Mapping of Hay-Harvesting Grasslands Using Harmonized Landsat Sentinel-2 Time Series and Deep Learning in Temperate Steppe

温带草原割草草地地图

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Recently, the research team led by Hu Yunfeng from the Institute of Geographic Sciences and Natural Resources Research of the Chinese Academy of Sciences published an academic paper titled "Mapping of Hay-Harvesting Grasslands Using Harmonized Landsat Sentinel-2 Time Series and Deep Learning in Temperate Steppe" in the SCI first-tier Top journal IEEE Transactions on Geoscience and Remote Sensing (with an impact factor of 8.6). This paper, by leveraging remote sensing and deep learning, proposed a method for mapping hay-harvesting grasslands in the temperate steppe, providing a reference for pastoral area forage management, ecological protection, and intelligent decision-making. The first author of the paper is Lu Wei, a doctoral student from the Institute of Geography of the Chinese Academy of Sciences (his research direction is grassland remote sensing and extraction of remote sensing image information). In the vast temperate grasslands of northern China, the way of grassland utilization is undergoing a profound transformation. For thousands of years, the temperate grasslands of Eurasia have been dominated by free-range grazing, with herders "following the grass and water" and moving with the seasons. At that time, there was no concept of "harvesting grass", and livestock could only survive the long winter by digging through the snow and eating dried grass. This traditional nomadic way of life gave rise to a glorious grassland civilization, but it also made the livestock industry highly vulnerable to climate fluctuations. In history, when severe winters arrived and the grass withered and the snow was thick, there were frequent incidents of large-scale livestock deaths, which even became an important reason for the northern nomadic people to migrate southward. Since the 21st century, with the economic development of China's pastoral areas and the improvement of mechanization levels, the management concepts of the livestock industry have begun to change. Drawing on the experience of "artificial pastures" in the West, the government and herders gradually designated "harvesting areas" on the natural grasslands, and concentrated harvested and dried the grass in late summer and early autumn to reserve feed for the livestock for the winter. This change not only effectively alleviated the problem of insufficient winter fodder, but also promoted the income increase of herders and improved the ecological management of the grassland, marking that the livestock industry in the semi-arid temperate grassland regions is moving towards systematization and modernization. However, for a long time, there has been a lack of systematic data on the space of grassland harvesting areas in northern semi-arid grasslands of China. Due to the scattered operation of herders, diverse management entities, and the low level of informatization of grassroots management departments, the government has difficulty obtaining comprehensive and accurate information on grassland utilization. This data gap has brought considerable uncertainty to the assessment of grassland utilization intensity, the planning of fodder reserves, and ecological management.

论文第一作者为中国科学院地理所博士研究生鲁维(研究方向:草原遥感,遥感影像信息提取)

在中国北方广袤的温带草原上,草原利用方式正经历一场深刻的变革。几千年来,欧亚大陆的温性草原以自由放牧为主,牧民“逐水草而居”,随季节迁徙。那时并没有“收割牧草”的概念,牲畜在冬季只能靠拨雪觅食、啃食枯草来度过漫长寒冬。这种传统的游牧方式虽孕育了辉煌的草原文明,却也让牧业极易受到气候波动的影响。历史上,当严冬突至、草枯雪厚时,牲畜大批死亡的灾情屡见不鲜,甚至成为北方游牧民族南迁的重要原因之一。进入21世纪后,随着中国牧区经济发展和机械化水平的提升,牧业管理理念开始转变。借鉴西方“人工饲草地”的经验,牧区政府和牧民逐步在天然草地上划定“打草场”,在夏末秋初集中收割、晾晒牧草,为牲畜储备越冬饲料。这一变化,不仅有效缓解了冬季饲草短缺问题,还促进了牧民增收、改善了草原生态管理,标志着半干旱温带草原地区的畜牧业正迈向系统化、现代化。然而,长期以来,中国北方半干旱草原缺乏系统的打草场空间数据。由于牧民分散经营、管理主体多样,加之基层管理部门信息化水平较低,政府难以获取全面、准确的草原利用信息。这种数据缺口给草原利用强度评估、饲草储备规划以及生态管理带来了不小的不确定性。



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