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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >A PROCESS-BASED BOREAL ECOSYSTEM PRODUCTIVITY SIMULATOR USING REMOTE SENSING INPUTS
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A PROCESS-BASED BOREAL ECOSYSTEM PRODUCTIVITY SIMULATOR USING REMOTE SENSING INPUTS

机译:基于过程的基于遥感输入的工业生态系统生产力仿真器

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This paper describes a boreal ecosystems productivity simulator (BEPS) recently developed at the Canada Centre for Remote Sensing to assist in natural resources management and to estimate the carbon budget over Canadian landmass (10(6)-10(7) km(2)). BEPS uses principles of FOREST biogeochemical cycles (FOREST-BGC) (Running and Coughlan, 1988) for quantifying the biophysical processes governing ecosystems productivity, but the original model is modified to better represent canopy radiation processes. A numerical scheme is developed to integrate different data types: remote sensing data a 1-km resolution in lambert conformal conic projection, daily meteorological data in Gaussian or longitude-latitude gridded systems, and soil data grouped in polygons. The processed remote sensing data required int he model are leaf area index (LAI) and land-cover type. The daily meteorological data include air temperature, incoming shortwave radiation, precipitation, and humidity. The soil-data input is the available water-holding capacity. The major outputs of BEPS include spatial fields of net primary productivity (NPP) and evapotranspiration. The NPP calculated by BEPS has been tested against biomass data obtained in Quebec, Canada. A time series of LAI over the growing season of 1993 in Quebec was derived by using 10-day composite normalized difference vegetation index images acquired by the advanced very high resolution radiometer at 1-km resolution (resampled). Soil polygon data were mosaicked, georeferenced, and rasterized in a geographic information system (ARC/INFO). With the use of the process-based model incorporating all major environmental variables affecting plant growth and development, detailed spatial distributions of NPP (annual and four seasons) in Quebec are shown in this paper. The accuracy of NPP calculation is estimated to be 60% for single pixels and 75% for 3x3 pixel areas (9 km(2)). The modeled NPP ranges from 0.6 kg C/m(2)/year at the southern border to 0.01 kg C/m(2)/year at the northern limit of the province. The total annual NPP in Quebec is estimated top be 0.24 Gt C in 1993, which is about 0.3-0.4% of the global NPP. (C) Elsevier Science Inc., 1997. [References: 42]
机译:本文介绍了加拿大遥感中心最近开发的一种寒带生态系统生产力模拟器(BEPS),以协助自然资源管理并估算加拿大陆地的碳预算(10(6)-10(7)km(2))。 。 BEPS使用森林生物地球化学循环原理(FOREST-BGC)(Running and Coughlan,1988)来量化控制生态系统生产力的生物物理过程,但是对原始模型进行了修改以更好地表示冠层辐射过程。已开发出一种数值方案来集成不同的数据类型:兰伯特保形圆锥投影中的1 km分辨率的遥感数据,高斯或经纬度网格化系统中的每日气象数据以及以多边形分组的土壤数据。模型所需的已处理遥感数据是叶面积指数(LAI)和土地覆盖类型。每日气象数据包括气温,短波辐射,降水和湿度。土壤数据输入是可用的持水量。 BEPS的主要产出包括净初级生产力(NPP)和蒸散的空间领域。 BEPS计算的NPP已针对加拿大魁北克获得的生物量数据进行了测试。通过使用先进的超高分辨率辐射计以1 km分辨率(重新采样)获取的10天复合归一化植被指数图像得出了1993年魁北克生长期的LAI时间序列。在地理信息系统(ARC / INFO)中对土壤多边形数据进行镶嵌,地理参考和栅格化。通过使用基于过程的模型并结合影响植物生长和发育的所有主要环境变量,本文显示了魁北克省NPP(年度和四个季节)的详细空间分布。 NPP计算的准确性对于单个像素估计为60%,对于3x3像素区域(9 km(2))估计为75%。建模的NPP范围从南部边界的0.6 kg C / m(2)/年到该省北部界限的0.01 kg C / m(2)/年。估计魁北克的年度NPP总量在1993年最高为0.24 Gt C,约占全球NPP的0.3-0.4%。 (C)Elsevier Science Inc.,1997年。[参考:42]

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