排序方式： 共有122条查询结果，搜索用时 15 毫秒
1.
2.
沙尘源区AVHRR数据地表温度时序变化与沙尘干量TSP数据的对比分析——以2001年春季北方强沙尘过程为例 总被引：7，自引：11，他引：7
根据沙尘暴起沙、传输与降沉模型系统对参数的需求，中日亚洲沙尘暴项目在源区、传输区和降沉区布设了先进的仪器设备，其中沙尘干量TSP数据是主要获取的数据，同时利用气象卫星获取沙尘过程的云图和反演沙尘过程的地表物理参数。由于不同土地利用／覆盖对沙尘暴过程中起沙的贡献不一样，研究中用局地分裂窗算法反演NOAA／AVHRR热红外波段数据的地面温度参数；取得大范围的时序地面温度数据后参照1：10万土地利用／覆盖类型重采样图层选点提取地表温度，形成不同点时间序列变化曲线；最后将不同地类的地表温度时序变化曲线与观测点沙尘干量TSP时序变化曲线对比分析，发现两者具有较好的对应关系，说明沙尘暴过程地表温度变化现象与沙尘有密切的关系。结果表明，利用遥感数据反演地面温度参数可以作为沙尘预报模型的重要参数。 相似文献
3.
目前 ,我国气象部门相当普遍地拥有气象卫星观测资料 ,但是 ,这些资料如何在城市气象服务以及为城市建设规划等方面的决策研究中发挥作用 ,急待进一步研究并开展工作。本文试图通过合理的反演处理 ,给出卫星观测对地面温度的测量结果 ,由此可比较细致地分析了解地面热状况及其与土地利用类型 ,地面覆盖性质等的关系。本文利用有限的 NOAA- AVHRR气象卫星遥感资料 ,采用修正的 Ulivieri分裂窗方法反演出同期的地表温度场 ,通过对北京地区的卫星观测资料进行算例分析 ,揭示出一个 2 0 0 km× 2 0 0 km范围内的地面温度分布特征。反演结果可以明显地揭示出城市热岛现象的变化规律 ,并且能较为清楚地反映出相对的高温区和低温区 相似文献
4.
Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect. 相似文献
5.
The grazing exclusion program used by the Tibetan government to protect the ecological environment has changed the vegetation and impacted the surface heat balance in North Tibet. However, little information is available to describe the in?uences of the current grazing exclusion program on local surface heat balance. This study uses the records of fenced grassland patch locations to identify the impact of grazing exclusion on surface heat balance in North Tibet. The records of fenced grassland patch locations, including the longitude, latitude, and elevation of the vertices of each fenced patch (polygon shapes), were provided by the agriculture and animal husbandry bureaus of the counties where the patches were located. ArcGIS 10.2 was used to create polygon shapes based on patch location records. Based on satellite data and the surface heat balance system determined by the model, values for changes in land surface temperature (LST), albedo and evapotranspiration (ET) induced by grazing exclusion were obtained. All of these can influence surface heat balance and alter the fluctuation of LST in the northern Tibetan Plateau. The LST trends for day and night showed an asymmetric diurnal variation, with a larger magnitude of warming in the day than cooling at night. The maximum decrease in absorbed shortwave of LST (-0.5 - -0.4 ℃ per decade) occurred in the central region, while the minimum decrease (-0.2 - -0.1 ℃ per decade) occurred in the eastern region. The decreased latent heat lead to the LST increased maximum (>1 ℃ per decade) occurred in the central region, The eastern region increased at a rate of 0.2-0.5 ℃ per decade, while the minimum increase (0-0.1 ℃ per decade) occurred in the northwestern region. 相似文献
6.
徐静波 《测绘与空间地理信息》2016,(1):122-124
研究庐山地区的地表温度,对于本地区的生态保护和开发具有重要意义。本文使用了目标区域内Landsat TM/ETM+从2000~2010年间共8幅影像数据,利用单通道算法和NDVI地表辐射率估算方法反演了区域内的温度场,并生成了历年温度对比效果图。分析推断目标区域内的温度场可能存在一个短年限的温度变化起伏规律,对庐山周边山区的影响有待进一步研究。 相似文献
7.
针对鲜有资源型城市的地表热环境研究这一情况,该文基于Landsat8遥感数据,反演了太原市在2013—2015年间共3期的地表温度。提出一个考虑空间格局结构的城市热岛效应指数,在3期数据中,太原市区整体热岛效应指数分别为9.1%、9.8%和8.9%;同时,根据城市功能和路网结构将太原市区划分为6个分区,从分区级层面量化分析了地表热环境的时空分异特征规律,结果表明,太原市区地表温度整体呈现空间分散化特征,不同分区也呈现出不同的时空格局演变过程;最后,选取40个地表温度实测样本点验证反演精度,最大误差绝对值为1.1℃,最小误差绝对值为0.2℃,均方根误差为0.7℃。 相似文献
8.
Land surface temperature (LST) is an important aspect in global to regional change studies, for control of climate change and balancing of high temperature. Urbanization is one of the influencing factors increasing land surface and atmospheric temperature, by the emission of greenhouse gases (e.g. CO2, NO and methane). In the present study, LST was derived from Landsat-8 of multitemporal data sets to analyse the spatial structure of the urban thermal environment in relation to the urban surface characteristics and land use–land cover (LULC). LST is influenced by the greenhouse gases i.e. CO2 plays an important role in increasing the earth’s surface temperature. In order to provide the evidence of influence of CO2 on LST, the relationship between LST, air temperature and CO2 was analysed. Landsat-8 satellite has two thermal bands, 10 and 11. These bands were used to accurately to calculate the temperature over the study area. Results showed that the strength of correlation between ground monitoring data and satellite data was high. Based on correlation values of each month April (R2 = 0.994), May (R2 = 0.297) and June (R2 = 0.934), observed results show that band 10 was significantly correlating with air temperature. Relationship between LST and CO2 levels were obtained from linear regression analysis. band 11 was correlating significantly with CO2 values in each of the months April (R2 = 0.217), May (R2 = 0.914) and June, (R2 = 0.934), because band 11 is closer to the 15-micron band of CO2. From the results, it was observed that band 10 can be used for calculating air temperature and band 11 can be used for estimation of greenhouse gases. 相似文献
9.
Land and Sea Surface Temperatures (LST and SST) are both recognized as Essential Climate Variables, and are routinely retrieved by a wealth of satellites. However, for validated approaches, the latest data are usually not available to the general public. We offer to bridge this gap, by using Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI), with its 15 min temporal resolution. Here, we present generic algorithms for the retrieval of both LST and SST, valid for the SEVIRI instrument onboard MSG platforms 8–11, which we validate using hourly data of 4 ground stations and 11 buoys in Spain over the years 2015 to 2018. These validations show that in the best conditions of surface homogeneity (cloud-free summer nights), errors in our LST estimation are below 1.5 K for stations with good thermal homogeneity. Comparison with LSA-SAF (Land Surface Analysis - Satellite Application Facility) LST shows differences below 2 K for most of SEVIRI disk, with higher differences in arid areas and during daytime. As for SST retrieval, the average error amount to 0.67 K for cloud-free buoy data. These algorithms have been implemented in a near-real time processing chain, which provide actualized LST and SST maps every 15 min within 5 min of image reception. These maps, along with other products, can be freely consulted from a dedicated webpage (https://www.uv.es/iplsat). 相似文献
10.
“源-汇”景观格局的热岛效应研究——以武汉市为例 总被引：1，自引：0，他引：1
论文基于2017年Landsat 8遥感影像,通过GIS技术选取城市地表温度、源汇景观密度、源汇景观贡献度和景观效应指数,结合地理空间分析和数理统计方法,分析了武汉市局部源汇景观格局对城市地表温度的贡献及其效应。结果表明：① 武汉市城区热岛(urban heat island, UHI)季节变化明显,夏季热岛强度大、范围广,呈“大”字型分布,工业集聚区和经济开发区产生的UHI更显著;② 武汉市城区平均地表温度(land surface temperature, LST)在距市中心约8 km处达到峰值后沿城乡梯度逐渐下降,呈现“倒钩型”特征,这一现象与景观密度变化密切相关;③ LST与源(正向)、汇(负向)景观密度存在极强相关性,不透水表面是城区热岛的主要贡献因子;④ 相同密度的水体和绿地,水体更具有削弱城市热岛效应的功能;⑤ 一般当汇-源景观面积比>0.89(汇区密度>0.47)时,局部景观格局对城市热岛有缓解作用,且局部汇区越集中缓解效果越显著。 相似文献