首页> 外文期刊>Pedosphere: A Quarterly Journal of Soil Science >Using Remote Sensing and GIS Technologies to Estimate Grass Yield and Livestock Carrying Capacity of Alpine Grasslands in Golog Prefecture, China
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Using Remote Sensing and GIS Technologies to Estimate Grass Yield and Livestock Carrying Capacity of Alpine Grasslands in Golog Prefecture, China

机译:利用遥感和GIS技术估算高洛格地区高寒草地的草产量和畜牧业承载力

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摘要

Remote sensing data from the Terra Moderate-Resolution Imaging Spectroradiometer (MODIS) and geospatial data were used to estimate grass yield and livestock carrying capacity in the Tibetan Autonomous Prefecture of Golog, Qinghai, China. The MODIS-derived normalized difference vegetation index (MODIS-NDVI) data were correlated with the aboveground green biomass (AGGB) data from the aboveground harvest method. Regional regression model between the MODIS-NDVI and the common logarithm (LOG10) of the AGGB was significant (r(2) = 0.51, P < 0.001), it was, therefore, used to calculate the maximum carrying capacity in sheep-unit year per hectare. The maximum livestock carrying capacity was then adjusted to the theoretical livestock carrying capacity by the reduction factors (slope, distance to water, and soil erosion). Results indicated that the grassland conditions became worse, with lower aboveground palatable grass yield, plant height, and cover compared with the results obtained in 1981. At the same time, although the actual livestock numbers decreased, they still exceeded the proper theoretical livestock carrying capacity, and overgrazing rates ranged from 27.27% in Darlag County to 293.99% in Baima County. Integrating remote sensing and geographical information system technologies, the spatial and temporal conditions of the alpine grassland, trend, and projected stocking rates could be forecasted for decision making.
机译:来自Terra中度分辨率成像光谱仪(MODIS)的遥感数据和地理空间数据被用于估算青海省Golog西藏自治州的草产量和牲畜承载能力。 MODIS衍生的归一化差异植被指数(MODIS-NDVI)数据与地上收获方法的地上绿色生物量(AGGB)数据相关。 MODIS-NDVI与AGGB的常用对数(LOG10)之间的区域回归模型显着(r(2)= 0.51,P <0.001),因此,该模型用于计算绵羊单位年的最大承载能力每公顷。然后,通过减少因子(坡度,距水的距离和土壤侵蚀)将最大的牲畜承载能力调整为理论牲畜承载能力。结果表明,与1981年的结果相比,草地条件变得更糟,地上可食草的产量,株高和覆盖率较低。同时,尽管实际牲畜数量有所减少,但仍超过了合理的理论牲畜承载力,放牧率从达拉格县的27.27%到白马县的293.99%不等。结合遥感和地理信息系统技术,可以预测高寒草原的时空状况,趋势和预计的放养率,以进行决策。

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