Subjects: Geosciences >> Geography submitted time 2024-07-04 Cooperative journals: 《干旱区研究》
Abstract： Net Ecosystem Productivity (NEP) is a crucial indicator for assessing the arbon sequestration capacity of terrestrial ecosystems, and Land Use/Cover Change (LUCC) is a key factor influencing regional differences in carbon uptake. Analyzing the trends of LUCC and NEP is essential for achieving regional carbon peaking and carbon neutrality goals. Based on the LUCC and MODIS remote sensing data from 2000 to 2020 in the Aksu River Basin, the annual average carbon sequestration rate of each land use/cover type in the region was estimated. The LUCC for the next 40 years was simulated by the PLUS model, and the spatial and temporal trend of NEP for the next 40 years in the river basin was predicted. The results show that: (1) the total NEP in the basin has shown an increasing trend in the past 20 years, with an uptake rate of 0.136 Mt C·(10a)-1, and the average carbon sequestration rate of forest area is the highest; (2) the total carbon uptake in the Aksu River Basin will continue to increase in the future 40 years. The increase in forest area is the main way of increasing carbon uptake in the Aksu River Basin, and the positive role of ecological protection projects plays a key role in this process.
Subjects: Geosciences >> Geography submitted time 2022-04-14 Cooperative journals: 《干旱区地理》
Abstract：以哈萨克斯坦北部雨养耕作区为研究靶区，基于春小麦产量统计数据和遥感光谱指数，开 展了春小麦估产最优预测时期及植被指数分析，采用回归分析、随机森林、支持向量机及双向循环 神经网络模型估算春小麦产量，并对比分析了不同模型的模拟精度。结果表明：北哈萨克斯坦州、 阿克莫拉州和库斯塔纳州20072016年春小麦估产的最佳预测时期为6月26日8月5日，该时期是春小麦产量形成的关键时期。北哈萨克斯坦州春小麦估产最优植被指数为7月12日的绿度叶绿素指数（Green chlorophyll index, CIgreen），阿克莫拉州春小麦估产最优植被指数为8月5日的绿度动态宽波段指数（Green wide dynamic range vegetation index, WDRVIgreen），库斯塔纳州春小麦最优估产植被指数为7月12日WDRVIgreen。对比分析4种模型模拟春小麦产量的精度，在样本点较少的情况下，双向循环神经网络模型相比其他模型在估算哈萨克斯坦北部三州春小麦产量上精度较高；春小麦产量与植被净初级生产力NPP相关性分析结果显示，北哈萨克斯坦州、阿克莫拉州和库斯塔纳州决定系数R2在0.50以上面积占比分别为44%、94%和77%，表明上述估产模型可应用于哈萨克斯坦北部三州春小麦估产，尤其是阿克莫拉州和库斯塔纳州。
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