黄土高原植被变化对环境影响的数值模拟   总被引：14，自引：10，他引：4  

梁玲  吕世华  柳媛普 《高原气象》2006,25(4):575-582

使用美国NCAR新版MM5非静力平衡模式,模拟了黄土高原2003年6月26~30日的一次降水过程。该试验是通过改变黄土高原局部地区植被覆盖情况,对比分析植被改变区域内各气象要素的变化情况。结果表明:植被改善能使雨量增加,径流量减小,湿度增大,温度日较差减小,使气候变的温和。植被退化却使雨量减少,径流加大,易使水土流失,对水土保持不利。试验较全面地揭示了非均匀地表大气边界层内的温、湿场与陆面相互作用的机理。  相似文献   

澳大利亚植被覆盖对亚澳季风影响的数值模拟(Ⅱ): 对东亚夏季风环流的影响   总被引：2，自引：1，他引：1  

鲍艳  吕世华  刘海辉 《高原气象》2006,25(5):772-780

在文献[1]的基础上,对澳大利亚大陆植被覆盖变化对北半球夏季越赤道气流和东亚季风环流季节变化的影响进行了研究.结果表明,植被覆盖变化对东亚季风建立前后南风越赤道气流建立时间、强弱和南半球主要环流系统都有显著的影响.绿化导致了索马里越赤道气流的建立提前,增强了不同时期南风越赤道气流的强度,但对90°E以东来自澳大利亚高压的几支越赤道气流影响不大.同时,绿化促使南半球澳大利亚高压和马斯克林高压提前建立,西太平洋副热带高压北进提前,且强度减弱,导致西南气流更容易深入东亚内陆和西太平洋.这些影响促使盛夏期西南亚季风的影响区域和强度都有所扩展,对东南季风则影响不大.沙漠化则使索马里气流略微减弱,西太平洋副热带高压在春夏季节则一直偏强,至7月中旬,才有明显东撤,阻碍了越赤道气流的北上,西南季风在此影响下强度和影响范围均有所缩减.  相似文献   

2000—2015 年伊犁河谷植被覆盖时空变化特征   总被引：1，自引：0，他引：1       下载免费PDF全文

孙国军  李卫红  朱成刚  崔东  刘海军 《干旱区地理》2020,43(6):1551-1558

利用 2000—2015 年的 EOS／MODIS 数据,采用趋势分析、Hurst 指数、变异系数法对伊犁河 谷植被时空变化及未来趋势进行分析,结果显示：空间分布上,伊犁河谷植被覆盖度呈北部、南部、 东部偏高,西部、中部偏低的分布特征;时间变化上,2000—2015 年,伊犁河谷植被覆盖度波动减 小,减速为 6.25%·(10 a)^-1;区域分布上,伊犁河谷植被表现为低波动变化,波动程度中等以及下占 73.16%,波动程度高的区域占 26.84%。未来预测表明,伊犁河谷植被覆盖呈退化趋势,其中,持续 退化的面积占 57.55%,持续改善的面积占 13.51%。  相似文献   

基于MODIS积雪产品的高亚洲融雪末期雪线高度遥感监测   总被引：4，自引：0，他引：4  

王晓茹  唐志光  王建  王欣  魏俊锋 《地理学报》2020,75(3):470-484

以2001—2016年逐日MODIS积雪产品为主要数据源,在高亚洲区域发展了大尺度融雪末期雪线高度的遥感提取方法,并对其2001—2016年的时空变化特征进行了分析。提取方法首先对逐日的MODIS积雪覆盖率产品进行去云处理,获得积雪覆盖日数（SCD）数据集;并用冰川年物质平衡观测数据、融雪末期Landsat数据对提取终年积雪的MODIS SCD阈值进行率定;最后以MODIS SCD提取的终年积雪面积结合地形“面积—高程”曲线实现大尺度融雪末期雪线高度信息的提取。结果表明：① 高亚洲融雪末期雪线高度的空间异质性较强,总体上呈南高北低的纬度地带性分布规律;并因受山体效应的影响,雪线高度由高海拔地区向四周呈环形逐渐降低的特点。② 高亚洲2001—2016年融雪末期雪线高度总体上表现为明显的增加趋势。在744个30 km的监测格网中,24.2%的格网雪线高度呈显著增加,而仅0.9%的格网呈显著下降。除兴都库什、西喜马拉雅外,其他地区雪线高度均表现为升高趋势,显著上升的地区主要分布在天山、喜马拉雅中东部和念青唐古拉山等,其中以东喜马拉雅升高最为显著（8.52 m yr ^-1）。③ 夏季气温是影响高亚洲融雪末期雪线高度变化的主要因素,两者具有显著的正相关关系（R = 0.64,P < 0.01）。  相似文献   

喜马拉雅山脉中段土地覆被的垂直分异特征     

张镱锂  吴雪  郑度 《地理学报》2020,75(5):931-948

喜马拉雅山脉中段的珠穆朗玛峰等地,海拔高差巨大、生境复杂多变、土地覆被类型多样且植被垂直带谱完整,是全球范围内研究土地覆被垂直变化的理想场所。本文基于30 m空间分辨率的土地覆被数据（2010年）和DEM数据,在ArcGIS和Matlab平台的支持下,提出并运用脊线法、样带法和扇区法3种山地南北坡划分方法,研究了喜马拉雅山土地覆被垂直分布与结构差异。结果表明：① 山地土地覆被分布具有明确的垂直地带性结构特征,喜马拉雅中部土地覆被垂直带谱为南六北四式,土地覆被垂直带谱中具有人类活动的特点。② 南北坡之间的土地覆被垂直带谱差异明显,南坡土地覆被类型完整多样,北坡相对简单;对同类型土地覆被而言,南坡较北坡分布高程低、幅度宽。③ 依据各类型分布面积比随海拔变化情况,土地覆被类型在南北坡上的垂直分布可分为4种模式：冰川雪被、稀疏植被和草地为单峰分布型,裸地为南单峰北双峰分布型。④ 3种划分方法中,南坡的土地覆被垂直带结构具有相似性,而北坡的土地覆被垂直带结构存在差异,扇区法较好地反映了土地覆被自然分布格局。  相似文献   

喜马拉雅中部甘达基河流域尼泊尔国鸟(棕尾虹雉)生境分布变化     

Raju RAI  Basanta PAUDEL  谷昌军  Narendra Raj KHANAL 《资源与生态学报(英文版)》2020,11(2):223-231

甘达基河流域(Gandaki River Basin,GRB)是喜马拉雅中部地区的一部分,该地区栖息着许多珍稀的野生动物。由于气候和人类活动的影响,许多珍稀保护物种的生境处于危险之中。本研究基于最大熵(MaxEnt)模型,运用生物气候、土地覆被和DEM数据,分析各环境要素对棕尾虹雉(Lophophorusimpejanus)的生境适宜性的影响,评估棕尾虹雉现在状况和未来栖息地分布的变化。研究表明,目前棕尾虹雉的高度适宜栖息地面积约为749 km^2,主要分布在流域北部、东部和西部,尤其是郎塘国家公园、马纳斯卢峰自然保护区和安纳布尔纳峰自然保护区等保护区内。到2050年,棕尾虹雉的高度适宜栖息地面积将减少至561 km^2,主要在流域北部和西北部(即Chhyo,Tatopani,Humde和Chame地区)。未来环境变化的模拟表明,由于适宜栖息地面积的减少,棕尾虹雉面临的生存风险将增加。  相似文献   

Accuracy assessment of NLCD 2011 percent impervious cover for selected USA metropolitan areas     

《International Journal of Applied Earth Observation and Geoinformation》2020

The emergence of high-resolution land cover data has created the opportunity to assess the accuracy of impervious cover (IC) provided by the National Land Cover Database (NLCD). We assessed the accuracy of the 900 m² NLCD2011 %IC for 18 metropolitan areas throughout the conterminous United States using reference data from 1 m² land cover data developed as part of the United States Environmental Protection Agency’s EnviroAtlas project. Agreement was assessed from two perspectives: 1) sensitivity to the size of the assessment unit used for the comparison, and 2) utility of NLCD %IC to serve as a proxy for high-resolution IC. The former perspective was considered because statistical relationships can be sensitive to assessment unit size and shape, and the latter perspective was considered because high resolution (reference) %IC data are not available nationwide. The utility of NLCD %IC as a proxy for the high resolution data was assessed for seven lattice (square) cell sizes ranging from 1 ha to 200 ha using four EnviroAtlas IC indicators: 1) %IC per 100 ha (1 km²); 2) %IC by Census block group; 3) %IC within a 15 m (radius) of the riparian zone, and; 4) %IC within a 50 m (radius) of the riparian zone. Agreement was quantified as per assessment unit deviation (NLCD %IC – reference %IC) and summarized as Mean Absolute Deviation (MAD) and Mean Deviation (MD) both within and across the 18 metropolitan areas. Ordinary least squares (OLS) regression (y = reference %IC and x = NLCD %IC) was also used to evaluate the quality of the NLCD %IC data. MAD was ≤ 5% for six of the seven lattice cell sizes. MAD was also ≤ 5% for Census block groups > 100 ha and for both riparian units. These results suggest that uncertainty attributable to the measurement of %IC was no greater than the uncertainty related to the effect of IC on aquatic resources that have been derived from studies of aquatic condition (e.g., benthic fauna) over a range of %IC. Overall, agreement was variable from one metropolitan area to the next. Agreement improved as assessment unit size increased and declined as the level of urbanization (NLCD %IC) increased. NLCD %IC tended to underestimate reference %IC overall, but NLCD %IC was sometimes greater than reference %IC in urbanized settings.  相似文献   

Moving from plot-based to hillslope-scale assessments of savanna vegetation structure with long-range terrestrial laser scanning (LR-TLS)     

《International Journal of Applied Earth Observation and Geoinformation》2020

Reliable quantification of savanna vegetation structure is critical for accurate carbon accounting and biodiversity assessment under changing climate and land-use conditions. Inventories of fine-scale vegetation structural attributes are typically conducted from field-based plots or transects, while large-area monitoring relies on a combination of airborne and satellite remote sensing. Both of these approaches have their strengths and limitations, but terrestrial laser scanning (TLS) has emerged as the benchmark for vegetation structural parameterization – recording and quantifying 3D structural detail that is not possible from manual field-based or airborne/spaceborne methods. However, traditional TLS approaches suffer from similar spatial constraints as field-based inventories. Given their small areal coverage, standard TLS plots may fail to capture the heterogeneity of landscapes in which they are embedded. Here we test the potential of long-range (>2000 m) terrestrial laser scanning (LR-TLS) to provide rapid and robust assessment of savanna vegetation 3D structure at hillslope scales. We used LR-TLS to sample entire savanna hillslopes from topographic vantage points and collected coincident plot-scale (1 ha) TLS scans at increasing distances from the LR-TLS station. We merged multiple TLS scans at the plot scale to provide the reference structure, and evaluated how 3D metrics derived from LR-TLS deviated from this baseline with increasing distance. Our results show that despite diluted point density and increased beam divergence with distance, LR-TLS can reliably characterize tree height (RMSE = 0.25–1.45 m) and canopy cover (RMSE = 5.67–15.91%) at distances of up to 500 m in open savanna woodlands. When aggregated to the same sampling grain as leading spaceborne vegetation products (10–30 m), our findings show potential for LR-TLS to play a key role in constraining satellite-based structural estimates in savannas over larger areas than traditional TLS sampling can provide.  相似文献   

Update and spatial extension of strategic forest inventories using time series remote sensing and modeling     

《International Journal of Applied Earth Observation and Geoinformation》2020

Up-to-date forest inventory information relating the characteristics of managed and natural forests is fundamental to sustainable forest management and required to inform conservation of biodiversity and assess climate change impacts and mitigation opportunities. Strategic forest inventories are difficult to compile over large areas and are often quickly outdated or spatially incomplete as a function of their long production cycle. As a consequence, automated approaches supported by remotely sensed data are increasingly sought to provide exhaustive spatial coverage for a set of core attributes in a timely fashion. The objective of this study was to demonstrate the integration of current remotely-sensed data products and pre-existing jurisdictional inventory data to map four forest attributes of interest (stand age, dominant species, site index, and stem density) for a 55 Mha study region in British Columbia, Canada. First, via image segmentation, spectrally homogenous objects were derived from Landsat surface-reflectance pixel composites. Second, a suite of Landsat-based predictors (e.g., spectral indices, disturbance history, and forest structure) and ancillary variables (e.g., geographic, topographic, and climatic) were derived for these units and used to develop predictive models of target attributes. For the often difficult classification of dominant species, two modelling approaches were compared: (a) a global Random Forests model calibrated with training samples collected over the entire study area, and (b) an ensemble of local models, each calibrated with spatially constrained local samples. Accuracy assessment based upon independent validation samples revealed that the ensemble of local models was more accurate and efficient for species classification, achieving an overall accuracy of 72% for the species which dominate 80% of the forested areas in the province. Results indicated that site index had the highest agreement between predicted and reference (R² = 0.74, %RMSE = 23.1%), followed by stand age (R² = 0.62, %RMSE = 35.6%), and stem density (R² = 0.33, %RMSE = 65.2%). Inventory attributes mapped at the image-derived unit level captured much finer details than traditional polygon-based inventory, yet can be readily reassembled into these larger units for strategic forest planning purposes. Based upon this work, we conclude that in a multi-source forest monitoring program, spatially localized and detailed characterizations enabled by time series of Landsat observations in conjunction with ancillary data can be used to support strategic inventory activities over large areas.  相似文献   

Satellite image analysis using crowdsourcing data for collaborative mapping: current and opportunities     

Wei Su  Xiaodong Zhang 《International Journal of Digital Earth》2020,13(6):645-660

ABSTRACT

Researchers are continually finding new applications of satellite images because of the growing number of high-resolution images with wide spatial coverage. However, the cost of these images is sometimes high, and their temporal resolution is relatively coarse. Crowdsourcing is an increasingly common source of data that takes advantage of local stakeholder knowledge and that provides a higher frequency of data. The complementarity of these two data sources suggests there is great potential for mutually beneficial integration. Unfortunately, there are still important gaps in crowdsourced satellite image analysis by means of crowdsourcing in areas such as land cover classification and emergency management. In this paper, we summarize recent efforts, and discuss the challenges and prospects of satellite image analysis for geospatial applications using crowdsourcing. Crowdsourcing can be used to improve satellite image analysis and satellite images can be used to organize crowdsourced efforts for collaborative mapping.  相似文献