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。     

基于 DTW 距离的时序 NDVI 数据植被信息提取--以秦巴山区为例

秦巴山区是我国重要的生态屏障,对该区的植被信息提取开展研究,可为区内生态服务功能及自然资源开发利用提供基础数据。通过加窗处理改进DTW距离相似性算法,结合临近度模糊分类方法对2005—2014年的MODIS NDVI时序数据进行植被信息提取。首先利用S-G滤波对MODIS NDVI时序数据进行重建;再利用2013年的采样数据构建各类植被的标准NDVI时序曲线,逐像元计算与标准NDVI时序曲线的加窗DTW距离,利用临近度模糊分类实现植被信息提取;最后验证提取精度。结果表明,算法具有较高的运行效率,可避免错误匹配,以较高的精度(总体精度83.8%,kappa系数0.77)实现长时间序列的植被信息提取。     

西南地区2001-2014年植被变化时空格局

时序植被动态变化研究一直是全球变化研究的热点之一,对地区生态治理有重要意义。基于西南地区2001至 2014年的MODIS植被指数数据集以及DEM数据和土地利用数据,进行季节合成植被指数（SINDVI）的趋势模拟、空间统计和相关分析,探讨西南地区植被变化趋势和空间分异特征,研究结果表明:（1）74.52%的区域SINDVI变化不显著,显著改善的区域占22.07%,而显著退化的区域占3.41%,改善面积远远大于退化面积。（2）从地形因子结果来看,中低海拔地区和缓坡地区植被变化趋势最明显,海拔3 500 m以下植被变化趋势比海拔3 500 m以上明显。随着坡度的增加,改善趋势和退化趋势都在变小。（3）从土地利用分析结果来看,SINDVI变化趋势在人工表面最明显,改善和退化趋势都相对较大。（4）受人类活动的影响,人工表面和裸地的增多、林地的减少是植被呈退化趋势的主要原因。