Portable Instrument for Normalized Difference Vegetation Index

By using four specially designed narrow bandpass filters and photodetectors in the instrument,the incident and reflected radiances of sun light on the vegetation are optically sensed, at the red and near infrared bands, then the normalized difference vegetation index(NDVI) is processed by a microprocessor.Compared with conventional spectrometer measuring method of NDVI, the instrument is easy to be used,compact, light and low-cost.     

Object-oriented Natural and Artificial Oasis Distinguishing in Landsat Imagery: Taking Minqin Oasis as an Example

Taking Minqin Oasis in the downstream area of the Shiyang River Basin which is located in the east of Hexi Corridor as an example, the Landsat 8 OLI image was chosen as the data source. Under the consideration of the basic concept of the artificial oasis and natural oasis in this paper, combining with the information of the spectrum, texture, shape and context basing on the image data preprocessing and multi-scale segmentation, we introduce a series of indexes such as NDVI、maximum difference, compactness, shape index, the space adjacency relation and so on to construct a rule set for distinguish between natural oasis and artificial oasis. The obtained results were further compared with the results based on the maximum likelihood method. As a result, the total accuracy of using the object-oriented image analysis method to distinguishing between natural oasis and artificial oasis is 91.75%, and the Kappa coefficient is 0.65 by using the rule set established in this paper. Compared with the results based on the maximum likelihood method, the overall accuracy is improved by 10.40% and the Kappa coefficient is 0.13. The Kappa coefficient of the artificial oasis is increased by 0.19, and the Kappa coefficient of the natural oasis condition is increased by 0.30. The results showed that the object-oriented image analysis method can overcome the limitations of the classification method that only using spectral feature to a certain extent, avoid the confusion caused by the phenomenon of “same object with different spectrums” and “same spectrum with different objects”, and increase the accuracy of distinguishing between the artificial oasis and natural oasis.     

生态工程背景下西双版纳NDVI时空变化分析

利用中分辨率成像光谱仪(MODIS)所合成的MOD13Q1数据,从时间变化、空间分异、重心迁移和地形因子4个方面分析了西双版纳生态工程实施前(2004～2010年)和实施后(2011～2017年)NDVI(植被归一化指数)值的变化特征,并探讨夏季NDVI值和气象因子的关系。结果表明:①2004～2010年西双版纳NDVI以-0.176%/a的速率下降,而2011～2017年NDVI以0.221%/a的速率上升。②西双版纳NDVI频度呈"单峰"结构,生态工程实施后NDVI阈值0.9所占面积比例增加最为显著(增加了17.2%),NDVI重心由西南方向(迁移距离7.58 km)转向东南方向(迁移距离4.75 km)。③与2004～2010年相比,2011～2017年NDVI在海拔720～870 m、坡度13°～16°以及东北方向上恢复成效最为显著,增长率分别为2.7%,1.4%和1.2%。④夏季气温过高、降水过多以及日照时数少是导致夏季NDVI值最低的主要因素之一。⑤生态工程的实施对2011～2017年西双版纳NDVI的上升具有重要影响,但西双版纳NDVI下降区域的面积比重仍然较大,部分地区的生态环境建设需要继续加强。     

塔里木河生态输水的累积生态响应

以塔里木河第12～18次生态输水为例,采用经验统计模型和克里金插值法分析了输水前后塔里木河下游地下水埋深和夏季归一化差异植被指数(NDVI)的时空变化,剖析了地下水和植被对生态输水的累积生态响应规律。结果表明:累积生态输水量与最小地下水埋深呈对数曲线正相关关系,其累积效应的增长性由强到弱;地下水埋深对生态输水的累积时间响应具有滞后性,输水80 d后累积效应最显著;沿河道方向,库尔干监测断面累积空间效应最显著;垂直河道方向,地下水对累积输水的空间响应随河道距离增加而减弱;NDVI与近3 a累积输水量呈显著正相关关系,大西海子水库、台特玛湖及河道附近NDVI增长显著。推荐近期输水量为2.5亿～5.0亿m~3/次,合理输水时间为4—6月和9—11月,适宜输水间隔5～12个月,预期连续年份5次输水后累积效应可达最小地下水埋深3.5 m、平均地下水埋深4.2 m。     

汉江上游植被指数变化及其归因分析

植被对调节流域水文过程、维持生态平衡具有重要作用,分析汉江上游植被变化和驱动因子具有重要价值。采用MODIS/Terra的NDVI数据和Land Cover数据分析了汉江上游不同土地利用类型的NDVI的变化规律,结合气象数据和DMSP灯光数据分析了气候变化和人类活动对植被NDVI的影响,分析了植被指数变化的主导性驱动因子。结果表明,2001-2017年汉江上游NDVI整体上呈增加趋势,年均NDVI介于0.5～0.62之间;同种土地利用类型的NDVI年际变化不大,不同土地利用类型的NDVI变化趋势基本一致,NDVI从高到低依次为落叶阔叶林、混交林、草地、农用地、灌丛、常绿针叶林。月平均最高气温是影响月NDVI变化的主导因子,夏季NDVI变化与日照时数和降水量关系较大,冬季NDVI变化与气温相关性较高。气温和降水与NDVI年变化的相关系数高于平均灯光强度变化,即年尺度上气象因素对植被变化的影响高于人类活动。     

青藏高原1982~2015年FPAR时空变化分析

植被吸收利用太阳光合有效辐射比率反映了植被固碳释氧能力,根据青藏高原GIMMS NDVI3g（1982~2015年）和MODIS NDVI（2001~2015年）数据,采用非线性半理论半经验模型进行FPAR反演及时空变化分析。结果表明：①2001~2015年GIMMS NDVI3g和MODIS NDVI反演FPAR在空间分布上具有较高的一致性,相关系数为0.82（P<0.01）,年际变化趋势一致至少6年的区域占80%;②青藏高原FPAR受坡度和海拔影响较大,其中15~35坡度FPAR变化最快,700~2 100 m海拔区间FPAR值最大;不同坡向对应的FPAR除南坡方向偏低外其他方向差异不大。③1982~2015年青藏高原四季FPAR时空变化研究中,冬季FPAR年际变化最明显,约78.5%的区域表现为增长趋势;秋季FPAR下降区域最多,但超过71.5%区域变化不显著;④基于MODIS NDVI和GIMMS NDVI两数据反演的所有植被类型的FPAR都在2012年间出现小幅度下降趋势,且不同植被类型FPAR的年际变化趋势各不相同。     

滹沱河流域植被覆盖时空演变及其与 SPEI 的相关关系

选择2001-2015年MODIS NDVI(250m)及14个气象站点气温、降水数据,通过计算标准化降水蒸散指数(SPEI),探究滹沱河流域近15年植被覆盖时空演变特征,分别从月、季节、年等尺度探究植被覆盖与SPEI的相关关系。结果显示:(1)近15年滹沱河流域归一化植被指数(NDVI)呈显著增加趋势,增速为0.024/(10a)。(2)植被恢复以明显改善为主,覆盖范围占整个流域面积的51.58%,主要分布于流域中、上游。(3)滹沱河流域SPEI总体上呈波动上升趋势,干旱程度有所降低,流域中游变湿趋势最显著。(4)6月、7月是干旱条件对植被覆盖影响最显著的月份,其中,6月气温对NDVI的影响大于降水,而7月降水对NDVI的影响大于气温;夏季干旱程度对植被覆盖度的影响最为明显;NDVI年际变化与SPEI具有显著正相关关系,干旱对植被生长状态有较大影响。     

基于亮温—植被指数—气溶胶光学厚度的MODIS火点监测算法研究

MODIS火灾产品的火点检测算法主要以4和11μm通道亮温数据来识别火点,在应用于不同地区和不同季节时有一定局限性。在分析MODIS现有火点检测算法的基础上,对算法相关阈值及参数进行适当调整,同时考虑火灾前后NDVI的变化,以及林火燃烧过程中伴生烟羽使火点下风方气溶胶光学厚度明显增加的特点,构建了基于亮温—植被指数—气溶胶光学厚度的火点识别算法,并应用多次火灾个例对本算法进行验证。结果表明:算法提高了对高温热点和低温焖烧火点的识别能力,有效降低了高温热点的误报率和低温火点的漏报率,使火点检测算法在不同环境的适应性有所增强。     

An Anti noise Identification Methodfor Winter Wheat based on Satellite Time series Data

China As one of the major crops in the world,the spatial distribution information of winter wheat plays an important role in monitoring winter wheat growth,assisting economic decision making and addressing regional food security under climate change.This paper proposed a new anti noise identification method for winter wheat identification based on the 250 m MODIS NDVI time series dataset during the period from September 30,2014 to June 26,2015.With the method,the spatial distribution of winter wheat in Henan province was extracted based on the analysis of winter wheat phenology.Results indicated that the total identification accuracy of winter wheat was 93.0%,94.0% and 86.0% for the whole study area,fragmentary land area and regular land area,respectively.Compared with the traditional identification method for winter wheat based on satellite time series data,the identification accuracies with the proposed method in different filtering scenarios were not only high but also similar to each other.It strongly proved that the new method had a good performance in noise immunity and stability and can be applied to the rapid extraction of winter wheat in a large scale based on satellite time series dataset.This new method provided a new technical support for the operational extraction of winter wheat.     

南水北调中线工程水源区植被时空演化特征

研究南水北调中线水源区植被时空分布和演化特征,对水源区生态环境保护与社会经济长期稳定发展具有重要意义。利用2010—2019年南水北调中线水源区中分辨率成像光谱仪(MODIS)归一化植被指数(NDVI)数据,基于NDVI最大值合成和一元线性回归方法研究水源区植被时空演化特征,并结合水源区地表温度、降水与土壤湿度等数据探讨植被变化原因。结果表明:①水源区NDVI空间分布与地形强相关,2010—2019年,水源区NDVI均值为整体上升趋势;②2013—2015年水源区NDVI呈现显著的“下降-恢复”特征,可能与2014年水源区地表温度和降水异常导致的旱情、2015年水源区降水恢复以及丹江口水库蓄水水位上升有关;③2010—2019年,水源区植被发生显著变化的区域主要集中在低海拔的人口密集区,反映这些地区的植被更易受气候变化、城镇扩张和“退耕还林、植树造林”政策的影响。此外,南水北调中线工程通水后,丹江口水库水位上升是导致水库区域NDVI降低的原因。研究结果可为南水北调中线水源区生态环境保护提供科学依据。