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首页> 外文会议>Asian conference on remote sensingACRS >QUANTIFYING GROSS PRIMARY PRODUCTIVITY OF AN INDIAN MANGROVE FOREST USING GEO-LEO SATELLITE DATA
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QUANTIFYING GROSS PRIMARY PRODUCTIVITY OF AN INDIAN MANGROVE FOREST USING GEO-LEO SATELLITE DATA

机译：使用Geo-Leo卫星数据量化印度红树林的总初级生产力

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Gross primary productivity (GPP) is total carbon assimilation by plants through the process of photosynthesis. In view of increasing anthropogenic influences and global changes, quantification of carbon assimilation through photosynthesis has gained tremendous significance. Precise estimation of GPP is essential part of several ecosystem models. Mangrove ecosystem, that offers significant protection to coastal environment, is governed by changes in salinity and other micro-environment factors. Globally mangroves are facing serious threat and are undergoing degradation due to anthropogenic pressure. In view of global changes, an assessment of carbon assimilation potential of mangroves is required for developing into a carbon sink and conservation of this fragile ecosystem is highly essential. In the present study, estimation and validation of mangrove GPP was carried out in Bhitarkanika national park (Odisha, India). Light Use Efficiency (LUE) was modelled from seasonal, diurnal in-situ photosynthetic rate observations on 11 dominant mangrove species. For estimation of GPP, 'vegetation photosynthetic model' framework was modified using water, temperature and salinity scalars derived from IRS Resourcesat 2 LISS-4, a Low earth orbit (LEO) satellite data. The incident Photosynthetically Active Radiation (PAR) was derived from insolation product obtained from Geostationary (GEO) satellite KALPANA-1 VHRR for the observation period. Amongst all the species, highest LUE was found m Excoecaria agallocha in winter and summer (5 53 and 0.55 g C m~(-2) MJ~(-1), respectively), and in Aegiceras corniculatum in post-monsoon season (0.58 g C m~(-2) MJ~(-1)). Seasonal 8-day average GPP was found to vary from 3.41 g Cm~(-2) to 14.4 g C m~(-2), with the highest in winter. Comparison of modelled estimates showed fairly good agreement with MODIS GPP (r = 0.89; n=118) having comparable coefficient of variation (41.8% in modelled and 49.5% in MODIS GPP). The present modelling approach of estimating GPP through GEO-LEO satellite can be used to quantify carbon sink in other Indian mangrove ecosystems.
机译：总初级生产力（GPP）是植物通过光合作用过程的总碳同化。鉴于增加的人为影响和全球变化，通过光合作用量化碳同化的量化具有巨大的意义。 GPP的精确估计是若干生态系统模型的重要组成部分。红树林生态系统，为沿海环境提供重大保护，受到盐度和其他微环境因素的变化。全球红树林面临严重的威胁，并且由于人为压力而正在进行降解。鉴于全球变化，需要评估红细胞的碳同化潜力，以发展成为碳汇，保护这种脆弱的生态系统是非常重要的。在本研究中，红树林GPP的估算和验证在Bhitarkanika国家公园（Odisha，India）进行。光利用效率（Lue）是从季节性，昼夜原位的季节性光合速率观察到11种占优势红树林。为了估计GPP，“植被光合模型”框架使用来自IRS Resource at 2 Liss-4，低地球轨道（Leo）卫星数据的水，温度和盐度标量进行了修改。该事件光合作用辐射（PAR）衍生自从地质（地理）卫星Kalpana-1 VHRR获得的不染色产品进行观察期。在所有物种中，在冬季和夏季（5 53和0.55g C〜（-2）MJ〜（-1）和季风季节的Aegiceras Corniculatum（0.58 g C m〜（-2）mj〜（-1））。发现季节性为8日平均GPP从3.41g cm〜（-2）到14.4g c m〜（2），冬季最高，均为最高。模型估计的比较显示具有可比变异系数的MODIS GPP（R = 0.89; n = 118）的相当良好的一致性的变异系数（模拟中的41.8％，MODIS GPP中的49.5％）。通过Geo-Leo卫星估算GPP的本发明建模方法可用于量化其他印度红树林生态系统的碳汇。

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