Javascript must be enabled to continue!
Monitoring vegetation dynamics using multi-temporal Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images of Tamil Nadu
View through CrossRef
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.
Title: Monitoring vegetation dynamics using multi-temporal Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images of Tamil Nadu
Description:
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.
Related Results
Incorporating Vegetation Type Transformation with NDVI Time-Series to Study the Vegetation Dynamics in Xinjiang
Incorporating Vegetation Type Transformation with NDVI Time-Series to Study the Vegetation Dynamics in Xinjiang
Time-series normalized difference vegetation index (NDVI) is commonly used to conduct vegetation dynamics, which is an important research topic. However, few studies have focused o...
EVI and MDS/EVI are required for adult intestinal stem cell formation during postembryonic vertebrate development
EVI and MDS/EVI are required for adult intestinal stem cell formation during postembryonic vertebrate development
The gene ectopic viral integration site 1 (EVI) and its variant myelodysplastic syndrome 1 (MDS)/EVI encode zincāfinger proteins that have been recognized as important oncogenes in...
Generation of High-Resolution Time-Series NDVI Images for Monitoring Heterogeneous Crop Fields
Generation of High-Resolution Time-Series NDVI Images for Monitoring Heterogeneous Crop Fields
Various fusion methods of optical satellite images were proposed for monitoring heterogeneous farmlands requiring high spatial and temporal resolution. In this study, 3m normalized...
The Multi-Temporal Database of Planetary Image Data (MUTED): A Web-Tool to Support Surface Change Analyses on Mars, Moon, and Mercury
The Multi-Temporal Database of Planetary Image Data (MUTED): A Web-Tool to Support Surface Change Analyses on Mars, Moon, and Mercury
<p><strong>Introduction:</strong></p>
<p>The Multi-Temporal Database of Planetary Image Data (MUTED) is a comp...
Generation of High-Resolution Time-Series NDVI Images for Monitoring Heterogeneous Crop Fields
Generation of High-Resolution Time-Series NDVI Images for Monitoring Heterogeneous Crop Fields
Various fusion methods of optical satellite images have been proposed for monitoring heterogeneous farmlands requiring high spatial and temporal resolution. In this study, a three-...
Vegetation Indices Do Not Capture Forest Cover Variation in Upland Siberian Larch Forests
Vegetation Indices Do Not Capture Forest Cover Variation in Upland Siberian Larch Forests
Boreal forests are changing in response to climate, with potentially important feedbacks to regional and global climate through altered carbon cycle and albedo dynamics. These feed...
Identifikasi Ketersediaan Ruang Terbuka Hijau Kecamatan Kramat Jati Kodya Jakarta Timur Menggunakan Citra Pleiades
Identifikasi Ketersediaan Ruang Terbuka Hijau Kecamatan Kramat Jati Kodya Jakarta Timur Menggunakan Citra Pleiades
ABSTRACTThe development of big cities in Indonesia especially Jakarta City which is developing very rapidly is marked by the rapid development of physical development, thus affecti...
Response of Rice Ecological Indicators to Water Consumption Based on Multi-source Data in Irrigation District Scale
Response of Rice Ecological Indicators to Water Consumption Based on Multi-source Data in Irrigation District Scale
<p>The study of law of crop water consumption in small scale such as irrigation area requires remote sensing image data with high spatial and temporal resolution, how...

