生态建设对陕北植被变化的影响分析

干旱区地理 ›› 2014, Vol. 37 ›› Issue (2): 318-324.

生态建设对陕北植被变化的影响分析

李旺君^1，2，吕昌河¹

（1 中国科学院地理科学与资源研究所，北京 100101； 2 中国科学院大学，北京 100049）

收稿日期:2013-05-14 修回日期:2013-08-11 出版日期:2014-03-25
通讯作者: 吕昌河（1962-），男，山东莱芜人，研究员，博士生导师，主要从事土地利用、退化土地恢复、土地生产潜力等方面的研究.Email：luch@igsnrr.ac.cn
作者简介:李旺君（1982-），男，湖北麻城人，博士研究生，主要从事土地覆被/利用变化研究. Email：liwj.10b@igsnrr.ac.cn
基金资助:
国家重大科学研究计划（2012CB955304），国家自然科学基金（41071063）

Effects of ecological building on the vegetation change in Northern Shaanxi Province

LI Wang-jun^1，2，LU Chang-he¹

（1 Institute of Geographic Sciences and Nature Resources Research, CAS, Beijing 100101, China;2 University of Chinese Academy Sciences, Beijing 100049, China）

Received:2013-05-14 Revised:2013-08-11 Online:2014-03-25

摘要/Abstract

摘要： 运用趋势分析法及相关系数检验法，分析了陕北大规模生态建设工程实施以来植被NDVI变化趋势，检验了NDVI变化与降雨量、温度以及造林面积之间的关系。结果表明：陕北大部分地区植被明显转好（通过α=0.05检验），尤其是丘陵沟壑农耕区植被改善最为显著，12 a间NDVI净增0.123 3，提高24.90%，南部森林植被区，NDVI净增最低，只有0.045 0，增加率5.56%。NDVI变化格局与生态退耕格局在空间上呈现高度吻合的特征。NDVI变化与降雨量和温度没有显著的回归关系（R²<0.15），但与造林率（造林面积占县土地面积的比）回归关系显著（R²=0.560 8），说明降雨量、温度变化对陕北NDVI]变化没有明显的影响，而以退耕和植树造林为主的生态建设才是导致NDVI变化的主导因素。结论认为过去12 a的生态建设明显促进了陕北植被的恢复，改善了区域环境状况。

关键词: NDVI, 生态建设, 陕北

Abstract: This paper analyzed the trend of vegetation variation and its influencing factors in Northern Shaanxi Province，China since the implementation of the ecological building in 1999，based on NDVI （MODIS 13Q1），meteorological and statistical data. Correlation analysis and SLOPE approaches were used to detect the trend and to estimate amplitude of NDVI changes，and a regression method was used to analyze the relationship between [NDVI] change and rainfall，temperature and afforestation area. ArcGIS was used to map the spatial variation of the NDVI and its change trend. The results showed that in most parts of Northern Shaanxi，i.e. 72.58% of the total area，the vegetation was obviously improved during 2000-2011，in terms of [NDVI] changes at the 0.05 significance level. This improvement was most evident in the hilly and gully loess area，the key implementation area of the ecological building. In 27.18% of the study area，the NDVI had no significant change during the period，which mainly included forest vegetation in southern Ziwu and Huanglong Mountain areas，and a small part of grassland in Yulin and Dingbian. In a small area （0.24%） of the region，the [NDVI] showed an apparent decline trend，due to the land converted to urban and mining & industry land use. Among regions covered with different vegetation types，the region formerly cultivated for growing crops had most evident increase in the NDVI，increasing by 24.90% （0.122 3），with the amplitude （SLOPE value） of 0.014 3 during 2000-2011. The area covered by grass vegetation also had an apparent increase，increased by 23.15% （0.101 4） in NDVI with the SLOPE value of 0.011 8. The lowest increase appeared in the area covered by forest vegetation，where the NDVI increased only 5.56% （0.045 0） and the SLOPE value was 0.005 0. In the shrub and desert regions，the NDVI increased 10.48% （0.074 5） and 14.84% （0.068 3），respectively. Two representative regions were selected，i.e. Yan’an City with significant NDVI changes，and Dingbian County with non-significant [NDVI] changes，and conducted regression analyses to check possible effects of rainfall and temperature changes on the NDVI variation. It was found that the annual NDVI values were not correlated with the annual precipitation and temperature （R²<0.15） during 2000-2011. But regression analyses between changes in the mean regional NDVI and afforestation area for 25 counties in the study area，revealed a significant correlation （R²=0.561）. These regression results illustrated that the ecological building typified by returning the sloping farmland to forestland/grassland was the main factor affecting the NDVI change during 2000-2011 in northern Shaanxi Province，while precipitation and temperature had no or only a minor contribution to the change. In general，the spatial NDVI variation was in accordance with the distribution of the afforestation. It can be concluded that the ecological building implemented in 1999 have been an apparent positive effect on the environment，which greatly promoted the vegetation restoration in Northern Shaanxi Province.

Key words: NDVI, , ecological building, Northern Shaanxi province

中图分类号:

Q149

李旺君，吕昌河. 生态建设对陕北植被变化的影响分析[J]. 干旱区地理, 2014, 37(2): 318-324.

LI Wang-jun，LU Chang-he. Effects of ecological building on the vegetation change in Northern Shaanxi Province[J]. , 2014, 37(2): 318-324.

参考文献

［1］ FOLEY J A，LEVIS S，COSTA M H，et al. Incorporating dynamic vegetation cover within global climate models［J］. Ecological Applications，2000，10（6）：1620-1632.

［2］ YAN Feng，WU Bo，WANG Yanjiao. Estimating aboveground biomass in Mu Us Sandy Land using landsat spectral derived vegetation indices over the past 30 years［J］. Journal of Arid Land，2013，5（4）：521-530.

［3］ LUO Yanyun，LIU Tingxi，WANG Xixi，et al. Influences of landform as a confounding variable on SOM-NDVI association in semiarid Ordos Plateau［J］. Journal of Arid Land，2012，4（4）：450-456

［4］ ZHOU Liming，TUCKER C J，KAUFMANN R K，et al. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999［J］. Journal of Geophysical Research，2001，106（D17）：20069-20083.

［5］ XIN Zhongbao，XU Jiongxin，ZHENG Wei. Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau （1981- 2006）：Impacts of climate changes and human activities［J］. Science in China Series D：Earth Sciences. 2008，51（1）：67-78.

［6］闫俊杰，乔木，周宏飞，等. 基于MODIS-[NDVI]的新疆伊犁河谷植被变化［J］. 干旱区地理，2013，36（3）：512-519.

［7］ TUCKER C J. Red and photographic infrared linear combinations for monitoring vegetation［J］. Remote Sensing of Environment，1979，8（2）：127-150.

［8］ LUNETTA R S，KNIGHT J F，EDIRIWICKREMA J，et al. Land- cover change detection using multi-temporal MODIS NDVI data［J］. Remote Sensing of Environment，2006，105（2）：142-154.

［9］ DE JONG R，DEBRUIN S，De WIT A，et al. Analysis of monotonic greening and browning trends from global NDVI time-series［J］. Remote Sensing of Environment，2011，115（2）：692-702.

［10］ ZHOU Hongjian，VAN ROMPAEY A，WANG Jing-ai. Detecting the impact of the “Grain for Green” program on the mean annual vegetation cover in the Shaanxi province，China using SPOT-VGT NDVI data［J］. Land Use Policy，2009，26（4）：954-960.

［11］ PIAO Shilong，MOHAMMAT A，FANG Jingyun，et al. NDVI based increase in growth of temperate grasslands and its responses to climate changes in China［J］. Global Environmental Change，2006，16（4）：340-348.

［12］ DU PLESSIS W P. Linear regression relationships between NDVI，vegetation and rainfall in Etosha National Park，Namibia［J］. Journal of Arid Environments，1999，42（4）：235-260.

［13］武永峰，王秀芬，李茂松，等. 气候驱动格局下中国陆地植被指数变化［J］. 干旱区地理，2009，32（2）：166-174.

［14］ WHITE M A，THOMTON P E，RUNNING S W. A continental phenology model for monitoring vegetation responses to interannual climatic variability［J］. Global Biogeochemical Cycles，1997，11（2）：217-234.

［15］ BAI Z G，DENT D L，OLSSON L，et al. Proxy global assessment of land degradation［J］. Soil Use and Management，2008，24（3）：223-234.

SFSFDSFD

［17］ MA Junfei，LU Changhe，YU Bohua. Impacts of sloping land conversion program on the vegetation in Loess Hilly and Gully Area of Northern Shaanxi［J］. Ecological Economy，2009，5（2）：160- 167.

［18］中国科学院中国植被图编辑委员会.中国植被数据集，中国科学院［G］. 2001：101-104.

［19］林小惠，王军邦，李贵才，等. 基于MODIS遥感监测的东南亚地区植被动态［J］. 生态学杂志.2011，30（4）：629-635.

［20］ STOW D，DAESCHNER S，HOPE A，et al. Variability of the seasonally integrated normalized difference vegetation index across the north slope of Alaska in the 1990s［J］. International Journal of Remote Sensing，2003，24（5）：1111-1117.

［21］ LIU Yansui，GAO Jay，YANG Yanfeng. A holistic approach towards assessment of severity of land degradation along the Great Wall in Northern Shaanxi Province，China［J］. Environ Monit Assess，2003，82（2）：187-202.

［22］徐勇，SIDLE Roy C. 黄土丘陵区燕沟流域土地利用变化与优化调控［J］. 地理学报，2001，56（6）：657-666.

［23］封志明，张蓬涛，杨艳昭. 西北地区的退耕规模、粮食响应及政策建议［J］. 地理研究，2003，22（1）：105-113.

［24］ XIN Zhongbao，YU Xinxiao. Impact of vegetation restoration on hydrological processes in the middle reaches of the Yellow River，China［J］. Forestry Studies in China，2009，11（4）：209-218.

［25］戴声佩，张勃，王海军，等. 中国西北地区植被覆盖变化驱动因子分析［J］. 干旱区地理，2010，33（4）：636-643.

［26］ LIU Jianxiang，LI Zhiguang，ZHANG Xiaoping，et al. Responses of vegetation cover to the grain for green program and their driving forces in the He-Long region of the middle reaches of the Yellow River［J］. Journal of Arid Land，2013，5（4）：511-520.

[1]	卓静,胡皓,何慧娟,王智,杨承睿. 陕北黄土高原生态脆弱性时空变异及驱动因素分析[J]. 干旱区地理, 2023, 46(11): 1768-1777.
[2]	张维敏,王景红,刘璐,张勇. 陕北黄土高原红枣种植区水热资源变化及未来趋势预测[J]. 干旱区地理, 2021, 44(1): 73-79.
[3]	庞冉, 王文. 基于 MODIS 数据的吐鲁番盆地 2001—2017 年植被变化及水热组合影响分析[J]. 干旱区地理, 2020, 43(5): 1242-1252.
[4]	钱琛, 陈海滨, 侯现慧. 生态建设背景下陕西省植被覆盖时空变化及其影响因素研究 [J]. 干旱区地理, 2020, 43(2): 425-433.
[5]	王莺莺, 张依婧, 李飞, 吕妍. 作物生产潜力变化的区域差异——以陕西省为例[J]. 干旱区地理, 2019, 42(3): 615-624.
[6]	吴喜军, 李怀恩, 董颖. 煤炭开采对水资源影响的定量识别——以陕北窟野河流域为例[J]. 干旱区地理, 2016, 39(2): 246-253.
[7]	张翀, 任志远. 基于生态系统固碳的陕北大气CO₂治理成本核算[J]. 干旱区地理, 2016, 39(1): 122-129.
[8]	樊胜岳，乌日嘎，赵丹华，徐裕财. 沙漠化地区生态建设政策执行过程中的交易成本分析[J]. 干旱区地理, 2012, 35(5): 815-821.