China Crop Watch System with Remote Sensing. Wu Bingfang, Li Qiangzi IRSA, Chinese Academy of Sciences

Transcription

1 China Crop Watch System with Remote Sensing Wu Bingfang, Li Qiangzi IRSA, Chinese Academy of Sciences

2 Table of Content Overview of CCWS Crop growing condition monitoring Drought monitoring Crop acreage estimation Crop yield monitoring Updates of CCWS recently

3 China CropWatch System Established in 1998 and Operated since then Improved by operating

4 System Structure

5 Monitoring Contents and Frequency Crop growth and crop condition monitoring every ten days Drought monitoring of the entire China every ten days Agro-meteorological condition analysis of China every month Crop area estimation and yield prediction for wheat, rice, maize, soybean month Crop Proportion Monitoring year Cropping Index Monitoring year

6 China Crop Watch Bulletin

7 Clients State Council Ministry of Agriculture State Grain Administration State Development and Reform Commission Office of State Flood Control and Drought Relief Headquarters National Bureau of Statistics of China National Disaster Reduction Center of China Grain Trading companies Local governments...

8 Crop growing condition monitoring Instant crop growth monitoring get the crop growing status for certain period by comparing the remote sensed data (NDVI, for example) of the period with the data of the period in the history (last year, mostly), indicating the spatial difference of crop condition at a certain period Crop growing process monitoring Time series of NDVI image during the crop season are used and crop growth profiles are formed by getting statistical average of NDVI, LAI or NPP in a certain region such as a province or a country. The contrast of crop growing profiles between year and year before can reflect the crop growing continuance during crop growing season, indicating the crop condition through the crop growing season.

9 Crop growing condition monitoring system Analysis

10 DroughtWatch Data processing DroughtIndex DroughtGrade Statictics

11 DroughtIndex Suitability Analysis T for TCI,V for VCI,H for VHI

12 Operation at Information center, Ministry of Water Resources Distribution on internet, accessed by MWR

13 Crop Acreage Estimation Methods Acreage = area_arable * R1 * R2 Where: Acreage : crop acreage area_arable : area of arable land in a region R1 : planted proportion on arable land R2 : percentage of certain crop type on planted arable land Remote sensing data: planted proportion on arable land Transect line sampling: crop type proportion on planted arable land

14 Crop acreage Planting structure zoning Remote sensing data Cluster sampling Image processing Transect line sampling Field survey GVG sampling system arable acreage Crop planting proportion (R1) Planting proportion of crop species (R2) Planting acreage of crop species

15 Crop Planting Proportion (R1) Image processing flow for crop proportion extraction Radar data correction backsactter Filter and stretching Optical data Atmosphere correction 遥感影像预处理 Mosaic NDIF SAVI Geometric correction Non-arable mask Arable land Unsupervised classification Labeling

16 Crops Planting Proporation (R1) Crop planting proportion estimation validation Crop proportion accuracy assessment for the two test area Items kaifeng Taigu Planting area with Landsat TM Arable land from landuse map (1: ) Planting proportion from Landsat TM Planting area with IKONOS/ Qui ckbird Arable land from IKONOS/Quickbird Planting proportion from IKONOS/ Qui ckbi rd Error -0.43% 2. 28%

17 Crop Type Proportion (R2) Estimation Transect sampling A two stage sampling SSU:Belt/Line Transect PSU:4KM * 4 KM

18 Crop type proportion (R2) Estimation GVG field sampling system GIS GPS VIDEO For acquiring the real-time crop types proportion

19 Crop type proportion (R2) Estimation Accuracy assessment- Dehui site Type GVG ( % ) Landuse ( % ) Error ( % ) GVG ( % ) Landuse ( % ) Error ( % ) Paddy Corn other crops village urban area grassland idle land othe total Distributing plot of sample points and Landuse map Validation results of Dehui site

20 Crop type proportion (R2) Estimation Accuracy assessment-taigu Crops GVG ( %) Field mapping ( %) Error ( %) Crops GVG ( %) Field mapping ( %) Error ( %) Corn 谷物 Vegetable 红薯 Soya Bean 南瓜 Idle land 大棚 Durra 花生 Sun flower 菊花

21 Prediction Models Crop yield monitoring 1)Agro-meteorological Model Y = Yt + Yw + y 2) Remote Sensing Model Y = Yt + Y ndvi Y ndvi = a + bx+cx 2 3) Hybrid Model Y = a + b*rs + c*agro

22 Crop yield monitoring-system

23 Crop yield monitoring Crop yield results analysis and validation Comparison between field measures and prediction yield Count y For ecast ed For ecast ed For ecast ed Obser ved Rel at i ve Tr end Yi el d Fl uct uat e Yi el d Yi el d Yi el d Error( y/y) i n 2005 i n 2005 i n 2005 ( y) in 2005 (y) Quf u % Yanzhou % Zhouchen % Ji ni ng %

24 Updates of CCWS recently

25 Update of CCWS from recently 1.Provincial system development

26 Update of CCWS from recently 1. Provincial system development The system is developed on IDL 6.2 platform The database we used Microsoft access. Which is very cheaper and easy to learn. The system can run on one computer or internal network. The system will released by the end of the next month, every province can download the system from our website by free. (

27 CCWS in Key Period 1. Provincial system development Data need by the system was processed by CCWS and released on our r website and province users can download free Users can also process the data by themselves, but they need some e technical skills.

28 CCWS in Key Period 2. Uncertainty analysis of crop acreage and crop yield estimation The results have not available totally, and we would not release e the figures.

29 Thanks