基于GPS与无人机遥感反演草地生物量的放牧场利用强度评估
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国家重点研发计划(2017YFB0504203);国家自然科学基金(41461088);兵团空间信息创新团队(2016AB001)


Evaluation for natural grassland utilization intensity based on GPS and UAV remote sensing for grassland biomass inversion
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    摘要:

    天然草地是放牧畜牧业生产赖以生存的物质基础。为了评估天然草地利用情况,该文通过GPS获取牧群采食轨迹数据来估算采食强度,利用无人机遥感估算模型反演草地生物量的时空分布,将畜群采食强度与天然草地生物量进行融合,探索不同区域畜群的采食强度与草地生物量;分别将采食强度与生物量分类进行对比,根据两者的取值情况,获得各区域草地的利用情况,采食强度与天然草地生物量分类满足以下关系可得草地利用情况:若两者等级相等,则草地利用适中;若前者等级大于后者,则草地过度利用;若前者等级小于后者,则草地轻度利用。以新疆生产建设兵团第八师一五一团紫泥泉牧场为例,对研究区进行监测评估。结果表明,研究区中区域3被合理利用的草地面积最大,为612 m2,其他区域草地被不合理利用的面积占所在区域面积的50%以上。该方法对合理利用草地,实行划区轮牧,促进畜牧业健康发展具有重要意义。

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    Abstract: Natural grassland is the most important material basis for the survival of grazing livestock husbandry. Assessment of the utilization of natural grassland provides decision-making basis for livestock management department to implement the natural grassland development projects, and has important research and application value for promoting the sustainable development of the grazing livestock husbandry. However, grassland degradation is getting worse. And overgrazing is one of the main causes of grassland degradation. Therefore, it is particularly important to monitor natural grassland utilization timely and accurately. Grazing is one of the most important ways to utilize natural grassland and has an important impact on the sustainable development of the ecosystem. What’s more, grassland is the basis for developing grassland animal husbandry, and grassland biomass is one of the important indicators to determine whether the utilization of natural grassland resources is reasonable. Hence, we put forward that the process of natural grassland utilization was an interactive process between grazing behavior and vegetation growth. Therefore, we studied the evaluation method of the utilization of natural grassland, during which we took grazing behavior and grassland vegetation growth into account at the same time. Firstly, the herd trajectory data acquired from global positioning system (GPS) weaned on the head of sheep was used to analyze feeding intensity. In order to quantify grazing pressure, a feeding intensities (FI) map was created using a grid cell method with the tracking data recorded by the global positioning system (GPS). Secondly, the grassland biomass data was gained by using unmanned aerial vehicle (UAV) remote sensing data. With the existing remote sensing estimation model, the grassland yield distribution of natural grassland was estimated. Thirdly, the feeding intensity and natural grassland biomass was fused by using the multi value extraction point method, and the feeding intensity and grassland biomass of different regions could be obtained. The feeding intensity and biomass were classified, respectively. Finally, according to the hierarchical relationship between the feeding intensity and the biomass, the information about utilization of grassland in various regions was obtained. When the feeding intensity and the natural grassland biomass could meet the following relationship, the information about utilization of grassland could be obtained. If the levels of feeding intensity and biomass were equal, the grassland was moderately used. If the level of feeding intensity was greater than that of biomass, the grassland was overused. If the level of feeding intensity was less than that of biomass, the grassland was light used. Taking pasture of Regiment 151 of the Eighth Division of the Xinjiang Production and Construction Corps as an example, the research area was monitored and assessed. The results showed that the area of grassland that was moderately used in Zone 3 in the study area was the largest, which was 612 m2, while in other areas, more than 50% of the area was unreasonably used. The method is of great significance to the rational use of grassland, rotational grazing, and the healthy development of livestock husbandry.

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汪传建,江红红,尹小君,孙世泽,张雅,李冬.基于GPS与无人机遥感反演草地生物量的放牧场利用强度评估[J].农业工程学报,2018,34(19):82-87. DOI:10.11975/j. issn.1002-6819.2018.19.011

Wang Chuanjian, Jiang Honghong, Yin Xiaojun, Sun Shize, Zhang Ya, Li Dong. Evaluation for natural grassland utilization intensity based on GPS and UAV remote sensing for grassland biomass inversion[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE),2018,34(19):82-87. DOI:10.11975/j. issn.1002-6819.2018.19.011

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  • 收稿日期:2018-04-03
  • 最后修改日期:2018-07-30
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  • 在线发布日期: 2018-09-07
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