Authors

Tran Thi Thanh Dung 1* , Duong Thi Thuy Nga 1*

Affiliations

1 Ho Chi Minh City University of Science, Vietnam National University Ho Chi Minh City

*Corresponding author: trttdung@hcmus.edu.vn; dttnga@hcmus.edu.vn

Abstracts

Drought is a constant threat to Vietnam which causes great damage to the economy as well as forest ecosystems. Due to the increasingly complex drought-related impacts, remote sensing technology with outstanding advantages compared to traditional research methods has been applied effectively in research, monitoring, and coping with drought. Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) were calculated from Landsat imagery. The Temperature Vegetation Dryness Index (TVDI) with the combination of LST and NDVI index, was used as an indicator for drought risk assessment in Cu Chi District in 2005, 2010, 2015, and 2020. The results show a significant increase in dry areas between 2005-2010 and 2015-2020. On the other hand, the results of the TVDI index and mapping drought of Cu Chi district on February 13, 2005, February 11, 2010, January 24, 2015 and February 23, 2020 are a basis for risk assessment and drought monitoring.

Keywords

TVDI , Landsat 8 , Drought , Cu Chi District

Cite this paper

Tran Thị Thanh Dung, Duong Thi Thuy Nga (2020), Applying TVDI based on remote sensing data to evaluate the drought in Cu Chi District. Vietnam Journal of Hydrometeorology, 4, 41-52. 

References

1. Asian Development Bank 6 ADB Avenue, 2010. Mandaluyong City 1550 Metro Manila, Philippines, RPT10280. Available online: www.adb.org.

2. Avdan, U., Jovanovska, G., 2016. Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data. Journal of Sensors, 2016:1-8. Doi: https://doi.org/10.1155/2016/1480307.

3. Ayad, M., Fadhil, A.Q., Qader, S.H., Wu, W., 2020. Drought Monitoring Using Spectral and Meteorological Based Indices Combination: A Case Study in Sulaimaniyah, Kurdistan Region of Iraq.  In: Ayad M. Fadhil Al-Quraishi Abdelazim M. Negm (editors). Environmental Remote Sensing and GIS in Iraq. Springer Water, 377-393. Doi: https://doi.org/10.1007/978-3-030-21344-2.

4. Bao, Y., Gama, G., Gang, B., Yongmei, Alatengtuya, Yinshan and Husiletu, 2013. Monitoring of drought disaster in Xilin Guole grassland using TVDI model. Taylor & Francis group, London, pp. 299-310.

5. Belal, A.A., El-Ramady, H.R., Mohamed, E.S., Saleh, A.M., 2012. Drought risk assessment using remote sensing and GIS techniques. Arabian Journal of Geosciences, 7: 35-53. Doi: https://doi.org/10.1007/s12517-012-0707-2

6. Carlson, T.N., Gillies, R.R., Perry, E.M., 1994. A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover. Remote Sensing Reviews, 9(1):161-173. Doi: https://doi.org/10.1080/02757259409532220.

7. Carlson, T.N., Ripley, D.A., 1997. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62(3): 241-252.

8. Department of the Interior U.S. Geological Survey (USGS), 2015. Landsat 8 (L8) Data User’s Handbook. Version 1

9. Gao, Z.Q., Gao, W., Chang, N.B., 2011. Integrating temperature vegetation dryness index (TVDI) and regional water stress index (RWSI) for drought assessment with the aid of LANDSAT TM/ETM+ images. International Journal of Applied Earth Observation and Geoinformation, 13(3): 495-503. Doi: https://doi.org/10.1016/j.jag.2010.10.005

10. Hien, L.T.T., 2013. Application of the normalized difference vegetation index of Landsat imagery to assess the desertification in Binh Thuan Province. Vietnam Journal of Earth Sciences, 35(4): 357-363.

11. Huang, L., Guan, Q., Dong, Y., Zhang, D., Huang, W., Liang, D., 2011. Using Temperature Vegetation Drought Index for Monitoring Drought Based on Remote Sensing Data. Advanced Materials Research, 356-360 (2012): 2854-2859. Doi: https://doi.org/10.4028/www.scientific.net/AMR.356-360.2854.

12. Hung, T.L., 2014. Studies of land surface temperature distribution using multispectral image Landsat. Vietnam Journal of Earth sciences 36(1): 82-89

13. Kogan, F.N., 1990. Remote sensing of weather impacts on vegetation in non-homogeneous areas.  International Journal of Remote Sensing, 11(8): 1405-1419.

 14. Kogan, F.N., 1995. Droughts of the late 1980s in the United States as derived from NOAA polar-orbiting satellite data. Bulletin of the American Meteorological, 76(5): 655-668.

15. Liu, L., Liao, J., Chen, X., Zhou, G., Su, Y., Xiang, Z., Wang, Z., Liu, X., Li, Y., Wu, J., Xiong, X., Shao, H., 2017. The Microwave Temperature Vegetation Drought Index (MTVDI) based on AMSR-E brightness temperatures for long-term drought assessment across China (2003–2010). Remote Sensing of Environment, 199: 302-320. Doi: https://doi.org/10.1016/j.rse.2017.07.012.

16. Yuan, L., Heping, T., Hua, W., 2007. Dynamic drought monitoring in Guangxi using revised temperature vegetation dryness index. Wuhan University Journal of Natural sciences, 12(4): 663-668.

17. Moran, M.S., Clarke, T.R., Inoue, Y., Vidal, A., 1994. Estimating crop water deficit using the relation between surface–Air temperature and spectral vegetation index. Remote Sensing of Environment, 49(3): 246-263. Doi: https://doi.org/10.1016/0034-4257(94)90020-5

18. Myneni, R.B., Hall, F.G., Sellers, P.J., Marshak, A.L.,1995. The Interpretation of Spectral Vegetation Indexes. IEEE Transactions on Geoscience and Remote Sensing, 33(2): 481-486. Doi:  https://doi.org/10.1109/TGRS.1995.8746029

19. NASA Earth Observatory, 2013. Available online: http://earthobservatory.nasa.gov/Features/MeasuringVegetation/measuring_vegetation_3.php.

20. National Aeronautics and Space Administration (NASA), 2001. Landsat 7 Science Data User’s Handbook.

21. Orhan, O., Ekercin, S., Dadaser-Celik, F., 2014. Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey. The Scientific World Journal, 2014, Article ID 142939, pp. 11. Doi: https://doi.org/10.1155/2014/142939.

22. People’s Committee of Ho Chi Minh City, Viet Nam (2012). Decision No. 05/2012 / QD-UBND dated February 3, 2012 of the People's Committee of Ho Chi Minh City approving the Project on afforestation and greenery of the city in the period of 2011-2015, http://www.congbao.hochiminhcity.gov.vn/cong-bao/van-ban/quyet-dinh/so/05-2012-qd-ubnd/ngay/03-02-2012/noi-dung/31922/32724.

23. Prasad, A.K., Singh, R.P., Tare, V., Kafatos, M., 2007. Use of vegetation index and meteorological index for the prediction of crop yield in India. International Journal of Remote Sensing, 28(23): 5207-5235. Doi: https://doi.org/10.1080/01431160601105843.

24. Price, J.C., 1990. Using spatial context in satellite data to infer regional scale evapotranspiration. IEEE Transactions on Geoscience and Remote Sensing, 28(5): 940-948.

25. Rulinda, C.M., Bijker, W., Stein, A., 2010. Image mining for drought monitoring in Eastern Africa using Meteosat SERVIRI data. International Journal of Applied Earth Observation and Geoinformation, 12(1): S63-S68.

26. Sandholt, I., Rasmussen, K., Andersen, J., 2002. A simple interpretation of the surface temperature/ vegetation index space for assessment of surface moisture status. Journal of Remote Sensing of Environment, 79: 213-224.

27. Sobrino, J.A., Jimenez-Munoz, J.C., Paolini, L., 2004. Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment, 90(4): 434-440.

28. Son, N.T., Chen, C.F., Chen, C.R., Chang, L.Y., Minh, V.Q., 2012. Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data. International Journal of Applied Earth Observation and Geoinformation, 18: 417-427.

29. Snyder, W.C., Wan, Z., Zhang, Y., Feng, Y.Z., 1998. Classification based emissivity for land surface temperature measurement from space. International Journal of Remote Sensing, 19(14): 2753-2774.

30. Tao, J., Zhongfa, Z., Shui, C., 2011. Drought monitoring and analysing on typical Karst ecological fragile area based on GIS. Procedia Environmental Sciences, 10: 2091-2096.

31. Tucker, C.J., 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8 (2), 127-150.

32. Thuan, N.D., Giang, N.Q., 2018. Assessment of the Occurrence of Drought in Luc Ngan District, Bac Giang Province Using Remote Sensing Technology. Vietnam Journal of Agricultural Sciences,16(9): 820-829.

33. Valor, E., Caselles, V., 1996. Mapping land surface emissivity from NDVI. Application to European African and South American areas. Remote sensing of Environment, 57(3): 167-184.

34. Van, T.T., Lan, H.T., Trung, L.V., 2009. Study on determination of urban surface temperature by thermal remote sensing method. Vietnam Journal of Earth Sciences, 31(2): 168-177.

35. Wang, C., Qi, S., Niu, Z., Wang, J., 2004. Evaluating soil moisture status in China using the temperature vegetation dryness index (TVDI). Canadian Journal of Remote Sensing, 30(5): 671-679. Doi: https://doi.org/10.5589/m04-029.

36. Wang, P.X., Li, X.W., Gong, J.Y., Song, G.H., 2001. Vegetation temperature condition index and its application for drought monitoring. Proceedings of International Geoscience and Remote Sensing Symposium, Sydney, Australia, 9-14 July 2001, pp. 141-143.

37. Wardlow, B.D., Anderson, C.M., Verdin, J.P., 2012. Remote Sensing of Drought: Innovative Monitoring Approaches. CRC Press, First Eds.: pp. 484.

38. Xu, H.Q., Chen, B.Q., 2004. Remote sensing of the urban heat island and its changes in Xiamen City of SE China. Journal of Environmental Sciences, 16(2): 276-281.