REMOTE SENSING INDICATORS FOR CROP GROWTH MONITORING AT

DIFFERENT SCALES

Zongnan Li1, 2 and Zhongxin Chen1, 2*

1Key Laboratory of Resources Remote Sensing and

Digital Agriculture, MOA, Beijing 1000812Institute of Agricultural Resources and Regional

Planning, CAAS, Beijing 100081

IGARSS 2011, Vancouver, 24-29 July, 2011

Outline

Ⅰ. INTRODUCTION

Ⅱ. DATA AND PROCESS

Ⅲ. RESULT &DISCUSSION

Ⅳ. CONCLUSION

Ⅰ. INTRODUCTION

Crop growth is critical agricultural information. It can be used in the scientific management of crop and agricultural practice. It is also important in yield estimation and prediction

There are several methods for crop growth monitoring, including in-situ field agronomic method, crop growth diagnostic model, and remote sensing method

Remote sensing indicators are widely useed in vegetation monitoring

Vegetation indices (VIs)are still the important indicators for regional crop growth monitoring

Problem with VIs’ application

Some VIs are sensitive to the soil background and non-vegetation fraction

The scale effect

—— different spatial resolutions

—— spatial heterogeneity of land surface

Research Objectives

• Through testing the relationship between VIs and crop growth parameters, to investigate – if there is/are optimal crop growth monitoring

indicators at canopy scale and regional scale for different crop phenological stages

– if there are any trends for the relationship between VIs and crop growth parameters at different spatial scales

field experiment

field experiment

canopy spectracanopy spectra

crop parameters

crop parameters

crop yield crop yield

HJ-1 Im

ageryH

J-1 Imagery

LAIin-situ

LAIin-situ

Geom. Correction

Geom. Correction

Atmos. Correction

Atmos. Correction

VIsVIs

VIsVIs

Correlation analysis

Correlation analysis

Relationsip betw

een VIs and crop grow

th

Relationsip betw

een VIs and crop grow

th

VIs at different

scales

VIs at different

scales

scalingup

scalingup

Correlation analysis

Correlation analysis

LAIregional

LAIregional

Relationsip between

VIs and LAI at different scales

Relationsip between

VIs and LAI at different scales

Ⅱ. DATA AND PROCESS

research region

Field experiment plots in Langfang (116°36′E, 39°36′N).

Regional study in Hebei province

Ⅱ. DATA AND PROCESS

• Field experiment and observation

5 levels for N fertilizer treatments; 4 times repeat

N application treatments: N1- 0; N2- 15kg/ha; N3- 45 kg/ha; N4- 105 kg/ha; N5- 225kg/ha

Ⅱ. DATA AND PROCESS

• Field experiment and observation

canopy spectra, LAI, foliar chlorophyll, plant hight, coverage and biomass were measured at 5 phenological stages on 3/30, 4/14, 4/24, 5/5 and 5/17, 2009.

Canopy spectra Canopy LAIChlorophyll SPAD

Ⅱ. DATA AND PROCESS

• Field experiment and observation

early elongation stage jointing stage

heading stage milk stage

LAI evolution for various N applications

HJ-1A CCD Image 3/25/2009

HJ-1A CCD Image 4/21/2009

SpecificationBands (μm)

Blue:0.43-0.52Green:0.52-0.60Red:0.63-0.69infrared: 0.76-0.90

Swath 360×360kmResolution 30m

Ⅱ. DATA AND PROCESS

• Caculation of VIs & Correlation analysis

Ⅱ. DATA AND PROCESS

• Processing of HJ-1 multi-spectral images

Ⅱ. DATA AND PROCESS

• LAI Inversion (Beer’s law)

where

KNDVI=0.29

NDVI∞=0.97

NDVIs=0.11

LAI in study region

March 25 (elongation)April 21 (heading)

High crop cover Low crop coverCanopy

Ⅲ. RESULT &DISCUSSION• Remote sensing indicators for crop growth at canopy scale

(sample sizes =20)

Date and Crop Stages

2009-3-30 2009-4-14 2009-5-5 2009-5-17

early elongation

stagejointing stage heading stage milk stage

NDVI 0.5173* 0.8462** 0.8778** 0.9068**

PVI 0.5484* 0.6612** 0.7033** 0.8165**

SAVI(L=0.1) 0.5060* 0.8447** 0.8146** 0.8993**

SAVI(L=0.2) 0.5494* 0.8507** 0.7815** 0.8857**

SAVI(L=0.3) 0.5680* 0.8229** 0.7544** 0.8857**

SAVI(L=0.5) 0.5504* 0.8191** 0.7416** 0.8737**

MSAVI 0.5504* 0.8191** 0.7484** 0.8677**

EVI 0.5504* 0.8236** 0.7379** 0.8361**

Ⅲ. RESULT &DISCUSSION

• Remote sensing indicators for crop growth at regional scalesLow crop cover/the sample sizes n=30.

Date 2009-3-25 early elongation stage 2009-4-21 heading stage

Resolution 240m 480m 960m 240m 480m 960m

PVI 0.9288 0.9362 0.9440 0.9592 0.9357 0.9536

SAVI(L=0.1) 0.9431 0.9504 0.9723 0.9697 0.9643 0.9665

SAVI(L=0.3) 0.9514 0.9486 0.9746 0.9689 0.9654 0.9686

SAVI(L=0.5) 0.9472 0.9474 0.9722 0.9689 0.9638 0.9700

MSAVI 0.9440 0.9446 0.9714 0.9685 0.9621 0.9674

EVI 0.9262 0.9582 0.9472 0.9400 0.9361 0.9499

good but no obvious trendgood but no obvious trend

Ⅲ. RESULT &DISCUSSION• Remote sensing indicators for crop growth at regional scales

High crop cover/the sample sizes n=30.

Date 2009-3-25 early elongation stage 2009-4-21 heading stage

Resolution 240m 480m 960m 240m 480m 960m

PVI 0.9261 0.9450 0.9799 0.5750 0.6512 0.7261

SAVI(L=0.1) 0.9536 0.9816 0.9943 0.9437 0.9512 0.9519

SAVI(L=0.3) 0.9456 0.9726 0.9898 0.8247 0.8349 0.8936

SAVI(L=0.5) 0.9394 0.9671 0.9888 0.7209 0.8006 0.8284

MSAVI 0.9408 0.9651 0.9877 0.7784 0.8260 0.8770

EVI 0.9125 0.9463 0.9639 0.7932 0.8072 0.8598

Ⅳ. CONCLUSION

• At canopy scale, SAVI with different L values are suitable for winter wheat growth monitoring.

• At regional scale, soil –adjusted vegetation indices have limitations in dense crop coverage.

• For dense crop coverage, the relationship between VIs improve with the increased pixel size, But this trend is not obvious for low crop coverage.

Acknowledgements

The research was supported by the MOA 948 program project with contract no. 2010-S2 and 2009-Z31, and international corporation project from MOST(Ministry of Science and Technology of China ) with contract no. 2010DFB10030.

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