scholarly journals Analysis of a Warm-Season Surface-Influenced Mesoscale Convective Boundary in Northwest Mississippi

2011 ◽  
Vol 12 (5) ◽  
pp. 1007-1023 ◽  
Author(s):  
Jamie Dyer
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Rapid Change ◽  
Convective Precipitation ◽  
Alluvial Valley ◽  
Convective Boundary ◽  
Mesoscale Convective ◽  
Lower Mississippi River

Abstract The lower Mississippi River alluvial valley in southeastern Arkansas, northeastern Louisiana, and northwestern Mississippi is characterized by widespread agriculture with few urban areas. Land use is predominantly cultivated cropland with minimal topographic variation; the eastern edge of the alluvial valley is defined by a rapid, although small, change in elevation into a heavily forested landscape, however. This change in land use/land cover has been shown to potentially enhance precipitation through generation of a weak mesoscale convective boundary. This project defines the influence of the land surface on associated precipitation processes by simulating a convective rainfall event that was influenced by regional surface features. Analysis was conducted using a high-resolution simulated dataset generated by the Weather Research and Forecasting Model (WRF). Results show that the strongest uplift coincides with an abrupt low-level thermal boundary, developed primarily by a rapid change from sensible to latent heat flux relative to the agricultural and forested areas, respectively. In addition, surface heating over the cultivated landscape appears to destabilize the boundary layer, with precipitation occurring as air is advected across the land cover boundary and the associated thermal gradient. This information can be used to define and predict surface-influenced convective precipitation along agricultural boundaries in other regions where the synoptic environment is weak.

scholarly journals Impact of Multitemporal Land Use and Land Cover Change on Land Surface Temperature Due to Urbanization in Hefei City, China

2021 ◽  
Vol 10 (12) ◽  
pp. 809
Author(s):  
Jing Sun ◽  
Suwit Ongsomwang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Decomposition Analysis ◽  
Lulc Change ◽  
Main Components ◽  
The Impact

Land surface temperature (LST) is an essential parameter in the climate system whose dynamics indicate climate change. This study aimed to assess the impact of multitemporal land use and land cover (LULC) change on LST due to urbanization in Hefei City, Anhui Province, China. The research methodology consisted of four main components: Landsat data collection and preparation; multitemporal LULC classification; time-series LST dataset reconstruction; and impact of multitemporal LULC change on LST. The results revealed that urban and built-up land continuously increased from 2.05% in 2001 to 13.25% in 2020. Regarding the impact of LULC change on LST, the spatial analysis demonstrated that the LST difference between urban and non-urban areas had been 1.52 K, 3.38 K, 2.88 K and 3.57 K in 2001, 2006, 2014 and 2020, respectively. Meanwhile, according to decomposition analysis, regarding the influence of LULC change on LST, the urban and built-up land had an intra-annual amplitude of 20.42 K higher than other types. Thus, it can be reconfirmed that land use and land cover changes due to urbanization in Hefei City impact the land surface temperature.

scholarly journals MODELING THE DEVELOPMENTS IN URBANISATION AND RELATIONSHIP WITH VEGETATION COVER IN ALANYA

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 291-297
Author(s):  
B. İşler ◽  
Z. Aslan
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Landsat 8 ◽  
World Population ◽  
Land Use Land Cover ◽  
Temperature And Precipitation ◽  
Atmospheric Variables

Abstract. The increase in the world population and the migration of people from rural to urban areas causes an increase in artificial surfaces and causes many negative effects on the ecosystem, regional climate variations and global diversity. Nowadays, as the effects of climate change are felt more and more, it has gained importance in researches on this subject. Therefore, the estimation of the change in the vegetation density for the coming years and the determination of the land use / land cover (LULC) change in cities are very essential for urban planning. In this study, the effects of regional urbanization on vegetation are examined by using satellite data and atmospheric variables. In the vegetation analysis, multi-time index values obtained from TERRA-MODIS satellite, EVI (Enhanced Vegetation Index) and LST (Land Surface Temperature) were taken into account between the years of 2005 and 2018 in Alanya, Turkey. Temperature and precipitation were selected as the atmospheric variables and expected variations in EVI value until 2030 were estimated. In the study employed a wavelet-transformed artificial neural network (WANN) model to generate long-term (12-year) EVI forecasts using LST, temperature and precipitation. The relationship between land use / land cover and urbanization is investigated with NDBI (Normalized Difference Built-up Index) data obtained from the Landsat 8 OLI / TIRS satellite sensor. The simulation results show that The EVI value, which was 0.30 in 2018, will decrease to 0.25 in 2030.

Application of the complete CORINE land covers for modelling in WRF model

2021 ◽  
Author(s):  
Hajnalka Breuer ◽  
Zsuzsanna Zempléni ◽  
Ákos Varga
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Wrf Model ◽  
Hungarian Academy ◽  
Substantial Effect ◽  
Convective Precipitation ◽  
Near Surface ◽  
Land Cover Types ◽  
One Year

<p>Land use information is crucial in weather modelling as it determines the energy partitioning of the land surface. Based on the partitioning heating of near surface air and moisture supply of the planetary boundary layer is determined. These processes affect the general calculation of temperature, but it also has substantial effect on precipitation formation, especially on convective precipitation.</p><p>In this study the CORINE 44 categories are integrated into the WRF model. Usually the 44 land cover types are recategorized into a standard USGS or MODIS land use types. Here we present a dataset and application with the complete integration of the 44 types.</p><p>One-year runs are created with the CORINE land cover compared to the standard USGS dataset. Along with the new land cover types vegetation parameters had be defined as well. Four runs refer to a USGS-reference, CORINE2USGS converted, CORINE-USGS parameter, CORINE-newparameters where the effect of land cover and parameter change is analyzed. The modelled area covers the whole European region with 50 km resolution using the WRF 4.2 model. Regionally, on a monthly average 5-30% difference in precipitation and around 1 °C differences occur.</p><p>The research was supported by the Hungarian National Research, Development and Innovation Office, Grant No. FK132014. Hajnalka Breuer's work was additionally financed by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.</p>

scholarly journals Remote Sensing-Based Quantification of the Relationships between Land Use Land Cover Changes and Surface Temperature over the Lower Himalayan Region

2019 ◽  
Vol 11 (19) ◽  
pp. 5492 ◽  
Author(s):  
Ullah ◽  
Tahir ◽  
Akbar ◽  
Hassan ◽  
Dewan ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Linear Regression Analysis ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Total Study Area

Population growth and population inflow from other regions has caused urbanization which altered land use land cover (LULC) in the lower Himalayan regions of Pakistan. This LULC change increased the land surface temperature (LST) in the region. LULC and LST changes were assessed for the period of 1990–2017 using Landsat data and the support vector machine (SVM) method. A combined cellular automata and artificial neural network (CA-ANN) prediction model was used for simulation of LULC changes for the period of 2032 and 2047 using transition potential matrix obtained from the data years of 2002 and 2017. The accuracy of the CA-ANN model was validated using simulated and classified images of 2017 with correctness value of 70% using validation modules in QGIS. The thermal bands of Landsat images from the years 1990, 2002 and 2017 were used for LST derivation. LST acquired for this period was then modeled for 2032 and 2047 using urban indices (UI) and linear regression analysis. The SVM land cover classification results showed a 5.75% and 4.22% increase in built-up area and bare soil respectively, while vegetation declined by 9.88% during 1990–2017. The results of LST for LULC classes showed that the built-up area had the highest mean LST as compared to other classes. The future projection of LULC and LST showed that the built-up area may increase by 12.48% and 14.65% in 2032 and 2047, respectively, of the total LULC area which was ~11% in 2017. Similarly, the area with temperature above 30 °C could be 44.01% and 58.02% in 2032 and 2047, respectively, of the total study area which was 18.64% in 2017. This study identified major challenges for urban planners to mitigate the urban heat island (UHI) phenomenon. In order to address the UHI in the study area, an urban planner might focus on urban plantation and decentralization of urban areas.

Land use and land cover change impact on surface temperature: the scale issue

2020 ◽  
Author(s):  
Dan Li ◽  
Liang Wang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Cover Change ◽  
Land Surface ◽  
Heterogeneous Terrain ◽  
Convective Boundary ◽  
Time Approximation ◽  
One Dimensional ◽  
Dimensional Models

<p>While land use and land cover change (LULCC) is often a temporal phenomenon (i.e., a patch transitions from one land cover type to another), many studies use a space-for-time approximation that quantifies the LULCC impact (say on surface temperature or fluxes) by comparing two adjacent patches of different land covers. An important consideration embedded in this space-for-time approximation is the scale, which determines what assumptions we can make when constructing models for studying land-atmosphere interactions over heterogeneous terrain. Most previous studies employ one-dimensional models without considering the appropriate scale associated with these models. In this presentation, the scale issue in studying LULCC-induced surface temperature anomalies will be discussed using a hierarchy of models. Typical one-dimensional models based on the surface energy balance and/or convective boundary layer dynamics will be compared to two-dimensional models where horizontal advection is explicitly considered. The results highlight the importance of scale in determining the sensitivity of land surface temperature to changes in albedo and moisture/vegetation characteristics. </p>

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals Spatiotemporal Influence of Land Use/Land Cover Change Dynamics on Surface Urban Heat Island: A Case Study of Abuja Metropolis, Nigeria

2021 ◽  
Vol 10 (5) ◽  
pp. 272
Author(s):  
Auwalu Faisal Koko ◽  
Wu Yue ◽  
Ghali Abdullahi Abubakar ◽  
Akram Ahmed Noman Alabsi ◽  
Roknisadeh Hamed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Urban Expansion ◽  
Urban Heat Islands ◽  
Sustainable Land Use ◽  
Land Use Land Cover ◽  
Urban Centers ◽  
Rapid Urbanization ◽  
Urban Heat

Rapid urbanization in cities and urban centers has recently contributed to notable land use/land cover (LULC) changes, affecting both the climate and environment. Therefore, this study seeks to analyze changes in LULC and its spatiotemporal influence on the surface urban heat islands (UHI) in Abuja metropolis, Nigeria. To achieve this, we employed Multi-temporal Landsat data to monitor the study area’s LULC pattern and land surface temperature (LST) over the last 29 years. The study then analyzed the relationship between LULC, LST, and other vital spectral indices comprising NDVI and NDBI using correlation analysis. The results revealed a significant urban expansion with the transformation of 358.3 sq. km of natural surface into built-up areas. It further showed a considerable increase in the mean LST of Abuja metropolis from 30.65 °C in 1990 to 32.69 °C in 2019, with a notable increase of 2.53 °C between 2009 and 2019. The results also indicated an inverse relationship between LST and NDVI and a positive connection between LST and NDBI. This implies that urban expansion and vegetation decrease influences the development of surface UHI through increased LST. Therefore, the study’s findings will significantly help urban-planners and decision-makers implement sustainable land-use strategies and management for the city.

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