区的10 景SPOT5多光谱影像计算的植被覆盖度统一变换到7 月上旬,结果显示:视觉效果上明显好转,且空间上连续一致;变换前后植被覆盖度的统计量对比结果也符合植被生长规律;利用外业样点数据与对应位置的植被覆盖度变换结果进行回归分析,结果发现各植被覆盖类型的R2均在0.8左右,表明变换结果与实测值非常接近,时相变换的效果较好,从而可以很好地促进相关研究精度的提高。 Abstract:Fractional vegetation cover (FVC) is an important index of land surface vegetation status. It is also an indicator of ecological environment changes and an important spatial parameter for various ecological modeling. The traditional methods of FVC measurement are time-consuming and labor-intensive, and thus difficult to obtain large-scale time series FVC data. Remote sensing technique is an effective approach to estimate FVC, but it is very difficult to acquire high and moderate resolution remote sensing images covering the entire study area during the same period because of the cloud cover and other weather conditions. Consequently, the FVC data derived from multi-temporal images inevitably lead to uncertain research results. To address the problem, this paper proposes a novel method to eliminate the impact of acquisition time differences on FVC from high and moderate resolution remote sensing images. For FVC data derived from images with different resolutions and acquisition dates, this proposed temporal transformation method is used to estimate high resolution FVC combined with a low-resolution time series FVC. Firstly, low and high resolution FVC data can be calculated from time series MODIS images and acquired SPOT images respectively using the dimidiate pixel model. Secondly, the vegetation cover is divided into different vegetation types based on the land use map derived from these SPOT images. And for each MODIS pixel, the area percentages of various types of vegetation cover are calculated based on the spatial overlay of MODIS image and land use data. As a result, the area percentage data represent that the area ratio of the different vegetation types within each MODIS pixel. Thirdly, the pure pixels of various types of vegetation cover can be extracted based on the area percentage data where the ratio is equal to 1, and the FVC time series curve of each type of vegetation cover can be generated based on these pure pixels and time series MODIS FVC data. Finally, the sub-pixel FVC variation of each type of vegetation cover can be extracted from MODIS pixels based on the pixel unmixing technique, and then apply them to the same location of SPOT FVC. Thus, the SPOT FVC can be transformed from its acquisition date to the specific date, which satisfies the need of our research. The feasibility of this temporal transformation method is examined in the upstream of Miyun Reservoir. The FVC data derived from 10 SPOT images are transformed to the same date of early July. The case study results show that: (1)The visual effects of the transformed FVC are significantly improved and consistent with the spatial patterns of vegetation cover; (2)The changes of FVC statistics information before and after the transformation are also in line with the laws of vegetation growth; (3) The linear regression of the FCV data on field measurement samples shows strong positive correlations between them, and the R2 is about 0.8 for each vegetation cover indicating the transformation results is close to the field measured values. The transformation results with higher precision can promote the accuracy of related researches. This method has also a certain reference value for the transformation of other parameters. 参考文献 相似文献 引证文献

昆明市主城区城市森林建设定量评价

以2003，2005，2009年3景TM数据和2013，2014年2景Landsat 8遥感影像为数据源，以昆明市主城区为研究对象，利用可见光波段提取归一化植被指数，像元二分模型估算植被覆盖度，根据“国家森林城市”评价指标定量分析昆明市主城区森林覆盖情况，并统计城市森林覆盖率、道路铁路绿化率、湖泊和河流水岸绿化率三项主要指标，分析昆明市主城区森林城市建设情况。结果表明：5景植被覆盖度分布图均显示昆明市主城区西山区和官渡区有林地覆盖区域植被覆盖等级相对较高，五华区和盘龙区植被覆盖等级较低。城市用地植被覆盖等级较低，草地、林地等植被覆盖等级较高。道路、铁路、湖泊、河流等指标基本达到“国家森林城市”评价指标的标准。由于近几年昆明市城乡建设中，大量土地需求导致部分草地、农田转变为城市用地，工业用地等，使得城市森林指标覆盖指标逐渐降低，到2014年达到了标准边缘。 Based on three different phases of TM image acquired in 2003, 2005, 2009 and two different phases of Landsat 8 image acquired in 2013, 2014 in this paper, this paper takes Kunming urban area as the research object to extract the normalized difference vegetation index by visible light and to estimate vegetation coverage by the dimidiate pixel model. Following the “National Forest City”, three main indexes of urban forest coverage, roads and railways coverage, water and lakes bank coverage are statistics to analyze evaluation index of Kunming urban area and to analyze the forest city construction situation. The results show: First, five phases vegetation coverage map shows that the level of vegetation coverage in Xishan and Guandu forestland coverage area is relatively high, while the level of vegetation coverage is low in Wuhua and Panlong; Second, urban land vegetation coverage level is low, but grassland and forest vegetation coverage level is higher; Last, the indicators of the roads, railways, lakes and rivers reached the standard of “National Forest City” evaluation index. This is due to the fact that a large number of land demands in the urban construction result in part of the grassland and farmland transforming into urban land and indus-trial land in recent years. So this study shows that the urban forest coverage indicators gradually reduce and reach the standard by 2014.

Study on Vegetation Fraction Cover Retrieval over Chuxiong Prefecture from TM Imagery

The paper retrieved vegetation fraction cover over Chuxiong Prefecture from TM Imagery by dimidiate pixel model on February 19h, 2003. The results showed that the mean vegetation fractional cover in Chuxiong prefecture was 0.400117, it’s secondary area mean vegetation fractional cover from large to small were Lufen county, Shuangbai county,Chuxiong city, Yaoan county, Dayao county, Wuding county, Nanhua county, Yongren county, Mouding county, Yuanmou county.

Dynamic Monitoring of Vegetation Coverage in Daliuta Mine Based on ENVI and GIS Technology

Researching dynamic variation of vegetation coverage has positive significance for vegetation restoration and ecological reconstruction. Landsat TM/ETM+ remote sensing data of the 2002, 2005, 2007, 2009 and 2011 was analyzed by ENVI and GIS technology, divided the vegetation coverage into 6 grades based on dimidiate pixel model, concluded the variation of ecological environment based on transfer matrix method, taked the Daliuta Mine as a case. The results indicated that average vegetation coverage in Daliuta Mine has increased integrally, and vegetation coverage changed from low, medium low and medium to medium and medium high, the vegetation coverage has somewhat. The dynamic monitoring of vegetation coverage can effectively reflect the variation of ecological environment in Daliuta Mine. This study provided a theoretical basis for the ecological reconstruction and sustainable development of Daliuta Mine.

Vegetation Fraction Change Monitoring in Beijing by Remote Sensing

Vegetation fraction was a most important index to score the vegetation coverage on the land surface. Improved dimidiate pixel model was applied to calculate and analyze the vegetation fraction change from September 2000 to September 2013 in Beijing, China. The results showed that vegetation coverage of Beijing in 2013 year was much better than 2000 year. The area of low and middle-low coverage of Beijing in 2013 decreased 379 km2 and 591 km2 respectively, and the area of high and middle coverage increased 885 km2 and 85 km2 respectively. The research provided a necessary reference for the related researches of vegetation fraction.

Evaluation of Spatiotemporal Variations of Global Fractional Vegetation Cover Based on GIMMS NDVI Data from 1982 to 2011

Fractional vegetation cover (FVC) is an important biophysical parameter of terrestrial ecosystems. Variation of FVC is a major problem in research fields related to remote sensing applications. In this study, the global FVC from 1982 to 2011 was estimated by GIMMS NDVI data, USGS global land cover characteristics data and HWSD soil type data with a modified dimidiate pixel model, which considered vegetation and soil types and mixed pixels decomposition. The evaluation of the robustness and accuracy of the GIMMS FVC with MODIS FVC and Validation of Land European Remote sensing Instruments (VALERI) FVC show high reliability. Trends of the annual FVCmax and FVCmean datasets in the last 30 years were reported by the Mann–Kendall method and Sen’s slope estimator. The results indicated that global FVC change was 0.20 and 0.60 in a year with obvious seasonal variability. All of the continents in the world experience a change in the annual FVCmax and FVCmean, which represents biomass production, except for Oceania, which exhibited a significant increase based on a significance level of p = 0.001 with the Student’s t-test. Global annual maximum and mean FVC growth rates are 0.14%/y and 0.12%/y, respectively. The trends of the annual FVCmax and FVCmean based on pixels also illustrated that the global vegetation had turned green in the last 30 years. A significant trend on the p = 0.05 level was found for 15.36% of the GIMMS FVCmax pixels on a global scale (excluding permanent snow and ice), in which 1.8% exhibited negative trends and 13.56% exhibited positive trends. The GIMMS FVCmean similarly produced a total of 16.64% significant pixels with 2.28% with a negative trend and 14.36% with a positive trend. The North Frigid Zone represented the highest annual FVCmax significant increase (p = 0.05) of 25.17%, which may be caused mainly by global warming, Arctic sea-ice loss and an advance in growing seasons. Better FVC predictions at large regional scales, with high temporal resolution (month) and long time series, would advance our ability to understand the characteristics of the global FVC changes in the last 30 years and predict the response of vegetation to global climate change.

青海省东部农业区植被覆盖时空演变遥感监测与分析

PDF HTML阅读 XML下载 导出引用 引用提醒 青海省东部农业区植被覆盖时空演变遥感监测与分析 DOI: 10.5846/stxb201301230138 作者: 作者单位: 西北农林科技大学水利与建筑工程学院,西北农林科技大学水利与建筑工程学院,西北农林科技大学水利与建筑工程学院,西北农林科技大学水利与建筑工程学院,山东省水利勘测设计院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家科技支撑计划项目（2011BAD29B01）；国家高技术研究发展计划（"863"计划）项目（14110209）；西北农林科技大学基本科研创新重点项目（Z109021202） Spatiotemporal variation of fractional vegetation cover and remote sensing monitoring in the eastern agricultural region of Qinghai Province Author: Affiliation: College of Water Resources and Architectural Engineering,Northwest Agriculture and Forestry University,College of Water Resources and Architectural Engineering,Northwest Agriculture and Forestry University,College of Water Resources and Architectural Engineering,Northwest Agriculture and Forestry University,College of Water Resources and Architectural Engineering,Northwest Agriculture and Forestry University,Shandong Survey and Design Institute of Water Conservancy Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:基于象元二分模型，利用MODIS植被指数产品定量估算研究区2000-2009年生长季（4-9月）植被覆盖度，采用相关系数法和有序聚类分析方法对植被覆盖度时空变化趋势及突变进行了分析，并结合DEM分析其对地形因子的响应。结果显示：1）研究区2000-2009年整体植被覆盖度在波动中呈不显著增加趋势，其中2001年是显著突变年份，表明研究区植被覆盖度发生比较显著的变化；2）通过对地形因子的响应分析，植被覆盖度在高程2500m和4100m，坡度4°和26°发生突变；对各高程带、坡度带植被覆盖度年际变化趋势及突变年份进行分析，获得了各带的变化趋势及其突变年份。对研究获得的结果进行讨论，结果表明：研究区降水量的变化及退耕还林措施是植被覆盖度变化的重要影响因素，其中退耕还林措施对植被覆盖度变化的影响较大。 Abstract:Based on dimidiate pixel model, the normalized difference vegetation index (NDVI) datasets deduced from MODIS product were used to calculate the fractional vegetation cover (FVC) in the eastern agricultural region of Qinghai Province in vegetation growing season(Apr.-Sep.) from 2000 to 2009. The correlation coefficient method and the ordered clustering analysis method were applied to detect the spatiotemporal trend and identify abrupt change points. In addition, DEM was considered to investigate the influence of terrain factors on fractional vegetation cover. The results indicated that: 1) fractional vegetation cover of the study area showed a slightly upward trend from 2000 to 2009 and the change was not significant; The year of 2001 was a significant abrupt change point, suggesting that the fractional vegetation cover changed significantly. 2) According to the analysis of fractional vegetation cover responding to terrain factors, the abrupt change points of fractional vegetation cover can be found at: 2500 m and 4100 m in the elevation zones, 4 degrees and 26 degrees in the slope zones, respectively. The trend and the abrupt change points in each specific elevation zone and slope zone were obtained through the investigation of interannual variation and abrupt change year between fractional vegetation cover and both elevation and slope zones. Furthermore, the contributing factors to spatiotemporal variation of fractional vegetation cover and its responding to terrain factors were further discussed. It can be conclude that changes in precipitation and returning cultivated land into forest measurs were the important influence factors, but the latter had a greater influence. 参考文献 相似文献 引证文献

喀斯特与非喀斯特区域植被覆盖变化景观分析——以广西壮族自治区河池市为例

With the Landsat-TM images in 1990、2000 and 2010 as a data source,fractional vegetation cover in Hechi District was calculated by using the dimidiate pixel model based on NDVI and was classified into five grades. Overlaying the fractional vegetation cover maps and the geological map,the impact on fractional vegetation cover exerted by geological structure was analyzed. Finally,the landscape pattern of change in fractional vegetation cover during this period was studied using a landscape pattern analysis program FRAGSTATS by analyzing 10 Landscape indices at class-level and at landscapelevel to show the changing feature of landscape pattern. The results indicate that: 1) The fractional vegetation cover in the study area was increased from 1990 to 2010 and the region with high and relatively high vegetation fractions were still dominant in the area. 2) The landscape heterogeneity and fragmentation of the study area were declined,while landscape dominance was increased in the study area. 3) The patch shape of the study area mainly depended on natural landform andnatural environment condition from 1990 to 2010. 4) The aggregation degree of the whole landscape was generally increased. The whole landscape in the study area has been more and more controled by several types of the vegetation coverage grades during 1990—2010.The ecological restoration of vegetation landscape in the study area was significant,which tallies with economic social development in the stage of 1990—2010. The research findings will lead to the change of ecological restoration of vegetation landscape in no-karst district is more obvious than it in karst district. The landscape in karst district is more scattered and more complex than it in no-karst district. Ecological conditions in karst district is more easily destroyed and difficultly restored than it in no-karst district. These may explain the particularity of karst ecosystem.

Spatio-temporal patterns of precipitation-use efficiency of vegetation and their controlling factors in Inner Mongolia

Aims Precipitation-use efficiency(PUE) is an important indicator for understanding how net primary productivity(NPP) in arid and semi-arid ecosystems responds to variations in precipitation. The objective of this study was to determine the spatio-temporal patterns and responses to climatic and biotic factors of PUE at a regional scale. Methods CASA(Carnegie-Ames-Stanford Approach) model was used to simulate NPP in Inner Mongolia during 2001–2010 based on the MOD13A1 data and spatially interpolated meteorological data. PUE was calculated as the ratio of NPP to annual precipitation. The effects of fraction of vegetation cover(FVC) and leaf area index(LAI) on PUE were also investigated. The FVC was calculated with the dimidiate pixel model based on the MOD13A1 data. LAI data were acquired as the MODIS LAI products. Important findings The multi-year average PUE of Inner Mongolia was 0.94 g C·m–2·mm–1, exhibiting apparent increasing trend at an average rate of 0.55 g C·m–2·mm–1 per 10° with changes in longitude from 105° E to 120° E. The spatial patterns of PUE showed significant differences among vegetation types. The PUE was highest in shrubs and lowest in desert. The spatial distribution of PUE responded differentially to climatic factors in different precipitation ranges. Where precipitation was less than 75 mm, PUE showed a significant negative correlation with temperature and precipitation(R2 = 0.226, p 0.05). In the area with precipitation of 175–300 mm, PUE exhibited a significant positive correlation with temperature and precipitation(R2 = 0.878, p 0.001), and increased significantly(R2 = 0.94, p 0.001) with precipitation at a rate of 0.57 g C·m–2·mm–1 per 100 mm. In the area where precipitation was higher than 475 mm, PUE increased spatially with increasing temperature and decreasing precipitation. In this precipitation range, the effect of temperature on spatial variance of PUE was 8.61 times of that of precipitation. The inter-annual variation of PUE also had different responses to climatic factors in different precipitation ranges. Where precipitation was less than 220 mm, PUE displayed a positive correlation with precipitation and a negative correlation with temperature. In the area with precipitation of 220–310 mm, precipitation had a much greater effect than temperature on the inter-annual variations of PUE. Where precipitation was higher than 310 mm, PUE showed positive correlations with both temperature and precipitation. In relatively humid parts of this precipitation range, however, the PUE showed a poor correlation with precipitation, but a stronger correlation with temperature. FVC was linearly related with the spatial distribution(R2 = 0.73, p 0.001) and inter-annual variations of PUE(R2 = 0.11, p 0.001). LAI showed a linear relationship with the inter-annual variations of PUE(R2 = 0.42, p 0.001). In the area where LAI was less than 3.15 and with non-forest vegetation, LAI was linearly related with the spatial distribution of the PUE.

Research on vegetation cover information extraction technologies under different terrain conditions

Aims We compared a variety of vegetation cover extraction methods by hyperspectral remote sensing that are currently popular. Our aims were to systematically study vegetation information extraction technology and provide a reference for further study of vegetation cover. Methods The methods of vegetation index, dimidiate pixel model, principal component regression (PCR), partial least squares regression first order differential (PLSR) and linear spectral mixture decomposition model were used to extract vegetation information. Important findings The vegetation cover estimation ability of dimidiate pixel models established by different normalized differential vegetation index (NDVI) was higher than that of the regression models established by NDVI directly. The optimization model for shady slopes was PLSR model based on the first order differential (FD) with modeling R2 = 0.810, root mean square error (RMSE) = 6.29 and validation R2 = 0.773, RMSE = 8.85. The optimization model for sunny slopes was PLSR model based on the second order differential (SD), with modeling R2 = 0.823, RMSE = 6.04 and validation R2 = 0.801, RMSE = 7.35. The optimization model for plains was full confine linear spectral mixture model (FCLS), with validation R2 = 0.852, RMSE = 5.86.

Vegetation fractional coverage change in a typical oasis region in Tarim River Watershed based on remote sensing

Vegetation fractional coverage (VFC) is an important index to describe and evaluate the ecological system. The vegetation index is widely used to monitor vegetation coverage in the field of remote sensing (RS). In this paper, the author conducted a case study of the delta oasis of Weigan and Kuqa rivers, which is a typical saline area in the Tarim River Watershed. The current study was based on the TM/ETM+ images of 1989, 2001, and 2006, and supported by Geographic Information System (GIS) spatial analysis, vegetation index, and dimidiate pixel model. In addition, VBSI (vegetation, bare soil and shadow indices) suitable for TM/ETM+ images, constructed with FCD (forest canopy density) model principle and put forward by ITTO (International Tropical Timber Organization), was used, and it was applied to estimate the VFC. The estimation accuracy was later proven to be up to 83.52%. Further, the study analyzed and appraised the changes in vegetation patterns and revealed a pattern of spatial change in the vegetation coverage of the study area by producing the map of VFC levels in the delta oasis. Forest, grassland, and farmland were the three main land-use types with high and extremely-high coverage, and they played an important role in maintaining the vegetation. The forest area determined the changes of the coverage area, whereas the other two land types affected the directions of change. Therefore, planting trees, protecting grasslands, reclaiming farmlands, and controlling unused lands should be included in a long-term program because of their importance in keeping regional vegetation coverage. Finally, the dynamic variation of VFC in the study area was evaluated according to the quantity and spatial distribution rendered by plant cover digital images to deeply analyze the reason behind the variation.