Spatio-temporal analysis of vegetation dynamics for Saurashtra region of Gujarat

Dhanapriya, M; Kumaraperumal, R.; Kannan, Balaji; Bhatt, Hiren

doi:10.5958/2454-8634.2018.00019.0

Cited by 4 publications

(7 citation statements)

References 0 publications

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“…The NDVI and EVI registered lower values in the year of 2016 when compared to other years as there was a drought occurring in the study area region (Figs.6 & 7).Lower NDVI and EVI were observed in crop land than the other classes which address the sensitivity of indices towards the type of plant species/crops cultivated. These results were corroborated with Hussein et al (2017) andDhanapriya et al (2018). The NDVI showed no variation within the years during the study period except for the years 2011 and 2012.…”

supporting

confidence: 91%

“…Similar study is also conducted by many researchers to comprehend the present condition of land use types. (Dhanapriya et al, 2018, Arulbalaji, 2019, Prajesh et al, 2019and Butt et al, 2015. NDVI and EVI vegetation pro le analysis MODIS (MOD13Q1) satellite data products i.e., NDVI and EVI were available in 16-day composite and processed for a better understanding of vegetation dynamics of Tamil Nadu for the period of 11 years.…”

Section: Land Use and Land Cover Mapmentioning

confidence: 99%

“…By investigating the deviations in the remote sensing data, phenological changes can be studied throughout the crop growth period (Dhanapriya et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Monitoring vegetation dynamics using multi-temporal NDVI and EVI images for different agro climatic zones of Tamil Nadu

Priya

Kalpana

Pazhanivelan

et al. 2023

Preprint

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Vegetation indices serves as an essential tool in monitoring variations in vegetation. The vegetation indices used often viz., normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were computed from MODIS vegetation index products. These two products characterize the global range of vegetation states and processes more effectively. This study is investigated to monitor the seasonal dynamics of vegetation by using time series NDVI and EVI indices, throughout the various agro climatic zones present in the Tamil Nadu from 2011 to 2021. Utilising the MOD13Q1 data product to procure the vegetation indices viz., NDVI and EVI for the years 2011 to 2021. The data sources were processed and extracted the NDVI and EVI values using ArcGIS software. There was a significant difference in vegetation intensity and status of vegetation over time, with NDVI having a larger value than EVI, indicating that biomass intensity varies over time in Tamil Nadu. Among the deciduous forest, crop land and scrub/ degraded forest, the deciduous forest showed highest mean values for NDVI and EVI. The study showed that vegetation indices extracted from MODIS offered the valuable information on vegetation status and condition at a short temporal time period.

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supporting

confidence: 91%

Section: Land Use and Land Cover Mapmentioning

confidence: 99%

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Monitoring vegetation dynamics using multi-temporal NDVI and EVI images for different agro climatic zones of Tamil Nadu

Priya

Kalpana

Pazhanivelan

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The findings reported that a higher NDVI value was recorded in the semi-arid region than in the EVI. Similarly, higher and lower NDVI and EVI values were recorded in North and South American forest biomes (Huete et al, 2002) and also in the Saurashtra region of Gujarat (Dhanapriya et al, 2018), respectively. There was a variation in NDVI and EVI profiles for cropland due to the different sowing times practised in different parts of the study area region and the weather parameters' sensitivity.…”

Section: Ndvi and Evi Profile Based On Land Usementioning

confidence: 76%

“…Presently, remote sensing data is used to recognize and characterize the variations in vegetation status over time. By investigating the remote sensing data deviations, phenological changes can be studied throughout the crop growth period (Dhanapriya et al, 2018). Vegetation indices act as an important role in monitoring variations in the crop and forest vegetation, thereby strengthening the capacity to predict, mitigate, as well as adapt towards the changes in vegetation.…”

Section: Introductionmentioning

confidence: 99%

Monitoring vegetation dynamics using multi-temporal Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images of Tamil Nadu

Priya,

Kalpana,

Pazhanivelan

et al. 2023

JANS

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Vegetation indices serve as an essential tool in monitoring variations in vegetation. The vegetation indices used often, viz., normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were computed from MODIS vegetation index products. The present study aimed to monitor vegetation's seasonal dynamics by using time series NDVI and EVI indices in Tamil Nadu from 2011 to 2021. Two products characterize the global range of vegetation states and processes more effectively. The data sources were processed and the values of NDVI and EVI were extracted using ArcGIS software. There was a significant difference in vegetation intensity and status of vegetation over time, with NDVI having a larger value than EVI, indicating that biomass intensity varies over time in Tamil Nadu. Among the land cover classes, the deciduous forest showed the highest mean values for NDVI (0.83) and EVI (0.38), followed by cropland mean values of NDVI (0.71) and EVI (0.31) and the lowest NDVI (0.68) and EVI (0.29) was recorded in the scrubland. The study demonstrated that vegetation indices extracted from MODIS offered valuable information on vegetation status and condition at a short temporal time period.

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Analysis of Terrestrial Vegetation Trends and Correlation Between Vegetation Indices and Climatic Factors

Dhanapriya

Bhatt

Vyas

2022

Research Anthology on Ecosystem Conservation and Preserving Biodiversity

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The chapter analyzes terrestrial vegetation trends and correlation of vegetation indices with climatic factors like LST, Net Radiation, and TRMM. The result shows the positive vegetation trend might be due to the increased vegetation growth and productivity. Negative vegetation trend might be due to changes in a crop choice. Correlation of vegetation indices with climatic factors like LST showed weak to moderate positive correlation. Net radiation showed moderate negative correlation and TRMM showed a weak negative or positive correlation for both the Kharif and Rabi seasons.

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Spatio-temporal analysis of vegetation dynamics for Saurashtra region of Gujarat

Cited by 4 publications

References 0 publications

Monitoring vegetation dynamics using multi-temporal NDVI and EVI images for different agro climatic zones of Tamil Nadu

Monitoring vegetation dynamics using multi-temporal NDVI and EVI images for different agro climatic zones of Tamil Nadu

Monitoring vegetation dynamics using multi-temporal Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images of Tamil Nadu

Analysis of Terrestrial Vegetation Trends and Correlation Between Vegetation Indices and Climatic Factors

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