This study examines vegetation indices in arid savannas and mangroves, using MODIS-MYD13Q1 data for Botswana, South Africa, and Henry’s Island, India. Seasonal variations and the contributions of Mangrove Forest Index-MFI and Mangrove Vegetation Index-MVI in understanding mangrove dynamics through K-means clustering of MFI data are showcased. Challenges in mangrove analysis are addressed despite the Normalized Difference Vegetation Index-NDVI’s effective tracking of arid vegetation changes. The study highlights MVI and MFI’s solutions for evaluating mangrove environments. K-means clustering efficiently categorize MVI data into winter and summer periods, revealing distinct clusters for long-term trends and seasonal peaks in mangrove dynamics. Though NDVI is good for arid vegetation it is inadequate in the analysis of mangrove forests. Therefore MVI and MFI prove better here. NDVI suits arid regions, while MFI and MVI excel for mangrove assessments. Seasonal variations in mangroves are tracked through peak MFI values in different seasons. MVI values indicate seasonal dynamics, and In Botswana, NDVI tendencies decrease with variations in rainfall, but MFI shows a positive slope, peaking in spring and summer and decreasing in autumn and winter. NDVI’s effectiveness in arid regions contrasts with the optimal performance of MFI and MVI in assessing mangroves. Categorizing mangroves into five types, seasonal variations are tracked through maximum MFI values in Winter (0.23), Summer (0.27), and Monsoon (0.58) over three years, while MVI values vary: 4.18 in Summer, 7.14 in Monsoon, and 4.15 in Winter. While MFI trends indicate a positive slope, increasing in spring/summer and declining in autumn/winter, NDVI trends show a reduction over time, peaking during Botswana’s rainy season and dropping noticeably in 2015 and 2016. Mangrove penology-based studies recently uses various approaches to understand and map patterns of the specific species.