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Monitoring of Net Primary Production in California Rangelands Using Landsat and MODIS Satellite Remote Sensing

机译:使用Landsat和MODIS卫星遥感监测加利福尼亚牧场的净初级生产力

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In this study, we present results from the CASA (Carnegie-Ames-Stanford Approach) model to estimate net primary production (NPP) in grasslands under different management (ranching versus unmanaged) on the Central Coast of California. The latest model version called CASA Express has been designed to estimate monthly patterns in carbon fixation and plant biomass production using moderate spatial resolution (30 m to 250 m) satellite image data of surface vegetation characteristics. Landsat imagery with 30 m resolution was adjusted by contemporaneous Moderate Resolution Imaging Spectroradiometer (MODIS) data to calibrate the model based on previous CASA research. Results showed annual NPP predictions of between 300 - 450 grams C per square meter for coastal rangeland sites. Irrigation increased the predicted NPP carbon flux of grazed lands by 59 grams C per square meter annually compared to unmanaged grasslands. Low intensity grazing activity appeared to promote higher grass regrowth until June, compared to the ungrazed grassland sites. These modeling methods were shown to be successful in capturing the differing seasonal growing cycles of rangeland forage production across the area of individual ranch properties.
机译:在这项研究中,我们介绍了来自CASA(卡内基-艾姆斯-斯坦福方法)模型的结果,以估算加利福尼亚中部海岸不同管理(牧场和非牧场)下草原的净初级生产(NPP)。最新的模型版本称为CASA Express,旨在使用中等植被表面分辨率的空间分辨率(30 m至250 m)卫星图像数据来估算碳固定和植物生物量生产的每月模式。通过同时进行的中等分辨率成像光谱仪(MODIS)数据调整了分辨率为30 m的Landsat影像,以基于先前的CASA研究对模型进行校准。结果表明,沿海牧场地的年度NPP预测为每平方米300-450克碳。与未管理的草地相比,灌溉每年使放牧土地的预测NPP碳通量每平方米增加59克碳。与未湿润的草地相比,低强度放牧活动似乎促进了直到六月的更高的草草再生。这些建模方法被证明可以成功捕获整个牧场性质的牧场草料生产的不同季节生长周期。

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