scholarly journals An Elevation-Based Stratification Model for Simulating Land Use Change

2018 ◽  
Vol 10 (11) ◽  
pp. 1730 ◽  
Author(s):  
Erqi Xu ◽  
Hongqi Zhang ◽  
Lina Yao
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Surface ◽  
Socioeconomic Development ◽  
Accuracy Assessment ◽  
Elevation Gradient ◽  
Management Strategies ◽  
Rapid Expansion ◽  
Land Uses ◽  
Simulation Performance

Land use significantly influences the planet’s land surface and associated biogeochemical processes. With fierce conflict between various land uses, it is important to project the land system process to support decision-making. Lack of insight into scale differences of land use change (LUC) increased uncertainties in previous studies. To quantify the differences in LUCs within an elevation gradient, in this study, a novel model, the stratified land use change simulation model (SLUCS), was developed by using an elevation-based stratification strategy. This model consists of four modules. First, an elevation-based stratification module to develop a quantitative method for generating stratifications using elevation and land-use characteristics. Second, a non-spatial land-use demand module to forecast the overall land use area and make zoning constraints to simulate LUCs. Third, a stratified suitability estimation module that uses the stratified logistic regression method to reveal the regional relationship of the driving factors with LUCs at different stratifications. Finally, a spatial allocation of the land-use module, which projects a spatially explicit LUC. The SLUCS model was applied and tested in the Guizhou and Guangxi Karst Mountainous Region. Results validated the effectiveness of the model, and further demonstrated an improved spatial consistency with the reference, a higher accuracy assessment, and a better simulation performance in conversion areas than the traditional method. Three scenarios from 2015 to 2030 with different land-use priorities were designed and projected. Each scenario presented the same LUC trends, but with different magnitudes, including the rapid expansion of built-up land, the restoration of forest and water, and the loss of farmland and grassland. Priority of the socioeconomic development and ecological protection of the scenarios forecasted a sharper increase in the built-up land and in forests than the historical extrapolation scenario. The SLUCS model visually projected the LUC trajectory and competition between land uses, which suggests specific tradeoffs among management strategies to support sustainable land uses.

scholarly journals Regional Variations of Land-Use Development and Land-Use/Cover Change Dynamics: A Case Study of Turkey

2019 ◽  
Vol 11 (7) ◽  
pp. 885 ◽  
Author(s):  
Ustaoglu ◽  
Aydınoglu
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Rural Areas ◽  
Urban Areas ◽  
Urban Land ◽  
Temporal Changes ◽  
Rapid Expansion ◽  
Land Uses ◽  
Hierarchical Levels ◽  
Spatio Temporal

. Population growth, economic development and rural-urban migration have caused rapid expansion of urban areas and metropolitan regions in Turkey. The structure of urban administration and planning has faced different socio-economic and political challenges, which have hindered the structured and planned development of cities and regions, resulting in an irregular and uneven development of these regions. We conducted detailed comparative analysis on spatio-temporal changes of the identified seven land-use/cover classes across different regions in Turkey with the use of Corine Land Cover (CLC) data of circa 1990, 2000, 2006 and 2012, integrated with Geographic Information System (GIS) techniques. Here we compared spatio-temporal changes of urban and non-urban land uses, which differ across regions and across different hierarchical levels of urban areas. Our findings have shown that peri-urban areas are growing more than rural areas, and even growing more than urban areas in some regions. A deeper look at regions located in different geographical zones pointed to substantial development disparities across western and eastern regions of Turkey. We also employed multiple regression models to explain any possible drivers of land-use change, regarding both urban and non-urban land uses. The results reveal that the three influencing factors-socio-economic characteristics, regional characteristics and location, and development constraints, facilitate land-use change. However, their impacts differ in different geographical locations, as well as with different hierarchical levels.

scholarly journals State of Amphibia 2020: Five years of amphibian research, diversity and resources

2021 ◽  
Author(s):  
Molly C. Womack ◽  
Emma Steigerwald ◽  
David Blackburn ◽  
David C. Cannatella ◽  
Alessandro Catenazzi ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Management Strategies ◽  
Genomic Data ◽  
Data Availability ◽  
Rapid Expansion ◽  
Database Integration ◽  
Community Resources ◽  
Research Fields ◽  
Geographic Regions

Amphibians are a clade of over 8,400 species that provide unique research opportunities and challenges. With amphibians undergoing severe global declines, taking stock of our current understanding of amphibians is imperative. Focusing on 2016–2020, we assessed trends in amphibian publishing, conservation research, systematics, and community resources. We show that while research and data availability are increasing rapidly, information is not evenly distributed across research fields, clades, or geographic regions, leading to substantial knowledge gaps. A complete review of amphibian NCBI resources indicates that genomic data are poised for rapid expansion, but amphibian genomes pose significant challenges. A review of recent conservation literature and cataloged threats on 1,261 species highlight the need to address land use change and disease using adaptive management strategies. We underscore the importance of database integration for advancing amphibian research and conservation and suggest other understudied or imperiled clades would benefit from similar assessments.

scholarly journals Rapid expansion of human impact on natural land in South America since 1985

2021 ◽  
Vol 7 (14) ◽  
pp. eabg1620
Author(s):  
Viviana Zalles ◽  
Matthew C. Hansen ◽  
Peter V. Potapov ◽  
Diana Parker ◽  
Stephen V. Stehman ◽  
...  
Keyword(s):  
Land Use ◽  
South America ◽  
Land Cover ◽  
Human Impact ◽  
Land Surface ◽  
Rapid Expansion ◽  
Tree Cover ◽  
Land Uses ◽  
Natural Ecosystems ◽  
Natural Land

Across South America, the expansion of commodity land uses has underpinned substantial economic development at the expense of natural land cover and associated ecosystem services. Here, we show that such human impact on the continent’s land surface, specifically land use conversion and natural land cover modification, expanded by 268 million hectares (Mha), or 60%, from 1985 to 2018. By 2018, 713 Mha, or 40%, of the South American landmass was impacted by human activity. Since 1985, the area of natural tree cover decreased by 16%, and pasture, cropland, and plantation land uses increased by 23, 160, and 288%, respectively. A substantial area of disturbed natural land cover, totaling 55 Mha, had no discernable land use, representing land that is degraded in terms of ecosystem function but not economically productive. These results illustrate the extent of ongoing human appropriation of natural ecosystems in South America, which intensifies threats to ecosystem-scale functions.

scholarly journals Changes in Coastal Agricultural Land Use in Response to Climate Change: An Assessment Using Satellite Remote Sensing and Household Survey Data in Tien Hai District, Thai Binh Province, Vietnam

Land ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 627
Author(s):  
Duong H. Nong ◽  
An T. Ngo ◽  
Hoa P. T. Nguyen ◽  
Thuy T. Nguyen ◽  
Lan T. Nguyen ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Management Strategies ◽  
Household Survey ◽  
Extreme Weather Events ◽  
Agricultural Land Use ◽  
Landsat 8 ◽  
Land Uses

We analyzed the agricultural land-use changes in the coastal areas of Tien Hai district, Thai Binh province, in 2005, 2010, 2015, and 2020, using Landsat 5 and Landsat 8 data. We used the object-oriented classification method with the maximum likelihood algorithm to classify six types of land uses. The series of land-use maps we produced had an overall accuracy of more than 80%. We then conducted a spatial analysis of the 5-year land-use change using ArcGIS software. In addition, we surveyed 150 farm households using a structured questionnaire regarding the impacts of climate change on agricultural productivity and land uses, as well as farmers’ adaptation and responses. The results showed that from 2005 to 2020, cropland decreased, while aquaculture land and forest land increased. We observed that the most remarkable decreases were in the area of rice (485.58 ha), the area of perennial crops (109.7 ha), and the area of non-agricultural land (747.35 ha). The area of land used for aquaculture and forest increased by 566.88 ha and 772.60 ha, respectively. We found that the manifestations of climate change, such as extreme weather events, saltwater intrusion, drought, and floods, have had a profound impact on agricultural production and land uses in the district, especially for annual crops and aquaculture. The results provide useful information for state authorities to design land-management strategies and solutions that are economic and effective in adapting to climate change.

scholarly journals Social Sensing for Urban Land Use Identification

2020 ◽  
Vol 9 (9) ◽  
pp. 550
Author(s):  
Adindha Anugraha ◽  
Hone-Jay Chu ◽  
Muhammad Ali
Keyword(s):  
Land Use ◽  
Accuracy Assessment ◽  
Urban Land ◽  
Demographic Characteristics ◽  
Urban Land Use ◽  
Land Uses ◽  
Land Use Classification ◽  
Residential Areas ◽  
Social Sensing ◽  
Land Use Maps

The utilization of urban land use maps can reveal the patterns of human behavior through the extraction of the socioeconomic and demographic characteristics of urban land use. Remote sensing that holds detailed and abundant information on spectral, textual, contextual, and spatial configurations is crucial to obtaining land use maps that reveal changes in the urban environment. However, social sensing is essential to revealing the socioeconomic and demographic characteristics of urban land use. This data mining approach is related to data cleaning/outlier removal and machine learning, and is used to achieve land use classification from remote and social sensing data. In bicycle and taxi density maps, the daytime destination and nighttime origin density reflects work-related land uses, including commercial and industrial areas. By contrast, the nighttime destination and daytime origin density pattern captures the pattern of residential areas. The accuracy assessment of land use classified maps shows that the integration of remote and social sensing, using the decision tree and random forest methods, yields accuracies of 83% and 86%, respectively. Thus, this approach facilitates an accurate urban land use classification. Urban land use identification can aid policy makers in linking human activities to the socioeconomic consequences of different urban land uses.

Changes in Land Use Influenced by Anthropogenic Activity

2020 ◽  
Author(s):  
Lang Wang ◽  
Zong-Liang Yang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Management ◽  
Land Surface ◽  
Anthropogenic Activities ◽  
Urban Expansion ◽  
Management Strategies ◽  
Terrestrial Ecosystems ◽  
Anthropogenic Activity ◽  
Management Actions

The terms “land cover” and “land use” are often used interchangeably, although they have different meanings. Land cover is the biophysical material at the surface of the Earth, whereas land use refers to how people use the land surface. Land use concerns the resources of the land, their products, and benefits, in addition to land management actions and activities. The history of changes in land use has passed through several major stages driven by developments in science and technology and demands for food, fiber, energy, and shelter. Modern changes in land use have been increasingly affected by anthropogenic activities at a scale and magnitude that have not been seen. These changes in land use are largely driven by population growth, urban expansion, increasing demands for energy and food, changes in diets and lifestyles, and changing socioeconomic conditions. About 70% of the Earth’s ice-free land surface has been altered by changes in land use, and these changes have had environmental impacts worldwide, ranging from effects on the composition of the Earth’s atmosphere and climate to the extensive modification of terrestrial ecosystems, habitats, and biodiversity. A number of different methods have been developed give a thorough understanding of these changes in land use and the multiple effects and feedbacks involved. Earth system observations and models are examples of two crucial technologies, although there are considerable uncertainties in both techniques. Cross-disciplinary collaborations are highly desirable in future studies of land use and management. The goals of mitigating climate change and maintaining sustainability should always be considered before implementing any new land management strategies.

scholarly journals Effects of Urbanization on Watershed Evapotranspiration and Its Components in Southern China

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 645 ◽  
Author(s):  
Qingzhou Zheng ◽  
Lu Hao ◽  
Xiaolin Huang ◽  
Lei Sun ◽  
Ge Sun
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Surface ◽  
Southern China ◽  
Hydrologic Model ◽  
Water Evaporation ◽  
Water Yield ◽  
Positive Trend ◽  
Significant Downward Trend ◽  
Effects Of Land Use

Understanding the effects of land use change on evapotranspiration (ET) and its partitioning to transpiration and evaporation is important for accurately evaluating the likely environmental impacts on watershed water supply, climate moderation, and other ecosystem services (e.g., carbon sequestration and biodiversity). This study used a distributed hydrologic model, MIKE SHE, to partition evapotranspiration into soil evaporation, transpiration, ponded water evaporation, and interception, and examined how the ET partitions affected the water balance in the Qinhuai River Basin from 2000 to 2013. Simulated daily ET was compared to measurements at an eddy flux research site during 2016–2017 (R2 = 0.72). Degradation in rice-wheat rotation fields and expansion of impervious surfaces impacted not only total watershed evapotranspiration, which showed a significant downward trend (p < 0.05), but also its partitioning. A significant (p < 0.01) decrease in transpiration was detected. Ponded water evaporation was the only ET partition that exhibited a significant positive trend (p < 0.05). We concluded that the reduced transpiration as a result of land use and land cover change was the primary factor driving the variation of watershed scale evapotranspiration. In addition, there was an increase in annual water yield (23%) as a response to significant reduction in ET (7%) due to a 175% expansion of urban area in the study watershed. Our study provided insights to the mechanisms of land surface–water cycle interaction and better understanding of the effects of land use change on urban micro-climate such as “urban dry island” and “urban heat island” effects.

scholarly journals Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES)

2019 ◽  
Vol 12 (1) ◽  
pp. 179-193 ◽  
Author(s):  
Chantelle Burton ◽  
Richard Betts ◽  
Manoel Cardoso ◽  
Ted R. Feldpausch ◽  
Anna Harper ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Dynamics ◽  
Fire Disturbance ◽  
Substantial Contribution ◽  
Surface Model ◽  
The Impact

Abstract. Disturbance of vegetation is a critical component of land cover, but is generally poorly constrained in land surface and carbon cycle models. In particular, land-use change and fire can be treated as large-scale disturbances without full representation of their underlying complexities and interactions. Here we describe developments to the land surface model JULES (Joint UK Land Environment Simulator) to represent land-use change and fire as distinct processes which interact with simulated vegetation dynamics. We couple the fire model INFERNO (INteractive Fire and Emission algoRithm for Natural envirOnments) to dynamic vegetation within JULES and use the HYDE (History Database of the Global Environment) land cover dataset to analyse the impact of land-use change on the simulation of present day vegetation. We evaluate the inclusion of land use and fire disturbance against standard benchmarks. Using the Manhattan metric, results show improved simulation of vegetation cover across all observed datasets. Overall, disturbance improves the simulation of vegetation cover by 35 % compared to vegetation continuous field (VCF) observations from MODIS and 13 % compared to the Climate Change Initiative (CCI) from the ESA. Biases in grass extent are reduced from −66 % to 13 %. Total woody cover improves by 55 % compared to VCF and 20 % compared to CCI from a reduction in forest extent in the tropics, although simulated tree cover is now too sparse in some areas. Explicitly modelling fire and land use generally decreases tree and shrub cover and increases grasses. The results show that the disturbances provide important contributions to the realistic modelling of vegetation on a global scale, although in some areas fire and land use together result in too much disturbance. This work provides a substantial contribution towards representing the full complexity and interactions between land-use change and fire that could be used in Earth system models.

scholarly journals If They Come, Where will We Build It? Land-Use Implications of Two Forest Conservation Policies in the Deep Creek Watershed

Forests ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 581
Author(s):  
Markandu Anputhas ◽  
Johannus Janmaat ◽  
Craig Nichol ◽  
Adam Wei
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Population Growth ◽  
Forest Conservation ◽  
Agricultural Land ◽  
Urban Land Use ◽  
Land Use Type ◽  
Land Uses ◽  
Conservation Policies ◽  
Creek Watershed

Research Highlights: Forest conservation policies can drive land-use change to other land-use types. In multifunctional landscapes, forest conservation policies will therefore impact on other functions delivered by the landscape. Finding the best pattern of land use requires considering these interactions. Background and Objectives: Population growth continues to drive the development of land for urban purposes. Consequently, there is a loss of other land uses, such as agriculture and forested lands. Efforts to conserve one type of land use will drive more change onto other land uses. Absent effective collaboration among affected communities and relevant institutional agents, unexpected and undesirable land-use change may occur. Materials and Methods: A CLUE-S (Conversion of Land Use and its Effects at Small Scales) model was developed for the Deep Creek watershed, a small sub-basin in the Okanagan Valley of British Columbia, Canada. The valley is experiencing among the most rapid population growth of any region in Canada. Land uses were aggregated into one forested land-use type, one urban land-use type, and three agricultural types. Land-use change was simulated for combinations of two forest conservation policies. Changes are categorized by location, land type, and an existing agricultural land policy. Results: Forest conservation policies drive land conversion onto agricultural land and may increase the loss of low elevation forested land. Model results show where the greatest pressure for removing land from agriculture is likely to occur for each scenario. As an important corridor for species movement, the loss of low elevation forest land may have serious impacts on habitat connectivity. Conclusions: Forest conservation policies that do not account for feedbacks can have unintended consequences, such as increasing conversion pressures on other valued land uses. To avoid surprises, land-use planners and policy makers need to consider these interactions. Models such as CLUE-S can help identify these spatial impacts.

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