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MAPPING AND ASSESSMENT OF MAPPING AND ASSESSMENT OF GRASSHOPPER HABITAT BASED ON GRASSHOPPER HABITAT BASED ON LANDSAT TM IMAGERY IN THE LANDSAT TM IMAGERY IN THE QINGHAI LAKE REGION OF CHINA QINGHAI LAKE REGION OF CHINA Shao Xiang NI Shao Xiang NI ( ( Key Lab of Virtual Geographic Environment, Sc Key Lab of Virtual Geographic Environment, Sc hool of Geographic Science, hool of Geographic Science, Nanjing Normal University, Nanjing Nanjing Normal University, Nanjing , , China China ) ) Paper ID: 2009558P2BCB Paper ID: 2009558P2BCB

Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

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MAPPING AND ASSESSMENT OF GRASSHOPPER HABITAT BASED ON LANDSAT TM IMAGERY IN THE QINGHAI LAKE REGION OF CHINA. Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science, Nanjing Normal University, Nanjing , China ) Paper ID: 2009558P2BCB. INTRODUCTION. - PowerPoint PPT Presentation

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Page 1: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

MAPPING AND ASSESSMENT OF MAPPING AND ASSESSMENT OF GRASSHOPPER HABITAT BASED GRASSHOPPER HABITAT BASED ON LANDSAT TM IMAGERY IN ON LANDSAT TM IMAGERY IN

THE QINGHAI LAKE REGION OF THE QINGHAI LAKE REGION OF CHINACHINA

Shao Xiang NIShao Xiang NI((Key Lab of Virtual Geographic EnvironmenKey Lab of Virtual Geographic Environmen

t, School of Geographic Science,t, School of Geographic Science,Nanjing Normal University, NanjingNanjing Normal University, Nanjing, , ChinaChina))

Paper ID: 2009558P2BCBPaper ID: 2009558P2BCB

Page 2: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

INTRODUCTIONINTRODUCTION In China, rangeland grasshoppers (In China, rangeland grasshoppers (OrthopteraOrthoptera::

AcrididaeAcrididae) have brought serious harms to live) have brought serious harms to livestock farming and induced many environmentstock farming and induced many environmental problems. al problems.

During the past period, a great deal of effort bDuring the past period, a great deal of effort based on the conventional methods has been mased on the conventional methods has been made to monitor the occurrence and plague of gade to monitor the occurrence and plague of grasshoppers. However, good results have not arasshoppers. However, good results have not achieved because of remote location and bad acchieved because of remote location and bad accessibility, and insufficient funds and facilities.cessibility, and insufficient funds and facilities.

Page 3: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

Since early 1970’s satellite image data have Since early 1970’s satellite image data have been used in monitoring migratory locust in been used in monitoring migratory locust in many regions.many regions.

In these works, locust monitoring was In these works, locust monitoring was conducted through its ‘habitat’. It means that conducted through its ‘habitat’. It means that a correlation analysis was carried out between a correlation analysis was carried out between habitat features and locust activities and, habitat features and locust activities and, therefore, locust occurrence probability was therefore, locust occurrence probability was estimated. estimated.

However, the similar method has not been used However, the similar method has not been used for grasshopper monitoring. for grasshopper monitoring.

Page 4: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

2 STUDY AREA2 STUDY AREA

The Qinghai Lake region is located in The Qinghai Lake region is located in Qinghai Province ,China (Fig. 1) with Qinghai Province ,China (Fig. 1) with the elevation ranging from 3 200 m the elevation ranging from 3 200 m to 4 200 m above sea level.to 4 200 m above sea level.

The region is a very important sheep The region is a very important sheep grazing base. However, grasshoppers grazing base. However, grasshoppers have made harms not only to have made harms not only to grassland, but also induced grassland, but also induced environment issues.environment issues.

Page 5: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

Location of the study areaLocation of the study area

Page 6: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,
Page 7: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

Major grasshopper speciesMajor grasshopper species

Page 8: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

3 DATA AND METHODS3 DATA AND METHODS 118 sampling sites were selected and investigated118 sampling sites were selected and investigated

in July to August, 2000-2003. At each site, data of lanin July to August, 2000-2003. At each site, data of landform, vegetation, soil and moisture condition werdform, vegetation, soil and moisture condition were collected, and grasshopper density was estimated. e collected, and grasshopper density was estimated.

The data of temperature, precipitation and evaporaThe data of temperature, precipitation and evaporation of these sites were obtained from local meteortion of these sites were obtained from local meteorological stations or through field observationological stations or through field observation

A database was establishedA database was established for the follow-up analy for the follow-up analysis. sis.

Landsat TM image data were radiantly and geometrLandsat TM image data were radiantly and geometrically corrected, and ically corrected, and the grasshopper habitats werthe grasshopper habitats were classifiede classified by Gaussian maximum likelihood classi by Gaussian maximum likelihood classifier. fier.

Page 9: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

After that, After that, assessment on grasshopper assessment on grasshopper habitatshabitats in terms of probable grasshopper in terms of probable grasshopper occurrence was conducted. occurrence was conducted.

Firstly, Firstly, an index system was designedan index system was designed, , which was consisted of the habitat elements, which was consisted of the habitat elements, i.e., topography, vegetation and soil, and i.e., topography, vegetation and soil, and their ratings with indices representing their ratings with indices representing grasshopper occurrence probability. grasshopper occurrence probability.

Moreover, Moreover, 12 test sites were randomly 12 test sites were randomly selected and assessedselected and assessed using the index using the index system and thesystem and the in situ in situ data collected in field data collected in field to test the method. to test the method.

Page 10: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,
Page 11: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,
Page 12: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

4 RESULTS AND 4 RESULTS AND DISCUSSIONDISCUSSION

4.1 grasshopper habitat 4.1 grasshopper habitat ClassificationClassification

4.1.1 Classification scheme4.1.1 Classification scheme The features of a given type of The features of a given type of grasshopper grasshopper

habitathabitat are closely related with landform, are closely related with landform, soil properties, moisture conditions, soil properties, moisture conditions, vegetation type. vegetation type.

Page 13: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

Grasshopper habitats belong to a same type Grasshopper habitats belong to a same type are similar in grasshopper species and denare similar in grasshopper species and density. sity.

Using the data collected in field, Using the data collected in field, a classifica classification scheme of grasshopper habitat ation scheme of grasshopper habitat (Tab(Table 1) was designed and used in grasshopper le 1) was designed and used in grasshopper habitat classification from Landsat TM imahabitat classification from Landsat TM images.ges.

Page 14: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

Habitat type Habitat type Dominant grass speciesDominant grass species Dominant grasshopper Dominant grasshopper speciesspecies

①①Steppe dominated Steppe dominated by by Stipa KryloviiStipa Krylovii ((SKsSKs))

Stipa KryloviiStipa Krylovii, , Stipa brevifloraStipa breviflora, , Agrophyron cristAgrophyron cristatum, Orimus kokonoricaatum, Orimus kokonorica

Chorthippus dubiusChorthippus dubius, , MyrmelMyrmeleotettix palpaliseotettix palpalis

②②Steppe domi. by Steppe domi. by Achnatherum splendAchnatherum splendes es ((ASsASs))

Achnatherum splendesAchnatherum splendes,, Agrophyron cristatum Agrophyron cristatum, , OrOrimus kokonoricaimus kokonorica

Chorthippus dubiusChorthippus dubius, , MyrmelMyrmeleotettix palpaliseotettix palpalis

③③Steppe domi. bySteppe domi. by S Stipa pupureatipa pupurea ( (SPsSPs))

Stipa pupureaStipa pupurea, Kobresia parva, , Kobresia parva, Kobresia capillifolKobresia capillifoliaia, , Leymus secalinumLeymus secalinum

Chorthippus dubiusChorthippus dubius

④④High-cold meadoHigh-cold meadow (w (HCHC))

Kobresia humilis,Kobresia humilis, Kobresia capillifolia, Kobresia Kobresia capillifolia, Kobresia pygmaeapygmaea, , StipaStipa spp., spp., Potentilla Potentilla spp.spp.

ChorthippusChorthippus, , fallaxChorthipfallaxChorthippus dubiuspus dubius

⑤⑤High-cold shrub High-cold shrub meadowmeadow((HCsHCs))

Salix cuplaris, Potentilla fruiticosaSalix cuplaris, Potentilla fruiticosa , , Caragana jubCaragana jubataata, , Kobresia capillifoliaKobresia capillifolia, , Kobresia humillisKobresia humillis, , PolyPolygonum viviparumgonum viviparum

Chorthippus fallaxChorthippus fallax,,Chorthippus dubiusChorthippus dubius

⑥⑥Abandoned farmlAbandoned farmland (and (AFAF))

Stipa Krylovii, Stipa brevifloraStipa Krylovii, Stipa breviflora ,, Achnatherum sple Achnatherum splendesndes

Chorthippus dubiusChorthippus dubius,, Myrmel Myrmeleotettix palpaliseotettix palpalis

Table 1 The scheme for grasshopper habitat classification

Page 15: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

4.1.2 Image Classification of 4.1.2 Image Classification of grasshopper habitatgrasshopper habitat A supervised classificationA supervised classification for for

grasshopper habitat on TM image was grasshopper habitat on TM image was conducted based on the training data conducted based on the training data collected from 189 sampling sites. collected from 189 sampling sites.

After that, After that, a spectral statistics for the a spectral statistics for the trainingtraining data was obtained (Fig. 2), and was data was obtained (Fig. 2), and was used in grasshopper habitat classification. used in grasshopper habitat classification.

Finally, Finally, a check on classification a check on classification accuracyaccuracy was carried out at 50 randomly was carried out at 50 randomly selected sites, with an overall accuracy of selected sites, with an overall accuracy of 84.23% achieved.84.23% achieved.

Page 16: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,
Page 17: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

Fig.2 Spectral statistics of the Fig.2 Spectral statistics of the training datatraining data

SKs ASsSKs ASs

SKs ASs

Page 18: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

SPs MMSPs MM

MM

SPs

Page 19: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

HC HCsHC HCs

HC meadow

HCs

Page 20: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

AFAF

AF

Page 21: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,
Page 22: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

4.2 Grasshopper habitat4.2 Grasshopper habitat assessmentassessment

4.2.1 Assessment method 4.2.1 Assessment method An index system used for An index system used for

grasshopper habitat assessmentgrasshopper habitat assessment was established (Table 2).was established (Table 2).

Page 23: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

Table 2 The index system for grasshopper habitat assessment

Habitat elementHabitat element

Damage degree of grasshoppers to grasslandDamage degree of grasshoppers to grassland

Seriously ( )ⅠSeriously ( )Ⅰ Rather Rather seriously ( )Ⅱseriously ( )Ⅱ General ( )ⅢGeneral ( )Ⅲ No damage No damage

( )Ⅳ( )Ⅳ

VegetationVegetation

Vegetation index Vegetation index (NDVI) ((NDVI) (FF11))

0.24-0.380.24-0.380.18-0.24 or0.18-0.24 or

0.38-0.450.38-0.450.12-0.18 or 0.12-0.18 or

0.45-0.500.45-0.50<0.12 or >0.50<0.12 or >0.50

Dominant Dominant speciesspecies((FF22))

Stipa KryloviiStipa Krylovii or or AchnaAchnatherum stherum splendensplendens

Stipa purpureaStipa purpureaStipa purpureaStipa purpurea,,

Kobresia Kobresia spp.spp.

KobresiaKobresia spp. spp. or or KK.. tibe tibe

ticatica

Total coverage Total coverage ((FF33) ) <60%<60% 60% -75 %60% -75 % 75% -85 %75% -85 % >85%>85%

TopographyTopographyElevation (Elevation (FF4)4) 3200-3300m3200-3300m 3300-3400m3300-3400m 3400-3500m3400-3500m >3500m>3500m

Aspect (Aspect (FF5)5) SS AEAE or or SWSW NE NE or or NWNW NN

SoilSoil

Soil type (Soil type (FF6)6) Light chestnut Light chestnut ChestnutChestnut Dark chestnut Dark chestnut

Marsh soil or Marsh soil or high-cold high-cold meadow meadow soilsoil

Texture (Texture (FF7)7) LoamLoam Sandy loamSandy loam Clay loamClay loam Sandy Sandy

Moisture Moisture content (content (FF8)8)

15-25%15-25% <15%<15% 25-35%25-35%<15% or <15% or

>35%>35%

Page 24: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

Based on this index system, Based on this index system, a a grading schemegrading scheme for grasshopper for grasshopper habitats in terms of grasshopper habitats in terms of grasshopper occurrence probability was occurrence probability was established (Table 3).established (Table 3).

Page 25: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

Table 3 The grading scheme for grasshopper habitat

Grade of Grade of grasshopper grasshopper

probable probable occurrenceoccurrence

Elements used in habitat assessmentElements used in habitat assessmentGrade Grade valuevalue

((FF))

FF11 FF22 FF33 FF44 FF55 FF66 FF77 FF88

ⅠⅠ 16.016.0 12.012.0 16.016.0 8.08.0 8.08.0 8.08.0 5.65.6 6.46.4 >70.0>70.0

ⅡⅡ 12.012.0 9.09.0 12.012.0 6.06.0 6.06.0 6.06.0 4.24.2 4.84.8 50.0-70.050.0-70.0

ⅢⅢ 8.08.0 6.06.0 8.08.0 4.04.0 4.04.0 4.04.0 2.82.8 3.23.2 30.0-50.030.0-50.0

ⅣⅣ 4.04.0 3.03.0 4.04.0 2.02.0 2.02.0 2.02.0 1.41.4 1.61.6 <30.0<30.0

Page 26: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

4.2.2 Verification on the method4.2.2 Verification on the method

In order to verify the index system In order to verify the index system and the grading scheme, a total of 12 and the grading scheme, a total of 12 test sites were selected randomly test sites were selected randomly from the study area and the field from the study area and the field check was carried out. The result check was carried out. The result was showed in Table 4. was showed in Table 4.

Table 4 Grasshopper habitat

assessment of the selected sites

Page 27: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

*Code*Code:: ASsASs (Steppe dominated by (Steppe dominated by Achnatherum splendensAchnatherum splendens); ); HCmHCm (High- (High-cold meadow); cold meadow); HCsmHCsm (High-cold shrub meadow); (High-cold shrub meadow); SKsSKs (Steppe domi. by (Steppe domi. by Stipa KryloviiStipa Krylovii); ); SPsSPs(Steppe domi. by (Steppe domi. by Stipa purpereaStipa purperea). ).

**GD--Grasshopper density (heads/ m2) observed in field.**GD--Grasshopper density (heads/ m2) observed in field.

Site Site No.No.

Habitat Habitat type*type*

Elements used for habitat assessmentElements used for habitat assessmentTotalTotal GD**GD** GradeGrade

FF11 F2F2 FF33 FF44 FF55 FF66 FF77 FF88

11 SKsSKs 1616 1212 1212 88 88 88 5.65.6 6.46.4 76.0476.04 5050 ⅠⅠ

22 SKsSKs 1616 1212 88 88 66 88 5.65.6 4.84.8 68.468.4 2323 ⅡⅡ

33 HCsmHCsm 44 33 44 44 22 22 2.82.8 1.61.6 23.323.3 66 ⅣⅣ

44 SKsSKs 1212 1212 44 88 44 88 5.65.6 4.84.8 58.458.4 1313 ⅡⅡ

55 SPsSPs 1212 99 1212 66 88 66 5.65.6 3.23.2 61.861.8 3535 ⅡⅡ

66 ASsASs 1616 1212 88 88 66 88 5.65.6 6.46.4 70.070.0 1616 ⅠⅠ

1111 HCmHCm 44 66 1212 22 66 22 2.82.8 1.61.6 36.436.4 44 ⅢⅢ

1313 SKsSKs 1616 1212 1212 88 88 88 5.65.6 6.46.4 76.076.0 5050 ⅠⅠ

3030 SPsSPs 1212 99 1212 66 88 66 5.65.6 3.23.2 61.861.8 3030 ⅡⅡ

3131 ASsASs 1616 1212 1616 88 88 88 5.65.6 6.46.4 80.080.0 3232 ⅠⅠ

3232 SPsSPs 1212 99 1616 66 88 66 5.65.6 4.84.8 67.467.4 5555 ⅡⅡ

3434 ASsASs 1616 1212 1212 88 66 88 5.65.6 4.84.8 72.472.4 3030 ⅠⅠ

Page 28: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

Table 4 shows that:Table 4 shows that:

1) In total 12 test sites, there are 8 1) In total 12 test sites, there are 8 sites which demonstrated a good sites which demonstrated a good relation between relation between grade value (grade value (FF)) calculated from the grading scheme calculated from the grading scheme and and grasshopper densitygrasshopper density observed observed in field. in field.

Page 29: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

2) Of the remaining 4 sites, there are 3 2) Of the remaining 4 sites, there are 3 sites (No. 4, 31 and 34) which have grassites (No. 4, 31 and 34) which have grasshopper density observed in field shopper density observed in field lowelower than the theoretical valuer than the theoretical value coming fr coming from the assessment.om the assessment.

Field check indicated that its major reaField check indicated that its major reason was that these sites experienced son was that these sites experienced cchemical sprayhemical spray for grasshopper contro for grasshopper control l just in the previous yearjust in the previous year. .

Page 30: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

3) Test site No.5 showed also 3) Test site No.5 showed also deviation deviation from the normal value, and its reason from the normal value, and its reason needs further investigated. needs further investigated.

From the results it can be concluded tFrom the results it can be concluded that the method for grasshopper habitahat the method for grasshopper habitat assessment is generally feasible. t assessment is generally feasible.

Page 31: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

5 CONCLUSION5 CONCLUSION From the research carried out in From the research carried out in

the Qinghai Lake region, China it the Qinghai Lake region, China it could be concluded:could be concluded:

The Satellite image data The Satellite image data assisted grasshopper habitat assisted grasshopper habitat classification and the approach classification and the approach of grasshopper habitat of grasshopper habitat assessment in terms of its assessment in terms of its occurrence probability is occurrence probability is valuable and quite feasible to valuable and quite feasible to grasshoppers control. grasshoppers control.

Page 32: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

ACKNOWLEDGEMENTSACKNOWLEDGEMENTS The author would like to express sincere thaThe author would like to express sincere tha

nks to Dr. J. J. Jiang, Dr. J. C. Wang, Dr. Y. Znks to Dr. J. J. Jiang, Dr. J. C. Wang, Dr. Y. Zha and Dr. Y. C. Wei at School of Geographic ha and Dr. Y. C. Wei at School of Geographic Science, Nanjing Normal University and Mr. Science, Nanjing Normal University and Mr. A. Q. Gong, Mr. S. H. Zhang and Mrs. W. J. A. Q. Gong, Mr. S. H. Zhang and Mrs. W. J. Wang at Qinghai Provincial General GrasslaWang at Qinghai Provincial General Grassland Station for their helps in the study.nd Station for their helps in the study.

Page 33: Shao Xiang NI ( Key Lab of Virtual Geographic Environment, School of Geographic Science,

END!END!