scholarly journals Influence of Land Use Land Cover on Cyclone Track Prediction – A Study During Aila Cyclone

2012 ◽  
Vol 6 (1) ◽  
pp. 33-41 ◽  
Author(s):  
K. V.S. Badarinath ◽  
D. V. Mahalakshmi ◽  
Satyaban Bishoyi Ratna
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Mesoscale Model ◽  
Surface Processes ◽  
Land Use Land Cover ◽  
Land Surface Processes ◽  
Mm5 Model ◽  
Land Cover Data ◽  
The Impact

Land-surface processes are one of the important drivers for weather and climate systems over the tropics. Realistic representation of land surface processes in mesoscale models over the region will help accurate simulation of numerical forecasts. The present study examines the influence of Land Use/ Land Cover Change (LULC) on the forecasting of cyclone intensity and track prediction using Mesoscale Model (MM5). Gridded land use/land cover data set over the Indian region compatible with the MM5 model were generated from Indian Remote Sensing Satellite (IRS-P6) Advanced Wide Field Sensor (AWiFS) for the year 2007-2008. A case study of simulation of ‘Aila’ cyclone has been considered to see the impact of these two sets of LULC data with the use of MM5 model. Results of the study indicated that incorporation of current land use/land cover data sets in mesoscale model provides better forecasting of cyclonic track.

scholarly journals Thirty Years of Land Use/Land Cover Changes and Their Impact on Urban Climate: A Study of Kano Metropolis, Nigeria

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1106
Author(s):  
Auwalu Faisal Koko ◽  
Yue Wu ◽  
Ghali Abdullahi Abubakar ◽  
Akram Ahmed Noman Alabsi ◽  
Roknisadeh Hamed ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Expansion ◽  
Urban Climate ◽  
Land Use Land Cover ◽  
Spectral Indices ◽  
The Impact

Rapid urban expansion and the alteration of global land use/land cover (LULC) patterns have contributed substantially to the modification of urban climate, due to variations in Land Surface Temperature (LST). In this study, the LULC change dynamics of Kano metropolis, Nigeria, were analysed over the last three decades, i.e., 1990–2020, using multispectral satellite data to understand the impact of urbanization on LST in the study area. The Maximum Likelihood classification method and the Mono-window algorithm were utilised in classifying land uses and retrieving LST data. Spectral indices comprising the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) were also computed. A linear regression analysis was employed in order to examine the correlation between land surface temperature and the various spectral indices. The results indicate significant LULC changes and urban expansion of 152.55 sq. km from 1991 to 2020. During the study period, the city’s barren land and water bodies declined by approximately 172.58 sq. km and 26.55 sq. km, respectively, while vegetation increased slightly by 46.58 sq. km. Further analysis showed a negative correlation between NDVI and LST with a Pearson determination coefficient (R2) of 0.6145, 0.5644, 0.5402, and 0.5184 in 1991, 2000, 2010, and 2020 respectively. NDBI correlated positively with LST, having an R2 of 0.4132 in 1991, 0.3965 in 2000, 0.3907 in 2010, and 0.3300 in 2020. The findings of this study provide critical climatic data useful to policy- and decision-makers in optimizing land use and mitigating the impact of urban heat through sustainable urban development.

A Simple Reclassification Method for Correcting Uncertainty in Land Use/Land Cover Data Sets Used with Land Surface Models

2007 ◽  
Vol 164 (8-9) ◽  
pp. 1789-1809 ◽  
Author(s):  
Joseph G. Alfieri ◽  
Dev Niyogi ◽  
Margaret A. LeMone ◽  
Fei Chen ◽  
Souleymane Fall
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Data Sets ◽  
Land Use Land Cover ◽  
Land Surface Models ◽  
Land Cover Data ◽  
Surface Models

scholarly journals Remote Sensing Image-Based Analysis of the Impact of Land Use/Land Cover Changes on Land Surface Temperature

2019 ◽  
Vol 8 (4) ◽  
pp. 1834-1839
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Spectral Radiance ◽  
Land Use Land Cover ◽  
The Impact ◽  
The City

This study evaluated the land use/land cover (LULC) changes in Tuguegarao City and analyzed its impact on Land Surface Temperature (LST). It was carried out using Remote Sensing and Geographic Information System (GIS) techniques. Three Landsat TM and ETM+ images data were acquired for the years 1990, 2005 and 2016 from USGS Earth Explorer portal. ArcGIS software was used to determine the area statistics of the different land cover and to make the final LULC map. LST for the study area was taken from the thermal infrared band of the satellite images by converting the image digital number into degrees Kelvin using the LMin and LMax spectral radiance scaling factors. The largest areal change appeared in the built-up area with an increase of 1120.32 ha. However, this study detected higher LST in the crop land, grassland and barren land areas of the city rather than the built-up parts of the city which does not follow many of previous studies. The results of the study can be presented to the Local Government Unit so that they can draft appropriate laws for the betterment of the city specially that rapid urbanization and uncontrolled population growth may have extreme impact on the environment.

scholarly journals Land Use/Land Cover Changes and the Relationship with Land Surface Temperature Using Landsat and MODIS Imageries in Cameron Highlands, Malaysia

Land ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 372
Author(s):  
Darren How Jin Aik ◽  
Mohd Hasmadi Ismail ◽  
Farrah Melissa Muharam
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Cameron Highlands ◽  
The Impact

Mountainous regions are more sensitive to climatic condition changes and are susceptible to recent increases in temperature. Due to urbanization and land use/land cover (LULC) issues, Cameron Highlands has been impacted by rising land surface temperature (LST) variation. Thus, this study was carried out to explore the impact of the LULC change on LST in the Cameron Highlands from 2009 to 2019 using remote sensing images acquired from Landsat 7 ETM+, Landsat 8 Operational Land Imager (OLI/TIRS), and Moderate Resolution Imaging Spectroradiometer (MODIS) 11A Thermal sensors. A split-window algorithm was applied to Landsat 8 images (2013–2019) to derive the LST. Air temperature data of the study area were also obtained to cross-validate data sources. Based on the validation results, the accuracy of LULC and LST outputs were more than 94.6% and 80.0%, respectively. The results show that the current trend of urban growth continues at a rate of 0.16% per year, and the area experienced an LST increase of 2 °C between 2009 and 2019. This study is crucial for land planners and environmentalists to understand the impacts of LULC change on LST and to propose appropriate policy measures to control development in Cameron Highlands.

Impact of land use land cover change on East Asia

2020 ◽  
Author(s):  
Ui-Yong Byun ◽  
Eun-Chul Chang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
East Asia ◽  
Land Cover Change ◽  
Land Surface ◽  
Temporal Change ◽  
Weather Prediction ◽  
Regional Climate ◽  
Land Use Land Cover ◽  
The Impact

<p>  Many socioeconomic changes have occurred in East Asia in recent decades. Due to the economic structural change and economic growth, a large population has been concentrated in the cities, resulting in rapid urban expansion. Besides, the surrounding agricultural land for food resources has also expanded, and deforestation has also been active at the same time. These land use/land cover change (LULCC) significantly alter the energy properties of the land surface. Although land surface characteristics that have vigorous variability over time, it is common in a numerical model to treat the information as a static condition. In a numerical weather prediction model aiming at short-term forecasting, the ground characteristics without temporal change are valid; however, in the numerical climate model integrated over several decades, consideration of such variability is essential.<br>   In this study, we examine the impact of LULCC using the GRIMs (Global/Regional Integrated Model system), which covered regional climate simulation. Temporal change LULC over East Asia, especially cropland and urban, is constructed based on Land Use Harmonization data. Through the comparison of sensitivity experiments considered the LULCC overtime or not, it is confirmed that land surface effect on regional climate change over East Asia. </p>

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