光谱学与光谱分析
光譜學與光譜分析
광보학여광보분석
SPECTROSCOPY AND SPECTRAL ANALYSIS
2013年
11期
3106-3110
,共5页
蒋金豹%Michael D. Steven%何汝艳%蔡庆空
蔣金豹%Michael D. Steven%何汝豔%蔡慶空
장금표%Michael D. Steven%하여염%채경공
光谱特征%水浸胁迫%植被%识别模型对比分析%归一化均值距离
光譜特徵%水浸脅迫%植被%識彆模型對比分析%歸一化均值距離
광보특정%수침협박%식피%식별모형대비분석%귀일화균치거리
Spectral features%Waterlogging stress%Vegetation%Identification model%Normalized distance between means
随着全球气候变暖，我国洪涝灾害发生的频率及影响范围都不断增加。通过野外模拟试验，研究植被（玉米、甜菜）在水浸胁迫下的光谱变化特征，以构建高光谱遥感模型对水涝灾害范围进行监测。试验于2008年5月-8月在英国诺丁汉大学Sutton Bonington校区（52.8°N ，1.2°W）进行，每周采集一次样本并在室内测量其光谱数据。试验结果表明植被光谱在550，800～1300 nm区域反射率都稍有降低，而在680 nm区域反射率则略微增大。选取NDVI ，SIPI ，PRI ，SRPI ，GNDVI及R800* R550/R680共六个植被指数识别水浸胁迫下的植被，研究表明，指数SIPI与 R800* R550/R680对水浸胁迫玉米比较敏感，而指数SIPI ，PRI及 R800* R550/R680对水浸胁迫甜菜比较敏感。为寻找最优的识别模型，计算对照与水浸胁迫植被指数之间的归一化均值距离并进行对比分析，发现植被指数 R800* R550/R680的归一化均值距离在胁迫早期即大于其他指数的距离，说明该指数识别水浸胁迫植被的能力优于其他指数，且具有较强的敏感性与稳健性。因此，可以利用该指数快速地提取水浸面积，为救灾减灾决策提供信息支持。
隨著全毬氣候變暖，我國洪澇災害髮生的頻率及影響範圍都不斷增加。通過野外模擬試驗，研究植被（玉米、甜菜）在水浸脅迫下的光譜變化特徵，以構建高光譜遙感模型對水澇災害範圍進行鑑測。試驗于2008年5月-8月在英國諾丁漢大學Sutton Bonington校區（52.8°N ，1.2°W）進行，每週採集一次樣本併在室內測量其光譜數據。試驗結果錶明植被光譜在550，800～1300 nm區域反射率都稍有降低，而在680 nm區域反射率則略微增大。選取NDVI ，SIPI ，PRI ，SRPI ，GNDVI及R800* R550/R680共六箇植被指數識彆水浸脅迫下的植被，研究錶明，指數SIPI與 R800* R550/R680對水浸脅迫玉米比較敏感，而指數SIPI ，PRI及 R800* R550/R680對水浸脅迫甜菜比較敏感。為尋找最優的識彆模型，計算對照與水浸脅迫植被指數之間的歸一化均值距離併進行對比分析，髮現植被指數 R800* R550/R680的歸一化均值距離在脅迫早期即大于其他指數的距離，說明該指數識彆水浸脅迫植被的能力優于其他指數，且具有較彊的敏感性與穩健性。因此，可以利用該指數快速地提取水浸麵積，為救災減災決策提供信息支持。
수착전구기후변난，아국홍로재해발생적빈솔급영향범위도불단증가。통과야외모의시험，연구식피（옥미、첨채）재수침협박하적광보변화특정，이구건고광보요감모형대수로재해범위진행감측。시험우2008년5월-8월재영국낙정한대학Sutton Bonington교구（52.8°N ，1.2°W）진행，매주채집일차양본병재실내측량기광보수거。시험결과표명식피광보재550，800～1300 nm구역반사솔도초유강저，이재680 nm구역반사솔칙략미증대。선취NDVI ，SIPI ，PRI ，SRPI ，GNDVI급R800* R550/R680공륙개식피지수식별수침협박하적식피，연구표명，지수SIPI여 R800* R550/R680대수침협박옥미비교민감，이지수SIPI ，PRI급 R800* R550/R680대수침협박첨채비교민감。위심조최우적식별모형，계산대조여수침협박식피지수지간적귀일화균치거리병진행대비분석，발현식피지수 R800* R550/R680적귀일화균치거리재협박조기즉대우기타지수적거리，설명해지수식별수침협박식피적능력우우기타지수，차구유교강적민감성여은건성。인차，가이이용해지수쾌속지제취수침면적，위구재감재결책제공신식지지。
With the global climate warming ,flooding disasters frequently occurred and its influence scope constantly increased in China .The objective of the present paper was to study the leaf spectral features of vegetation (maize and beetroot) under water-logging stress and design a hyperspectral remote sensing model to monitor the flooding disasters through a field simulated experi-ment .The experiment was carried out in the Sutton Bonington Campus of University of Nottingham (52 .8°N ,1 .2°W) from May to August in 2008 ,and samples were collected one time every week and spectra were measured in the laboratory .The result showed that the reflectance of the maize and beetroot decreased in the 550 and 800~1 300 nm region ,and the reflectance slightly increased in the 680 nm region .This paper chose NDVI ,SIPI ,PRI ,SRPI ,GNDVI and R800 * R550/R680 to identify the vegeta-tion under waterlogging stress ,respectively .The result suggested that the SIPI and R800 * R550/R680 was sensitive for maize un-der waterlogging stress ,and then SIPI and PRI and R800 * R550/R680 was sensitive for beetroot under waterlogging stress .In or-der to seek the best identifiable model ,the normalized distances between means of control and stressed vegetation indices were calculated and analyzed ,the result indicated that the distance of R800 * R550/R680 is more than that of indices’ in the early stress stage ,illustrated that the index identifiable ability for waterlogging stress is better than other indices ,then the index has the strong sensitivity and stability .Therefore ,the index R800 * R550/R680 could be used to quickly extract flooding disaster area by using hyperspectral remote sensing ,and would provide information support for disaster relief decisions .
