Study the Relationship Between LULC, LST, NDVI, NDWI and NDBI in Greater Arba Minch Area, Rift Valley, Ethiopia

Jothimani, Muralitharan; Gunalan, Jagadeshan; Duraisamy, Radhakrishnan; Abebe, Abel

doi:10.2991/ahis.k.210913.023

Cited by 9 publications

(4 citation statements)

References 47 publications

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“…For the past few decades, NDVI has often been used to assess vegetation percentage in the region. The NDVI ranges from -1 to 1; high NDVI values indicate that the thick vegetative area and low NDVI values suggest the nonvegetative area (Muralitharan et al 2021).…”

Section: Ndvi and Ndwi Calculationmentioning

confidence: 99%

Decadal Land Use and Land Cover Transformation in Shaheed Bhagat Singh Nagar of Punjab Based on Geospatial Technology

Sohal,

Kaushal,

Arora

et al. 2024

Preprint

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Land use and land cover (LU/LC) is observed to be the primary factor of environmental change on a worldwide scale. Timely and accurate information on LU/LC is very important for efficient planning and management activities. The present study mainly focused on land use and land cover change analysis in district Shaheed Bhagat Singh Nagar of Punjab using remote sensing and geospatial technology. Satellite data of IRS P6 LISS-III (2012 and 2022) were analysed for LU/LC mapping using visual interpretation techniques. The study area was divided into seven LU/LC classes i.e.: agriculture, built-up, waterbody, forest/tree clad area, riverine sand, algae bloom and fallow land /barren land/waste land in which agriculture covers maximum while riverine sand covers minimum area. Satellite derived NDVI and NDWI has been used to derive the spatial variability of vegetation and water. In decadal change the alterations encompass positive trends such as increased agricultural area (31.29%), as well as negative trends including decreased algae bloom (59.82%). Overall accuracy for LISS-III 2012 and LISS-III 2022 were 88.3% and 86.66% respectively with kappa coefficient value as 0.86, and 0.83, respectively. Hotspot areas with major changes were seen in Block Nawanshahr with major increase in built-up area, as well as in Block Saroya and Balachaur of study area with major decrease in Forest area.

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Section: Ndvi and Ndwi Calculationmentioning

confidence: 99%

Decadal Land Use and Land Cover Transformation in Shaheed Bhagat Singh Nagar of Punjab Based on Geospatial Technology

Sohal,

Kaushal,

Arora

et al. 2024

Preprint

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“…The NDWI is a ratio ranging from -1 to 1, with values near 1 indicating the presence of water and values near -1 indicating the absence of water. (Jothimani et al 2021).…”

Section: Calculation Of Ndvi and Ndwimentioning

confidence: 99%

“…It has also been proven to be an efficient indicator of water content in wetland environments, such as Chilika Lake, the present study area. It has been used in several studies to track changes in water content in aquatic systems, such as the expansion and contraction of wetland areas (Ashok et al 2021) and to identify potential areas of eutrophication (Jothimani et al 2021). NDWI has also been used to monitor the health of vegetation in ecosystems and identify water stress in crops (Rahaman et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Land Use/Cover Dynamics and Associated Impacts on Eutrophication, Land Surface Temperature, and Ecosystem Service Values: An Eco-Climatological Investigation of Chilika Lake, India.

Saini,

Gupta

et al. 2023

Preprint

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Asia’s largest water lagoon, Chilika Lake, located in Odisha, India, is a vital economic and environmental source for the region. For the last few decades, many studies provided fragmented reports on the rapid deterioration of environmental conditions due to climate changes from intensive urban and industrial activities. The present study, for the first time provides comprehensive information about the transition of the landscape, which had occurred in the region with their associated impact on surface temperature and ecological services. Remote sensing techniques were utilised to classify land use and land cover dynamics over a period of 30 years (1991–2021). Landsat data were used to create maps for the Normalised Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Land Surface Temperature (LST) to apprehend the spatial and temporal variability and its ecological functions. The findings revealed that the lake area shrank by around 11.7% in the last three decades, owing to the conversion of mangrove and wetland areas into agricultural and urban land. The NDVI maps revealed a decline in plant cover in the catchment region, indicating a decrease in the lake's ecological services, whereas the NDWI maps indicated a reduction in the catchment area of the lake, and these maps highlighted eutrophication spots on lake surface images due to increasing nutrient concentrations and decreased water quality in the lake. LST maps indicated a rise in surface temperature, which might be attributed to decreasing vegetative cover and water bodies, which tend to alter the lake's thermal regime. The CA-Markov model forecast map for 2026 suggested that the lake area would further decrease while urban and agricultural land would rise. The prediction map for 2021 compared to the existing map showed a slight improvement in lake levels caused by the pandemic, limited urban activity, and other possibilities.

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“…That is, the NDVI is used to estimate vegetation density and productivity, the NDWI is used to estimate water content on earth, in plants and soil, whereas the NDBI is used to estimate the density of built-up areas, all on the earth's surface [13]. Also as cited by [14] the remote sensing indices, NDVI, NDWI, and NDBI help to extract areas of vegetation, water bodies, and built-up covers respectively. By assessing the effects of land surface temperature on different land cover types especially during the COVID lockdown period, the dynamics of the landscape under fluctuating surface temperature will inform proper maintenance de-cisions by the authorities.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Analysis of COVID-19 Lockdown Impact on the Land Surface Temperatures of Different Land Cover Types in Louisiana

Loh,

Twumasi,

Ning

et al. 2023

JGIS

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The COVID-19 pandemic posed a serious threat to life on the entire planet, necessitating the imposition of a lockdown mechanism that restricted people's movements to stop the disease's spread. This period experienced a decline in air pollution emissions and some environmental changes, offering a rare opportunity to understand the effects of fewer human activities on the earth's temperature. Hence, this study compares the changes in Land Surface Temperature (LST) that were observed prior to the pandemic (March & April 2019) and during the pandemic lockdown (March & April 2020) of three parishes in Louisiana. The data for this study was acquired using Landsat 8 Thermal Infrared Sensor (TIRS) Level 2, Collection 2, Tier 2 from the Google Earth Engine Catalog. For better visualization, the images that were derived had a cloud cover of less than 10%. Also, images for the three study areas were processed and categorized into four main classes: water, vegetation, built-up areas, and bare lands using a Random Forest Supervised Classification Algorithm. To improve the accuracy of the image classifications, three Normalized Difference Indices namely the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Normalized Difference Built-Up Index (NDBI) were employed using the Near Infrared (NIR), Red, Green and SWIR bands for the calculations. After, these images were processed in Google Earth Engine to generate the LST products gridded at 30 m with a higher spatial resolution of 100 m according to the pre-pandemic (2019) and lockdown (2020) periods for the three study areas. Results of this study showed a decrease in LST values of the land cover classes from 2019 to 2020, with LST values in East Baton Parish decreasing from 44˚C to 38˚C, 42˚C to 38˚C in

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Study the Relationship Between LULC, LST, NDVI, NDWI and NDBI in Greater Arba Minch Area, Rift Valley, Ethiopia

Cited by 9 publications

References 47 publications

Decadal Land Use and Land Cover Transformation in Shaheed Bhagat Singh Nagar of Punjab Based on Geospatial Technology

Decadal Land Use and Land Cover Transformation in Shaheed Bhagat Singh Nagar of Punjab Based on Geospatial Technology

Land Use/Cover Dynamics and Associated Impacts on Eutrophication, Land Surface Temperature, and Ecosystem Service Values: An Eco-Climatological Investigation of Chilika Lake, India.

Spatiotemporal Analysis of COVID-19 Lockdown Impact on the Land Surface Temperatures of Different Land Cover Types in Louisiana

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