scholarly journals Sensitivity of Convection-Permitting Regional Climate Simulations to Changes in Land Cover Input Data: Role of Land Surface Characteristics for Temperature and Climate Extremes

2021 ◽  
Vol 9 ◽  
Author(s):  
Merja H. Tölle ◽  
Evgenii Churiulin
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Input Data ◽  
Regional Climate ◽  
Surface Characteristics ◽  
Heat Fluxes ◽  
Area Index ◽  
Land Cover Types ◽  
Land Cover Maps

Characterization of climate uncertainties due to different land cover maps in regional climate models is essential for adaptation strategies. The spatiotemporal heterogeneity in surface characteristics is considered to play a key role in terrestrial surface processes. Here, we quantified the sensitivity of model results to changes in land cover input data (GlobCover 2009, GLC 2000, CCI, and ECOCLIMAP) in the regional climate model (RCM) COSMO-CLM (v5.0_clm16). We investigated land cover changes due to the retrieval year, number, fraction and spatial distribution of land cover classes by performing convection-permitting simulations driven by ERA5 reanalysis data over Germany from 2002 to 2011. The role of the surface parameters on the surface turbulent fluxes and temperature is examined, which is related to the land cover classes. The bias of the annual temperature cycle of all the simulations compared with observations is larger than the differences between simulations. The latter is well within the uncertainty of the observations. The land cover class fractional differences are small among the land cover maps. However, some land cover types, such as croplands and urban areas, have greatly changed over the years. These distribution changes can be seen in the temperature differences. Simulations based on the CCI retrieved in 2000 and 2015 revealed no accreditable difference in the climate variables as the land cover changes that occurred between these years are marginal, and thus, the influence is small over Germany. Increasing the land cover types as in ECOCLIMAP leads to higher temperature variability. The largest differences among the simulations occur in maximum temperature and from spring to autumn, which is the main vegetation period. The temperature differences seen among the simulations relate to changes in the leaf area index, plant coverage, roughness length, latent and sensible heat fluxes due to differences in land cover types. The vegetation fraction was the main parameter affecting the seasonal evolution of the latent heat fluxes based on linear regression analysis, followed by roughness length and leaf area index. If the same natural vegetation (e.g. forest) or pasture grid cells changed into urban types in another land cover map, daily maximum temperatures increased accordingly. Similarly, differences in climate extreme indices are strongest for any land cover type change to urban areas. The uncertainties in regional temperature due to different land cover datasets were overall lower than the uncertainties associated with climate projections. Although the impact and their implications are different on different spatial and temporal scales as shown for urban area differences in the land cover maps. For future development, more attention should be given to land cover classification in complex areas, including more land cover types or single vegetation species and regional representative classification sample selection. Including more sophisticated urban and vegetation modules with synchronized input data in RCMs would improve the underestimation of the urban and vegetation effect on local climate.

scholarly journals A Sensitivity Assessment of COSMO-CLM to Different Land Cover Schemes in Convection-Permitting Climate Simulations over Europe

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1595
Author(s):  
Mingyue Zhang ◽  
Merja H. Tölle ◽  
Eva Hartmann ◽  
Elena Xoplaki ◽  
Jürg Luterbacher
Keyword(s):  
Land Cover ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Regional Climate ◽  
Plant Cover ◽  
Horizontal Resolution ◽  
Area Index ◽  
Climate Simulations ◽  
Simulation Results ◽  
Land Cover Maps

The question of how sensitive the regional and local climates are to different land cover maps and fractions is important, as land cover affects the atmospheric circulation via its influence on heat, moisture, and momentum transfer, as well as the chemical composition of the atmosphere. In this study, we used three independent land cover data sets, GlobCover 2009, GLC2000 and ESACCI-LC, as the lower boundary of the regional climate model COSMO-CLM (Consortium for Small Scale Modeling in Climate Mode, v5.0-clm15) to perform convection-permitting regional climate simulations over the large part of Europe covering the years 1999 and 2000 at a 0.0275° horizontal resolution. We studied how the sensitivity of the impacts on regional and local climates is represented by different land cover maps and fractions, especially between warm (summer) and cold (winter) seasons. We show that the simulated regional climate is sensitive to different land cover maps and fractions. The simulated temperature and observational data are generally in good agreement, though with differences between the seasons. In comparison to winter, the summer simulations are more heterogeneous across the study region. The largest deviation is found for the alpine area (−3 to +3 °C), which might be among different reasons due to different classification systems in land cover maps and orographical aspects in the COSMO-CLM model. The leaf area index and plant cover also showed different responses based on various land cover types, especially over the area with high vegetation coverage. While relating the differences of land cover fractions and the COSMO-CLM simulation results (the leaf area index, and plant coverage) respectively, the differences in land cover fractions did not necessarily lead to corresponding bias in the simulation results. We finally provide a comparative analysis of how sensitive the simulation outputs (temperature, leaf area index, plant cover) are related to different land cover maps and fractions. The different regional representations of COSMO-CLM indicate that the soil moisture, atmospheric circulation, evaporative demand, elevation, and snow cover schemes need to be considered in the regional climate simulation with a high horizontal resolution.

scholarly journals Index-based Approach in Relation to Built-up and LST Dynamics; A Study of Lahore, Pakistan

2021 ◽  
Vol 12 (1) ◽  
pp. 32-40
Author(s):  
Kanwal Javid ◽  
Muhammad Ameer Nawaz Akram ◽  
Shazia Pervaiz ◽  
Rumana Siddiqui ◽  
Nausheen Mazhar
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Urban Areas ◽  
World View ◽  
Urban Expansion ◽  
Land Development ◽  
Water Bodies ◽  
Pollution Level ◽  
Area Index ◽  
Land Cover Types

In 21st century, cities outpaced in size and also in density due to development of economic sector. Consequently, the wide spread expansion of urban areas is resulting in the loss of productive green cover and water bodies. Therefore, realizing this alarming situation, the present study is aimed to investigate and evaluate the pattern of urban expansion by considering two major land cover types (i) built-up area (ii) other classes (vegetation, waterbody, soil etc.) during the last six years (2015-2020). For this study Sentinel imagery was acquired from USGS Earth Explorer, while Modis Terra images were acquired from World View NASA. New built-up area index (NBUI), normalized difference vegetation index (NDVI), worldview water index (WV-WI) and land surface temperature (LST) were calculated in order to analyze variations in Lahore’s major land cover types and its varying temperature patterns. Spatial analysis presented the obvious impacts of land development on Lahore. NBUI indicated that the built-up area has increased drastically from 34.0% in 2015 to 84.2% in 2020; NDVI analysis depicted a decline from 0.76% to 0.73%, in the green spaces of Lahore during the study period; WV-WI portrayed inconsistent values of water bodies, a gift of massive rise in the built-up area in Lahore. LST results presented that the temperature was 42.21°C in 2015, which simultaneously increased and recorded at 49.51°C in 2020. The increase in LST exhibited the alarming situation for urban environment and can become threat to increase the air pollution level in Lahore. Therefore, this study will serve as a snapshot for policy makers to control the menace of unplanned urbanization by formulating stringent policies to protect environment.

scholarly journals Ecological Connectivity in Agricultural Green Infrastructure:  Suggested Criteria for Fine Scale Assessment and Planning

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 807
Author(s):  
Simone Valeri ◽  
Laura Zavattero ◽  
Giulia Capotorti
Keyword(s):  
Land Cover ◽  
Green Infrastructure ◽  
Rural Areas ◽  
Urban Areas ◽  
Landscape Heterogeneity ◽  
Agricultural Landscapes ◽  
Spatial Pattern Analysis ◽  
Fine Scale ◽  
Unique Type

In promoting biodiversity conservation and ecosystem service capacity, landscape connectivity is considered a critical feature to counteract the negative effects of fragmentation. Under a Green Infrastructure (GI) perspective, this is especially true in rural and peri-urban areas where a high degree of connectivity may be associated with the enhancement of agriculture multifunctionality and sustainability. With respect to GI planning and connectivity assessment, the role of dispersal traits of tree species is gaining increasing attention. However, little evidence is available on how to select plant species to be primarily favored, as well as on the role of landscape heterogeneity and habitat quality in driving the dispersal success. The present work is aimed at suggesting a methodological approach for addressing these knowledge gaps, at fine scales and for peri-urban agricultural landscapes, by means of a case study in the Metropolitan City of Rome. The study area was stratified into Environmental Units, each supporting a unique type of Potential Natural Vegetation (PNV), and a multi-step procedure was designed for setting priorities aimed at enhancing connectivity. First, GI components were defined based on the selection of the target species to be supported, on a fine scale land cover mapping and on the assessment of land cover type naturalness. Second, the study area was characterized by a Morphological Spatial Pattern Analysis (MSPA) and connectivity was assessed by Number of Components (NC) and functional connectivity metrics. Third, conservation and restoration measures have been prioritized and statistically validated. Notwithstanding the recognized limits, the approach proved to be functional in the considered context and at the adopted level of detail. Therefore, it could give useful methodological hints for the requalification of transitional urban–rural areas and for the achievement of related sustainable development goals in metropolitan regions.

scholarly journals How Can We Represent Seasonal Land Use Dynamics in SWAT and SWAT+ Models for African Cultivated Catchments?

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1541
Author(s):  
Albert Nkwasa ◽  
Celray James Chawanda ◽  
Anna Msigwa ◽  
Hans C. Komakech ◽  
Boud Verbeiren ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Swat Model ◽  
Agricultural Practices ◽  
Area Index ◽  
Land Use Dynamics ◽  
Cropping Seasons ◽  
Decision Tables ◽  
Land Cover Maps

In SWAT and SWAT+ models, the variations in hydrological processes are represented by Hydrological Response Units (HRUs). In the default models, agricultural land cover is represented by a single growing cycle. However, agricultural land use, especially in African cultivated catchments, typically consists of several cropping seasons, following dry and wet seasonal patterns, and are hence incorrectly represented in SWAT and SWAT+ default models. In this paper, we propose a procedure to incorporate agricultural seasonal land-use dynamics by (1) mapping land-use trajectories instead of static land-cover maps and (2) linking these trajectories to agricultural management settings. This approach was tested in SWAT and SWAT+ models of Usa catchment in Tanzania that is intensively cultivated by implementing dominant dynamic trajectories. Our results were evaluated with remote-sensing observations for Leaf Area Index (LAI), which showed that a single growing cycle did not well represent vegetation dynamics. A better agreement was obtained after implementing seasonal land-use dynamics for cultivated HRUs. It was concluded that the representation of seasonal land-use dynamics through trajectory implementation can lead to improved temporal patterns of LAI in default models. The SWAT+ model had higher flexibility in representing agricultural practices, using decision tables, and by being able to represent mixed cropping cultivations.

Identifying land cover suitability factors for photovoltaic installations with focus on cropland and urban areas

2021 ◽  
Author(s):  
Madhura Yeligeti ◽  
Wenxuan Hu ◽  
Yvonne Scholz ◽  
Kai von Krbek
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Energy Systems ◽  
Energy System ◽  
Climatic Conditions ◽  
System Modelling ◽  
Solar Photovoltaic ◽  
Land Cover Types ◽  
The World ◽  
Urban Settlements

<p>Solar photovoltaic (PV) systems will foreseeably be an integral part of future energy systems. Land cover area analysis has a large influence on estimatiin of long-term solar photovoltaic potential of the world in high spatial detail. In this regard, it is often seen in contemporary works, that the suitability of various land cover categories for PV installation is considered in a yes/no binary response. While some areas like natural parks, sanctuaries, forests are usually completely exempted from PV potential calculations, other land over categories like urban settlements, bare, sparsely vegetated areas, and even cropland can principally support PV installations to varying degrees. This depends on the specific land use competition, social, economic and climatic conditions, etc. In this study, we attempt to evaluate these ‘factors of suitability’ of different land cover types for PV installations.</p><p>As a basis, the openly available global land cover datasets from the Copernicus Land Monitoring Service were used to identify major land cover types like cropland, shrubland, bare, wetlands, urban settlements, forests, moss and snow etc. For open area PV installations, with a focus on cropland, we incorporated the promising technology of ‘Agri-voltaics’ in our investigation. Different crops have shown to respond positively or negatively, so far, to growing under PV panels according to various experimental and commercial sources. Hence, we considered 18 major crops of the world (covering 85% of world cropland) individually and consequently, evaluated a weighted overall suitability factor of cropland cover for PV, for three acceptance scenarios of future.</p><p>For rooftop PV installations in urban areas, various socio-economic and geographical influences come in play. The rooftop area available and further usable for PV depends on housing patterns (roof type, housing density) which vary with climate, population density and socio-economic lifestyle. We classified global urban areas into several clusters based on combinations of these factors. For each cluster, rooftop area suitability is evaluated at a representative location using the land cover maps, the Open Street Map and specific characteristics of the cluster.</p><p>Overall, we present an interdisciplinary approach to integrate technological, social and economic aspects in land cover analysis to estimate PV potentials. While the intricacies may still be insufficient for planning small localized energy systems, this can reasonably benefit energy system modelling from a regional to international scale.</p>

scholarly journals Investigating the rank-size relationship of urban areas using land cover maps

2008 ◽  
Vol 35 (17) ◽  
Author(s):  
Tsuguki Kinoshita ◽  
Etsushi Kato ◽  
Koki Iwao ◽  
Yoshiki Yamagata
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Size Relationship ◽  
Relationship Of ◽  
Land Cover Maps

scholarly journals ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1 km resolution based on satellite information for use in land surface, meteorological and climate models

2013 ◽  
Vol 6 (2) ◽  
pp. 563-582 ◽  
Author(s):  
S. Faroux ◽  
A. T. Kaptué Tchuenté ◽  
J.-L. Roujean ◽  
V. Masson ◽  
E. Martin ◽  
...  
Keyword(s):  
Land Cover ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Climate Models ◽  
Area Index ◽  
Surface Parameters ◽  
Climatic Environment

Abstract. The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1 km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo). Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover) and GLC2000 (Global Land Cover) by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography). The leaf area index (LAI) from MODIS and normalized difference vegetation index (NDVI) from SPOT/Vegetation (a global monitoring system of vegetation) yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas) and, inside the nature tile, fractions of 12 plant functional types (PFTs) representing generic vegetation types – principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land – as incorporated by the SVAT model ISBA (Interactions Surface Biosphere Atmosphere) developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of versatile land occupation nomenclatures.

scholarly journals Time Series Analysis Using Digital Classification of Data on Land Use and Land Cover in Dohuk Governorate

2021 ◽  
Vol 910 (1) ◽  
pp. 012124
Author(s):  
Mohammed Younis Salim ◽  
Narmin Abduljaleel Ibrahim
Keyword(s):  
Land Cover ◽  
Classification Accuracy ◽  
Urban Areas ◽  
Bare Soil ◽  
Error Matrix ◽  
Ndvi Index ◽  
Open Forests ◽  
Soil And Water

Abstract This study deals with the analysis and detection of changes in land cover patterns and land uses, especially forests in Amadiya district in Dohuk Governorate. It carred out in northern of Iraq by area is (2775.21) km2 and the district is located astronomically between longitudes (01/04 ° 43), (17/08 ° 44), it extends between two circles of latitude, which are (16/50 ° 36) and ('30.'21 ° 37) north, during the periods (1999-2006-2013-2019). Application of the Supervised Classification and the detection of change over time in a comparative manner and by relying on the satellite images of the Land sat ETM satellite were used. The Landsat OLI satellite with a distinctive capacity of 30 meters in the Arc map 10.6.1 program, and one of the indicators of environmental degradation in the land cover patterns, which is the NDVI index for all study periods, was used to reveal the role of natural and human factors that lead to changes in the land cover patterns in the study area. The classification revealed the existence of five types of common land cover, which included dense forests, open forests, urban areas, bare soil and water, which showed clear changes in these land coverings during the period from 1999 to 2019, which were represented by a decrease in forests, bare soil and water by a percentage of (54.76601%), (5.212329%), (2.149469%) respectively, while the Dense and urban areas by (16.35919%) and (21.51301%) in 2019, respectively. The classification accuracy of the Spatial indication was estimated based on the error matrix from there we found that the accuracy was (93.29%) this indicates that the classification accuracy is very good It is acceptable and can relied upon and recommended for classification.

scholarly journals An Assessment of Changes the Land Use Land Cover and Impact of the It Park at Talwade Pune On the Nearby Villages

2020 ◽  
pp. 172-179
Author(s):  
Ujjwala Khare ◽  
Prajakta Thakur
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Rapid Growth ◽  
Urban Areas ◽  
Satellite Images ◽  
Ground Truth ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Tertiary Sector ◽  
Land Cover Maps

<p>The expansion of urban areas is common in metropolitan cities in India. Pune also has experienced rapid growth in the fringe areas of the city. This is mainly on account of the development of the Information Technology (IT) Parks. These IT Parks have been established in different parts of Pune city. They include Hinjewadi, Kharadi, Talwade and others like the IT parks in Magarpatta area. The IT part at Talwade is located to close to Pune Nashik Highway has had an impact on the villages located around it. The surrounding area includes the villages of Talwade, Chikhli, Nighoje, Mahalunge, Khalumbre and Sudumbre.</p> <p>The changes in the land use that have occurred in areas surrounding Talwade IT parks during the last three decades have been studied by analyzing the LANDSAT images of different time periods. The satellite images of the 1992, 2001 and 2011 were analyzed to detect the temporal changes in the land use and land cover.</p> <p>This paper attempts to study the changes in land use / land cover which has taken place in these villages in the last two decades. Such a study can be done effectively with the help of remote sensing and GIS techniques. The tertiary sector has experienced a rapid growth especially during the last decade near the IT Park. The occupation structure of these villages is also related to the changes due to the development of the IT Park.</p> <p>The land use of study area has been analysed using the ground truth applied to the satellite images at decadal interval. Using the digital image processing techniques, the satellite images were then classified and land use / land cover maps were derived. The results show that the area under built-up land has increased by around 14 per cent in the last 20 years. On the contrary, the land under agriculture, barren, pasture has decreased significantly.</p>

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