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Patterns of current and past biodiversity can be measured by the elements of the Dynamic Habitat Index (DHI) and this can help in the prediction of future patterns of biodiversity. DHI is an indirect indicator of biodiversity and can be obtained by using remote sensing technology. Further, annual greenness variations and wildlife richness can be represented by the DHIs. Regions with high cumulative DHI components tend to have elevated species richness, while areas with fluctuating DHI levels experience increased richness of threatened species, highlighting environmental impacts on biodiversity. In this study, we compute the DHI index by leveraging fPAR data from 2001 to 2015 across India. By integrating knowledge of Indian subcontinental terrestrial zones, in contrast to the index and employing trajectory analysis to evaluate changes over 15 years, this assessment offers insights into the potential implications for continental biodiversity amid fluctuating drought conditions. Results showed that the north-east zone, showed the highest (mean DHI cum < 9) and lowest value of mean DHI cum in the trans-Himalayan zone (mean DHI cum < 1.3). The high mean DHI cum shows the high vegetation productivity, high biodiversity, and high species richness in the north-east zone. Similarly, the lowest value shows very low vegetation productivity and biodiversity. The highest and lowest values of the mean DHI min (minimum annual cover) are in the north-east zone (mean DHI min < 0.6) and the trans-Himalayan zone (mean DHI min < 0.11). Similarly, the highest and lowest values of mean DHI sea (seasonal variation in greenness) are in the trans-Himalayan zone and the north-east zone. Further, to find the intermediate value of DHI indices, a relationship between year and DHI component was established, and results indicated that the value of the coefficient of correlation of DHI-cum varied between −0.88 and 0.97. Thus, this study suggests that these outcomes suggest that biodiversity and threatened species richness can be monitored by DHI based on remote sensing.

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Assessment of Biodiversity Pattern by Using Dynamic Habitat Indices from MODIS at Broad Scale Across India

  • 章节

  • 发表日期：

    2025年

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  • Priyankar Kumar

摘要

Patterns of current and past biodiversity can be measured by the elements of the Dynamic Habitat Index (DHI) and this can help in the prediction of future patterns of biodiversity. DHI is an indirect indicator of biodiversity and can be obtained by using remote sensing technology. Further, annual greenness variations and wildlife richness can be represented by the DHIs. Regions with high cumulative DHI components tend to have elevated species richness, while areas with fluctuating DHI levels experience increased richness of threatened species, highlighting environmental impacts on biodiversity. In this study, we compute the DHI index by leveraging fPAR data from 2001 to 2015 across India. By integrating knowledge of Indian subcontinental terrestrial zones, in contrast to the index and employing trajectory analysis to evaluate changes over 15 years, this assessment offers insights into the potential implications for continental biodiversity amid fluctuating drought conditions. Results showed that the north-east zone, showed the highest (mean DHI cum < 9) and lowest value of mean DHI cum in the trans-Himalayan zone (mean DHI cum < 1.3). The high mean DHI cum shows the high vegetation productivity, high biodiversity, and high species richness in the north-east zone. Similarly, the lowest value shows very low vegetation productivity and biodiversity. The highest and lowest values of the mean DHI min (minimum annual cover) are in the north-east zone (mean DHI min < 0.6) and the trans-Himalayan zone (mean DHI min < 0.11). Similarly, the highest and lowest values of mean DHI sea (seasonal variation in greenness) are in the trans-Himalayan zone and the north-east zone. Further, to find the intermediate value of DHI indices, a relationship between year and DHI component was established, and results indicated that the value of the coefficient of correlation of DHI-cum varied between −0.88 and 0.97. Thus, this study suggests that these outcomes suggest that biodiversity and threatened species richness can be monitored by DHI based on remote sensing.