APPLICATION OF REMOTE SENSING DATA

FOR OPERATIONAL CROP MONITORING IN RUSSIA:

MODERN STATUS AND PROBLEMS

Igor Savin

V.V. Dokuchaev Soil Science Institute

Moscow, Russia savin_iyu@esoil.ru

Governmental Crop Monitoring in

Russia

Ministry of

Agriculture Ministry of

Agriculture

RosGydromet RosGydromet

Scientific Institutes: 1. Institute of Agrometeorology

2. Space Research Institute

3. V.V. Dokuchaev Soil Science

Institute

Scientific Institutes: 1. Institute of Agrometeorology

2. Space Research Institute

3. V.V. Dokuchaev Soil Science

Institute

Motivation for RS usage

Big territory

Frequent problems with drought and flooding

Crop production prediction

Control on efficiency of agricultural lands usage

Necessity in more objective information

RS System for agricultural land monitoring RS System for agricultural land monitoring

http://www.agrocosmos.gvc.ruhttp://www.agrocosmos.gvc.ru

VEGA (VEGA (VEGetationVEGetation Analysis)Analysis)

TERRA/AQUA-MODIS 2001-2015

Landsat-4, 5, 7, 8 1989-2015

Main Data in VEGAMain Data in VEGA

EO-1 Hyperion (14000 scenes) 2001-2015

ORBVIEW-3 (80000 scenes) 2005-2007

Kanopus-B, Resurs-P (25000 scenes) 2013-2015

Meteor-M (13000 scenes) 2010-2015

Area of InterestArea of Interest

Status on 6 September 2015

Main Tasks and ResultsMain Tasks and Results

Arable lands usage monitoring Crop recognition and crop acreage

assessment

Crop status monitoring Crop yield prediction

Level of Data AnalysisLevel of Data Analysis

Farm

Country

Field

Region

JECAM

Average plot size

is near 70 ha

400*3000 m

2014

2015

Winter crop mask (Tula region)

Number of plots

VEGA

sum mistake Winter

crop

Other

crop

Field

observation

Winter

crop 98 129 227 56.83

Other

crop 45 373 418 10.77

sum 143 502 645

mistake 31.47 25.70

Weeds geography

Afonin et al., 2009)

Weeds in Krasnoyarsk region

Weeds in Krasnoyarsk region

weeds

Weeds and NDVI

?

weeds winter crop

Weeds and NDVI

Network of Test Sites

Conclusion

Spatial resolution of MODIS data is not enough to monitor near half of the arable parcels in Russia

Weeds strongly effect NDVI, deteriorating the results of crop monitoring and yield forecasting

The number of test polygons has to be increased for more precise calibration and validation of RS based approaches

The RS based approaches along have to be used with care