Agricultural monitoring of Russia using Remote Sensing:

an overview

Russian Academy of Sciences Space Research Institute

Savin I., Bartalev S., Loupian E.

Some features of R&D at IKI Focus is on national level (entire Russia) monitoring with

application, if suitable, to sub-continental, or potentially, global coverage

Primary sources of EO data are moderate resolution satellite instruments (mainly MODIS and SPOT-VGT), while resent developments in Russia are rapidly increase the potential role of high-res. (e.g. SPOT-HRV/HRVIR) data for national monitoring

Focus on long-term time-series data analysis

Development of automatic satellite data receiving and processing chains to perform monitoring in the routine and repeatable manner

Source: GOSKOMSTAT

< 1%1-10%10-20%20-40%> 40%

% of sown area by administrative regions according to official statistics

Sown area distribution in Russia

Main crops in Russia

54%

32%9%

5%

GrainsForage cropsIndustrial cropsVegatables

34%

23%

18%

6% 19%

Spring wheatSpring barleyWinter wheatWinter ryeOther

Source: GOSKOMSTAT

Agricultural Monitoring with EO data in Russia

Development of the national agricultural monitoring system with use of EO data has been initiated by Russian Ministry of Agriculture in year 2003

Main agricultural monitoring system developing institutions:

Main Computational Center, Russian Ministry of Agriculture

Space Research Institute, Russian Academy of Sciences

Main thematic focuses of agricultural monitoring development

Arable lands area and dynamic assessment

Crop / land-use type mapping

Monitoring of impact of extreme meteorological conditions on crop growth

Crop yield forecast and assessment

Earth Observation data for agricultural monitoring of Russia

(i) Operative data

- NOAA-AVHRR

- Terra-MODIS

- SPOT-Vegetation

- SPOT-HRV/HRVIR

(ii) Historical data- Landsat-TM/ETM (1990-1995-2000)

(iii) Data under consideration for nearest future - IRS-AWIFS

- Kosmos-CX

VEGETATION and MODIS data archive at IKI

MODIS data products:MOD09GHK, MOD09GQK, MODMGGAD,

MOD09GST(Surface Reflectance Products)

Geographical coverage:Northern Eurasia (above 40ºN)Time frame: 2002 – ongoingTemporal resolution: dailyMain spectral bands used:

i. 440 – 480 nmii. 620 – 670 nmiii. 841 – 976 nmiv. 1630 – 1650 nm

Spatial resolution: 250&500m (nadir view)

VEGETATION data products:S10 products

(ten-days maximum NDVI composites)

Geographical coverage:Northern Hemisphere (above 40ºN)Time frame: 1998 – ongoingTemporal resolution: 10 daysSpectral bands:

i. 430 – 470 nmii. 610 – 680 nmiii. 780 – 890 nmiv. 1580 – 1750 nm

Spatial resolution: 1.15km (nadir view)

MODIS receiving stations for agricultural monitoring in Russia

MODIS data pre-processing stepsMODIS daily products

Snow/cloud detection

Cloud shadow detection

Best resolution selection and temporal compositing

Comparison with standard MODIS monthly data composites

Standard MODIS-Terra

MOD13A3 1km productMOD13A3.A2006182.h19v02.004

MOD13A3.A2006182.h20v02.004

Improved MODIS-Terra

250&500m productStart date – 2005/07/01

End date – 2005/08/01

RGB:841 - 876 nm

2105 - 2155 nm620 - 670 nm

MODIS derived arable lands map for Russia

MODIS derived arable lands map of Russia

Rostovskaya oblast Stavropolskiy kray

MODIS derived map GLC2000

Comparison of MODIS derived arable lands with GLC 2000

Comparison of MODIS derived arable lands with land-cover map

- MODIS arable lands

Tambovskaya and Penzenskaya oblasts of RussiaSource: Land-cover map of USSR, 1:4 million, 1989

- arable lands- non-arable lands

Land-Use map:

Comparison of MODIS derived arable lands area with official statistics

Crop types classification using MODIS time-series data

PVI increasePVI decrease

April 30, 2003 May 25, 2003

September 23, 2003August 30, 2003-0,05

0

0,05

0,1

0,15

0,2

0,25

0,3

12.3

1.2

001

2.1

9.2

002

4.1

0.2

002

5.3

0.2

002

7.1

9.2

002

9.7

.2002

10.2

7.2

002

12.1

6.2

002

2.4

.2003

Time

PVI

0,00

0,05

0,10

0,15

0,20

0,25

0,30

2.1.

2005

3.3.

2005

4.3.

2005

5.3.

2005

6.3.

2005

7.3.

2005

8.3.

2005

9.2.

2005

10.3

.200

5

Time

winter wheat

spring barley

sunflower

PVI

Snow Winter cropFallow land

MODIS derived crop types : Rostov region, 2003

– Water bodies– Deciduous forest– Grassland– Built-up area

Sunflower

Winter crop

Clean fallow

– Clean fallow– Winter crops– Sunflower

Validation test sites in Rostov region

Clean fallow SunflowerWinter crops

Arable lands area comparison

y = 1,04x - 46,9R2 = 0,93

0

500

1000

1500

2000

2500

3000

0 500 1000 1500 2000 2500 3000official satatistics (sq.км)

MO

DIS

der

ived

dat

a (s

q.км

)

Rice acreage assessment

0

50

100

150

200

250

id 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

dekad

ND

VI

(rel

.val

ue) Rice in

Kalmykia, Russia

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Cco

rr

dekad

rice acreage(1000 ha) according:

Calculated based on vector masks Predicted at the beginning of the season based on MODIS

2004 2005 2006 2007 2008vector masks 4.9 5.4 5.8 5.8 5.4

official statistics 4.8 5.1 5.5 5.6 5.7

Crops affected by spring frost

20-24 April 2009

Mostly affected

regions

Maximal impact

on early grain

crops

Crops affected by drought 2009

Maximal impact

on later grain

and technical

crops

Crops affected by drought

July 2009

Yield assessment with NDVI time-series by administrative regions (year-analogue method)

Crops yield prediction based on regression analysis

Li near Regressi on wi th95,00% Mean Prediction Interval

0,6500 0,7000 0,7500

ndv i_ar

20,0

30,0

40,0

ww

_y A

A

AA

A

A

A

A

A

w w_y = -80,16 + 155,69 * ndv i _arR-Square = 0,93

Adygea (winter wheat)

region O2 O3 J3 F1 F2 F3 M1 M2 M3 A1 A2 A3 M1 M2 M3 J1 J2Kabardino-Balkaria 0 0 0.928095 0.990346 0 0 0 0 0 0 0 0 0 0 0 0Karacheavo-Cherkessia 0 0 0 0 0 0 0 0 0 0.918450 0 0 0Stavropol 0 0 0 0 0 0 0 0.819710 0 0 0 0.896070 0.971387Krasnodar 0 0 0 0 0 0 0 0.838434 0 0 0 0 0.892490 0.942365 0.956444Adygea 0 0 0.932812 0 0 0 0 0 0 0 0 0 0.974098 0Rostov 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.946906Volgograd 0 0.891109 0 0 0 0 0 0 0 0 0 0 0 0 0Voronezh 0 0 0 0 0 0.803667 0.878573 0 0 0.997912Belgorod 0 0 0 0 0.987377 0.995856 0 0Orenburg 0.840599 0 0 0 0 0 0 0 0 0 0.862699Kursk 0 0 0 0 0 0 0 0 0 0.878315 0.982881Samara 0 0 0 0 0 0.902545 0 0 0.938675 0 0.955563Tambov 0 0 0 0 0 0 0 0 0 0 0.932496 0 0 0 0 0 0

User access to agricultural monitoring results

www.agrocosmos.gvc.ru

Forthcoming Challenges

To extend arable lands map for entire Northern Eurasia region

To develop operational mode for crop types mapping on entire Russia level

To develop operational land-use change monitoring (e.g. land abandonment, aforestation, newly-ploughed virgin lands and etc.)

To develop operational monitoring of risk of crop damage due to insects invasions (locusts, Colorado potato beetle…)

To combine moderate and high-resolution satellite data to improve crop area estimated accuracy

To introduce a new methods of crop yield forecasting based on crop growth modeling