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:印度中部地区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:本文报告了在印度中部地区热带落叶林Kanha国家公园(KNP)上的田间和卫星数据测量生物物理参数。现场测量(GBH,LAI,垃圾,土壤水分)在KNP中进行了超过10.1ha的次数,用于具有指定测量方案和采样的生物物理参数的表征。使用IRS-Liss-III,IMS-1MX,Spot-Impation和EOS-MODIS仪器的多日期观察进行了基于卫星的偏远森唱分析(LAI,Phailology和NPP)。秩相关分析使用在KNP所选的Quadrates中收集的现场数据显示SAL(Shorea Robusta)是主要的森林物种,其次是Lendia,Jamun(Syzygium Cumini),Saja,Harra和Dhawda等。萨尔的田间测量显示为20厘米的GBH范围到170厘米。不同的森林类,如萨尔;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月的多谱数据归类为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月份植被生长/叶子而不是5月)。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LAI(6.95米〜2 / m〜2),最低莱(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协议(R = 0.79)。从现场 - 植被分析观察到NPP在8.4 TC / HA /年(干燥的落叶林)到14.25TC / HA /年(潮湿的落叶林)在KNP中变化。

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