fr1.t09.5 - gis and agro- geoinformatics applications

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FR1.T09.5 - GIS and Agro- Geoinformatics Applications. Feature Analysis of Groundwater Discharge Points in Coastal Regions around Mt. Chokaisan, Japan by Using ALOS PALSAR DATA. Yoichi KAGEYAMA, Hikaru SHIRAI, and Makoto NISHIDA. Department of Computer Science and Engineering, - PowerPoint PPT Presentation

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Feature Analysis of Groundwater Discharge Points in Coastal Regions around Mt. Chokaisan, Japan by Using ALOS PALSAR DATAFR1.T09.5 - GIS and Agro-Geoinformatics ApplicationsYoichi KAGEYAMA, Hikaru SHIRAI, and Makoto NISHIDA

Department of Computer Science and Engineering, Graduate School of Engineering and Resource Science, Akita University, JAPAN

12Table of Contents MotivationStudy areaData analysisResults and DiscussionSummary

Submarine groundwater dischargeRain or SnowGroundwater flowsmountainSeaSubmarine groundwater discharge

-A key role in linking land and sea water circulation

-Collecting water directly-Water quality, amount of discharge, and discharge location are quite different.

3

previously presented studyUse ALOS AVNIR-2 data

1Y. Kageyama, C. Shibata, and M. Nishida, Feature Analysis of Groundwater Discharge Points in Coastal Regions around Mt. Chokaisan by Using ALOS AVNIR-2 Data, IEEJ Trans. EIS, Vol.131, No.10 (in press) properties of the AVNIR-2 data acquired in different seasons were well able to retrieval the sea surface information1.spreading of the groundwater discharge4ALOS AVNIR-2 (Advances Visible and Near Infrared Radiometer type 2)are passive sensors- the data will be affected by clouds the limited data are available.

ALOS PALSAR (Phased Array type L-band Synthetic Aperture Radar) are active sensor - we use the data regardless of the weather conditions. Analyzes features of the groundwater discharge points in coastal regions by using the ALOS PALSAR data as well as the AVNIR-2 data use of textures calculated from co-occurrence matrix classification maps regarding the textures were obtained with k-means. comparison the PALSAR classification maps with the AVNIR-2 ones.Purpose56Table of Contents MotivationData used and study areaData analysisResults and DiscussionSummary

Coastal region in Japan SeaAround the Mt.Chokaisan

Groundwater discharge at Kamaiso(Aug. 3, 2010)Study area

Well known as the origin of Crassostrea nipponaGroundwater discharge can affect the Its growth

7ALOS PALSAR dataWinter data(Jan. 30, 2010)

Autumn data(Oct. 7, 2009)

ALOS AVNIR-2Autumn data(Sep. 20, 2009)Winter data(Feb. 25, 2010)(R,G,B:band3,2,1)Band 10.420.50 blueBand 30.610.69 redBand 20.520.60 green Band 40.760.89 NIR(m)1270 MHz(L-band)8

Survey pointsKisakata beach(2 points)Fukuden(3points)Kosagawa beach(3points)Kosagawa fishing port (1point)Misaki(3points)Kamaiso(1point)Gakko River(2points)Ground surveyDate: Aug 3, 20109Comparison of sea and spring water in each water qualitySea waterSpring waterpH8.097.37Dissolved oxygen6.85mg/L10.2mg/LElectric conductivity4.21S/m0.002S/mSalinity27.6%0%Total Dissolved Solids45.6g/L0.1g/LSea water specific gravity1.023sg1.002sgWater temperature26.013.3Turbidity7.78NTU5.05NTU

:Sea Water:Spring water:Sea and spring water1011Table of Contents MotivationData used and study areaData analysisResults and DiscussionSummary

Preprosessing-Geometric correction-MaskingGrayscale conversion-16,32,64,128,256,512 For PALSAR dataTextures computed from co-occurrence matrixk-means algorithm to create the resulting classification- second order conformal transformation cubic convolution average RMS error was 0.41

Winter data(Jan. 30, 2010)Autumn data(Oct. 7, 2009)Geometric correction

12Preprosessing-Geometric correction-MaskingGrayscale conversion-16,32,64,128,256,512 Textures computed from co-occurrence matrixk-means algorithm to create the resulting classification

Masked imagesMaskingLand area-Various DNs-DNs are larger A hydrology experts commentjudged from the scale of Mt. Chokaisan,the submarine groundwater discharge exist ranging from land regions to 500 meters offing. 500mFor PALSAR data13Preprosessing-Geometric correction-MaskingGrayscale conversion-16,32,64,128,256,512 Textures computed from co-occurrence matrixk-means algorithm to create the resulting classification-Noise reductionPALSAR data (2bytes)16,32,64,128,256,512gray levels

163264128256

512For PALSAR dataGrayscale conversion

14Preprosessing-Geometric correction-MaskingGrayscale conversion-16,32,64,128,256,512 Textures computed from co-occurrence matrixk-means algorithm to create the resulting classificationTextures computed from co-occurrence matrix

Eight features-Mean, -Entropy, -Second moment, -Variance,Contrast, Homogeneity, Dissimilarity, Correspond

e.g., meanAverage the DNs of points around

For PALSAR data15Preprosessing-Geometric correction-MaskingGrayscale conversion-16,32,64,128,256,512 Textures computed from co-occurrence matrixk-means algorithm to create the resulting classificationk-meansFor PALSAR dataThe processing was ended: -the number of the maximum repetition amounted to 100 times,-moved pixels between clusters became 5% or less of the whole pixels.

k was set from 2 to 20.

1617Table of Contents MotivationData used and study areaData analysisResults and DiscussionSummary

33775599Filter size (e.g., mean)(a)mean(d)variance(b)entropy(c)second moment

Select of feature(f)homogeneity(e)contrast(g)dissimilarity(h)correlation

Select of feature(16 gray levels; mean; K=7)Autumn PALSAR resultsair18.7Wea waterAbout 21Spring waterAbout 10.51http://www.jma.go.jp/jp/amedas/Weather information during the data acquisition1large difference of temperature between spring water and air

The red clusters exist in Kosagawa, Misaki, Kamaiso.The green and blue clusters are also formeda spread of spring water.

8.2 21Autumn and winter PLASAR resultsIn kosagawa, Amount of submarine groundwater discharge has been reduced in January to March.

Autumn data(16 gray levels; mean; K=7)

Winter data(16 gray levels; mean; K=7)the red clusters are decreasing in winter 22Autumn data

Winter dataAutumn dataWinter dataair18.72.4Sea waterAbout 21About 12Spring waterAbout 10.5About 10.51http://www.jma.go.jp/jp/amedas/Weather information at the data acquisition1the difference of temperature between Sea and spring water in the winter data is smaller.Autumn and winter PLASAR results(16 gray levels; mean; K=7)10.5 1.5 23PLASAR and AVNIR-2 results in Autumn

AVNIR-2 data(band1,2,3; k=7)

The red clusters exist in Kosagawa, Misaki, and Kamaiso as well as the PALSAR classification results.PALSAR data(16 gray levels; mean; K=7)24PLASAR and AVNIR-2 results in WinterAVNIR-2 data(band1,2,3;k=7)Compared with the autumn data, the cluster of red is reduced

PALSAR data(16 gray levels, mean, K=7)

The conditions consistent with a decrease in the amount of submarine groundwater discharge in winter25SummaryThis study has analyzed the features regarding the groundwater discharge points in the coastal regions around Mt. Chokaisan, Japan. -The experimental results suggest that the Mean obtained from the co-occurrence matrix was good in extraction of the features of the groundwater discharge points from the ALOS PALSAR data. -The ALOS PALSAR data has the possibility of extracting the groundwater discharge points in the study area. -The k-means clustering results in the PALSAR and AVNIR-2 data agreed with the findings acquired by the ground survey.

26Thank you for your attention!