Driving factors and assessment of changes in the use of arable land in Tanzania

2021 ◽  
Vol 104 ◽  
pp. 105359
Author(s):  
Amani Michael Uisso ◽  
Harun Tanrıvermiş
Keyword(s):  
Arable Land ◽  
Driving Factors

scholarly journals Spatio-Temporal Variation Characteristics and Driving Forces of Farmland Shrinkage in Four Metropolises in East Asia

2020 ◽  
Vol 12 (3) ◽  
pp. 754 ◽  
Author(s):  
Yaxin Shi ◽  
Yishao Shi
Keyword(s):  
East Asia ◽  
Metropolitan Area ◽  
Index System ◽  
Arable Land ◽  
Driving Factors ◽  
Evaluation Index System ◽  
Primary Factor ◽  
Evaluation Index ◽  
Cultivated Land ◽  
Tokyo Metropolitan Area

The shrinkage of cultivated land is a general trend in metropolitan areas. However, previous studies have mainly paid attention to the shrinkage of arable land in major grain-producing areas, mixed agro-pastoral areas, ecologically fragile areas and construction areas of major engineering projects (such as the Three Gorges project). This paper analyses the characteristics and driving factors of cultivated land change on the metropolitan area scale and longer time dimension. Exemplified by four metropolises in East Asia, Tokyo, Beijing, Shanghai and Guangzhou, based on official statistics for the cities involved, using correlation analysis, principal component analysis and regression analysis methods and Statistical Product and Service Solutions (SPSS) 25 software, the main driving factors and differences in cultivated land shrinkage in Beijing, Shanghai, Guangzhou and the Tokyo metropolitan area are quantitatively revealed. The results show the following: (1) there are some differences in the shrinkage in arable land and spatial distributions among different cities. Tokyo and Guangzhou still have some cultivated land in central urban areas, while there is no arable land in the central areas of Beijing and Shanghai. (2) There is a clear difference in the main driving factors of cultivated land shrinkage between the Tokyo metropolitan area and Beijing, Shanghai and Guangzhou. Residential area and population are the main driving factors for the former, while economic development and urbanisation are the main driving factors for the latter three areas. It shows that the shrinkage of cultivated land is closely related to the developmental stage of urbanisation. (3) There is a rather obvious difference in the main driving factors of cultivated land change among Beijing, Shanghai and Guangzhou. Gross Domestic Product (GDP) is the primary factor leading to the shrinkage of arable land in Beijing, built-up area is the primary factor in Shanghai, and the Engel’s coefficient for rural residents is the primary factor in Guangzhou. This reflects the difference in measures for the utilisation and protection of cultivated land among different cities. (4) The socioeconomic factors that affect the contraction of cultivated land are varied. In this study, industrial restructuring is included in the evaluation index system, mainly because industrial transformation and upgrading is essential for sustainable development of emerging global cities, and agricultural production conditions are not included in the evaluation index system, mainly because they are more the result of urbanisation than the cause.

scholarly journals Physical and Socioeconomic Driving Forces of Land-Use and Land-Cover Changes: A Case Study of Wuhan City, China

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Xiangmei Li ◽  
Ying Wang ◽  
Jiangfeng Li ◽  
Bin Lei
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Arable Land ◽  
Driving Factors ◽  
Land Cover Changes ◽  
Physical Factors ◽  
Driving Mechanism ◽  
Urban Management ◽  
Wuhan City

To investigate precise nexus between land-use and land-cover changes (LUCC) and driving factors for rational urban management, we used remotely sensed images to map land use and land cover (LULC) from 1990 to 2010 for four time periods using Wuhan city, China, as a case study. Partial least squares (PLS) method was applied to analyze the relationships between LUCC and the driving factors, mainly focusing on three types of LULC, that is, arable land, built-up area, and water area. The results were as follows:(1)during the past two decades, the land-use pattern in Wuhan city showed dramatic change. Arable land is made up of the largest part of the total area. The increased built-up land came mainly from the conversion of arable land for the purpose of economic development.(2)Based on the Variable Importance in Projection (VIP), the joint effects of socioeconomic and physical factors on LUCC were dominant, though annual temperature, especially annual precipitation, proved to be less significant to LUCC. Population, tertiary industry proportion, and gross output value of agriculture were the most significant factors for three major types of LULC. This study could help us better understand the driving mechanism of urban LUCC and important implications for urban management.

scholarly journals Analysis of the Spatiotemporal Heterogeneity of Various Landscape Processes and Their Driving Factors Based on the OPGD Model for the Jiaozhou Bay Coast Zone, China

Land ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 7
Author(s):  
Wei Wang ◽  
Yecui Hu ◽  
Rong Song ◽  
Zelian Guo
Keyword(s):  
Jiaozhou Bay ◽  
Arable Land ◽  
Great Influence ◽  
Spatiotemporal Analysis ◽  
Driving Factors ◽  
Vegetation Coverage ◽  
Landscape Processes ◽  
Lower Elevation ◽  
Ecological Type ◽  
Administrative Center

To date, various studies have analyzed changes in the landscape but there are few studies which have explored landscape processes and the corresponding driving factors. This study makes up for this deficiency in the systematic theoretical exposition and the spatiotemporal analysis of landscape processes. The results show that the amount of arable land outflow and built-up land inflow have resulted in an increase of 92,311.11 ha of built-up land that is mostly distributed around the administrative center and along the coast of Jiaozhou Bay. The outflow of ecological land is a major resource for replenishing arable land, by 37,016.19 ha, especially in terms of the grassland that is distributed in the hilly areas west of Jiaozhou Bay. The outflow of the salt-field, fish-farm and ecological land outflow have good connectivity, a large patch size, and an irregular shape. The ecological type, elevation, slope, and vegetation coverage are the four factors that have a great influence on all landscape processes. A gentler slope and lower elevation, and proximity to cities and towns land will produce more arable land outflow and built-up land inflow. However, arable land inflow and ecological land outflow are the opposite. This research will guide natural resource management for a rapidly developing coastal zone.

scholarly journals Analysis of Multi-Scale Changes in Arable Land and Scale Effects of the Driving Factors in the Loess Areas in Northern Shaanxi, China

2014 ◽  
Vol 6 (4) ◽  
pp. 1747-1760 ◽  
Author(s):  
Lina Zhong ◽  
Wenwu Zhao ◽  
Zhengfeng Zhang ◽  
Xuening Fang
Keyword(s):  
Scale Effects ◽  
Arable Land ◽  
Driving Factors ◽  
Multi Scale ◽  
Northern Shaanxi

Dynamics of ecosystem services and their driving factors in China’s Beijing-Tianjin-Hebei regional development

2020 ◽  
Author(s):  
Suxiao Li ◽  
Guangchun Lei ◽  
Xiubo Yu
Keyword(s):  
Logistic Regression ◽  
Ecosystem Services ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Arable Land ◽  
Influential Factors ◽  
Driving Factors ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression ◽  
Urbanization Rate

<p><strong>Abstract:</strong> A comprehensive study on the dynamics of ecosystem services and their driving factors is the key prerequisite for enhancing local ecological sustainability. Based on relevant sets of big data, including spatial land data, soil data, DEM, climatic data and social-economic data, using InVEST model and multivariate logistic regression model, the study firstly assessed the spatiotemporal variation of ecosystem services for China’s Beijing-Tianjin-Hebei (Jing-Jin-Ji) region from 1990 to 2015. The study then analyzed the natural and socioeconomic factors affecting the ecosystem services. The results show that large spatial and quantitative differences exist in the supply of multiple ecosystem services, and the changes of different types of ecosystem services are driven by different factors. For water yield, the areas of arable land, wetland and built-up land and precipitation are the most influential factors; The areas of arable land, precipitation, temperature, altitude, urbanization rate and amount of nutrient applied per unit area are determinants of changes in nutrient retention; The areas of grassland and forest, temperature, altitude, GDP per capita and urbanization rate affect the soil retention to great extent; for carbon storage, its key influential factors are the areas of different land use types and urbanization rate. The study can facilitate identification of where and how to enhance multiple ecosystem services.</p><p><strong>Keywords:</strong> dynamics of ecosystem services, driving factors, InVEST, multivariate logistic regression model</p>

scholarly journals Spatio-Temporal Patterns of Land Use and Cover Change from 1990 to 2010: A Case Study of Jiangsu Province, China

2019 ◽  
Vol 16 (6) ◽  
pp. 907 ◽  
Author(s):  
Ge Shi ◽  
Peng Ye ◽  
Liang Ding ◽  
Agustin Quinones ◽  
Yang Li ◽  
...  
Keyword(s):  
Land Use ◽  
Environmental Changes ◽  
Population Change ◽  
Arable Land ◽  
Jiangsu Province ◽  
Driving Factors ◽  
Human Society ◽  
Continuous Increase ◽  
Per Capita ◽  
Land Use And Cover

Land use and cover change (LUCC) is one of the most significant parts of global environmental changes, which reflects the interaction between human society and natural resources. In China, the urbanization process is experiencing a rapid sprawl since the reform and open program in 1978, and there has been a serious change in situation in the human–land relationship. In this paper, taking Jiangsu province located in the eastern coastal developed region as an example, the historic evolution process of the land use situation from 1990 to 2010 was explored. Landsat images from three periods were analyzed, using the land use transition matrix model, the land use dynamic degree model, and the land use degree model to evaluate the LUCC of Jiangsu during two research periods from 1990 to 2000 and from 2000 to 2010. Additionally, logistic regression models and some quantitative analysis were applied to identify the major potential driving factors behind the LUCC during the research period based on different dimensions. The results showed the following: (1) the most obvious change was the continuous increase of built-up area and the decrease of arable land, which reflected the deterioration of the ecological environment and the accelerate of the urbanization trend. (2) The land use change dynamic degree from 2000 to 2010 was much greater than that from 1990 to 2000. (3) Socio-economic elements and human activities were the major driving forces of LUCC in Jiangsu province. Amongst these forces, the driving factors of the population change, GDP, per capita household income, and per capita housing area have an obvious effect on the arable land loss and the built-up area expansion.

Crop rotations with clover and their productivity

2020 ◽  
Author(s):  
Ol'ga Gladysheva ◽  
Oksana Artyuhova ◽  
Vera Svirina
Keyword(s):  
Forest Soil ◽  
Crop Rotation ◽  
Gray Forest Soil ◽  
Arable Land ◽  
Perennial Grasses ◽  
Crop Rotations ◽  
Field Crop ◽  
Pure Steam ◽  
Positive Effect

The results of long-term research in experiments with crop rotations with different clover saturation are presented. It is shown that the cluster has a positive effect on the main indicators of vegetation of dark-gray forest soil. The introduction of two fields of perennial grasses into the six-field crop rotation significantly increases both the humus reserves and increases the productivity of arable land by 1.5–2 times compared to the crop rotation with a field of pure steam.

Strategies for Soil Fertility Improvement of Arable Land in China

2018 ◽  
Vol 20 (5) ◽  
pp. 84
Author(s):  
Yingjie Hu ◽  
Xiangbin Kong ◽  
Yuzhen Zhang
Keyword(s):  
Soil Fertility ◽  
Arable Land ◽  
Soil Fertility Improvement

New Technologies to Combat Herbicide Resistance

2020 ◽  
Vol 31 (2) ◽  
pp. 90-92
Author(s):  
Rob Edwards
Keyword(s):  
Winter Wheat ◽  
Herbicide Resistance ◽  
Cover Crops ◽  
New Technologies ◽  
Green Revolution ◽  
Arable Land ◽  
Limited Range ◽  
Cultural Control ◽  
Arable Farming ◽  
The Uk

Herbicide resistance in problem weeds is now a major threat to global food production, being particularly widespread in wild grasses affecting cereal crops. In the UK, black-grass (Alopecurus myosuroides) holds the title of number one agronomic problem in winter wheat, with the loss of production associated with herbicide resistance now estimated to cost the farming sector at least £0.5 billion p.a. Black-grass presents us with many of the characteristic traits of a problem weed; being highly competitive, genetically diverse and obligately out-crossing, with a growth habit that matches winter wheat. With the UK’s limited arable crop rotations and the reliance on the repeated use of a very limited range of selective herbicides we have been continuously performing a classic Darwinian selection for resistance traits in weeds that possess great genetic diversity and plasticity in their growth habits. The result has been inevitable; the steady rise of herbicide resistance across the UK, which now affects over 2.1 million hectares of some of our best arable land. Once the resistance genie is out of the bottle, it has proven difficult to prevent its establishment and spread. With the selective herbicide option being no longer effective, the options are to revert to cultural control; changing rotations and cover crops, manual rogueing of weeds, deep ploughing and chemical mulching with total herbicides such as glyphosate. While new precision weeding technologies are being developed, their cost and scalability in arable farming remains unproven. As an agricultural scientist who has spent a working lifetime researching selective weed control, we seem to be giving up on a technology that has been a foundation stone of the green revolution. For me it begs the question, are we really unable to use modern chemical and biological technology to counter resistance? I would argue the answer to that question is most patently no; solutions are around the corner if we choose to develop them.

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