scholarly journals Spatially Variable Relationships between Karst Landscape Pattern and Vegetation Activities

2020 ◽  
Vol 12 (7) ◽  
pp. 1134 ◽  
Author(s):  
Wenjuan Hou ◽  
Jiangbo Gao
Keyword(s):  
Land Use ◽  
Landscape Pattern ◽  
Structural Changes ◽  
Vegetation Index ◽  
Morphological Characteristics ◽  
Mesh Size ◽  
Landscape Fragmentation ◽  
Vegetation Activity ◽  
Function Correlation ◽  
The Impact

Based on the theories of structure–function correlation in Geography, and landscape pattern-ecological function correlation in Landscape Ecology, the correlation between land use fragmentation and vegetation activity was quantified. Effective mesh size (meff) was calculated to represent landscape fragmentation for land use, and the normalized difference vegetation index (NDVI) was used to reflect vegetation activity. The geographically weighted regression (GWR) model was applied to explore the spatial non-stationary relationship between meff and NDVI in a karst basin of the southwestern China, where environmental factors (i.e., climate, topography, and vegetation) are spatially heterogeneous. The spatial variation and scale dependence of landscape fragmentation and its relationship with vegetation activity, as well as the influence of lithology types and landforms relief, were considered. Firstly, the optimal ‘slide window’ size for landscape fragmentation was determined to be 500 m, and spatial pattern of meff displayed clear heterogeneity with a serious degree of fragmentation. Landscape fragmentation was more severe in carbonate areas than non-carbonate areas, reflecting the influence of landforms relief. More serious fragmentation in dolomite areas meant that the impact of human activities on the landscape morphological characteristics was much more significant than that in the limestone areas with steeper slope. Multi-scale analysis was used to verify a neighborhood size of 7 km for GWR in the study area. Negative effects on vegetation activity from landscape structural changes were more significant in limestone areas, which may be due to the more vulnerable ecosystems there. This research can provide scientific guidance for landscape management in karst regions as it considers the multi-scaled and spatially heterogeneous effects of lithology, geomorphology, and human factors on landscape structure and its correlation with vegetation activity.

scholarly journals Rural-Spatial Restructuring Promoted by Land-Use Transitions: A Case Study of Zhulin Town in Central China

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 234
Author(s):  
Dong Han ◽  
Jiajun Qiao ◽  
Qiankun Zhu
Keyword(s):  
Land Use ◽  
Rural Development ◽  
Structural Changes ◽  
Land Use Changes ◽  
Central China ◽  
Rural Space ◽  
Spatial Restructuring ◽  
Local Actors ◽  
The Impact

Rural-spatial restructuring involves the spatial mapping of the current rural development process. The transformation of land-use morphologies, directly or indirectly, affects the practice of rural restructuring. Analyzing this process in terms of the dominant morphology and recessive morphology is helpful for better grasping the overall picture of rural-spatial restructuring. Accordingly, this paper took Zhulin Town in Central China as a case study area. We propose a method for studying rural-spatial restructuring based on changes in the dominant and recessive morphologies of land use. This process was realized by analyzing the distribution and functional suitability of ecological-production-living (EPL) spaces based on land-use types, data on land-use changes obtained over a 30-year observation period, and in-depth research. We found that examining rural-spatial restructuring by matching the distribution of EPL spaces with their functional suitability can help to avoid the misjudgment of the restructuring mode caused by the consideration of the distribution and structural changes in quantity, facilitating greater understanding of the process of rural-spatial restructuring. Although the distribution and quantitative structure of Zhulin’s EPL spaces have changed to differing degrees, ecological- and agricultural-production spaces still predominate, and their functional suitability has gradually increased. The spatial distribution and functional suitability of Zhulin are generally well matched, with 62.5% of the matched types being high-quality growth, and the positive effect of Zhulin’s spatial restructuring over the past 30 years has been significant. We found that combining changes in EPL spatial area and quantity as well as changes in functional suitability is helpful in better understanding the impact of the national macro-policy shift regarding rural development. Sustaining the positive spatial restructuring of rural space requires the timely adjustment of local actors in accordance with the needs of macroeconomic and social development, and a good rural-governance model is essential.

scholarly journals Spatio-Temporal Variation Analysis of Landscape Pattern Response to Land Use Change from 1985 to 2015 in Xuzhou City, China

2018 ◽  
Vol 10 (11) ◽  
pp. 4287 ◽  
Author(s):  
Yantao Xi ◽  
Nguyen Thinh ◽  
Cheng Li
Keyword(s):  
Land Use ◽  
Landscape Pattern ◽  
Urban Areas ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Local Level ◽  
Land Use Changes ◽  
Landscape Patterns ◽  
Rapid Urbanization ◽  
Barren Land

Rapid urbanization has dramatically spurred economic development since the 1980s, especially in China, but has had negative impacts on natural resources since it is an irreversible process. Thus, timely monitoring and quantitative analysis of the changes in land use over time and identification of landscape pattern variation related to growth modes in different periods are essential. This study aimed to inspect spatiotemporal characteristics of landscape pattern responses to land use changes in Xuzhou, China durfing the period of 1985–2015. In this context, we propose a new spectral index, called the Normalized Difference Enhanced Urban Index (NDEUI), which combines Nighttime light from the Defense Meteorological Satellite Program/Operational Linescan System with annual maximum Enhanced Vegetation Index to reduce the detection confusion between urban areas and barren land. The NDEUI-assisted random forests algorithm was implemented to obtain the land use/land cover maps of Xuzhou in 1985, 1995, 2005, and 2015, respectively. Four different periods (1985–1995, 1995–2005, 2005–2015, and 1985–2015) were chosen for the change analysis of land use and landscape patterns. The results indicate that the urban area has increased by about 30.65%, 10.54%, 68.77%, and 143.75% during the four periods at the main expense of agricultural land, respectively. The spatial trend maps revealed that continuous transition from other land use types into urban land has occurred in a dual-core development mode throughout the urbanization process. We quantified the patch complexity, aggregation, connectivity, and diversity of the landscape, employing a number of landscape metrics to represent the changes in landscape patterns at both the class and landscape levels. The results show that with respect to the four aspects of landscape patterns, there were considerable differences among the four years, mainly owing to the increasing dominance of urbanized land. Spatiotemporal variation in landscape patterns was examined based on 900 × 900 m sub-grids. Combined with the land use changes and spatiotemporal variations in landscape patterns, urban growth mainly occurred in a leapfrog mode along both sides of the roads during the period of 1985 to 1995, and then shifted into edge-expansion mode during the period of 1995 to 2005, and the edge-expansion and leapfrog modes coexisted in the period from 2005 to 2015. The high value spatiotemporal information generated using remote sensing and geographic information system in this study could assist urban planners and policymakers to better understand urban dynamics and evaluate their spatiotemporal and environmental impacts at the local level to enable sustainable urban planning in the future.

scholarly journals Analysis of meteorological variations on wheat yield and its estimation using remotely sensed data. A case study of selected districts of Punjab Province, Pakistan (2001-14)

2017 ◽  
Vol 12 (3) ◽  
Author(s):  
Rafia Mumtaz ◽  
Shahbaz Baig ◽  
Iram Fatima
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Crop Yield ◽  
Vegetation Index ◽  
Wheat Yield ◽  
Least Square ◽  
Wheat Crop ◽  
Main Challenge ◽  
Normalised Difference Vegetation Index ◽  
The Impact

Land management for crop production is an essential human activity that supports life on Earth. The main challenge to be faced by the agriculture sector in coming years is to feed the rapidly growing population while maintaining the key resources such as soil fertility, efficient land use, and water. Climate change is also a critical factor that impacts agricultural production. Among others, a major effect of climate change is the potential alterations in the growth cycle of crops which would likely lead to a decline in the agricultural output. Due to the increasing demand for proper agricultural management, this study explores the effects of meteorological variation on wheat yield in Chakwal and Faisalabad districts of Punjab, Pakistan and used normalised difference vegetation index (NDVI) as a predictor for yield estimates. For NDVI data (2001-14), the NDVI product of Moderate Resolution Imaging spectrometer (MODIS) 16-day composites data has been used. The crop area mapping has been realised by classifying the satellite data into different land use/land covers using iterative self-organising (ISO) data clustering. The land cover for the wheat crop was mapped using a crop calendar. The relation of crop yield with NDVI and the impact of meteorological parameters on wheat growth and its yield has been analysed at various development stages. A strong correlation of rainfall and temperature was found with NDVI data, which determined NDVI as a strong predictor of yield estimation. The wheat yield estimates were obtained by linearly regressing the reported crop yield against the time series of MODIS NDVI profiles. The wheat NDVI profiles have shown a parabolic pattern across the growing season, therefore parabolic least square fit (LSF) has been applied prior to linear regression. The coefficients of determination (<em>R</em><sup>2</sup>) between the reported and estimated yield was found to be 0.88 and 0.73, respectively, for Chakwal and Faisalabad. This indicates that the method is capable of providing yield estimates with competitive accuracies prior to crop harvest, which can significantly aid the policy guidance and contributes to better and timely decisions.

scholarly journals Analysis of the Impact of Land Use and Occupation on the Biophysical Variables of the Cerrado Biome in Southwest Goiano, Brazil

2018 ◽  
Vol 11 (1) ◽  
pp. 399
Author(s):  
Victor H. Moraes ◽  
Pedro R. Giongo ◽  
Marcio Mesquita ◽  
Thomas J. Cavalcante ◽  
Matheus V. A. Ventura ◽  
...  
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Urban Areas ◽  
Vegetation Index ◽  
Land Use Changes ◽  
Weighted Average ◽  
Natural Vegetation ◽  
Agricultural Crops ◽  
Quantitative Classification ◽  
The Impact

The change in the use of natural vegetation by annual or perennial crops, sugarcane and fast-growing forests causes changes in the biophysical variables, and these changes can be monitored by remote sensing. The objective of this work was to evaluate, on a temporal scale, the impacts of land use changes on biophysical variables in the county of Santa Helena de Goias-Goias/Brazil. Between the years of 2000 to 2015 areas were identified for agricultural crops 1 (annual crops), water, agricultural crops 2 (sugarcane), natural vegetation, pasture and urban areas. The MODIS (Moderate Resolution Spectroradiometer) sensor products were selected for study: MOD11A2-Surface temperature; MOD16A2-Real evapotranspiration, MOD13Q1-Enhanced Vegetation Index and rainfall data from TRMM (Tropical Rainfall Measuring Mission). The geographic coordinates referring to the land uses were inserted in the LAPIG platform, searching the information of the biophysical variables referring to the selected pixel. The impact of land use change was evaluated by calculating the weighted average through the quantitative classification of the areas. It is concluded for the period of study that the index of average vegetation of the county had increase. There was an increase in the evapotranspiration volume of the county from 28% from 2000 to 2013 and the average surface temperature of the county showed a reduction of 2 &deg;C in the period from 2000 to 2015.

scholarly journals Density of Biogas Power Plants as An Indicator of Bioenergy Generated Transformation of Agricultural Landscapes

2019 ◽  
Vol 11 (9) ◽  
pp. 2500 ◽  
Author(s):  
Nandor Csikos ◽  
Malte Schwanebeck ◽  
Michael Kuhwald ◽  
Peter Szilassi ◽  
Rainer Duttmann
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Landscape Pattern ◽  
Power Plants ◽  
Biogas Production ◽  
Kernel Density ◽  
Shape Index ◽  
Agricultural Landscapes ◽  
The Impact ◽  
Impact Zones

The increasing use of biogas, produced from energy crops like silage maize, is supposed to noticeably change the structures and patterns of agricultural landscapes in Europe. The main objective of our study is to quantify this assumed impact of intensive biogas production with the example of an agrarian landscape in Northern Germany. Therefore, we used three different datasets; Corine Land Cover (CLC), local agricultural statistics (Agrar-Struktur-Erhebung, ASE), and data on biogas power plants. Via kernel density analysis, we delineated impact zones which represent different levels of bioenergy-generated transformations of agrarian landscapes. We cross-checked the results by the analyses of the land cover and landscape pattern changes from 2000 to 2012 inside the impact zones. We found significant correlations between the installed electrical capacity (IC) and land cover changes. According to our findings, the landscape pattern of cropland—expressed via landscape metrics (mean patch size (MPS), total edge (TE), mean shape index (MSI), mean fractal dimension index (MFRACT)—increased and that of pastures decreased since the beginning of biogas production. Moreover, our study indicates that the increasing number of biogas power plants in certain areas is accompanied with a continuous reduction in crop diversity and a homogenization of land use in the same areas. We found maximum degrees of land use homogenisation in areas with highest IC. Our results show that a Kernel density map of the IC of biogas power plants might offer a suitable first indicator for monitoring and quantifying landscape change induced by biogas production.

scholarly journals The Impact Of The Syrian Civil War On Land Use / Land Cover In Al-Yarmouk Basin During 2010–2018

2020 ◽  
Vol 13 (2) ◽  
pp. 147-153
Author(s):  
Yusra Al-Husban ◽  
Ahmad Ayen
Keyword(s):  
Land Use ◽  
Civil War ◽  
Land Cover ◽  
Vegetation Index ◽  
Land Use Land Cover ◽  
Palestinian Authority ◽  
Barren Area ◽  
Syrian Civil War ◽  
Yarmouk Basin ◽  
The Impact

The study goal is to monitor and evaluate the significant changes in land use/land cover (LULC) in Al-Yarmouk basin (YB) within only 8 year. (YB) is shared between Syria, Jordan, Palestinian Authority, and Israel. (YB) has been affected not only by water scarcity, frequent drought conditions; But nowadays provide proof that the major factor responsible for the current of the significant changes in (LULC) in the study area is the Syrian civil war that began in mid-2011, and the Syrian refugee influx into Jordan has been massive, more than 660,935 Syrians were registered in three camps; Za’atri the largest refugee camp in the world, Azraq and the Emirate, according to the Official figures, with the highest density about 58 not 50 person look; Fig.5 in YB. Landsat Thematic Mapper Landsat 5 (2010) and 8-OLI (2018) covering a period of 8 years. An on-screen digitizing methodology has been employed. The images of the study area were categorized into four different classes: vegetation, built-up area, barren area, and water bodies. Normalized difference vegetation index (NDVI) was applied at a threshold value≥ 0.1 to distinguish between the vegetated area and non-vegetated areas. IN this study, the NDVI and LULC based classification have indicated that significant change in (LULC) between a year 2010 and 2018. The Major change has been found in the vegetation area which decreased by (-12.02%), in addition, an increase of the built up area by (+1.69%). Al-Wehda dam area decreased by -0.08%. Linear regression trends showed a slight decrease in the mean rainfall during the study period (2010/2018). However, this finding is not statistically significant at the 95 % confidence level.

scholarly journals Spatial Clustering of Dengue Fever Incidence and Its Association with Surrounding Greenness

2018 ◽  
Vol 15 (9) ◽  
pp. 1869 ◽  
Author(s):  
Chi-Chieh Huang ◽  
Tuen Tam ◽  
Yinq-Rong Chern ◽  
Shih-Chun Lung ◽  
Nai-Tzu Chen ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Autocorrelation ◽  
Dengue Fever ◽  
Vegetation Index ◽  
Green Space ◽  
Hot Spot ◽  
Southern Taiwan ◽  
The Impact ◽  
The Relationship ◽  
Green Land

With more than 58,000 cases reported by the country’s Centers for Disease Control, the dengue outbreaks from 2014 to 2015 seriously impacted the southern part of Taiwan. This study aims to assess the spatial autocorrelation of the dengue fever (DF) outbreak in southern Taiwan in 2014 and 2015, and to further understand the effects of green space (such as forests, farms, grass, and parks) allocation on DF. In this study, two different greenness indexes were used. The first green metric, the normalized difference vegetation index (NDVI), was provided by the long-term NASA MODIS satellite NDVI database, which quantifies and represents the overall vegetation greenness. The latest 2013 land use survey GIS database completed by the National Land Surveying and Mapping Center was obtained to access another green metric, green land use in Taiwan. We first used Spearman’s rho to find out the relationship between DF and green space, and then three spatial autocorrelation methods, including Global Moran’s I, high/low clustering, and Hot Spot were employed to assess the spatial autocorrelation of DF outbreak. In considering the impact of social and environmental factors in DF, we used generalized linear mixed models (GLMM) to further clarify the relationship between different types of green land use and dengue cases. Results of spatial autocorrelation analysis showed a high aggregation of dengue epidemic in southern Taiwan, and the metropolitan areas were the main hotspots. Results of correlation analysis and GLMM showed a positive correlation between parks and dengue fever, and the other five green space metrics and land types revealed a negative association with DF. Our findings may be an important asset for improving surveillance and control interventions for dengue.

scholarly journals Ecological Effect of Ecological Engineering Projects on Low-Temperature Forest Cover in Great Khingan Mountain, China

2021 ◽  
Vol 18 (20) ◽  
pp. 10625
Author(s):  
Shuqing Wang ◽  
Run Zhong ◽  
Lin Liu ◽  
Jianjun Zhang
Keyword(s):  
Land Use ◽  
Ecological Restoration ◽  
Vegetation Index ◽  
Ecological Impact ◽  
Ecological Engineering ◽  
Ecological Effect ◽  
Series Data ◽  
Land Productivity ◽  
Forest Protection ◽  
The Impact

The evaluation of ecological restoration projects can provide support for further strengthening the efforts of ecological restoration work and implementing the strategic objectives of the ecological region. Considering the current problem of the single evaluation index, this study evaluated the implementation effect of ecological projects from different temporal and spatial dimensions. Based on the MODIS vegetation index time series data, this study first computed the Sustainable Development Goal (SDG) indicator 15.3.1 of Great Khingan Mountain (GKM) to evaluate the impact of ecological engineering on land use change and land productivity. As a common indicator, the Normalized Difference Vegetation Index (NDVI) values showed a trend of a decrease and then gradual increase after the start of the Natural Forest Protection Project (NFPP) II, which was related to the land use changes from the forest to the grassland during the implementation of the NFPP. However, land productivity maintained a steady trend because of the transition between the forest and grassland. Meanwhile, to detect changes in vegetation at a smaller scale, the LandTrendr algorithm was used to identify the magnitude of forest disturbance, the years when it occurred, and the year of restoration. After implementing the ecological project, the forests in the GKM region were only partially disturbed, and most of the forests in most areas maintained a stable trend. Our study highlighted the varying effectiveness of different indexes for NFPP and evaluated the ecological impact of ecological projects from multiple perspectives.

scholarly journals Satellite-Observed Effects from Ozone Pollution and Climate Change on Growing-Season Vegetation Activity over China during 1982–2020

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1390
Author(s):  
Zhaosheng Wang
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Large Scale ◽  
Vegetation Index ◽  
Growing Season ◽  
Ozone Pollution ◽  
Vegetation Growth ◽  
Vegetation Activity ◽  
The Impact

Remote sensing vegetation index data contain important information about the effects of ozone pollution, climate change and other factors on vegetation growth. However, the absence of long-term observational data on surface ozone pollution and neglected air pollution-induced effects on vegetation growth have made it difficult to conduct in-depth studies on the long-term, large-scale ozone pollution effects on vegetation health. In this study, a multiple linear regression model was developed, based on normalized difference vegetation index (NDVI) data, ozone mass mixing ratio (OMR) data at 1000 hPa, and temperature (T), precipitation (P) and surface net radiation (SSR) data during 1982–2020 to quantitatively assess the impact of ozone pollution and climate change on vegetation growth in China on growing season. The OMR data showed an increasing trend in 99.9% of regions in China over the last 39 years, and both NDVI values showed increasing trends on a spatial basis with different ozone pollution levels. Additionally, the significant correlations between NDVI and OMR, temperature and SSR indicate that vegetation activity is closely related to ozone pollution and climate change. Ozone pollution affected 12.5% of NDVI, and climate change affected 26.7% of NDVI. Furthermore, the effects from ozone pollution and climate change on forest, shrub, grass and crop vegetation were evaluated. Notably, the impact of ozone pollution on vegetation growth was 0.47 times that of climate change, indicating that the impact of ozone pollution on vegetation growth cannot be ignored. This study not only deepens the understanding of the effects of ozone pollution and climate change on vegetation growth but also provides a research framework for the large-scale monitoring of air pollution on vegetation health using remote sensing vegetation data.

scholarly journals Changing Consumption Patterns—Drivers and the Environmental Impact

2018 ◽  
Vol 10 (11) ◽  
pp. 4190 ◽  
Author(s):  
Rasadhika Sharma ◽  
Trung Nguyen ◽  
Ulrike Grote
Keyword(s):  
Land Use ◽  
Environmental Impact ◽  
Carbon Footprint ◽  
Structural Changes ◽  
Consumption Patterns ◽  
Population Increase ◽  
Environmental Damage ◽  
Secondary Literature ◽  
Beef Demand ◽  
The Impact

Economic growth coupled with population increase and globalization have engendered structural changes in consumption patterns around the world. Contingent on their composition, these changes can be demanding on natural resources and pose unsustainable challenges for the environment. The paper aims to provide a general framework to assess the link between changing consumption patterns and their environmental impact by focusing on the rising beef demand in Vietnam. It draws from secondary literature and data to find that the increased beef demand in Vietnam is mostly met domestically, but there is a major dependency on imports. Within Vietnam, the rising demand has contributed substantially to the carbon footprint and land use and raised waste disposal concerns. To understand the impact of Vietnamese beef demand at the global level, the paper looks at Australia. Carbon footprint and land use are estimated to provide a perspective on the plausible scale of environmental damage that can be ensued in the future. Changes in consumption patterns are an integral part of our world and will play a significant role in determining the sustainable future of our planet. Therefore, it is important to attain a better understanding of the theme and its possible impact on the environment.

Sign in / Sign up

Export Citation Format

Share Document