基于改进CASA模型的云南省植被NPP时空格局分析
收稿日期: 2023-09-11
修回日期: 2023-11-09
网络出版日期: 2024-02-21
基金资助
国家自然科学基金项目(32160405);云南省“万人计划”人才培养项目“典型高原湖滨湿地植被高光谱遥感反演及时空演变过程”(YNWR-QNBJ-2018-334)
Spatio-Temporal Pattern Analysis of Vegetation NPP in Yunnan Province Based on Improved CASA Model
Received date: 2023-09-11
Revised date: 2023-11-09
Online published: 2024-02-21
植被净初级生产力(NPP)是衡量生态系统生产力水平的指标之一,利用生态遥感相结合的手段对其估算具有重要意义。运用改进的CASA模型,基于MODIS植被指数产品、气象数据、土地覆被数据,对云南省2000年、2005年、2010年、2015年、2020年的植被NPP进行估算,采用Moran's I指数、Getis-Ord Gi*热点分析探讨其空间分布特征,并与我国生态功能保护区进行叠加分析。研究表明:1)云南省近20年植被NPP呈先减少再增加的趋势,平均值为822.98 gc/(m2·a);月度植被NPP夏季达到最高,冬季最低;不同植被类型中,常绿阔叶林的NPP值最高。2)各年份植被NPP空间分布均由南向北减少,全局空间自相关Moran's I指数均大于0.7,NPP热点区主要位于滇西南边境一带,冷点区位于滇西北、滇中城市化地区。3)植被净初级生产力热点区与生态功能保护区叠加相交于西双版纳生态功能保护区、西南喀斯特生态功能保护区,各年叠加面积占热点区域总面积的23%~26%。可见,云南省近20年NPP呈波动上升趋势,空间分布异质性明显。研究该结果可为云南植被监测、生态环境保护提供科学参考。
钱慧 , 张超 , 范金明 , 邓再春 , 朱夏力 , 李成荣 . 基于改进CASA模型的云南省植被NPP时空格局分析[J]. 林草资源研究, 2023 , 0(6) : 120 -128 . DOI: 10.13466/j.cnki.lczyyj.2023.06.015
Vegetation net primary productivity (NPP)is one of the indicators to measure the level of ecosystem productivity,it is of great significance to estimate it by using the combination of ecology and remote sensing.In this study,we applied the improved CASA model;based on the MODIS vegetation index product,meteorological data,and land cover data;estimated the vegetation NPP in Yunnan Province in 2000,2005,2010,2015,and 2020,and explored its spatial distribution characteristics using the Moran's I index,Getis-Ord Gi* hotspot analysis,and overlaying analysis with China's ecologically Functional Protected Areas in China were superimposed and analyzed.The results showed that:1)the vegetation NPP in Yunnan Province in the past 20 years showed a trend of decreasing and then increasing trend,with an average value of 822.98 gc/(m2 a);the monthly vegetation NPP reached the highest in summer and the lowest in winter;and among the different vegetation types,the evergreen broadleaf forests had the highest NPP values.2)The spatial distribution of vegetation NPP decreased from south to north in each year,and the global spatial autocorrelation Moran 's I index was greater than 0.7.The NPP hot spots were mainly located in the southwestern border of Yunnan,and the cold spots were located in the northwestern and central urbanization areas of Yunnan.3)NPP hotspot areas superimposed with ecological function reserve intersected in Xishuangbanna Ecological Function Reserve and Southwest Karst Ecological Function Reserve,and the superimposed area accounted for 23%~26% of the total area of hotspot areas in each year.The study shows that NPP in Yunnan Province has shown a fluctuating upward trend in the past 20 years,and the results can provide scientific references for vegetation monitoring and ecological environmental protection in Yunnan Province.
| [1] | Nemani R R, Keeling D C, Hashimoto H, et al. Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999[J]. Science, 2003, 300(5625):1560-1563. |
| [2] | Shvidenko Z A, Schepashchenko G D, Vaganov A E, et al. Net primary production of forest ecosystems of Russia:A new estimate[J]. Doklady Earth Sciences, 2008, 421(6):822-825. |
| [3] | 高艳妮, 于贵瑞, 张黎, 等. 中国陆地生态系统净初级生产力变化特征—基于过程模型和遥感模型的评估结果[J]. 地理科学进展, 2012, 31(1):109-117. |
| [4] | 王继燕, 李爱农, 靳华安. 湿地植被净初级生产力估算模型研究综述[J]. 湿地科学, 2015, 13(5):636-644. |
| [5] | 朱文泉, 陈云浩, 徐丹, 等. 陆地植被净初级生产力计算模型研究进展[J]. 生态学杂志, 2005, 25(3):296-300. |
| [6] | Christopher S P, James T R, Christopher B F, et al. Terrestrial ecosystem production:A process model based on global satellite and surface data[J]. Global Biogeochemical Cycles, 1993, 7(4):811-841. |
| [7] | 石志华, 刘梦云, 吴健利, 等. 基于CASA模型的陕西省植被净初级生产力时空分析[J]. 水土保持通报, 2016, 36(1):206-211,345. |
| [8] | 刘亮, 关靖云, 穆晨, 等. 2008—2018年伊犁河流域植被净初级生产力时空分异特征[J]. 生态学报, 2022, 42(12):4861-4871. |
| [9] | 张猛, 陈淑丹, 林辉, 等. 洞庭湖湿地净初级生产力估算研究[J]. 遥感学报, 2023, 27(6):1454-1466. |
| [10] | 孙舒, 王让会. 基于CASA模型的人工植被生物量的估算及特征分析[J]. 林业资源管理, 2012(6):61-66,100. |
| [11] | 何云玲, 张一平. 云南省自然植被净初级生产力的时空分布特征[J]. 山地学报, 2006, 24(2):193-201. |
| [12] | 孙治娟, 谢世友. 基于地理探测器的云南省净初级生产力时空演变及因子探测[J]. 生态学杂志, 2021, 40(12):3836-3848. |
| [13] | 谷雷, 岳彩荣, 张国飞, 等. 基于Google Earth Engine平台的大湄公河次区域2001—2019年植被NPP时空变化分析[J]. 西部林业科学, 2021, 50(2):132-139. |
| [14] | 周瑞伍. 云南植被主要类型分布区预测研究[D]. 昆明: 云南大学, 2015. |
| [15] | Zhang Xiao, Liu Liangyun, Chen Xidong, et al. GLC_FCS30:Global land-cover product with fine classification system at 30 m using time-series Landsat imagery[J]. Earth System Science Data, 2020, 13(6):2753-2776. |
| [16] | 朴世龙, 方精云, 郭庆华. 利用CASA模型估算我国植被净第一性生产力[J]. 植物生态学报, 2001(5):603-608. |
| [17] | 朱文泉, 潘耀忠, 张锦水. 中国陆地植被净初级生产力遥感估算[J]. 植物生态学报, 2007, 31(3):413-424. |
| [18] | Ruimy A, Saugier B, Dedieu G. Methodology for the estimation of terrestrial net primary production from remotely sensed data[J]. Journal of Geophysical Research:Atmospheres, 1994, 99(3):5263-5283. |
| [19] | 朱文泉, 潘耀忠, 何浩, 等. 中国典型植被最大光利用率模拟[J]. 科学通报, 2006, 51(6):700-706. |
| [20] | Ren H, Shang Y, Zhang S. Measuring the spatiotemporal variations of vegetation net primary productivity in Inner Mongolia using spatial autocorrelation[J]. Ecological Indicators, 2020, 112:106108. |
| [21] | 王川, 王丽莎, 张勇勇, 等. 2000—2020年祁连山NPP时空变化及驱动因素[J]. 生态学报, 2023, 43(23):1-11. |
| [22] | 万华伟, 李灏欣, 高吉喜, 等. 我国植被生态系统固碳能力提升潜力空间格局研究[J]. 生态学报, 2022, 42(21):8568-8580. |
| [23] | 王思云, 胡文英. 基于CASA模型的云南省植被净初级生产力遥感估算[J]. 云南地理环境研究, 2019, 31(5):71-78. |
| [24] | Richardson D A, Keenan F T, Migliavacca M, et al. Climate change,phenology,and phenological control of vegetation feedbacks to the climate system[J]. Agricultural and Forest Meteorology, 2013, 169:156-173. |
| [25] | 马思煜. 云南省农业干旱事件时空动态变化与驱动机制研究[D]. 西安: 西北大学, 2022. |
| [26] | 云南省林业厅造林绿化处. 云南林业造林绿化“十三五”开局良好[J]. 云南林业, 2017, 38(1):28-31. |
| [27] | 张良侠, 岳笑, 周德成, 等. 气候变化和人类活动对我国典型草原区植被恢复的影响[J]. 环境科学, 2023, 44(5):2694-2703. |
| [28] | Huang Tianbao, Ou Guanglong, Wu Yong, et al. Estimating the Aboveground Biomass of Various Forest Types with High Heterogeneity at the Provincial Scale Based on Multi-Source Data[J]. Remote Sensing, 2023, 15(14):3550-3550. |
| [29] | 李传华, 朱同斌, 周敏, 等. 河西走廊植被净初级生产力时空变化及其影响因子研究[J]. 生态学报, 2021, 41(5):1931-1943. |
| [30] | 王云霓, 代海燕, 海龙, 等. 华北落叶松人工林净初级生产力对气象因子的响应[J]. 林业资源管理, 2022(3):67-72. |
/
| 〈 |
|
〉 |
