全国干旱遥感监测运行系统的研制

该研究利用1981－1994的NOAA AVHRR 8km分辨率的NDVI资料，以及对应时段全国102个固定农业观测站的20cm深的土壤湿度资料，建立了植被状态指数（VCI）与土壤湿度之间的统计模型，由土壤湿度旱情等级标准来换算出每旬用VCI进行干旱监测的旱情等级标准，以确定出全国的旬旱情分布状况，在此工作的基础上建成了“全国干旱遥感则运行系统”，该运行系统使遥感手段监测全国干旱成为可能，将能提供每年3－9月每旬全国的干旱监测情况，为国家有关决策部门提供干旱减灾的决策依据。     

气象卫星观测资料的分析在城市区域气象环境研究中的应用

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     

复种指数遥感监测方法

复种指数是反映水土光与自然资源利用程度的指标 ,其实质是沿时间序列 ,反映某一种植制度对耕地的利用程度。联系复种指数与时间序列NDVI曲线的纽带是农作物年内的循环规律。时间序列的NDVI值蕴涵着植被的生长和枯萎的年循环节律 ,经时间序列谐函数分析法 (HarmonicAnalysisofTimeSeries ,HANTS)重构的NDVI曲线 ,可以准确地反映农作物的出苗、拔节、抽穗、收获等物理过程。因此 ,根据时间序列的NDVI曲线的周期性 ,可以反向捕捉到耕地农作物动态的信息 ,进而得到耕地的复种指数。本文依据上述原理 ,提出复种指数遥感监测的方法 ,然后用 1999年至 2 0 0 2年 4年的VGT(SPOT4卫星vegetation数据 )旬合成NDVI时间序列数据集提取了复种指数 ,并利用地面样区观测结果和统计数据进行检验 ,取得很高的精度。     

Seasonal and inter-annual relationships between vegetation and climate in central New Mexico, USA

Linear correlations between seasonal and inter-annual measures of meteorological variables and normalized difference vegetation index (NDVI) are calculated at six nearby yet distinct vegetation communities in semi-arid New Mexico, USA Monsoon season (June–September) precipitation shows considerable positive correlation with NDVI values from the contemporaneous summer, following spring, and following summer. Non-monsoon precipitation (October–May), temperature, and wind display both positive and negative correlations with NDVI values. These meteorological variables influence NDVI variability at different seasons and time lags. Thus vegetation responds to short-term climate variability in complex ways and serves as a source of memory for the climate system.     

Discrimination between climate and human-induced dryland degradation

In this study we present a technique to discriminate between climate or human-induced dryland degradation, based on evaluations of AVHRR NDVI data and rainfall data. Since dryland areas typically have high inter-annual rainfall variations and rainfall has a dominant role in determining vegetation growth, minor biomass trends imposed by human influences are difficult to verify. By performing many linear regression calculations between different periods of accumulated precipitation and the annual NDVI_max, we identify the rainfall period that is best related to the NDVI_max and by this the proportion of biomass triggered by rainfall. Positive or negative deviations in biomass from this relationship, expressed in the residuals, are interpreted as human-induced. We discuss several approaches that use either a temporally fixed NDVI peaking time or an absolute one, a best mean rainfall period for the entire drylands or the best rainfall period for each individual pixel. Advantages and disadvantages of either approach or one of its combinations for discriminating between climate and human-induced degradation are discussed. Depending on the particular land-use either method has advantages. To locate areas with a high likelihood of human-induced degradation we therefore recommend combining results from each approach.     

Grassland productivity in an alpine environment in response to climate change

Situated in a climatically stressful environment, alpine grassland is sensitive to subtle climate changes in its productivity. We remedy the current deficiency in studying grassland productivity by taking the integrated effect of all relevant factors into consideration. The relative importance of temperature, rainfall and evaporation to the alpine grassland productivity in western China was determined through analysis of their relationship with the normalized difference vegetation index (NDVI) between 1981 and 2000. Climate warming stimulated grassland productivity in the 1980s, but hampered it in the 1990s. Temperature is more important than rainfall to grassland productivity early in the growing season. However, their relative importance is reversed late in the growing season. Monthly summer month rainfall modified by maximum monthly temperature is a good predictor of alpine grassland productivity at 62.0 per cent. However, the best predictor is water deficiency, which is able to improve the estimation accuracy to 78.3 per cent. Hence, the impact of temperature on grassland productivity is better studied indirectly through evaporation.     

以植被指数0.12为指标看我国的荒漠化与草原界限的变化

 通过对荒漠化描述指标和方法的讨论,最后用植被指数(NDVI)作为描述荒漠化的指标,定性讨论了我国荒漠化和干草原区域近10 a的变化。结果表明,NDVI可以用来作为荒漠化特征的指标,NDVI的0.12线大致与200 mm降水量相对应。近10 a,我国的荒漠化在1998年以后有所扩大。     

基于决策树分类的大屯矿区地物信息提取及矿区污染分析

本文在对国内外遥感图像分类方法充分研究分析的基础上,选择决策树分类法对大屯矿区的Landsat 8遥感图像进行分类研究。选取样本提取并分析研究区典型地类光谱特征曲线,依据光谱曲线特征和归一化植被指数建立了土地利用分类决策树模型,通过反复试验和修正,筛选出适宜大屯矿区地物分类的决策树最优阈值,对研究区进行分类和精度评价,最后通过分类结果对研究区的水体污染状况进行简要分析。     

基于NDVI时间序列数据的江西省水稻种植制度变化研究

利用Savitzky-Golay滤波对覆盖江西省范围的SPOT VGT NDVI时间序列数据进行平滑处理的基础上,结合坡度数据,通过非监督分类的方法提取了江西省2000、2005和2010年水稻种植范围,并根据NDVI的年内动态变化,从水稻种植范围、水稻生长季起始时间、水稻复种指数和NDVI最大振幅等分析了江西省水稻种植和生长情况,探讨2000~2010年江西省水稻生产的变化。     

基于时序NDVI的昭觉植被覆盖度变化研究

归一化植被指数(NDVI)能精确地反映植被绿度、光合作用强度,在一定程度上反映着植被的演化信息,是评价生态环境状况的重要指标之一。本文利用Landsat TM数据分别对昭觉地区2009年和2014年的NDVI进行计算,并分别利用均值法、像元二分模型及NDVI差值植被指数对研究区域植被覆盖变化进行定量分析,结果表明:昭觉县NDVI均值上升了11.6%,植被覆盖度中极度改善的面积比例约占38%,昭觉县整体NDVI植被覆盖度显著提高,并对其变化原因进行简要分析,为生态环境建设提供决策依据。