Super typhoon Haiyan makes landfall
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VEGETATION - 2000

Lake Maggiore - Italy, 3-6 April 2000


Crop Growth Monitoring with Coupling of AVHRR and VEGETATION

Wu Bingfeng
Head, Agriculture and Environment
Institute of Remote Sensing Application
P.O. Box 9718, Beijing 100101
Wubf@irsa.irsa.ac.cn

Feng Renguo
Head, Land Resources and Remote Sensing
Science and Technology for Resources and Environment
Chinese Academy of Sciences
Sanlihe Road 52, Beijing 100864

Paper (pdf file, 526 k)

In agriculture, monitoring of crop growth and development, and early estimates of the final production to be expected are of general interest. Traditionally, the monitoring of crop growth and yield forecasts are made on the basis of samples by field visits or written inquiries. Problems encountered concern subjectivity in responses, respondent differences and non-response. On national scale, the processing of these sample data is an expensive and time-consuming procedure. In general, there is a need for an objective, standardized and possibly cheaper and faster methodology for crop growth monitoring and yield forecasts. China started to use remote sensing to monitor crop health and to forecast production in as early as 1983, but failed to put into operation. In 1997, Chinese Academy of Sciences initiates Crop Monitoring project with its purposes to realize operational crop monitoring on wheat, rice, corn and bean over the whole country.

Both NOAA AVHRR and SPOT VEGETATION data are used to monitor the crop growth over the entire country at dekad period during growing season from March to October. It includes:

  1. comparison of any dekad of the current growing season with the previous dekad of the same growing season;
  2. the current dekad with the same dekad of the previous growing season;
  3. the current dekad with the same dekad of the normal; and
  4. percent comparison of the current dekad with the maximum NDVI value within the normal.

AVHRR data were received by our own receiving station. VEGETATION data was obtained through a cooperation established with the Joint Research Centre of the European Commission in the framework of the "Share-cost action on the improvement of the VEGETATION mission". The red and near-infrared bands of the AVHRR data were calibrated to reflectance and the two thermal bands were calibrated to surface temperature. Geometrical rectification was done using orbit information from the TLE data allowing a registration accuracy at the sub pixel level. Clouds were masked interactively with individual verification of all field sites, and noises were detected and removed interactively. The ten days Maximum Value Composite (MVC) were produced.

In order to focus on crop growth information, only farming land pixels were kept. This was done by combining land cover database at a resolution of 1km, gridded from vector maps at a scale of 1:100,000. A detailed, quantitative and statistic analysis within the GIS system is accomplished by calculating the percentages of 5 categories, as well as the mean, maximum and minimum of the NDVI value, on a dekad basis, for crop masks, for each of the 31 provincial-level administrative zone. Pixels influenced by cloud are excluded from the calculation of the mean NDVI statistics. Each mean NDVI curve by selected administration can be viewed, analyzed and compared to other years within the statistical archive. Users have the flexibility to choose the comparison years and can electronically export the data or the NDVI curves into reports or presentations.

The differential image is a color image by assigning red, yellow, green, cyan and blue to five categories together with statistic table. This should be explained in the term of crop growth and at the same time, the reason as well as the recommendation should be addressed too, with ancillary information, such as the majority crop, the crop phonology, and the climate data.

All products are in a GIS digital format. The users can access a password-protected account containing the historical and current crop growth information as well as natural disaster via a Web browser on the Internet. The benefits are obvious for users and provider; the client saves money by not having to invest in a GIS package to view the products, while the provider can expand the client base provided the client has access to the Internet. Changes, revisions and updates are transparent to the client improving efficiency, ease of access and program flexibility. For some important decision makers, who may not find time to look at the website, but has the time to quick look the paper, we printed the products together with explanation on the hard copy and delivery to their desk within one day.