|
|||||
|
|
| 基于GIMMS 3g NDVI的近30年中国北部植被生长季始期变化研究 | |
| 引用本文： | 李净,刘红兵,李彩云,李龙.基于GIMMS 3g NDVI的近30年中国北部植被生长季始期变化研究[J].地理科学,2017,37(4):620-629. |
| 作者姓名： | 李净 刘红兵 李彩云 李龙 |
| 作者单位： | 1. 西北师范大学地理与环境科学学院,甘肃 兰州 730070 2.甘肃建筑职业技术学院,甘肃 兰州 730050 3.兰州大学资源环境学院,甘肃 兰州 730000 4.兰州资源环境职业技术学院, 甘肃 兰州 730020 |
| 基金项目： | 国家自然科学基金(41561016)、西北师范大学青年教师科研能力提升计划项目（NWNU-LKQN-14-4）资助 |
| 摘 要： | 基于全球库存建模与绘图研究第三代归一化差值植被指数（GIMMS 3g NDVI）、土地利用和气温降水数据,利用NDVI时间序列谐波分析法(HANTS)重构了中国北部地区原始植被NDVI,用一元六次多项式拟合了植被生长曲线并结合逐像元动态阈值法提取了中国北部地区1983~2012年植被生长季始期并分析了其时空变化及对气温和降水的响应情况。结果表明：①GIMMS 3g NDVI具有较长的时序特征和较好的数据质量,经HANTS时间序列谐波分析后能很好的表现植被生长季曲线特征,可用于后续植被生长季的研究。② 北部地区生长季始期均值主要集中分布在80~150βd之间,全区30βa平均为111.6βd,东北平原、华北平原、河套平原、新疆天山和阿尔泰地区生长季始期早于其它区域。③ 研究时段内北部地区生长季始期总体上呈提前趋势（R2=0.19）,空间上由西北向东北逐渐推移,明显提前的区域主要分布在内蒙古中东部、东北平原、陕西南部和新疆天山的部分地区,明显推迟的区域主要分布在青藏高原高寒地区。④ 因植被类型的不同和区域的差异,生长季始期对气温和降水的响应程度不同,春季气温是影响生长季始期变化的主要自然因素。 |
| 关 键 词： | 生长季始期 GIMMS 3g NDVI 谐波分析 多项式拟合 相关性 |
| 收稿时间： | 2016-04-29 |
| 修稿时间： | 2016-10-10 |
Changes of Green-up Day of Vegetation Growing Season Based on GIMMS 3g NDVI in Northern China in Recent 30 Years |
|
| Jing Li,Hongbing Liu,Caiyun Li,Long Li.Changes of Green-up Day of Vegetation Growing Season Based on GIMMS 3g NDVI in Northern China in Recent 30 Years[J].Scientia Geographica Sinica,2017,37(4):620-629. | |
| Authors: | Jing Li Hongbing Liu Caiyun Li Long Li |
| Institution: | 1. College of Geographical and Environmental Science, Northwest Normal University, Lanzhou 730070, Gansu, China 2. Gansu Construction Vocational Technical College, Lanzhou 730050, Gansu, China 3. College of Resource and Environment, Lanzhou University, Lanzhou 730000, Gansu, China 4. Lanzhou Resources & Environment Voc-Tech College, Lanzhou 730020, Gansu, China |
| Abstract: | Based on GIMMS 3g NDVI, landuse, temperature, precipitation and vegetation type data, the paper fitted the current year vegetation growing season curve and extracted the yearly green-up day of vegetation growing season in northern China in recent 30 years (from 1983 to 2012), analyzed its spatio-temporal changes and also the relationship between temperature and precipitation. In order to meet the actual vegetation growth, we used harmonic analysis of time-series method to reconstruct vegetation NDVI, dynamic threshold and a sixpolynomial fitting method. Some conclusions were as follows. 1) With longer time-series features and better data quality, GIMMS 3g NDVI data with time-series harmonic data analysis was very good to fit and show the actual characteristics of vegetation growing season curve in northern China and can be well used to further study of vegetation growing season in the future. 2) During the study period, green-up day of vegetation growing season mainly distributed from 80 days to 150 days, and the regional averaged value reached 111.6 days.Green-up day of vegetation growing season in regions such as northeast Plain, north China Plain, Hetao Plain, Tianshan, the Altai were earlier. 3) Green-up day of vegetation growing season in northern China showed an advanced tend in general and gradually transitioned from the northwest to the northeast. The significantly advanced regions mainly distributed in the eastern of Inner Mongolia, northeast China Plain, southern Shanxi and the Tianshan Mountains of Xinjiang section area, while the significantly delayed regions were in Qinghai-Tibet Plateau alpine regions. 4) Due to various vegetation types and regional differences and so on,green-up day of vegetation growing season responded to temperature and precipitation distinctly and temperature was the main factor that affecting green-up day of vegetation growing season changes. |
| Keywords: | green-up day of growing season GIMMS 3g NDVI harmonic analysis polynomial fitting correlation |
| 本文献已被 CNKI 等数据库收录！ | |
| 点击此处可从《地理科学》浏览原始摘要信息 | |
| 点击此处可从《地理科学》下载免费的PDF全文 | |