帮助 关于我们

返回检索结果

鄱阳湖区粮食供给功能的空间格局分析
Spatial Pattern of Food Provision Sevice in Poyang Lake Region, China

查看参考文献33篇

李鹏 1   姜鲁光 1 *   封志明 1   张景华 1   闫慧敏 1   赵慧霞 2  
文摘 在种植制度复杂、地块破碎及多阴雨天气的南方地区,应用卫星遥感植被指数时间序列数据提取复种指数受到中低空间分辨率的限制. 使用较高空间分辨率影像是提取该区域复种信息有效的数据源. 论文以鄱阳湖区为研究区,通过遥感解译提取水田空间信息;在界定单/双季稻生长期物候历的前提下,根据水稻不同生长期内归一化植被指数(NDVI)的明显差异,选择合理时间窗口的TM影像获取水田NDVI数据,采用非监督分类法提取单/双季稻的空间分布信息;结合湖区乡镇不同熟制水稻单产数据估算出基于栅格的水稻产量. 研究表明, 4月下旬到6月下旬是判别双季早稻与单季稻空间分布的合理时间窗口; 7月上旬到8月上旬及9月中旬到 10上旬是判别单季稻与双季晚稻空间分布的合理时间窗口. 2005年,单季稻播种面积为 3 081.58 km~2,晚稻/早稻播种面积为3 602.97 km~2,水稻复种指数为153.9%. 单季稻普遍分布在市县建成区周边,双季稻主要分布在河口三角洲等地. 全年水稻总产量约1 650×10~4t,单季稻占30.5%,双季稻占69.5%. 赣江下游地区两种熟制水稻产量均较高,而湖汊及湖区外围丘陵地区产量较低
其他语种文摘 Generally, in southern China with complex growing system, fragmentized and dispersed paddy field, and long-term overcast and rainy weather, the performance of using vegetation index (VI) time-series datasets derived from remote sensing imageries to extract multiple-cropping index was seriously constrained by the lower spatial resolution. Currently, the application of higher spatial resolution images can be the exclusive and effective way to extract the spatial pattern of different rice cropping systems annually in these regions. In this paper, firstly, the spatial distribution of paddy field in Poyang Lake Region (PLR) was obtained through one TM imagery interpretation. Secondly, the annual phenological calendar of various systems of paddy rice was defined with the agro-meteorological data. According to the significant characteristics that Normalized Difference Vegetation Index (NDVI) fluctuates sharply along with the growth process of paddy rice, map of NDVI for paddy field was derived from another TM image within the applicable time window. Then, different cropping systems of paddy rice were classified by means of Unsupervised Classification in Erdas Imagine 9. 2. Finally, yield of each raster (100 m) was calculated with unit yield from local statistical department. The results showed that, late April to late June can be the time window to differentiate early rice and single-season rice, while early July till early August and middle September to early October could be the time window for the differentiation between single-season rice and late rice. Specifically, the planting areas of single-season and early/ late rice are 3081. 58 km~2 and 3602. 97 km~2 in 2005, respectively, indicating that the multiplecropping index is 153. 9%. Single-season rice is generally distributed around the periphery of the built-up area, while double-season rice expanded along the delta. The total yield of -paddy rice reached to nearly 16. 5 million tons with a proportion of single-season to double-season approximating to 3: 7. The two seasons rice both had a higher yield in the lower reaches and delta area of the Ganjiang River
来源 自然资源学报 ,2011,26(2):190-200 【核心库】
关键词 粮食供给 ; 水稻熟制 ; 时间窗口 ; NDVI ; 鄱阳湖区
地址

1. 中国科学院地理科学与资源研究所, 北京, 100101  

2. 国家气象中心, 国家气象中心, 北京, 100081

语种 中文
文献类型 研究性论文
ISSN 1000-3037
学科 社会科学总论
基金 国家自然科学基金 ;  国家973计划
文献收藏号 CSCD:4127462

参考文献 共 33 共2页

1.  封志明. 粮食安全:西北地区退耕对粮食生态的可能影响. 自然资源学报,2002,17(3):299-306 CSCD被引 26    
2.  李晶. 区域粮食安全性分析与预测--以陕西省关中地区为例. 资源科学,2005,27(4):89-94 CSCD被引 38    
3.  傅泽强. 中国粮食安全与耕地资源变化的相关分析. 自然资源学报,2001,16(4):313-319 CSCD被引 221    
4.  谢俊奇. 基于改进的农业生态区法的中国耕地粮食生产潜力评价. 中国土地科学,2004,18(4):31-37 CSCD被引 44    
5.  封志明. 从栅格到县域:中国粮食生产的资源潜力区域差异分析. 自然资源学报,2007,22(5):747-755 CSCD被引 29    
6.  闫慧敏. 近20年中国耕地复种指数的时空变化. 地理学报,2005,60(4):559-566 CSCD被引 70    
7.  沈学年. 多熟种植,1983 CSCD被引 19    
8.  卞新民. 多元多熟种植制度复种指数计算方法探讨. 南京农业大学学报,1999,22(1):14-18 CSCD被引 1    
9.  郭柏林. 我国复种指数变化特征、效益和潜力. 经济地理,1997,17(3):8-13 CSCD被引 21    
10.  朱会义. 现阶段我国耕地利用集约度变化及其政策启示. 自然资源学报,2007,22(6):907-915 CSCD被引 107    
11.  高帆. 我国粮食生产的地区变化:1978~2003年. 管理世界,2005(9):70-78 CSCD被引 17    
12.  辛良杰. 近年来我国南方双季稻区复种的变化及其政策启示. 自然资源学报,2009,24(1):58-65 CSCD被引 86    
13.  范锦龙. 复种指数遥感监测方法研究,2003 CSCD被引 14    
14.  Defries R S. NDVI-derived land cover classifications at a global scale. International Journal of Remote Sensing,1994,15(17):3567-3586 CSCD被引 111    
15.  Xiao X. Mapping paddy rice agriculture in southern China using multi-temporal MODIS images. Remote Sensing of Environment,2005,95(4):480-492 CSCD被引 132    
16.  Lee R. Evaluating vegetation phenological patterns in Inner Mongolia using NDVI time-series analysis. International Journal of Remote Sensing,2002,23(12):2505-2512 CSCD被引 22    
17.  Doraiswamy P C. Crop condition and yield simulations using Landsat and MODIS. Remote Sensing of Environment,2004,92(4):548-559 CSCD被引 46    
18.  Xin J. Mapping crop key phenological stages in the North China Plain using NOAA time series images. International Journal of Applied Earth Observation and Geoinformation,2002,4(2):109-117 CSCD被引 16    
19.  彭代亮. 基于MODIS-NDVI的浙江省耕地复种指数监测. 中国农业科学,2006,39(7):1352-1357 CSCD被引 35    
20.  Peng D. Detection and estimation of mixed paddy rice cropping patterns with MODIS data. International Journal of Applied Earth Observation and Geoinformation,2011,13:13-23 CSCD被引 35    
引证文献 11

1 李鹏 不同辐射校正水平下水稻植被指数监测对比分析 遥感技术与应用,2012,27(1):121-127
CSCD被引 5

2 Li Peng Changes in rice cropping systems in the Poyang Lake Region,China during 2004-2010 Journal of Geographical Sciences,2012,22(4):653-668
CSCD被引 23

显示所有11篇文献

论文科学数据集
PlumX Metrics
相关文献

 作者相关
 关键词相关
 参考文献相关

版权所有 ©2008 中国科学院文献情报中心 制作维护:中国科学院文献情报中心
地址:北京中关村北四环西路33号 邮政编码:100190 联系电话:(010)82627496 E-mail:cscd@mail.las.ac.cn 京ICP备05002861号-4 | 京公网安备11010802043238号