首页> 外文会议>International Society for Photogrammetry and Remote Sensing Bhopal Workshop Earth Observation for Terrestrial Ecosystem >REMOTE SENSING BASED BIOPHYSICAL CHARACTERIZATION OF TROPICAL DECIDUOUS FOREST IN CENTRAL INDIA
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REMOTE SENSING BASED BIOPHYSICAL CHARACTERIZATION OF TROPICAL DECIDUOUS FOREST IN CENTRAL INDIA

机译:印度中部热带落叶林的遥感生物物理特征

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The paper reports the measurements of biophysical parameters using field and satellite data over a tropical deciduous forest Kanha National Park (KNP), central India. Field measurement (GBH, LAI, litter, soil moisture) was carried out over ten quadrates of 0.1ha in KNP for characterization of biophysical parameters with specified measurement protocol and sampling. Satellite based remote sen sing analysis (LAI, Phenology, and NPP) was carried out using multi date observations of IRS-LISS-III, IMS-1MX, SPOT-VEGETATION and EOS-MODIS instruments. Rank correlation analysis using field data collected in the selected quadrates at KNP showed Sal ( Shorea robusta) is dominant forest species followed by Lendia, Jamun (Syzygium cumini), Saja, Harra and Dhawda etc. Field measurement of Sal showed GBH range from 20 cm to 170 cm. Different forest classes such as Sal; Sal mixed with Jamun, Bamboo (Dendrocalamus strictus) etc, including grasslands/scrubland were classified with overall accuracy of 85.56 percent using March, May and October multi spectral data. Sal has distinct growth characteristics (low vegetation growth/ leaf fall in March instead of May) as compared to other vegetation species. As per the Leaf Area Index (LAI) measurement using hemispherical photographs, Sal showed the highest LAI (6.95 m~2/m~2) during September and lowest LAI (2.63 m~2/m~2) during March. Overall good agreement (r= 0.79) was found between the LAI generated from LISS-III and MODIS data product. It was observed from SPOT-VEGETATION analysis that NPP varied from 8.4 tC/ha/year (dry deciduous forest) to 14.25 tC/ha/year (Moist deciduous forest) in KNP.
机译:本文报告了使用现场和卫星数据在印度中部热带落叶林Kanha国家公园(KNP)的田间和卫星数据的测量。现场测量(GBH,LAI,垃圾,土壤水分)在KNP中进行了10个0.1Ha,用于指定测量方案和采样的生物物理参数表征。基于卫星的偏远森歌唱分析(LAI,Phabology和NPP)使用More Date Date观察IMS-Liss-III,IMS-1MX,Spot-Impation和EOS-Modis Instruments进行。使用在KNP的所选Quadrates中收集的现场数据进行排名相关分析显示SAL(Shorea Robusta)是林林种,其次是Lendia,Jamun(Syzygium Cumini),Saja,Harra和Dhawda等。野生渣的田间测量显示为20厘米的GBH范围到170厘米。不同的森林班等萨尔;与Jamun,Bamam(Dendrocalamus Strictus)等混合的SAL,包括草原/灌木丛,使用3月,5月和10月多次多光谱数据归类为85.56%的整体准确性。与其他植被物种相比,SAL具有不同的生长特性(3月份,而不是5月的植被生长/叶子)。根据使用半球形照片的叶面积指数(LAI)测量,SAL在3月期间显示最高的LAI(6.95米〜2 / m〜2)和最低的LAI(2.63米〜2 / m〜2)。从Liss-III和MODIS数据产品生成的LAI之间发现了整体良好的协议(R = 0.79)。从植物 - 植被分析中观察到,NPP在KNP中从8.4 TC / HA /年(干燥落叶林)变化至14.25吨/小时(湿润落叶林)。

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