Crop Phenology Estimation by Time Series MODIS medium-resolution data

被引:0
作者
Yu, Kun [1 ,2 ]
Wang, Zhiming [1 ]
Sun, Ling [1 ]
Wang, Jing [1 ]
Shan, Jie [1 ]
Lu, Bihui [1 ]
机构
[1] Jiangsu Acad Agr Sci, Inst Agr Informat, Nanjing 210014, Jiangsu, Peoples R China
[2] Minist Land & Resource, Key Lab Coastal Zone Exploitat & Protect, Nanjing 210024, Jiangsu, Peoples R China
来源
2017 6TH INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS | 2017年
关键词
MODIS; Crop Phenology; Remote Sensing; Vegetation Index; EVI; SCALE; NDVI;
D O I
暂无
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Crop phenology is a critical component of implementing agricultural activities and providing important indicators for climate related research. The needs for crop phenology estimation not only exist in large scale but also in medium or small scale. In this work, Jianhu County was chosen to test the ability of crop phenology estimation by Moderate Resolution Imaging Spectroradiometer (MODIS) data. 794 cloudy-free MODIS 250-m resolution images of Jianhu County from 2000 to 2013 were finally chosen. Two vegetation indices were compared to evaluate their effectiveness in crop phenology estimation. These were the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). EVI was less sensitive than NDVI to aerosol effects. Therefore, EVI was chosen to estimate crop phenology of Jianhu County. Then, the crop spatial distribution data were generated from RapidEye 5-m resolution images by visual interpretation to exclude those mixed pixels. In the long-term monitoring, ground survey and correlation analyses, we found that the MODIS-EVI time series data were suitable to estimate the turning green, the heading and the maturation of winter wheat and were suitable to estimate the transplanting, the heading and the maturation of rice. Because of the free availability and frequent coverage of MODIS data, the cost-effective assessment here by using MODIS 250-m resolution images may serve as a template applicable to other counties of Jiangsu province. Moreover, crop phenology estimation in county scale will be particularly helpful in providing some baseline information to yield estimation and food security, and will be useful to promote crop phenology estimation methods.
引用
收藏
页码:361 / 364
页数:4
相关论文
共 23 条
[1]  
[Anonymous], 2014, FAO Statistical Yearbook 2014
[2]   Monitoring turbidity in Tampa Bay using MODIS/Aqua 250-m imagery [J].
Chen, Zhiqiang ;
Hu, Chuanmin ;
Muller-Karger, Frank .
REMOTE SENSING OF ENVIRONMENT, 2007, 109 (02) :207-220
[3]   Monitoring phenological key stages and cycle duration of temperate deciduous forest ecosystems with NOAA/AVHRR data [J].
Duchemin, B ;
Goubier, J ;
Courrier, G .
REMOTE SENSING OF ENVIRONMENT, 1999, 67 (01) :68-82
[4]   Evaluation of earth observation based long term vegetation trends - Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT data [J].
Fensholt, Rasmus ;
Rasmussen, Kjeld ;
Nielsen, Thomas Theis ;
Mbow, Cheikh .
REMOTE SENSING OF ENVIRONMENT, 2009, 113 (09) :1886-1898
[5]   Overview of the radiometric and biophysical performance of the MODIS vegetation indices [J].
Huete, A ;
Didan, K ;
Miura, T ;
Rodriguez, EP ;
Gao, X ;
Ferreira, LG .
REMOTE SENSING OF ENVIRONMENT, 2002, 83 (1-2) :195-213
[6]   Monitoring paddy rice phenology using time series MODIS data over Jiangxi Province, China [J].
Li Shihua ;
Xiao Jiangtao ;
Ni Ping ;
Zhang Jing ;
Wang Hongshu ;
Wang Jingxian .
INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING, 2014, 7 (06) :28-36
[7]  
LIU HQ, 1995, IEEE T GEOSCI REMOTE, V33, P457, DOI 10.1109/36.377946
[8]  
Ma L., 2014, CHINA POPULATION RES, V24, P103
[9]   Interannual vegetation phenology estimates from global AVHRR measurements -: Comparison with in situ data and applications [J].
Maignan, F. ;
Breon, F. -M. ;
Bacour, C. ;
Demarty, J. ;
Poirson, A. .
REMOTE SENSING OF ENVIRONMENT, 2008, 112 (02) :496-505
[10]  
Moulin S, 1997, J CLIMATE, V10, P1154, DOI 10.1175/1520-0442(1997)010<1154:GSAOVP>2.0.CO