应用NOAA／AVHRR资料动态监测洪涝灾害的研究

以ＮＯＡＡ卫星为主要监测手段，对洪水、植被、土壤的光谱特征进行分析研究，提出了同时突出水体和植被的光谱分析思路。并根据客观分析需要，建立了洪涝灾情图像处理软件系统，对ＮＯＡＡ／ＡＶＨＲＲ图像资料进行投影、截取、放大、配准等一系列预处理。同时采用模糊非监督分类、比值、归一化植被指数方法对洪涝信息进行分析处理，确定受灾范围，量算受灾面积，划分受灾等级，提供灾情分布图，为防汛抗洪部门提供有力的科学依据。     

基于NOAA／AVHRR数据的景观格局分析——以塔里木河干流区域为例

在对NOAA／AVHRR数据进行灰度拉伸,直方图均衡化,多通道合成等方法处理后,应用IDRISI软件的空间分析功能,对塔里木河流域进行了景观格局的宏观分析,结果表明在塔里木河干流区城景观类型相对简单,各景观自身破碎度低,连通性较好,景观间的均匀度差,是一种典型的脆弱的干旱区陆河流域生态环境景观。     

基于NOAA/AVHRR热红外数据的城市热岛强度年内变化特征

采用ENVI/IDL编程技术,实现NOAA/AVHRR数据的校准、几何纠正、云污染识别与剔除、影像特征统计与输出等过程的批处理自动化操作。并以济南市中心城区为例,通过2005~2006年间获取的白天NOAA/AVHRR影像热红外波段调查了济南市区城市热岛强度的年内变化规律与过程。研究结果表明：① 济南市区全年大部分时间存在热岛现象,4~9月份城市热岛效应较为明显,尤以5、7、8月为甚。② 全年城市热岛平均强度2.77℃,最强的热岛效应出现于7月下旬至8月中旬间。③ 从季节分布来看,济南市区夏季热岛效应最明显,春季次之,秋、冬两季较弱。④ 城市热岛强度与城、郊地表温度存在正相关关系,但相关程度较差。     

多时机NOAA—AVHRR数据主成分分析的生物学意义

利用多时上NOAA－AVHRR的中国归一化植被指数NDVI数据进行主成分分析,并与从NDVI派生的4个生物不数作相关分析,结果表明：主成分变换既压缩了信息,将21个月的信息主要压缩到前4个主分量,又提取了关键的变化信息,第一主分量反映基本植被覆信息,第二、第三和第四主分量反映植被季相变化信息,正是由于一年12个月的NDVI曲线反映了植被季相变化特征,使得主成分变换得到的各主分量具有一定的生物学意义,而且17种中国典型植被在这4个主分量图像上存在一定的差异性,使其具有进行较高精度土地覆盖分类的潜力。     

Efficiency Research of Planted Rice Area Estimation From NOAA一AVHRR Data in Taihu Domain

运用NOAA-AVHRR资料估算水稻种植面积，是遥感应用领域中一个新的研究方向，结合国家“八五”攻关项目“太湖地区遥感话产”的要求，在太湖地区进行了初步的尝试:(1)根据估产精度要求和NOAA一AVHRR资料校正精度，探讨了运用NOAA一AVHRR资料估产所需的最小区域范围。(2)针对太湖地区的具休地理环境设计了提取水稻种植曲积的技术方案，并在试验区取得了初步成果。     

林火卫星遥感监测及早期报警技术研究

以我国林火发生率较高、卫星监测林火难度较大的西南林区为试验区，为大幅度提高林火报准率，开展了微机图像处理技术、地理信息系统（ＧＩＳ）、森林火灾的分布规律、ＡＶＨＲＲ林火信息提取技术和专家系统应用等研究。介绍了该项目的研究方法，叙述了研究成果的技术原理，展望了今后研究的主攻方向。     

运用NOAA AVHRR和Landsat TM数据估算多年水稻种植面积

介绍了综合运用NOAA AVHRR和Landsat TM数据进行多年水稻种植面积监测的一种方法,以湖北省为例,首先运用Landsat TM数据计算了该省1992年的水稻种植面积;接着运用1992年和1994年的NOAA AVHRR数据分别计算这两年的水稻像元数,以这两年水稻像元数的变化来反映水稻种植面积的变化;最后运用线性模型,估算1994年的水稻种植面积。所得的1994年水稻种植面积与湖北省农调队资料相比精度为84.5%。运用同样的方法估算1995年该省的水稻种植面积,精度达90%以上。     

通过AVHRR数据研究中国陆面温度分异规律

近年来国内外利用遥感方法在陆面温度精确反演中开展了大量的研究工作,采用了一个在大区域上适用的由NOAA？AVHRR数据反演陆面温度的方法,反演中国晴空条件下各月和全年平均陆面温度,分析了中国陆面温度的分异规律,并与气温的分异规律作了对比,同时对中国土地利用／土地覆盖变化研究（LUCC）样带上的陆面温度变化进行了分析,这项工作从晴空条件重新认识了地面温度场的空间分异,对于研究中国陆地土壤蒸发,植物光合作用,土地覆盖的分布具有重要的指示意义。     

Landsat TM热红外遥感数据定量反演地下水富集带的温度信息——以甘肃河西地区石羊河流域为例

利用ＬａｎｄｓａｔＴＭ６热红外遥感数据定量反演了干旱地区的地表温度,研究结果表明,研究区典型地表覆盖类型的地表亮温比地表真实温度低０．４～１Ｋ,遥感反演的地面真实温度与当地３月下旬的实测温度误差在０．８Ｋ以下,这说明用ＬａｎｄｓａｔＴＭ６定量反演干旱区的地表温度是可行的。研究结果还表明,地下水富集带地表温度具有异常现象,其地表温度比地表水体高５Ｋ左右,而比其它地表类型低７Ｋ以上,据此,可以利用热红外遥感技术有效地探测干旱区地下水富集带的信息。     

AVHRR数据小火点自动识别方法的研究

利用NOAA-AVHRR数据,采用多因子分析方法,通过建立小火点自动识别模型来提取小火点燃烧信息。经实验验证,该方法能较好地减少云体、裸地对火点判断的干扰,从而在一定程度上提高了对小火点的监测精度。     

Development and analysis of a 12-year daily 1-km forest fire dataset across North America from NOAA/AVHRR data

Fires in boreal and temperate forests play a significant role in the global carbon cycle. While forest fires in North America (NA) have been surveyed extensively by U.S. and Canadian forest services, most fire records are limited to seasonal statistics without information on temporal evolution and spatial expansion. Such dynamic information is crucial for modeling fire emissions. Using the daily Advanced Very High Resolution Radiometer (AVHRR) data archived from 1989 to 2000, an extensive and consistent fire product was developed across the entire NA forest regions on a daily basis at 1-km resolution. The product was generated following data calibration, geo-referencing, and the application of an active fire detection algorithm and a burned area mapping algorithm. The spatial-temporal variation of forest fire in NA is analyzed in terms of (1) annual and monthly patterns of fire occurrences in different eco-domains, (2) the influence of topographic factors (elevation zones, aspect classes, and slope classes), and (3) major forest types and eco-regions in NA. It was found that 1) among the 12 years analyzed, 1989 and 1995 were the most severe fire years in NA; 2) the majority of burning occurred during June-July and in low elevation zones (< 500 m) with gentle slopes (< 10°), except in the dry eco-domain where more fires occurred in higher elevation zones (> 2000 m); 3) most fires occurred in the polar eco-domain, sub-arctic eco-division, and in the taiga ( boreal forests), forest-tundras and open woodlands eco-provinces in the boreal forests of Canada. The tendency for multiple burns to occur increases with elevation and slope until about 2500 m elevation and 24° slope, and decreases therefore. In comparison with ground observations, the omission and commission errors are on the order of 20%.     

人体经络的三维数据模型和动画显示方法研究

本文叙述了人体三维形体的空间数据获得方法，提出一种基于齐次坐标变换的人体经络数据模型，为解决计算机人体经络模型的动画演示和经络穴位的透明叠加显示等问题提供了一条新思路，也为今后进一步应用数学方法或从整体综合的角度去研究经络打下了良好基础，并在分析Ｔａｒｇａ图象和ＦＬＩ动画格式的基础上，实现了它们在Ｗｉｎｄｏｗｓ环境下的显示方法。     

Dryland observation at local and regional scale — Comparison of Landsat TM/ETM+ and NOAA AVHRR time series

During the last few decades, many regions have experienced major land use transformations, often driven by human activities. Assessing and evaluating these changes requires consistent data over time at appropriate scales as provided by remote sensing imagery. Given the availability of small and large-scale observation systems that provide the required long-term records, it is important to understand the specific characteristics associated with both observation scales. The aim of this study was to evaluate the potentials and limits of remote sensing time series for change analysis of drylands. We focussed on the assessment and monitoring of land change processes using two scales of remote sensing data. Special interest was given to the influence of the spatial and temporal resolution of different sensors on the derivation of enhanced vegetation related variables, such as trends in time and the shift of phenological cycles. Time series of Landsat TM/ETM+ and NOAA AVHRR covering the overlapping time period from 1990 to 2000 were compared for a study area in the Mediterranean. The test site is located in Central Macedonia (Greece) and represents a typical heterogeneous Mediterranean landscape. It is undergoing extensification and intensification processes such as long-term, gradual processes driven by changing rangeland management and the extension of irrigated arable land. Time series analysis of NOAA AVHRRR and Landsat TM/ETM+ data showed that both sensors are able to detect this kind of land cover change in complementary ways. Thereby, the high temporal resolution of NOAA AVHRR data can partially compensate for the coarse spatial resolution because it allows enhanced time series methods like frequency analysis that provide complementary information. In contrast, the analysis of Landsat data was able to reveal changes at a fine spatial scale, which are associated with shifts in land management practice.