Introduction of CropWatch a global agricultural monitoring system. Zhang Miao, Wu Bingfang RADI, CAS Sep. 30 th, 2015

Transcription

1 Introduction of CropWatch a global agricultural monitoring system Zhang Miao, Wu Bingfang RADI, CAS Sep. 30 th, 2015 GLOBCAST Dissemination Event - 30 September 2015

2 Outline Methodology Activities and results Future direction

3 CropWatch Method

4 CropWatch Hierarchical approach Global: homogeneous crop mapping and reporting units Using CropWatch Agroclimatic Indicators (CWAIs) for rainfall, air temperature, photosynthetically active radiation, and potential biomass Regional: Major production zones In addition to CWAIS, Vegetation health index, uncropped arable land, cropping intensity, and maximum vegetation condition index Increasing level of detail, from environmentalclimatic to agronomic; from 25 km resolution to 16m National: 31 countries In addition to previous indicators, crop cultivated area, time profile clustering Sub-national for large countries Crop type proportion (some countries)

5 CropWatch Hierarchical approach Input Output Global 6Main Production Zones 30+1 Key Countries Sub countries Rainfall Air temperature PAR Potential biomass Vegetation Health Index Uncropped Arable Land Cropping Intensity Maximum VCI NDVI Crop area Time profile clustering Arable land fraction Crop structure (China, USA, Australia, Canada, etc.) Field survey of Pest & disease Crop Production System Zones (CPSZ) Climatically Indices (CI) Agricultural pattern Farming intensity Biomass trend Cropland use intensity Crop condition Production, Yield Cropland use intensity Crop condition Production, Yield Phytosanitary condition of crops (China) Global food supply analysis

6 Data used at global scale Photosynthetically active radiation (PAR) (remote sensing data) Spatial resolution: 0.25 ; Air temperature (Interpolated from Ground station data) Spatial resolution: 0.25 ; Precipitation (remote sensing data) Spatial resolution: 0.25 ; Potential NPP (Calculated by remote sensing data) Spatial resolution: 0.25 ; Weighted average over arable land and growing season Departure calculation 65 MRUs Abnormal weather pattern at global scale

7 Crop pattern and stress for 6 MPZs Agronomic indicators Vegetation health index (VHI) Maximum vegetation condition index (VCIx) Cropped arable land fraction (CALF) Cropping intensity (CI) Abnormal weather pattern by time series clustering

8 31 key producing countries Covering at least 80 percent of global production and export of the major cereals and soybean Sub-national monitoring for 9 large countries

9 31 key producing countries Integrated crop condition monitoring Vegetation health index Maximum vegetation condition index NDVI development profile NDVI departure clustering NDVI anomaly Crop condition only for cropped arable land

10 Crop area estimation Crop area in China, Canada, Australia, Egypt, and US CALF=Cropped Arable Land Fraction Crop area = Arable land area CALF Crop type proportion Remote Sensing based GVG survey Crop area in other countries relies on the regression of crop area against cropped arable land fraction Area a b CALF

11 Crop area estimation Transfer GVG system to cellphone Carry out field survey in US., Canada, Australia, Egypt, Thailand and India

12 Crop yield Three models in CropWatch Agro-meteorological model Biomass-HI model VI regression model Accumulated MTCI Accumulated NDVI

13 Special methods and indicators in China Optional Drought Indices for China Vegeatation Condition Index VCIj NDVIj NDV I NDV I m ax m in NDV I m in 100% Temperature Condition Index Vegetation Health Index TCIj T T max max Ts T min j 100 % VHI a * VCI (1 a) * TCI Normalized Difference Water Index a=r 2 vci/( R 2 vci+ R 2 tci) NDWI SWIR SWIR NIR NIR NDVIj NDVI of date j;ndvimax and NDVImin are the maximum and minimum NDVI of all dataset ; Tmax and Tmin are the maximum and minimum Ts of all dataset. SWIR is the shortwave infrared band and NIR near infrared band

14 Special methods and indicators in China Crop diseases and pests Leaf scale Canopy scale Regional scale

15 Activities and results

16 Temperature and Rainfall Temperature departure from 14 YA, degree April July, 2015 Rainfall departure from 14 YA (%) April July, 2015

17 Western Europe Major production zone Heat waves and low rainfall damaged summer crops in western Europe MPZ One quarter less than normal rainfall, April to July Extreme high temperature since early July Maximum VCI, April to July Potential biomass departure, April to July

18 National level NDVI Overall average condition in US Wheat condition was above average Soy and maize was at average condition Spatial NDVI patterns compared to 5YA NDVI departure profiles

19 Cropped and uncropped map Biomass departure from 14YA (%) National level United States, 2015 maize, rice, wheat, and soybean production, by state (thousand tons) States Maize Rice Wheat Soybean 2015 Δ% 2015 Δ% 2015 Δ% 2015 Δ% Alabama Arkansas California Colorado Georgia Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maryland Michigan Minnesota Mississippi Missouri Montana Nebraska New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania South Carolina South Dakota Tennessee Texas Virginia Washington Wisconsin Sub total Others United States

20 Crop condition in northeast China Crop condition development graph based on NDVI Maximum VCI, April to July Drought occurred in western Liaoning, not as severe as 2014 Overall crop condition was at 5Y average

21 Pests and diseases monitoring Distribution of the rice planthopper (a) and rice sheath blight (b) in China, August 2015 Distribution of maize northern leaf blight (a) and armyworm (b) in China, August 2015 Huang, 2015

22 Agricultural drought and impacts analysis Severe spring drought in Southwest China, 2010 Agricultural drought in China Mid April, 2010 Chongqing四川 Sichuan Guizhou 重庆 贵州 Yunnan 云南 Total 合计 冬小麦减产 万吨 Reduction in WW prod. (10kT) 占省 市 总产量(%) Percentage of total prod. (%) Total loss of winter wheat (WW) production reached t taking account 13.7% of four provinces production and 0.8% of the whole country s production

23 Area estimation and sampling, 2015 Cropped and uncropped arable land for winter crops GVG software using cellphone Cropped and uncropped arable land for summer crops Crop type proportion field survey

24 Maize Rice Wheat Soybean 2015 Δ(%) 2015 Δ(%) 2015 Δ(%) 2015 Δ(%) Anhui Chongqing Fujian Gansu Guangdong Guangxi Guizhou Hebei Heilongjiang Henan Hubei Hunan Inner Mongolia Jiangsu Jiangxi Jilin Liaoning Ningxia Shaanxi Shandong Shanxi Sichuan Xinjiang Yunnan Zhejiang Sub total Other provinces National total* *Production in Taiwan province is not included.

25 Maize Rice Wheat Soybean 2015 Δ(%) 2015 Δ(%) 2015 Δ(%) 2015 Δ(%) Anhui Chongqing Fujian Gansu Guangdong Guangxi Guizhou Hebei million tons, up %; Heilongjiang Henan Estimate for summer crops 752 is Hubei Hunan million tons, -1 up 0.5% from 2014 Inner Mongolia Jiangsu drought 3year Jiangxi Jilin Liaoning Ningxia Shaanxi Shandong Rice: million tons, 5 up %; 1 Shanxi Sichuan Xinjiang Yunnan Wheat: million tons, up 2% Zhejiang Sub total Other provinces National total* *Production in Taiwan province is not included. Total crop production for 2015 is million tons, 0.5% up from Total winter crops production is Maize: million tons, up 0.45%; Soybean: million tons, down 3%;

26 Global crop production for 2015

27 Global crop production for 2015 Global crop production reaches new record in 2015: the total production of maize and rice is stable with a global production of 987 million tons and 741 million tons, respectively, close to that of 2014; With a production of 725 million tons, wheat production has increased 1% over 2014; Soybean global production increases by 1% at 310 million tons.

28 Future directions An open global crop monitoring platform CropWatch bulletin CropWatch online CropWatch Project (assessment), and CropWatch Pro (processing)

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