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Yuh-Lurng Chung, Chaur-Tzuhn Chen Chen-Ni Hsi , Shih-Ming Liu 2004.11.04

Study on applying MODIS image into drought indicator analysis in Taiwan. Yuh-Lurng Chung, Chaur-Tzuhn Chen Chen-Ni Hsi , Shih-Ming Liu 2004.11.04. Introduction.

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Yuh-Lurng Chung, Chaur-Tzuhn Chen Chen-Ni Hsi , Shih-Ming Liu 2004.11.04

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  1. Study on applying MODIS image into drought indicator analysis in Taiwan Yuh-Lurng Chung, Chaur-Tzuhn Chen Chen-Ni Hsi , Shih-Ming Liu 2004.11.04

  2. Introduction When drought occurs, due to insufficient water supply, the variation/change of leaves in aridity can be sensed by spectral reflection of multi-temporal satellites.

  3. Overseas researches of employing satellite images to efficiently forecast and manage drought has achieved great outcomes.

  4. This research employ MODIS images to select sensitive thermal bandssuitable for monitoring drought. And by using bands for the calculation of all kinds of vegetation indices, it is expected to find proper and practical indices for drought monitoring, which could be used for future management and determination of drought disaster. Introduction

  5. Using bands for the calculation of all kinds of vegetation indices, it is expected to find proper and practical indices for drought monitoring, which could be used for future management and determination of drought disaster.

  6. Research Data/Information and Methodology 1. StudyArea Include whole Taiwan area of 19 districts. 2. Required Data/Information • Precipitation Data Information concerned includes the records of all rainfall stationsfrom the January of 1991 to the March of 2004 in the entire Taiwan area.

  7. Locations of All Taiwan Rainfall Stations Legend Boundary Rainfall station

  8. MODIS Images Thermal Bands of MODIS Image Seven MODIS Bands for Monitoring Earth’s Surface * A:atmospheric studies, L:land studies, O:oceanstudies

  9. By utilizing the information of surface regression through Kriging Model, our approach then can get drought indicator and drought amount of this area. Two images of the dry season (January 25, 2004) and wet season (June 30, 2004) are accordingly chosen for further analysis.

  10. Research Methodology Data from rainfall stations Select clear MODIS images without cloud Rainfall of continuous 30 days Threshold of Each County and City Preprocessing of MODIS images Cumulative rainfall of all Locate sample grassland areas NO Drought Amount>130mm Use MODIS images of dry and wet seasons to select thermal bands for drought monitor YES Calculate all indices& select some for preliminary analysis Climate Drought Indices Specify Ranges of Dry and Wet Seasons Using Climate Drought Indices Choose index for drought

  11. Discussions on Applying Drought Indices to Drought Monitor • Normalized Thermal Index(NTI) • Normalized Difference Vegetation Index (NDVI)

  12. Normalized Difference Water Index (NDWI) • Shortwave Infrared Water Stress Index (SIWSI)

  13. Results and Discussion Characteristics of Taiwan Rainfall Data Based on the rainfall data of 355 rainfall stations from 1992 to 2003, clearly shows different standards (levels) of different places in different periods. It also indicates the relativity of drought definition due to spatial and temporal factors.

  14. Precipitation within 30 consecutive days recorded by rainfall stations in each county in whole Taiwan Province Taipei Taoyuan Hsinchu Miaoli Taichung Janghua Nantou Yunlin Yilan Hualien Taitung Chiayi Tainan Kaohsiung January March May July September November Month Historical Curves of the first decile values of Cumulative

  15. Application of MODIS Images to Select Thermal Bands for Drought Monitor MODIS Images After Geometric Correction Original MODIS Image

  16. Extraction of Sample Sites of Grasslands From land-use maps we query all natural grasslands from the databaseof ArcGIS. And afterremoving thosesample cloud hovering, we mark those sample sites on the extracted images of natural grasslands without cloud covered. Legend Sample Boundary

  17. Select Thermal Bands of MODIS images for Drought Monitor Extractsdata for the seven MODIS bands, and compares the seven bands of dry season and wet season to find out what are the real differences.

  18. Differences of Thermal Infrared Band Values of MODIS Images of Grasslands in Dry and Wet Seasons Differences of Mean Thermal Infrared Bands of Taiwan Grasslands MODIS Images in Dry and Wet Seasons

  19. Number of Pixels Number of Pixels STD = STD Mean= Mean NTI NTI The Calculation of Normalized Thermal Index (NTI) The research done by Robert et al. (2002) about monitoring volcano indicates that NTI value are ranged between -0.850 ~ -0.950 due to the high surface temperature of the volcanic region. NTI Image and Histogram In Dry Season NTI Image and Histogram In Wet Season

  20. Statistics of NTI Values of MODIS Images in Dry and Wet Season, and T-test Note: T-test with confidence interval 5%

  21. Number of Pixels Number of Pixels STD= STD= Mean= Mean= NDVI NDVI The Calculation of Normalized Difference Vegetation Index (NDVI) MODIS NDVI Images in Dry Season MODIS NDVI Images in Wet Season

  22. Dry NDVI Wet NDVI Sample NDVI Differences of MODIS Grassland Images in Dry and Wet Seasons Statistics of NDVI Values of MODIS Images in Dry and Wet Season, and T-test

  23. Number of Pixels Number of Pixels STD STD Mean Mean NDWI NDWI The Calculation of Normalized Difference Water Index (NDWI) MODIS NDWI Images in Dry Season MODIS NDWI Images in Wet Season

  24. Dry NDWI Wet NDWI Sample Difference of MODIS NDWI Images of Grasslands in Dry and Wet Seasons Statistics of NDWI Values of MODIS Images in Dry and Wet Seasons, and T-test

  25. Difference Between NDVI and NDWI of MODIS Images of Grasslands in Dry and Wet Seasons

  26. Correlation Matrix Between NDVI and NDWI in DS and WS **: Distinct Correlation as distinction level if 0.01(**). DS: Dry Season WS: Wet Season

  27. Number of Pixels Number of Pixels SIWSI STD Mean Mean SIWSI Calculation of Shortwave Infrared Water Index (SIWSI) MODIS SIWSI Images of Taiwan in Dry Season MODIS SIWSI Image of Taiwan in Wet Season

  28. SIWSI Differences for Sample Sites of Grasslands in Dry and Wet Seasons, based on MODIS Images Statistics and T-test Table of SIWSI Values of grasslands in Dry and Wet Seasons (MODIS Images)

  29. Conclusion This research indicates MODIS images with 36 bands have substantial potential in drought sensing. It is hereby possible to replace the NOAA-AVHRR satellite images with MODIS images, for more precise image data/information.

  30. The MODIS Band 22 at the spatial resolution of 1,000 m is the most sensitive thermal bands to drought. And the NTI is the unique index of sensing thermal energy only available in MODIS images. Furthermore, this research hence utilizes the important wave bands which are chosen from the Band 22 to calculate NTI.

  31. We can conclude that the NDVI, NDWI and NTI are sensitive to the monitoring of surface vegetation status, water content of vegetation and surface temperature respectively. As a result, they hereby have practical usages for drought forecast and monitoring.

  32. The End

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