Optimized Soil Adjusted Vegetation Index Mapping of Pune District using Google Earth Engine
Uloženo v:
| Název: | Optimized Soil Adjusted Vegetation Index Mapping of Pune District using Google Earth Engine |
|---|---|
| Autoři: | nobin chandra paul, Ponnaganti Navyasree |
| Informace o vydavateli: | Springer Science and Business Media LLC, 2024. |
| Rok vydání: | 2024 |
| Popis: | This article explores the application of the Optimized Soil Adjusted Vegetation Index in mapping the vegetation cover of Pune District using Google Earth Engine. The map has been generated using Google Earth Engine from MODIS products (MOD13Q1) over a 23-year period (2000-2022) at spatial and temporal resolutions of 250 meters and 16 days, respectively. By incorporating the soil-brightness correction factor, this index enhances the accuracy of vegetation assessments, particularly in regions with low vegetative cover or mixed land use. In the OSAVI map of Pune district, the values range from -0.048 to 0.455, where negative values indicate non-vegetated surfaces and higher values, observed in tehsils like Mulshi, Velhe, Maval, and Bhor, suggest dense and healthy vegetation. Validation of the generated map was carried out by using high-resolution Google Earth images. This validation process showcased the effectiveness of the generated map in accurately identifying vegetation patterns within the Pune district. The alignment of the map’s results with the patterns observed in the Google Earth images solidifies its accuracy and reliability. The generated map can be a valuable tool for monitoring land degradation, assessing crop health, detecting abiotic stress indicators, monitoring agricultural drought and studying vegetation dynamics in arid and semi-arid regions where soil brightness can significantly impact NDVI measurements. The implications of this work are significant. By enhancing vegetation assessment accuracy, it provides reliable tools for policymakers and environmental managers to monitor and manage natural resources. |
| Druh dokumentu: | Article |
| DOI: | 10.21203/rs.3.rs-5605500/v1 |
| Rights: | CC BY |
| Přístupové číslo: | edsair.doi...........e8c08f28e3e5be21ec1cf159e3a55462 |
| Databáze: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | This article explores the application of the Optimized Soil Adjusted Vegetation Index in mapping the vegetation cover of Pune District using Google Earth Engine. The map has been generated using Google Earth Engine from MODIS products (MOD13Q1) over a 23-year period (2000-2022) at spatial and temporal resolutions of 250 meters and 16 days, respectively. By incorporating the soil-brightness correction factor, this index enhances the accuracy of vegetation assessments, particularly in regions with low vegetative cover or mixed land use. In the OSAVI map of Pune district, the values range from -0.048 to 0.455, where negative values indicate non-vegetated surfaces and higher values, observed in tehsils like Mulshi, Velhe, Maval, and Bhor, suggest dense and healthy vegetation. Validation of the generated map was carried out by using high-resolution Google Earth images. This validation process showcased the effectiveness of the generated map in accurately identifying vegetation patterns within the Pune district. The alignment of the map’s results with the patterns observed in the Google Earth images solidifies its accuracy and reliability. The generated map can be a valuable tool for monitoring land degradation, assessing crop health, detecting abiotic stress indicators, monitoring agricultural drought and studying vegetation dynamics in arid and semi-arid regions where soil brightness can significantly impact NDVI measurements. The implications of this work are significant. By enhancing vegetation assessment accuracy, it provides reliable tools for policymakers and environmental managers to monitor and manage natural resources. |
|---|---|
| DOI: | 10.21203/rs.3.rs-5605500/v1 |