scholarly journals Continuous and consistent land use/cover change estimates using socio-ecological data

2016 ◽  
Author(s):  
Michael Marshall ◽  
Michael Norton-Griffiths ◽  
Harvey Herr ◽  
Richard Lamprey ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Natural Vegetation ◽  
Additive Models ◽  
Sub Saharan Africa ◽  
Land Cover Types ◽  
Remote Sensing Classification ◽  
Functional Relationships ◽  
Macro Scale

Abstract. A growing body of research shows the importance of land use/cover change (LULCC) on modifying the earth system. Land surface models are used to stimulate land-atmosphere dynamics at the macro- (regional to global) scale, but bias and uncertainty remain that need to be addressed, before the importance of LULCC is fully realized. In this study, we propose a method of improving LULCC estimates for land surface modelling exercises. The method yields continuous (annual) long-term (30-year) estimates of LULCC driven by socio-ecological geospatial predictors available seamlessly across sub-Saharan Africa that can be used for both retrospective and prospective analyses. The method was developed with 2252 5 × 5 km2 sample frames of the proportion of several land cover types in Kenya over multiple years. Forty-three socio-ecological predictors were evaluated for model development. Machine learning was used for data reduction and simple (functional) relationships defined by generalized additive models were constructed on a subset of the highest ranked predictors (p ≤ 10) to estimate LULCC. The predictors explained 62 % and 65 % of the variance in the proportion of agriculture and natural vegetation, respectively, but were less successful at estimating more descriptive land cover types. In each case, population density on an annual basis was the highest ranked predictor. The approach was compared to a commonly used remote sensing classification procedure, given the wide use of such techniques for macro-scale LULCC detection, and out-performed it for each land cover type. The approach was used to demonstrate significant trends in expanding (declining) agricultural (natural vegetation) land cover in Kenya from 1983–2012, with the largest increases (declines) occurring in densely populated high agricultural production zones.

scholarly journals Continuous and consistent land use/cover change estimates using socio-ecological data

2017 ◽  
Vol 8 (1) ◽  
pp. 55-73 ◽  
Author(s):  
Michael Marshall ◽  
Michael Norton-Griffiths ◽  
Harvey Herr ◽  
Richard Lamprey ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Natural Vegetation ◽  
Additive Models ◽  
Sub Saharan Africa ◽  
Ecological Data ◽  
Land Cover Types ◽  
Remote Sensing Classification ◽  
Functional Relationships

Abstract. A growing body of research shows the importance of land use/cover change (LULCC) on modifying the Earth system. Land surface models are used to stimulate land–atmosphere dynamics at the macroscale, but model bias and uncertainty remain that need to be addressed before the importance of LULCC is fully realized. In this study, we propose a method of improving LULCC estimates for land surface modeling exercises. The method is driven by projectable socio-ecological geospatial predictors available seamlessly across sub-Saharan Africa and yielded continuous (annual) estimates of LULCC at 5 km  ×  5 km spatial resolution. The method was developed with 2252 sample area frames of 5 km  ×  5 km consisting of the proportion of several land cover types in Kenya over multiple years. Forty-three socio-ecological predictors were evaluated for model development. Machine learning was used for data reduction, and simple (functional) relationships defined by generalized additive models were constructed on a subset of the highest-ranked predictors (p ≤ 10) to estimate LULCC. The predictors explained 62 and 65 % of the variance in the proportion of agriculture and natural vegetation, respectively, but were less successful at estimating more descriptive land cover types. In each case, population density on an annual basis was the highest-ranked predictor. The approach was compared to a commonly used remote sensing classification procedure, given the wide use of such techniques for macroscale LULCC detection, and outperformed it for each land cover type. The approach was used to demonstrate significant trends in expanding (declining) agricultural (natural vegetation) land cover in Kenya from 1983 to 2012, with the largest increases (declines) occurring in densely populated high agricultural production zones. Future work should address the improvement (development) of existing (new) geospatial predictors and issues of model scalability and transferability.

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 Limitations of WRF land surface models for simulating land use and land cover change in Sub-Saharan Africa and development of an improved model (CLM-AF v. 1.0)

2021 ◽  
Vol 14 (6) ◽  
pp. 3215-3249
Author(s):  
Timothy Glotfelty ◽  
Diana Ramírez-Mejía ◽  
Jared Bowden ◽  
Adrian Ghilardi ◽  
J. Jason West
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Sub Saharan Africa ◽  
Land Surface Models ◽  
Surface Parameters ◽  
Temperature And Precipitation ◽  
Surface Models ◽  
Sub Saharan ◽  
Land Surface Parameters

Abstract. Land use and land cover change (LULCC) impacts local and regional climates through various biogeophysical processes. Accurate representation of land surface parameters in land surface models (LSMs) is essential to accurately predict these LULCC-induced climate signals. In this work, we test the applicability of the default Noah, Noah-MP, and Community Land Model (CLM) LSMs in the Weather Research and Forecasting (WRF) model over Sub-Saharan Africa. We find that the default WRF LSMs do not accurately represent surface albedo, leaf area index, and surface roughness in this region due to various flawed assumptions, including the treatment of the MODIS woody savanna land use and land cover (LULC) category as closed shrubland. Consequently, we developed a WRF CLM version with more accurate African land surface parameters (CLM-AF), designed such that it can be used to evaluate the influence of LULCC. We evaluate meteorological performance for the default LSMs and CLM-AF against observational datasets, gridded products, and satellite estimates. Further, we conduct LULCC experiments with each LSM to determine if differences in land surface parameters impact the LULCC-induced climate responses. Despite clear deficiencies in surface parameters, all LSMs reasonably capture the spatial pattern and magnitude of near-surface temperature and precipitation. However, in the LULCC experiments, inaccuracies in the default LSMs result in illogical localized temperature and precipitation changes. Differences in thermal changes between Noah-MP and CLM-AF indicate that the temperature impacts from LULCC are dependent on the sensitivity of evapotranspiration to LULCC in Sub-Saharan Africa. Errors in land surface parameters indicate that the default WRF LSMs considered are not suitable for LULCC experiments in tropical or Southern Hemisphere regions and that proficient meteorological model performance can mask these issues. We find CLM-AF to be suitable for use in Sub-Saharan Africa LULCC studies, but more work is needed by the WRF community to improve its applicability to other tropical and Southern Hemisphere climates.

scholarly journals Cooling Effect of Different Land Cover Types: A Case Study in Xi’an and Xianyang, China

2021 ◽  
Vol 13 (3) ◽  
pp. 1099
Author(s):  
Yuhe Ma ◽  
Mudan Zhao ◽  
Jianbo Li ◽  
Jian Wang ◽  
Lifa Hu
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Cooling Effect ◽  
Heat Island ◽  
Land Cover Types ◽  
Island Effect ◽  
Urban Heat

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.

scholarly journals Key Challenges for Land Use Planning and Its Environmental Assessments in the Abuja City-Region, Nigeria

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 443
Author(s):  
Evidence Chinedu Enoguanbhor ◽  
Florian Gollnow ◽  
Blake Byron Walker ◽  
Jonas Ostergaard Nielsen ◽  
Tobia Lakes
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Environmental Assessment ◽  
Land Use Planning ◽  
Environmental Sustainability ◽  
Sub Saharan Africa ◽  
Environmental Assessments ◽  
City Regions ◽  
Sub Saharan ◽  
Land Cover Maps

Land use planning as strategic instruments to guide urban dynamics faces particular challenges in the Global South, including Sub-Saharan Africa, where urgent interventions are required to improve urban and environmental sustainability. This study investigated and identified key challenges of land use planning and its environmental assessments to improve the urban and environmental sustainability of city-regions. In doing so, we combined expert interviews and questionnaires with spatial analyses of urban and regional land use plans, as well as current and future urban land cover maps derived from Geographic Information Systems and remote sensing. By overlaying and contrasting land use plans and land cover maps, we investigated spatial inconsistencies between urban and regional plans and the associated urban land dynamics and used expert surveys to identify the causes of such inconsistencies. We furthermore identified and interrogated key challenges facing land use planning, including its environmental assessment procedures, and explored means for overcoming these barriers to rapid, yet environmentally sound urban growth. The results illuminated multiple inconsistencies (e.g., spatial conflicts) between urban and regional plans, most prominently stemming from conflicts in administrative boundaries and a lack of interdepartmental coordination. Key findings identified a lack of Strategic Environmental Assessment and inadequate implementation of land use plans caused by e.g., insufficient funding, lack of political will, political interference, corruption as challenges facing land use planning strategies for urban and environmental sustainability. The baseline information provided in this study is crucial to improve strategic planning and urban/environmental sustainability of city-regions in Sub-Saharan Africa and across the Global South, where land use planning faces similar challenges to address haphazard urban expansion patterns.

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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