首页> 外文会议>Asian Conference on Remote Sensing(ACRS2006) vol.2; 20061009-13; Ulaanbaatar(MN) >Leaf Area Index Estimation by Using Remote Sensing Technique in Khao Phra Wihan National Park
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Leaf Area Index Estimation by Using Remote Sensing Technique in Khao Phra Wihan National Park

机译:考帕威汉国家公园基于遥感技术的叶面积指数估算

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Different vegetation types and other land cover types in Khao Phra Wihan National Park, Sisaket province have been classified by using 30 m resolution digital data of LANDSAT-5 TM. Leaf area estimation and tree data such as dimensions in girth, height, species list and crown cover of 30 field plots were collected. Then spectral reflectance value of each plot was correlate to the tree data and field plot characteristics. The tree data were use to derive leave area index by allometry equation of tropical forest, which is LA = 0.5101 (D~2H)~(0.5912) and finally use to determine a relationship to the satellite data in band ratio models. Then a best equation and model was selected using highest coefficient of determination (r~2) to calculate the leaf area. The results show that Transformed Vegetation Index (TVI) using LANDSAT TM bands of green, red and near infrared gives the best relationship for leaf area index estimation using linear regression, i.e. y = 21524TVI-18560,(r~2 = 0.6364). An average leaf area is 37,241.34 m~2/ ha . While the reflectance in infrared range fits in logarithmic model y = 9991NDVI~(1.7742) (r~2 = 0.672). An average leaf area of 37,014.73 m~2 / ha~(-1) is estimated for the National Park.
机译:通过使用LANDSAT-5 TM的30 m分辨率数字数据,对四色菊省Khao Phra Wihan国家公园中的不同植被类型和其他土地覆被类型进行了分类。收集了30个田地的叶面积估计值和树木数据,例如周长,高度,种类清单和树冠覆盖物的尺寸。然后将每个图的光谱反射率值与树木数据和田间图特征相关联。利用树木数据通过热带雨林的异度方程推导出落叶面积指数,LA = 0.5101(D〜2H)〜(0.5912),最后用于确定带比模型中与卫星数据的关系。然后使用最高确定系数(r〜2)选择最佳方程和模型,以计算叶片面积。结果表明,利用绿色,红色和近红外的LANDSAT TM波段的转化植被指数(TVI)与叶面积指数的线性回归估计具有最佳关系,即y = 21524TVI-18560,(r〜2 = 0.6364)。平均叶面积为37,241.34 m〜2 / ha。红外范围内的反射率符合对数模型y = 9991NDVI〜(1.7742)(r〜2 = 0.672)。据估计,国家公园的平均叶子面积为37,014.73 m〜2 / ha〜(-1)。

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