Drought and Desertification

Monitoring

Drought and Desertification

Monitoring

Zhan Yulin

Institute of Remote Sensing Applications, CAS

Jan. 23, 2007

Contents

Background

Drought monitoring

Desertification monitoring

Background

UN ESCAP -- the integrated system of water and land

resources for arid areas (2001-2004)Objectives

Enhance the capabilities of water and land management in arid areas by

using space technology

Participating Countries

China, D. P.R. Korea, Mongolia, Kazakstan, Uzbekistan, Pakistan

Scientific issues

Drought Monitoring, Desertification Monitoring …...

Background

European Commission -- A Surveillance System for

Assessing and Monitoring of Desertification (2005-2010)

Objectives

Assessing desertification and land degradation status.

Forecasting of desertification under selected climatic and socio-

economic scenarios.

Monitoring of desertification and land degradation status over

large areas.

Background

European Commission -- A Surveillance System for

Assessing and Monitoring of Desertification (2005-2010)Partners

39 organisations representing 10 EU Member States and 6 Third Country

States

China, Spain, Sweden, France, Germany, Greece, Italy, Netherlands,

Portugal, United Kingdom, Belgium, Chile, Algeria, Morocco, Senegal,

Tunisia

Drought is …

Lack of precipitation

A period of water shortage

Drought is…

WaterDemand

WaterSupply

Methods for drought monitoring

Vegetation Condition Index (VCI)

Crop Water Stress Index (CWSI)

Soil Thermal Inertial Model

Normalized Difference Temperature Index

(NDTI )

Temperature Vegetation Dryness Index

( TVDI) based on the NDVI-Ts Space

NDVI-Ts Space

wet edge Ts_min

dry edge Ts_max = a +b* NDVI

NDVI

Ts

Bare

soil Partial

cover

Full cover

Sandholt et al., 2002

)]*()*[(

)]*([

1122

11

NDVIbaNDVIba

NDVIbaTTVDI s

NDVIbaT

NDVIbaT

s

s

*

*

22max_

11min_

The Sketch map for NDVI-Ts space

Ts

NDVI

Theoretic Base of TVDI

The agricultural climatic regions (central weather bureau of China, 1994) and the distribution of the topsoil moisture observation stations

ACR I: Eastern Monsoon Agricultural Climatic Region ACR II: North-Western Arid Agricultural Climatic RegionACR III: Qingzang tableland Cold Agricultural Climatic Region

Drought -- Study region and dataset

Drought -- Study region and dataset

• NOAA-AVHRR 10 days composite NDVI , thermal infrared (Ch4 and Ch5) dataset from March-May in 2000

• The measured topsoil moisture collected from observation stations

Drought -- Data process

first ten days in March first ten days in April first ten days in May

270

280

290

300

310

320

0. 2 0. 4 0. 6 0. 8

270

280

290

300

310

320

0. 2 0. 4 0. 6 0. 8200

220240

260

280300

320

-0. 1 0 0. 1 0. 2 0. 3

200

220

240

260

280

300

320

-0. 1 0. 1 0. 3 0. 5 0. 7 0. 9200

220

240

260

280

300

320

0 0. 1 0. 2 0. 3 0. 4 0. 5 0. 6

The Extracted maximum and minimum Ts from NDVI-Ts space for small intervals of NDVI for ARC I in 2000

Drought -- Result

Very wet Wet Balanced Dry Severe drought

first ten days in March first ten days in April first ten days in May

Drought -- Result

the first ten days in March

y = -1. 9968x + 0. 8371

R2 = 0. 4616

0. 0

0. 2

0. 4

0. 6

0. 8

1. 0

0 0. 1 0. 2 0. 3 0. 4 0. 5

TVDI

the fi rst ten days i n May

y = -1. 0517x + 0. 7598

R2 = 0. 21310. 0

0. 2

0. 4

0. 6

0. 8

1. 0

0. 0 0. 1 0. 2 0. 3 0. 4

θ

θSevere drought

the fi rst ten days i n Apri l

y = -0. 7681x + 0. 6728

R2 = 0. 2388

0. 0

0. 2

0. 4

0. 6

0. 8

1. 0

0 0. 1 0. 2 0. 3 0. 4 0. 5

θ θ

Relations between TVDI and soil moisture in China

Drought – Conclusion and problem

Compared with VCI, CWSI and NDTI, TVDI is a promising method in monitoring drought for large region

the sensor view angle which can has some effect on Ts and NDVI has not been taken into consider

Although China is divided as three ACR, but it still has varied climate types and topography features.

Higher time-spatial resolution image and a more suitable regional dividing method can produce a more promising result with TVDI.

Desertification is …

Productive Soil turned into

Non- productive Desert

Factors of Desertification

Natural factors

climate

• temperature

• precipitation soil

• type

• erosion vegetation

• species

• biomass

Over mining

Overgrazing

Population increasing

Cutting unregularly

Human factors

Factors of Desertification

Desertification Indexes

Modified Soil Adjusted Vegetation Index (MSAVI)

Albedo

Land Surface Temperature (LST)

Fractional Vegetation Cover (FVC)

Temperature Vegetation Dryness Index (TVDI)

Comparison between Different Indexes

(a) MSAVI

(b)MSAVI+Albedo

(c)MSAVI+Albedo+LST

(d)MSAVI+Albedo+LST+TVDI

NonSlightModerateHeavyVery Heavy

(e)MSAVI+Albedo+LST +TVDI+FVC

NOAA 1995In Kerchin

Accuracy of Different Indexes

Index MSAVI Albedo LST FVC TVDI

Accuracy 68.91% 56.24% 43.56% 66.84% 30.57%

IndexMSAVI+Albedo MSAVI+LST MSAVI+TVDIFVC+Albed

o FVC+LST

Accuracy 86.59% 84.63% 77.65% 85.31% 82.49%

Index MSAVI+Albedo+LST

MSAVI+TVDI+Albedo

MSAVI+LST+TVDI

Albedo+TVDI+FVC

Albedo+LST+ FVC

Accuracy 90.23% 89.18% 86.84% 88.52% 87.67%

Index MSAVI+Albedo+LST+TVDI FVC+Albedo+LST+TVDI

Accuracy 93.83% 92.05%

Index MSAVI+Albedo+LST+TVDI+FVC

Accuracy 95.21%

Desertification climate types

Thornthwaite method

Desertification indicator system

level MSAVI FVC Albedo LST TVDI

Non >2.2 >0.6 <200 <30 <0.35

slight 1.9-2.2 0.3-0.6 200-220 30-36 0.35-0.45

moderate 1.2-1.9 0.23-0.3 220-260 36-40 0.45-0.56

severe 0.8-1.2 0.15-0.23 260-300 40-46 0.56-0.65

Very severe <0.8 <0.15 >300 >46 >0.65

Desertification indicator system in semi arid area for NOAA

>0.72>37>250<0.1<0.60Very severe

0.69-0.7234-37230-2500.1-0.310.60-0.90severe

0.60-0.6932-34205-2300.31-0.430.90-1.20moderate

0.54-0.6029-32180-2050.43-0.61.20-1.50slight

<0.54<29<180>0.6>1.50Non

TVDI陆面温度反照率植被覆盖度MSAVIlevel

>0.72>37>250<0.1<0.60Very severe

0.69-0.7234-37230-2500.1-0.310.60-0.90severe

0.60-0.6932-34205-2300.31-0.430.90-1.20moderate

0.54-0.6029-32180-2050.43-0.61.20-1.50slight

<0.54<29<180>0.6>1.50Non

TVDI陆面温度反照率植被覆盖度MSAVIlevel

Desertification indicator system in semi arid area for MODIS

Desertification distribution in China

Desertification distribution map from NOAA-Avhrr, 1995

Non

Slight Hyper Arid

Moderate

Severe

Very Severe

Water

Desertification distribution in Central Asia

Desertification distribution map from NOAA-Avhrr, 1995

Non

Slight Hyper Arid

Moderate

Severe

Very Severe

Water

Desertification distribution in China

Desertification distribution map from MODIS, 2001

Non

Slight Hyper Arid

Moderate

Severe

Very Severe

Water

Desertification distribution in Central Asia

Desertification distribution map from MODIS, 2001

Non

Slight Hyper Arid

Moderate

Severe

Very Severe

Water

Identifying the boundary of Desert

Occurrence of Onset of green-up

NDVI increases for at least one and a half months;

NDVI reached maximum during the particular periods;

NDVI is greater than 0.05;

This event must occur in April to August.

Identifying the boundary of Desert

AVHRR NDVI 8KmDataset 1982–2000

Study areas including Kazakhstan, Uzbekistan, Turkmenistan, Kirghiz, Tajikistan, Mongolia and western China.

1982 1986

1990 1993

Vegetated areas

Non-vegetated areas

Vegetated areas

Non-vegetated areas

Vegetated areas

Non-vegetated areas

Vegetated areas

Non-vegetated areas

Occurrence of onset of green-up in different years in the study areas

1997

2000

Vegetated areas

Non-vegetated areas

Vegetated areas

Non-vegetated areas

Vegetated areas

Non-vegetated areas

Vegetated areas

Non-vegetated areas

1995

1999

Occurrence of onset of green-up in different years in the study areas

Frequency of Occurrence of Onset of green-up in central Asia and western China (1982-2000)

•the onset of green-up event is never detected in the core desert areas.

•From desert steppe to typical steppe, the Frequency increases from 2 to 18.

•In lower onset frequency zone, the desert steppe (the transitional zone between desert and typical steppe) displayed a typical steppe-like phonological pattern in the wet year and a desert-like pattern in a dry year.

Identifying the boundary of Desert

Dynamic change of desertification

Coefficient of variation (CoV) of the NDVI

AVHRR NDVI 8Km Dataset 1982–2000

Annual pixel-level CoV of NDVI

The slope of the NDVI CoV (1982-2000)

ijijij /cov

NDVI CoV slope map for central Asia and western China(1982-2000).

•Areas without changes (near-zero CoV slope) are mapped in green

•Areas of improving vegetation cover (positive CoV slope) in red

•Areas of declining vegetation cover (negative CoV slope) in blue.

Dynamic change of desertification

Desertification monitoring based on geostatistical texture

0 10km 20km

海南省

北

Desertification in east of Hainan Island result from ilmenites’ over mining.

Desertification in Hainan is difficult to identify directly from origin radiometric bands •Distinguishing between beach sandlot and inner desert •Desertification classification in Hainan different from West-North in china

Hainan Island, china

DATA:TM(1989) and ETM+ (2003)

Desertification monitoring based on geostatistical texture

Method

1893× 3窗口

h=1 窗口移动方向

光谱影像 纹理影像

101

64

52

50

99

98

57

52

54

99

63

53

46

65

83

61

47

51

85

94

54

63

101

96

89

spectral bands geostatistical texture

2)()(2

1xDNhxDNEh

Desertification monitoring based on geostatistical texture

(a) 89年4、3、2合成 (b) 89年纹理波段合成 (d) 03年纹理波段合成(c) 03年4、3、2合成(a) 4、3、2 bands(1989) (b) Texture bands(1989) (c) 4、3、2 bands(2003) (d) Texture bands(2003)

Desertification monitoring based on geostatistical texture

极重度沙漠化

重度沙漠化 其它

北

极重度沙漠化

北

重度荒漠化其它

0 5km 10km中度荒漠化 轻度荒漠化

0 5km 10km

(a) 1989年分类结果 (b) 2003年分类结果(a) The classification result for 1989 (b) The classification result for 2003

Accuracy:92.4% Accuracy:94.7%

Desertification -- Conclusion

An integrated desertification indexes are proposed

Desertification monitoring method based on geostatistical texture

Desert boundary can be identified by using the occurrence of onset of green-up

Utilizing NDVI CoV, the Dynamic change of desertification was analyzed