Rakibul Hasan Chowdhury

Application of Remote Sensing and GIS for Drought Monitoring in the Khulna Region of Bangladesh. Presented by Rakibul Hasan Chowdhury ID: ASH-M Session:- 1 Introduction: Background of the Study Drought Drought is the most common natural disaster which refer to the dryness off soil and it occur fall of normal precipitation or absence of water supply Global Aspect WHO report that 55 million people are affect drought every year and recent decade their impact rate rise rapidly Bangladesh Aspect Bangladesh had faced economic loss of 500 million dollars and production loss of 42% of Aman paddy rice due to drought Mitigation Understanding drought causes is key to mitigating its effects and ensuring sustainable water management. 3 Working process 3.1 Analytical Area • Region: Khulna Division, Bangladesh • Located between 21°60' - 24°13' N and 88°34' - 89°58' E. • Area: 22,284.22 sq. km. • South site-Sundarban, west site-west Bangla(india), north site-Rajshahi 8 Data Sources No 1 Dataset Landsat 5 and Landsat 8 Product Resolution used Spatial Temporal NDVI 30 m 16 days Dataset Provider NASA LP DAAC at the USGS EROS Center 2 Landsat 5 and Landsat 8 LST 30 m 8 days NASA LP DAAC at the USGS EROS Center 3 PML-V2 ET 1000m Monthly PML_V2 4 CHIRPS Void data 0.50 Monthly UCSB/CHG fill 5 USGS NED (National Elevation Void data Dataset) fill 30m USGS Earth Explorer 9 Workflow 10 Data Analysis E = 0.004 × 𝑃𝑣 + 0.986 Determination of VCI 𝑁𝐷𝑉𝐼 = 𝑉𝐶𝐼 = 𝐿𝑆𝑇 = 𝑁𝐼𝑅 − 𝑅𝐸𝐷 𝑁𝐼𝑅 + 𝑅𝐸𝐷 𝑁𝐷𝑉𝐼 − 𝑁𝐷𝑉𝐼𝑚𝑖𝑛 × 100 𝑁𝐷𝑉𝐼𝑚𝑎𝑥 − 𝑁𝐷𝑉𝐼𝑚𝑖𝑛 𝑇𝐵 ʎ𝑇𝐵 1+ × 𝑙𝑛 ε 𝜌 𝑇𝐶𝐼 = 𝐿𝑆𝑇 max − 𝐿𝑆𝑇 𝐿𝑆𝑇 max − 𝐿𝑆𝑇 min Determination of TCI Were, 𝐿ʎ = 𝐺𝑎𝑖𝑛 × 𝐷𝑁 + 𝐵𝑖𝑎𝑠 𝑇𝐵 = 𝐾2 𝐾 ln 1 + 1 𝐿ʎ • 𝐾1 = 500 𝐾2 =1068 • λ : Wavelength of emitted radiance • 𝜌 = 1.438×10-2 m/cdotpK • 2 𝑁𝐷𝑉𝐼 − 𝑁𝐷𝑉𝐼𝑚𝑖𝑛 𝑃𝑣 = ቌ ቇ 𝑁𝐷𝑉𝐼𝑚𝑎𝑥 − 𝑁𝐷𝑉𝐼𝑚𝑖𝑛 Data Analysis Determination of VHI Determination of Moran I 𝐼= 𝑉𝐻𝐼 = 𝜎 × 𝑉𝐶𝐼 + 1 − 𝛼 𝑇𝐶𝐼 Determination of SPEI 𝑊𝐵 = 𝑃 − 𝐸𝑇 𝑁 σ𝑖𝑗 𝑊𝑖𝑗 𝑋𝑖 − 𝑋 𝑋𝑗 − 𝑋 𝑆0 σ𝑖 𝑋𝑖 − 𝑋 2 Were, N =Number of observations Xi, Xj = Values at locations i and j Input in R SPEI Value 𝑋 = Mean of the values Wij =​Spatial weight between i and j S0 = Sum of all spatial weights IDW map in GIS Result Analysis: VCI,TCI and VHI TCI Maps TCI Map Maps 2025 VHI Maps 2024 2010 12 Result Analysis: Trend of VCI, TCI and VHI VCI Over Years TCI Over Years VHI Over Years 13 Result Analysis: Coverage Area of VCI, TCI and VHI VCI Coverage Area Coverage area 80 R² = 0.7271 TCI Coverage Area 90.00% 70 80.00% 60 70.00% 90 R² = 0.8699 50.00% 50 40.00% 40 30.00% 20 30 20.00% 10 20 10.00% 0 10 0.00%- R² = 0.5609 60 40 30 80 70 60.00% 50 VHI Coverage Area - - 14 Result Analysis: SPEI and their condition SPEI Condition In Given years 2010 1 0.5 - SPEI 0 -0.5 -1 -1.5 -2 spei_2000 spei_2006 spei_2010 spei_2024 15 Drought Trend 16 Result Analysis: Moran I Analysis Year P Value Z score Moran Index 2000 0.0000 - - 2006 0.0000 - - 2010 00000 - - 2016 0.0000 - - 2020 0.0000 - - 2022 0.0000 - - 2024 0.0000 - - 17 Result Analysis : Correlation between Various Parameters 18 Discussion • Decreasing Vegetation Health - VCI, TCI, and VHI show a declining trend, indicating increasing drought severity over time. • Regional Hotspots of Drought -Southern districts (Bagerhat, Khulna, Satkhira) show persistent low VCI/VHI, indicating prolonged vegetation stress due to climate and land use changes. • Spatial & Temporal Patterns VCI (0.8; p < 0.001) and TCI reveal non-random, clustered drought impacts, mainly in central and southern Khulna. • Comprehensive Drought Assessment -Integrated use of multi-index (NDVI, LST), spatial modeling, and trend analysis effectively reveals drought evolution and drivers. 19 References • Alito, K. T., & Kerebih, M. S. (2024). Spatio-temporal assessment of agricultural drought using remote sensing and ground-based data indices in the Northern Ethiopian Highland. Journal of Hydrology: Regional Studies, 52, 101700. https://doi.org/10.1016/j.ejrh- • Bento, V. A., Gouveia, C. M., DaCamara, C. C., & Trigo, I. F. (2018). A climatological assessment of drought impact on vegetation health index. Agricultural and Forest Meteorology, 259, 286–295. https://doi.org/10.1016/j.agrformet- • Burka, A., Biazin, B., & Bewket, W. (2024). Spatial drought occurrences and distribution using VCI, TCI, VHI, and Google Earth Engine in Bilate River Watershed, Rift Valley of Ethiopia. Geomatics, Natural Hazards and Risk, 15(1),-. https://doi.org/10.1080/- Thank you 22