scholarly journals Targeting area and comparing the effect of different land use/land cover (LULC) scenarios on greenhouse gases (GHGs) emission reduction (Case study: Hyrcanian forests in Iran)

2020 ◽  
Author(s):  
Hamidreza Kamyab ◽  
Zahra Asadolahi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Greenhouse Gases ◽  
Baseline Scenario ◽  
Land Use Land Cover ◽  
Success Rates ◽  
Lulc Change ◽  
Project Area ◽  
Hyrcanian Forests ◽  
Multi Criteria Evaluation

Abstract Background Because the greenhouse gases (GHGs) emissions are known to be strongly influenced by land use/land cover (LULC) change, reducing emissions from deforestation and degradation (REDD) mechanism has attracted much attention as a strategy for understanding how different LULC scenarios effect on the GHGs emissions. Transition to other LULC types is one of the major challenges of Iran's Hyrcanian forests in Golestan province. To consider how LULC change scenarios affect GHGs, REDD project was executed in a period of 30 years (2018–2048) at intervals of 5 years. In this regard, study area was divided into the project area and leakage belt based on the Multi Criteria Evaluation (MCE) derived forest suitability map. In the baseline scenario, it was assumed that the trend of past LULC changes will continue. Results By implementation of the project scenario, some degradation activities were controlled. Project scenario was executed with different project success rates (PSR) of 90, 80, 70, 60 and 50% to examine its efficiency rate in reducing GHGs emissions. According to the results, 38206.8 hectares of forests within the project area will be destroyed by 2047 under the baseline. The destroyed area will be reach 39784.4 hectares in the leakage belt. The highest rate of forest destruction in the project area will occur in the last 5 years (1352 hectares per year), so the highest CO2 and non-CO2 emissions equal to 662655.3 tons/year and 278.94 tCO2e/year will happen in the last 5 years (2042–2047). Based on the results, reducing the PSR affected the efficiency of the project scenario. The highest and lowest rates of emissions reduction were observed respectively with PSR of 90 and 50%. Conclusions That's very important for developing countries especially Iran that are facing many challenging forest conservation decisions. This study innovated in methodology by integrating the MCE into the REDD steps. The MCE as a spatial targeting method could be applied to increase the efficiency of the REDD project, as we illustrated for the case of Hyrcanian forests.

scholarly journals Impact of Climate and Land Use/Land Cover Change on the Water Resources of a Tropical Inland Valley Catchment in Uganda, East Africa

Climate ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 83
Author(s):  
Geofrey Gabiri ◽  
Bernd Diekkrüger ◽  
Kristian Näschen ◽  
Constanze Leemhuis ◽  
Roderick van der Linden ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Water Resources ◽  
Land Cover ◽  
Rainy Season ◽  
Hydrological Processes ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Inland Valley ◽  
Headwater Catchment

The impact of climate and land use/land cover (LULC) change continues to threaten water resources availability for the agriculturally used inland valley wetlands and their catchments in East Africa. This study assessed climate and LULC change impacts on the hydrological processes of a tropical headwater inland valley catchment in Uganda. The hydrological model Soil and Water Assessment Tool (SWAT) was applied to analyze climate and LULC change impacts on the hydrological processes. An ensemble of six regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment for two Representative Concentration Pathways (RCPs), RCP4.5 and RCP8.5, were used for climate change assessment for historical (1976–2005) and future climate (2021–2050). Four LULC scenarios defined as exploitation, total conservation, slope conservation, and protection of headwater catchment were considered. The results indicate an increase in precipitation by 7.4% and 21.8% of the annual averages in the future under RCP4.5 and RCP8.5, respectively. Future wet conditions are more pronounced in the short rainy season than in the long rainy season. Flooding intensity is likely to increase during the rainy season with low flows more pronounced in the dry season. Increases in future annual averages of water yield (29.0% and 42.7% under RCP4.5 and RCP8.5, respectively) and surface runoff (37.6% and 51.8% under RCP4.5 and RCP8.5, respectively) relative to the historical simulations are projected. LULC and climate change individually will cause changes in the inland valley hydrological processes, but more pronounced changes are expected if the drivers are combined, although LULC changes will have a dominant influence. Adoption of total conservation, slope conservation and protection of headwater catchment LULC scenarios will significantly reduce climate change impacts on water resources in the inland valley. Thus, if sustainable climate-smart management practices are adopted, the availability of water resources for human consumption and agricultural production will increase.

scholarly journals Impact of Land Use Land Cover (LULC) Change on Surface Runoff in an Increasingly Urbanized Tropical Watershed

2019 ◽  
Vol 33 (12) ◽  
pp. 4087-4103 ◽  
Author(s):  
Ike Sari Astuti ◽  
Kamalakanta Sahoo ◽  
Adam Milewski ◽  
Deepak R. Mishra
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Runoff ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Tropical Watershed

Tracking the Land Use/Land Cover Change in an Area with Underground Mining and Reforestation via Continuous Landsat Classification

2019 ◽  
Vol 11 (14) ◽  
pp. 1719 ◽  
Author(s):  
Jiaxin Mi ◽  
Yongjun Yang ◽  
Shaoliang Zhang ◽  
Shi An ◽  
Huping Hou ◽  
...  
Keyword(s):  
Land Use ◽  
Random Forest ◽  
Land Cover ◽  
Large Scale ◽  
Underground Mining ◽  
Mining Area ◽  
Random Forest Classifier ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Mining Areas

Understanding the changes in a land use/land cover (LULC) is important for environmental assessment and land management. However, tracking the dynamic of LULC has proved difficult, especially in large-scale underground mining areas with extensive LULC heterogeneity and a history of multiple disturbances. Additional research related to the methods in this field is still needed. In this study, we tracked the LULC change in the Nanjiao mining area, Shanxi Province, China between 1987 and 2017 via random forest classifier and continuous Landsat imagery, where years of underground mining and reforestation projects have occurred. We applied a Savitzky–Golay filter and a normalized difference vegetation index (NDVI)-based approach to detect the temporal and spatial change, respectively. The accuracy assessment shows that the random forest classifier has a good performance in this heterogeneous area, with an accuracy ranging from 81.92% to 86.6%, which is also higher than that via support vector machine (SVM), neural network (NN), and maximum likelihood (ML) algorithm. LULC classification results reveal that cultivated forest in the mining area increased significantly after 2004, while the spatial extent of natural forest, buildings, and farmland decreased significantly after 2007. The areas where vegetation was significantly reduced were mainly because of the transformation from natural forest and shrubs into grasslands and bare lands, respectively, whereas the areas with an obvious increase in NDVI were mainly because of the conversion from grasslands and buildings into cultivated forest, especially when villages were abandoned after mining subsidence. A partial correlation analysis demonstrated that the extent of LULC change was significantly related to coal production and reforestation, which indicated the effects of underground mining and reforestation projects on LULC changes. This study suggests that continuous Landsat classification via random forest classifier could be effective in monitoring the long-term dynamics of LULC changes, and provide crucial information and data for the understanding of the driving forces of LULC change, environmental impact assessment, and ecological protection planning in large-scale mining areas.

Interactions between land use/land cover change, forest fires and landscape structure in Sierra de Gredos (Central Spain)

2006 ◽  
Vol 33 (3) ◽  
pp. 212-222 ◽  
Author(s):  
OLGA VIEDMA ◽  
JOSÉ M. MORENO ◽  
IGNACIO RIEIRO
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Landscape Structure ◽  
Landscape Patterns ◽  
Land Use Land Cover ◽  
Central Spain ◽  
Lulc Change ◽  
Burned Areas ◽  
In Fire

In fire-prone areas, like the Mediterranean, land abandonment and forestation may interact with fire to alter landscape properties and eventually fire hazard and occurrence. However, the spatial interactions among the two processes (land-use/land cover change [LULC] and fire) are poorly known. Here, we analysed the relative effect of LULC change and fire on the landscape structure of an area of Central Spain frequently affected by fire. A series of Landsat MSS images from 1975 to 1990 was analysed to quantify annual changes in LULC, map fire perimeters and evaluate the changes in landscape properties. The temporal dynamics were analysed by annually computing the fraction occupied by each LULC type and landscape structural properties (number, size, shape and arrangement of patches) that might play a role in fire propagation. All of these were calculated separately for the unburned or the burned areas during the study period, as well as for the entire area. At the whole landscape level, or in the unburned area, LULC changes were small, yet the two more flammable LULC types tended to increase, and the landscape tended to become more homogeneous. In the burned area, the area covered by pine woodlands tended to decrease, and that covered by shrublands to increase. Burned areas turned into shrublands only five years after fire. Landscape indices indicative of reduced fragmentation were also found. Both LULC change and fire altered landscape patterns in the whole area to create a less fragmented and more contiguous landscape than in 1975. The changes induced in the whole landscape by fire, in spite of the overall low disturbance rate, were sufficient to closely determine the changes in landscape composition (LULC types) and patterns.

scholarly journals Main directions in modern research of interaction between climate and land use/land cover changes

2020 ◽  
pp. 38-52
Author(s):  
L. A. Pysarenko ◽  
S. V. Krakovska
Keyword(s):  
Boundary Layer ◽  
Land Use ◽  
Chemical Composition ◽  
Land Cover ◽  
Atmospheric Boundary Layer ◽  
Meteorological Parameters ◽  
Regional Climate ◽  
Anthropogenic Factors ◽  
Land Use Land Cover ◽  
Lulc Change

The purpose of the research is to analyse and assess existing approaches in investigation of interconnections between climate and underlying surface. Land use/land cover (LULC) influences climate formation via physical and chemical properties (albedo, roughness, height, chemical composition etc.). Climate in its turn affects land cover by means of meteorological parameters (air temperature and humidity, precipitation, wind etc.) and causes both cyclic and irreversible changes in land cover. In addition, anthropogenic factors exacerbate surface-climate interactions through? for example, LULC change that usually causes an additional release of chemical compounds. The paper distinguishes three main directions of the “climate - LULC” interactions research that is conducted mainly with application of satellite monitoring products, observation dataset, geographic information systems (GIS) and numerical modelling. The first direction implies monitoring and research of cyclic changes and transformation of LULC influenced by natural and anthropogenic factors, using different GIS-based satellite and surface meteorological observation databases. Despite significant technical progress and great amount of studies conducted for detecting dynamics of LULC change for different time intervals, the problems of dealing with cloudiness and shadows from orographic and other objects still remain. The second direction investigates the influence of LULC change on the chemical composition in the atmospheric boundary layer and on the regional climate. Numerous researches were dedicated to the influence of different kinds of surface such as forests, grasslands, croplands, urban areas etc. on climate characteristics and also on fluxes, for example, CO2. The effect of midlatitude forests on climate remains to be one of the challenging and urgent issues. The third direction relates to LULC change modelling and regional climate modelling. For the last decade a spatial resolution of models was considerably increased and, as a result, representation of interaction between atmosphere and land improved. Online integrated numerical atmospheric models are found as the most promising ones. They include "meteorological parameters – atmospheric chemical composition" feedbacks and can consider LULC on global and regional scales. However, some issues still need improvement, namely radiative transfer, cloud microphysics, cloud-aerosol-precipitation interactions, as well as parametrizations of some types of land and their interaction with the atmospheric boundary layer.

scholarly journals Land Use/ Land Cover Dynamics Study and Prediction In Jaipur City us­ing CA Markov Model Integrated with Road Network

2021 ◽  
Author(s):  
Nitesh Kumar Mourya ◽  
Sana Rafi ◽  
Saima Shamoo
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Road Network ◽  
Markov Chain Model ◽  
Chain Model ◽  
Land Use Land Cover ◽  
Visual Interpretation ◽  
Lulc Change ◽  
Barren Land ◽  
Jaipur City

Abstract Land Use Land Cover (LULC) dynamics analysis is critical and should be done regularly. It draws attention to LULC developments that can be addressed before they become unmanageable disasters or circumstances. For the years 2000, 2010, and 2020, LULC change analysis was carried out in Jaipur City, Rajasthan, India. The LULC maps were created using Landsat data through a visual interpretation technique at a scale of 1:50,000. These maps were classified into vegetation, agriculture, built-up areas, barren land, and water bodies. LULC was predicted by extrapolating the current LULC change pattern. Using a Cellular Automata-Markov Chain Model (CA Markov) integrated with road network, the current LULC change trend was extrapolated and utilized to estimate the LULC map for the years 2020, 2030, 2040, and 2050. The strategy was validated by estimating LULC change for 2020 and comparing it to the actual LULC map for that year. The urban area contributed to 4. 75% in 2000 of the total area in Jaipur city. The percentage of area under urban class has increased to 9.68% in 2010 and 12.96% in 2020. The prediction based on 2000-2010 and 2010-2020 has shown an unprecedented decadal growth in the built-up area till 2050. The prediction based on the 2000-2010 period has shown a rise of 92.04 % during 2020-2030, 77.13 % during 2030-2040 and, 64.34 % during 2040-2050. The prediction based on the 2010-2020 period has shown a rise of 102.42% during 2020-2030, 73.56% during 2030-2040 and, 54.47 % during 2040-2050. This study is, therefore, calls for policy interventions to manage population and urban growth.

scholarly journals Drivers and Dynamics of Land Use Land Cover in Phewa Watershed, Kaski, Nepal

2020 ◽  
Vol 2 (1) ◽  
pp. 19-36
Author(s):  
Sudip Raj Regmi ◽  
Mahendra Singh Thapa ◽  
Raju Raj Regmi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Road Construction ◽  
Rate Of Change ◽  
Lake Area ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Barren Land ◽  
Area Change

Geospatial tools play an important role in monitoring Land Use Land Cover (LULC) dynamics. This study assessed the extent of LULC changes during 2003, 2010 and 2018 using temporal satellite imageries, computed the rate of change in area of Phewa Lake and explored the drivers of LULC change and lake area change in Phewa watershed. It used Landsat Imageries for 2003, 2010 and 2018 and carried out purposive household survey (N=60), key informant survey (N=5), focus group discussion (N=4) and direct field observation to explore the drivers of LULC change and lake area change. It generated LULC maps by using supervised classification and computed LULC change by applying post classification change detection technique. On screen digitization was done to find the area of Phewa Lake during 2010 and 2018. Agricultural land and urban areas were found to have increased by 11.63% and 1.46% respectively while forest area, barren land and water bodies were found to have decreased by 9.21%, 3.56% and 0.5% respectively between 2003 and 2010. Forest area, urban areas and barren land were found to have increased by 5.9%, 3.28% and 5.02% respectively while agricultural landand water bodies were observed to have decreased by 7.83% and 0.16% respectively between 2010 and 2018. During 2010-2018, rate of change in lake area was found to have decreased by 0.61% with periodic annual decrement by 2.59 ha. The drivers responsible for LULC change were alternative form of energy, community forestry, promotion of private forestry, migration for foreign employment, inadequate market price of agricultural products, road construction, soil erosion and population pressure. Lake area was found to have decreased due to sedimentation, encroachment and road construction. Further study is important to know the exact contributions of these drivers of LULC change and lake area change for the sustainability of Phewa watershed.

scholarly journals Monitoring and Predicting Spatio-Temporal Land Use/Land Cover Changes in Zaria City, Nigeria, through an Integrated Cellular Automata and Markov Chain Model (CA-Markov)

2020 ◽  
Vol 12 (24) ◽  
pp. 10452
Author(s):  
Auwalu Faisal Koko ◽  
Wu Yue ◽  
Ghali Abdullahi Abubakar ◽  
Roknisadeh Hamed ◽  
Akram Ahmed Noman Alabsi
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Cellular Automata ◽  
Land Cover ◽  
Markov Chain Model ◽  
Chain Model ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Barren Land ◽  
Spatio Temporal

Monitoring land use/land cover (LULC) change dynamics plays a crucial role in formulating strategies and policies for the effective planning and sustainable development of rapidly growing cities. Therefore, this study sought to integrate the cellular automata and Markov chain model using remotely sensed data and geographical information system (GIS) techniques to monitor, map, and detect the spatio-temporal LULC change in Zaria city, Nigeria. Multi-temporal satellite images of 1990, 2005, and 2020 were pre-processed, geo-referenced, and mapped using the supervised maximum likelihood classification to examine the city’s historical land cover (1990–2020). Subsequently, an integrated cellular automata (CA)–Markov model was utilized to model, validate, and simulate the future LULC scenario using the land change modeler (LCM) of IDRISI-TerrSet software. The change detection results revealed an expansion in built-up areas and vegetation of 65.88% and 28.95%, respectively, resulting in barren land losing 63.06% over the last three decades. The predicted LULC maps of 2035 and 2050 indicate that these patterns of barren land changing into built-up areas and vegetation will continue over the next 30 years due to urban growth, reforestation, and development of agricultural activities. These results establish past and future LULC trends and provide crucial data useful for planning and sustainable land use management.

scholarly journals Remote Sensing and GIS Application for Land use/ Land cover Change Analysis: Case Study of Jarmet Wet-Land and its Surrounding Environments in Western Ethiopia

2019 ◽  
Author(s):  
Amanuel Kumsa ◽  
Professor Sileshi Nemomissa ◽  
Asmamaw (PhD) Legas ◽  
Dessalegn Gurmessa
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Environmental Change ◽  
Land Cover Change ◽  
Natural Resource ◽  
Accuracy Assessment ◽  
Land Use Land Cover ◽  
Change Analysis ◽  
Lulc Change

Wetlands are one of the crucial natural resources. They provide invaluable biodiversity resources, aid in water quality improvement, support ground water recharge, help in moderating climate change and support flood control. Environment is in the other hand, where we live and something, we are very familiar with our day to day life. Geographic Information Systems (GIS), Remote Sensing and Global Positioning System (GPS) were a useful tool for wetland and environmental change analysis and to improve on the classification accuracy. This study investigates population and environmental change of Jarmet wetland and its surrounding area change analysis over the period of 1972 to 2015. The purpose of this study was to show land use/ land cover change of Jarmet wetland and its surrounding environment over years as a response to population growth. For this purpose, multi-temporal satellite imageries (Landsat MSS 1972, TM1986, ETM+ 2000, 2005 and 2015 and SRTM 2000) were obtained and used for LULC change analysis, elevation analysis and change detection analysis. ERDAS Imagine 2015, ARC GIS 10.5.1, Global Mapper11, ENVI 5.0 and DNR Garmin softwares were used to process the image data and accuracy assessment analysis. The result of LULC showed that there is spatial reduction in wetland, forest, Shrubland and grassland in the period of 43 years (1972-2015) by -1,722.8 ha, -296.2 ha, -1,718.7 ha and -661.9 ha respectively, due to increase in the farmland and plantation area as a response to overpopulation, lack of environmental policy implementation and irresponsible for natural resource degradation. The accuracy assessment of LULC change are done for recent satellite image showed the overall accuracy of 84.06% with Kappa index 75.19% this means this classification is accurately classified and handle greater than 75% of error. Finally, this study suggests that create strictly natural resource conservation law, stopping illegal expansion of farmland, educating society about the value of natural resource especially wetland and create a source of income for society rather than farming.

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