scholarly journals Land Cover/ Land Use Change and Climate Change in Dhofar Governorate, Oman

2021 ◽  
pp. 41-47
Author(s):  
E. Ramadan ◽  
T. Al-Awadhi ◽  
Y. Charabi
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Use Changes ◽  
Spatial Differentiation ◽  
Study Results ◽  
Vegetation Activity ◽  
The Status ◽  
Landsat Satellite

The study of land cover/land use dynamics under climate change conditions is of great significance for improving sustainable ecological management. Understanding the relationships between land cover and land use changes and climate change is thus very important. Understanding the interactive and cumulative effects of climate and land-use changes are a priority for urban planners and policy makers. The present investigation is based on Landsat satellite imagery to explore changes in vegetation spatial distribution between the years from 2000 to2018 The methodology is focused on vegetation indexes tracking and algebraic overlay calculation to analyzed vegetation and their spatial differentiation, land cover change pattern, and the relationships between vegetation dynamics and land cover change in Dhofar Governorate. The study results have revealed that the vegetation vigor is lower in all years compared to 2000. The scene of 2010 shows the minimum vegetation vigor, overall. Besides, the investigation shows a statistical relationship between rainfall and the status of the health of vegetation. Monsoon rainfall has an impact of the growth of vegetation. Between 2012 and 2013, the vegetation activity shows a decreasing trend. The analysis diagnoses an area affected by the worst degree of aridity situated in the southeastern of Dhofar Mountains. Climate change is the main driving factor resulted from both human activities and rainfall fluctuation.

scholarly journals Evaluation of the effects of minimum winter temperatures on changing the type of cultivation and changing the use of agricultural lands. (Case study: Urmia county)

2021 ◽  
Author(s):  
ghasem farahmand ◽  
shariar khaledi ◽  
manijeh ghahroudi tali
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Pearson Correlation ◽  
Land Use Changes ◽  
Human Interaction ◽  
Temperature Changes ◽  
Time Period ◽  
Winter Temperatures ◽  
Landsat Satellite

Abstract Land use and land cover change (LULC) and climate change are among the major threats to the global environment. Assessing the causes of land use change and its relationship with climate change is one of the important issues that understanding its process can help better human interaction with the environment. Therefore, the purpose of this study is to evaluate the effects of climate change on changing land use and land cover. The indicators used to achieve the mentioned goal are: ((average minimum winter temperatures), Number of days (≤ 0°C), Number of days (≤-10°C) and 30-year Landsat satellite images)), CMIP5(CanESM2) model was used to predict temperature changes and CA-MARKOV model was used to predict land use changes and finally Pearson correlation coefficient test was used to measure the correlation. The results of the study indicated that, there is a direct relationship between changes of minimum winter temperatures and changing the type of cultivation and land use in Urmia city. Also, simulation of temperature changes showed that there is the highest (> 0.8) correlation between rcp4.5 scenarios and land use changes, which indicates a high probability of changes in the specified time period (2018–2033).

scholarly journals LAND USE/LAND COVER CHANGES USING MULTI-TEMPORAL SATELLITE

2020 ◽  
Vol VI-3/W1-2020 ◽  
pp. 83-90
Author(s):  
H. T. T. Nguyen ◽  
Q. T. N. Chau ◽  
A. T. Pham ◽  
H. T. Phan ◽  
P. T. X. Tran ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Land Use Changes ◽  
Natural Forest ◽  
Land Use Land Cover ◽  
Multi Temporal ◽  
Land Use Policies ◽  
Landsat Satellite ◽  
Social Economic Development

Abstract. Producing the map of land use land cover change (LULCC) at the local extent is fundamental for a variety of applications such as vegetation, forest covers, soil degradation, and global warming. Understanding the directions and spread trend of LULCC plays significant role in obtaining useful data for the local authorities in making land-use policies under the context of climate change. Dak Nong is located in the Central Highlands of Vietnam having the largest tropical forest. Over the past decades, the natural forest in the region has significantly declined due to the pressure of population growth and social-economic development. The current study analyzed the LULCC in the province over the four periods: 2005–2018, 2005–2010, 2010–2015, and 2015–2018. Information from Landsat satellite imagery captured in 2005, 2010, 2015, and 2018 was utilized to create the LULC maps and detect the land-use changes. The Random Forest (RF) was employed to categorize the images into nine different LULC classes. The study showed that classification accuracy was achieved from 72.49% to 84.55% with a kappa coefficient of 0.69 to 0.81. The findings revealed a significant decrease in the natural forest over time from 53.1% to 42.7%, 36.8%, and 34.6% in 2005, 2010, 2015, and 2018, respectively. Meanwhile, the other types of LULC showed an increase in the area over the periods, especially croplands. It was noticeable that the continuous decrease in the forest area over the years has put pressure on the natural environmental resources and generated the risk of climate change.

scholarly journals Impacts of land use changes on soil erosion in Pa Deng sub-district, adjacent area of Kaeng Krachan National Park, Thailand

2012 ◽  
Vol 7 (No. 1) ◽  
pp. 10-17 ◽  
Author(s):  
S. Wijitkosum
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
National Park ◽  
Land Use Changes ◽  
Influential Factors ◽  
Geographical Information ◽  
Adjacent Area ◽  
Erosion Risk ◽  
Study Results

Soil erosion has been considered as the primary cause of soil degradation since soil erosion leads to the loss of topsoil and soil organic matters which are essential for the growing of plants. Land use, which relates to land cover, is one of the influential factors that affect soil erosion. In this study, impacts of land use changes on soil erosion in Pa Deng sub-district, adjacent area of Kaeng Krachan National Park, Thailand, were investigated by applying remote sensing technique, geographical information system (GIS) and the Universal Soil Loss Equation (USLE). The study results revealed that land use changes in terms of area size and pattern influenced the soil erosion risk in Pa Deng in the 1990–2010 period. The area with smaller land cover obviously showed the high risk of soil erosion than the larger land cover did.

scholarly journals The Impact of Land Use/Land Cover Change (LULCC) on Water Resources in a Tropical Catchment in Tanzania under Different Climate Change Scenarios

2019 ◽  
Vol 11 (24) ◽  
pp. 7083 ◽  
Author(s):  
Kristian Näschen ◽  
Bernd Diekkrüger ◽  
Mariele Evers ◽  
Britta Höllermann ◽  
Stefanie Steinbach ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Water Resources ◽  
Land Cover ◽  
Water Balance ◽  
Land Cover Change ◽  
Sub Saharan Africa ◽  
Climate Change Scenarios ◽  
Land Use Land Cover ◽  
The Impact

Many parts of sub-Saharan Africa (SSA) are prone to land use and land cover change (LULCC). In many cases, natural systems are converted into agricultural land to feed the growing population. However, despite climate change being a major focus nowadays, the impacts of these conversions on water resources, which are essential for agricultural production, is still often neglected, jeopardizing the sustainability of the socio-ecological system. This study investigates historic land use/land cover (LULC) patterns as well as potential future LULCC and its effect on water quantities in a complex tropical catchment in Tanzania. It then compares the results using two climate change scenarios. The Land Change Modeler (LCM) is used to analyze and to project LULC patterns until 2030 and the Soil and Water Assessment Tool (SWAT) is utilized to simulate the water balance under various LULC conditions. Results show decreasing low flows by 6–8% for the LULC scenarios, whereas high flows increase by up to 84% for the combined LULC and climate change scenarios. The effect of climate change is stronger compared to the effect of LULCC, but also contains higher uncertainties. The effects of LULCC are more distinct, although crop specific effects show diverging effects on water balance components. This study develops a methodology for quantifying the impact of land use and climate change and therefore contributes to the sustainable management of the investigated catchment, as it shows the impact of environmental change on hydrological extremes (low flow and floods) and determines hot spots, which are critical for environmental development.

Comprehensive evaluation of the effects of climate change and land use and land cover change variables on runoff and sediment discharge

2020 ◽  
Author(s):  
Huilan Zhang
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Land Cover Change ◽  
Hydrological Modeling ◽  
Sediment Load ◽  
Statistical Analyses ◽  
Sediment Discharge ◽  
Runoff Depth

<p>Climate change and various human activities have resulted in noticeable changes in watershed hydrological and soil erosion regimes. In this study, a comprehensive investigation was conducted to distinguish between the effects of climate variables and those of land use and land cover change (LUCC) variables on runoff and sediment discharge in a watershed located at upper reaches of the Yangtze River. Statistical analysis results revealed significant and slight increasing trends in runoff and sediment discharge, respectively. Abrupt changes occurred in 1974 and 1995, which divided the entire time series into a decrease–increase–decrease tendency pattern; this pattern was the response to climate changes and the Reforestation and Returning Farmland to Forest project in China. In addition, redundancy analysis was used for partition statistical analyses, and the contributions of climate change and LUCC to runoff and sediment discharge were at the ratio of 4:1. Since 1990, the effect of LUCC has increased notably and its relationship with hydrological variables changed from positive to negative in approximately 1995. Finally, simulations performed using the distributed Basic Pollution Calculation Center (BPCC) model confirmed that climate and LUCC variables reduced the runoff depth and sediment load between 1980 and 2003. The contributions of climate fluctuation and LUCC to runoff depth were at the ratio of 5:1, and those to sediment load were at the ratio of 3:1, which exhibited the dominant role of climate change and the high sensitivity of sediment load to human interference. Overall, the results of distributed hydrological modeling were consistent with those of statistical analyses. The results provided detailed information and explained the mechanics underlying hydrological processes and soil erosion.</p><p> </p>

scholarly journals Assessment and simulation of land use and land cover change impacts on the land surface temperature of Chaoyang District in Beijing, China

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9115 ◽  
Author(s):  
Muhammad Amir Siddique ◽  
Liu Dongyun ◽  
Pengli Li ◽  
Umair Rasool ◽  
Tauheed Ullah Khan ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Cover Change ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Rapid Urbanization ◽  
K Value ◽  
Vegetation Water ◽  
Landsat Satellite

Rapid urbanization is changing the existing patterns of land use land cover (LULC) globally, which is consequently increasing the land surface temperature (LST) in many regions. The present study is focused on estimating current and simulating future LULC and LST trends in the urban environment of Chaoyang District, Beijing. Past patterns of LULC and LST were identified through the maximum likelihood classification (MLC) method and multispectral Landsat satellite images during the 1990–2018 data period. The cellular automata (CA) and stochastic transition matrix of the Markov model were applied to simulate future (2025) LULC and LST changes, respectively, using their past patterns. The CA model was validated for the simulated and estimated LULC for 1990–2018, with an overall Kappa (K) value of 0.83, using validation modules in IDRISI software. Our results indicated that the cumulative changes in built-up to vegetation area were 74.61 km2 (16.08%) and 113.13 km2 (24.38%) from 1990 to 2018. The correlation coefficient of land use and land cover change (LULCC), including vegetation, water bodies and built-up area, had values of r =  − 0.155 (p > 0.005), −0.809 (p = 0.000), and 0.519 (p > 0.005), respectively. The results of future analysis revealed that there will be an estimated 164.92 km2 (−12%) decrease in vegetation area, while an expansion of approximately 283.04 km2 (6% change) will occur in built-up areas from 1990 to 2025. This decrease in vegetation cover and expansion of settlements would likely cause a rise of approximately ∼10.74 °C and ∼12.66 °C in future temperature, which would cause a rise in temperature (2025). The analyses could open an avenue regarding how to manage urban land cover patterns to enhance the resilience of cities to climate warming. This study provides scientific insights for environmental development and sustainability through efficient and effective urban planning and management in Beijing and will also help strengthen other research related to the UHI phenomenon in other parts of the world.

scholarly journals Can we reconcile differences in estimates of carbon fluxes from land-use change and forestry for the 1990s?

2008 ◽  
Vol 8 (1) ◽  
pp. 3843-3893 ◽  
Author(s):  
A. Ito ◽  
J. E. Penner ◽  
M. J. Prather ◽  
C. P. de Campos ◽  
R. A. Houghton ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Carbon Fluxes ◽  
Terrestrial Carbon ◽  
Co2 Fertilization ◽  
Uncertainty Range ◽  
Inverse Models ◽  
The Usa

Abstract. The effect of Land Use Change and Forestry (LUCF) on terrestrial carbon fluxes can be regarded as a carbon credit or debit under the UNFCCC, but scientific uncertainty in the estimates for LUCF remains large. Here, we assess the LUCF estimates by examining a variety of models of different types with different land cover change maps in the 1990s. Annual carbon pools and their changes are separated into different components for separate geographical regions, while annual land cover change areas and carbon fluxes are disaggregated into different LUCF activities and the biospheric response due to CO2 fertilization and climate change. We developed a consolidated estimate of the terrestrial carbon fluxes that combines book-keeping models with process-based biogeochemical models and inventory estimates and yields an estimate of the global terrestrial carbon flux that is within the uncertainty range developed in the IPCC 4th Assessment Report. We examined the USA and Brazil as case studies in order to assess the cause of differences from the UNFCCC reported carbon fluxes. Major differences in the litter and soil organic matter components are found for the USA. Differences in Brazil result from assumptions about the LUC for agricultural purposes. The effects of CO2 fertilization and climate change also vary significantly in Brazil. Our consolidated estimate shows that the small sink in Latin America is within the uncertainty range from inverse models, but that the sink in the USA is significantly smaller than the inverse models estimates. Because there are different sources of errors at the country level, there is no easy reconciliation of different estimates of carbon fluxes at the global level. Clearly, further work is required to develop data sets for historical land cover change areas and models of biogeochemical changes for an accurate representation of carbon uptake or emissions due to LUC.

scholarly journals Global Transition Rules for Translating Land-use Change (LUH2) To Land-cover Change for CMIP6 using GLM2

2019 ◽  
Author(s):  
Lei Ma ◽  
George C. Hurtt ◽  
Louise P. Chini ◽  
Ritvik Sahajpal ◽  
Julia Pongratz ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Human Impacts ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
Transition Rule ◽  
The Relationship ◽  
Earth System Models

Abstract. Information on historical land-cover change is important for understanding human impacts on the environment. Over the last decade, global models have characterized historical land-use changes, but few have been able to relate these changes with corresponding changes in land-cover. Utilizing the latest global land-use change data, we make several assumptions about the relationship between land-use and land-cover change, and evaluate each scenario with remote sensing data to identify optimal fit. The resulting transition rule can guide the incorporation of land-cover information within earth system models.

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