The Study on Dynamic Change of Cultivated Land Resources and Driving Forces - A Study Case of Lixian County, Hebei Province

2014 ◽  
Vol 707 ◽  
pp. 232-236
Author(s):  
Can Zhang ◽  
Hui Chun Shi ◽  
Xia Xia Lv
Keyword(s):  
Driving Forces ◽  
Dynamic Change ◽  
Arable Land ◽  
Reduction Rate ◽  
Principal Component ◽  
Economic Factor ◽  
Cultivated Land ◽  
Land Resources ◽  
Annual Reduction ◽  
Statistical Yearbook

In this paper, Lixian County 2001-2010 dynamic changes of cultivated land resources were studied. Studies have shown that: the past 10 years the average annual reduction rate of 0.72% Lixian County arable land, and the reduction since 2002, much faster, In the spatial region, most dramatic change is more economically developed society Liwu Town, Dabaichi Town, Xinxing Town and Liushi Town. According to the statistical Yearbook 2001-2010 review, we select factor and use principal component analysis. The main driving factors of impacting Lixian County arable land resources change are economic factor, demographic factor and progress in agricultural technology factor.

The Analysis of Dynamic Change of Cultivated Land and Driving Forces in Suzhou City

2012 ◽  
Vol 616-618 ◽  
pp. 1421-1424
Author(s):  
Hai Min Su ◽  
Ai Xia He
Keyword(s):  
Principal Component Analysis ◽  
Survey Data ◽  
Social System ◽  
Driving Forces ◽  
Dynamic Change ◽  
Arable Land ◽  
Principal Component ◽  
Cultivated Land ◽  
Suzhou City ◽  
Per Capita

According to statistical and survey data from 1991 to 2010 at provincial and county levels, trend of cultivated land change and its driving forces in Suzhou City during the last 20 years were discussed in this article. It was found that: since 1990s, the total area of arable land and per capita availability were reducing; as a result of the principal component analysis, the 10 driving forces of arable land were analyzed which could be classified into three types, i.e, the development of economy, social system and population and progress of science and technology in agriculture. As to the economy factors, population and social system factors were the main driving forces, which play an important role in the change of cultivated land.

Analysis on the Change of Arable Land Area and its Driving Force in Hefei City

2013 ◽  
Vol 726-731 ◽  
pp. 4879-4882
Author(s):  
Hong Mei Zhang ◽  
Yang Gao
Keyword(s):  
Principal Component Analysis ◽  
Driving Forces ◽  
Arable Land ◽  
Principal Component ◽  
Component Analysis ◽  
Land Resource ◽  
Cultivated Land ◽  
Land Change ◽  
Land Area ◽  
Per Capita

In recent years, the decrease of total arable land area and the area per capita of available arable land resource are serious problems in China. These problems will become more serious with the development of economy. In this paper, based on the statistical data of cultivated land in Hefei city from 1998 to 2009, their driving forces of the cultivated land change were analyzed by means of principal component analysis. The results showed the changing trends. The total and per capita of cultivated land were declining, but the speed of change was not the same. The sharp decrease was occurred in the period of 2002-2005. Nine affecting factors having influenced on cultivated land change which were analyzed by principal component analysis. The results show that population growth, economic development and efficiency of agricultural production were main driving forces affecting cultivated land change in Hefei city.

scholarly journals Dynamic Changes Analysis and Hotspots Detection of Land Use in the Central Core Functional Area of Jing-Jin-Ji from 2000 to 2015 Based on Remote Sensing Data

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Yafei Li ◽  
Gaohuan Liu ◽  
Chong Huang
Keyword(s):  
Land Use ◽  
Driving Forces ◽  
Transportation Network ◽  
Dynamic Change ◽  
Remote Sensing Data ◽  
Research Area ◽  
Central Core ◽  
Cultivated Land ◽  
Functional Area ◽  
Dynamic Changes

The article uses GIS spatial analysis and grid technologies to study the dynamic changes, hotspot regions, and driving forces in land use of the central core functional area of Jing-Jin-Ji. The research results are as follows: from 2000 to 2015, the main types of land use in the central core functional area of Jing-Jin-Ji are cultivated land, woodland, and built-up land. In the period of 2005–2010, the transfer between built-up land and cultivated land was frequent. The dynamic degree of single land use in unused land was highest. It also finds out that the dynamic degree of the integrated land use from 2005 to 2010 was higher. The center of gravity transfer of the dynamic degree of integrated land use was concentrated in research area. As for the hotspots, their number and scope are increasing, and the positions located in the edge of original main urban area and developed transportation network. The main characteristics of land use dynamic change in the study area are the rapid decrease of cultivated land area and rapid growth of built-up land. The spatial agglomeration of economic factors caused by human activities has an important influence on the spatial and temporal dynamic changes of land use.

Empirical Study on Utilization Benefit of Cultivated Land in Changsha

2014 ◽  
Vol 675-677 ◽  
pp. 1283-1287
Author(s):  
Jin Hua Tang ◽  
Ying Hui Li ◽  
Hui Li
Keyword(s):  
Empirical Study ◽  
Arable Land ◽  
Cultivated Land ◽  
Land Resources ◽  
Land Utilization ◽  
The Status

In order to realize the status of cultivated land resources in Changsha and to protect cultivated land resources. According to output benefit coefficient, consumption and return coefficient, population and substitution coefficient and intensive cultivation coefficient, cultivated land utilization benefits were quantitatively analyzed in Changsha from 2002 to 2011. The results showed that: the trend of the quantity of cultivated land was upward in general in Changsha. But the quality of cultivated land decreased. At the same time, the output benefit of arable land was good in 2004, 2006 and 2008, but the rest of year was lower, and the tendency was dropping. On this basis, the effectiveness of the strategies was improved to use of arable land resources.

scholarly journals The temporal and spatial scales of arable land loss and its impact in Guangxi, China: A Commentary

2022 ◽  
Vol 9 (1) ◽  
pp. 76-84
Author(s):  
Haiying Feng ◽  
Victor Squires
Keyword(s):  
Spatial Scales ◽  
Arable Land ◽  
Mountainous Area ◽  
Cultivated Land ◽  
Land Resources ◽  
Land Loss ◽  
Policy Interventions ◽  
Geomorphic Features ◽  
Spatial Differences ◽  
Abandoned Cropland

Cropland abandonment because of rural depopulation or policy interventions has become a key issue in Chinese mountainous areas. One such region is the Guangxi Karst Mountainous Area (GKMA), a zone where more than 59% of total land area is hilly and arable land of a commercially viable size is almost non-existent. The rugged terrain and land fragmentation in upland karst areas result in the scarcity of land suitable for cultivation. Although depopulation and declining agriculture since 2000 within the GKMA have led to vast areas of abandoned cropland, the spatiotemporal distribution that underlies this pattern as well as its causes remain little understood. Geomorphic features also bring about differences in the distribution of settlements. Settlements with different degrees of distribution are accompanied by spatial differences in cultivated land resources, which lead to differences in the sufficiency of cultivated land resources. In this paper we provide an overview of the magnitude of the problem of arable land loss. settlements and analyze the spatial distribution and the spatial agglomeration of the cultivated land.

Land Use Dynamic Change and Driving Force Analysis in Qingdao

2012 ◽  
Vol 518-523 ◽  
pp. 6004-6007
Author(s):  
Xing Yuan Xiao ◽  
Tao Jiang
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Driving Force ◽  
Driving Forces ◽  
Dynamic Change ◽  
Fuzzy Comprehensive Evaluation ◽  
Base Number ◽  
Cultivated Land ◽  
Unused Land ◽  
Land Use Types

Using GIS and such models as dynamic degree, analyzed the land-use change in Qingdao according to the statistics of land-use data from 2000 to 2010 years and based on these, the author selects eight natural and socio-economic indexes, and takes districts as the study unit to calculate the driving force indexes with the fuzzy comprehensive evaluation method, and makes the spatial-division thematic maps of the driving forces which cause the land-use change in this region base on GIS. The results show that in Qingdao the land-use types which have the largest change rate is residential area and mining sites, followed by the unused land, water and cultivated land, and the garden plot is the smallest. There is a decreasing of cultivated land and unused land while other types have increased; because of a large base number, cultivated land reduces most among all land-use types. There exists a big spatial difference among these driving forces for land-use change. According the driving force indexes we divided them into four regions.

scholarly journals Integrating Remote Sensing and a Markov-FLUS Model to Simulate Future Land Use Changes in Hokkaido, Japan

2021 ◽  
Vol 13 (13) ◽  
pp. 2621
Author(s):  
Zhanzhuo Chen ◽  
Min Huang ◽  
Daoye Zhu ◽  
Orhan Altan
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Planning ◽  
Land Use Changes ◽  
Arable Land ◽  
Cultivated Land ◽  
Land Resources ◽  
Forest Protection ◽  
Land Protection ◽  
The Past

As the second largest island in Japan, Hokkaido provides precious land resources for the Japanese people. Meanwhile, as the food base of Japan, the gradual decrease of the agricultural population and more intensive agricultural practices on Hokkaido have led its arable land use to change year by year, which has also caused changes to the whole land use pattern of the entire island of Hokkaido. To realize the sustainable use of land resources in Hokkaido, past and future changes in land use patterns must be investigated, and target-based land use planning suggestions should be given on this basis. This study uses remote sensing and GIS technology to analyze the temporal and spatial changes of land use in Hokkaido during the past two decades. The types of land use include cultivated land, forest, waterbody, construction, grassland, and others, by using the satellite images of the Landsat images in 2000, 2010, and 2019 to achieve this goal to make classification. In addition, this study used the coupled Markov-FLUS model to simulate and analyze the land use changes in three different scenarios in Hokkaido in the next 20 years. Scenario-based situational analysis shows that the cultivated land in Hokkaido will drop by about 25% in 2040 under the natural development scenario (ND), while the cultivated land area in Hokkaido will remain basically unchanged in cultivated land protection scenario (CP). In forest protection scenario (FP), the area of forest in Hokkaido will increase by 1580.8 km2. It is believed that the findings reveal that the forest land in Hokkaido has been well protected in the past and will be protected well in the next 20 years. However, in land use planning for future, Hokkaido government and enterprises should pay more attention to the protection of cultivated land.

Profitability of dairy farming in relation to the type of feeding system

2011 ◽  
Vol 28 (1) ◽  
pp. 55-59 ◽  
Author(s):  
Jan Frelich ◽  
Martin Šlachta ◽  
František Střeleček ◽  
Jana Lososová
Keyword(s):  
Arable Land ◽  
Principal Component ◽  
Dairy Farming ◽  
Plant Production ◽  
Feeding Strategies ◽  
Feeding System ◽  
Financial Health ◽  
Profit Rate ◽  
Permanent Housing ◽  
Cow Performance

Profitability of dairy farming in relation to the type of feeding systemWe investigated the profitability of dairy farms in relation to the type of feeding system (seasonal pasture vs. permanent housing). An economic analysis was carried out of data on the structure and financial health of 50 farms in 2007 using questionnaires filled in by the farmers. The Principal Component Analysis (PCA) was applied to reveal causal relationships between a number of characteristics of the farms. The two axis of PCA explained 40.48% and 16.13% of the variability among the selected farm characteristics. Profitability related more to the number of subsidies, the area of arable land, the number of livestock and to the milk and plant production than to the area of meadows and pastures. Although a better cow performance was achieved on farms with confined herds, the profit per agricultural area and profit rate did not differ significantly between the two feeding strategies (P>0.05). The profit was 3,259 and 3,655 CZK/ha on average and the profit rate 7.9% and 5.6% on average on farms with pastured herds and on farms with confined herds, respectively. A lowering of input costs and a more effective utilisation of grasslands may further enhance profitability.

scholarly journals Analysis and prediction of LUCC change in Huang-Huai-Hai river basin

2020 ◽  
Vol 12 (1) ◽  
pp. 1406-1420
Author(s):  
Jianwei Wang ◽  
Kun Wang ◽  
Tianling Qin ◽  
Hanjiang Nie ◽  
Zhenyu Lv ◽  
...  
Keyword(s):  
Land Use ◽  
River Basin ◽  
Land Use Planning ◽  
Climate Model ◽  
Dynamic Change ◽  
Cultivated Land ◽  
Emission Scenarios ◽  
Future Change ◽  
Land Use Types ◽  
Downstream Area

AbstractLand use/cover change plays an important role in human development and environmental health and stability. Markov chain and a future land use simulation model were used to predict future change and simulate the spatial distribution of land use in the Huang-Huai-Hai river basin. The results show that cultivated land and grassland are the main land-use types in the basin, accounting for about 40% and 30%, respectively. The area of cultivated land decreased and artificial surfaces increased from 1980 to 2010. The degree of dynamic change of land use after the 1990s was greater than that before the 1990s. There is a high probability of exchange among cultivate land, forest and grassland. The area of forest decreased before 2000 and increased after 2000. Under the three emission scenarios (RCP2.6, RCP4.5, and RCP8.5) of IPSL-CM5A-LR climate model, the area of cultivated land will decrease and that of grassland will increase in the upstream area while it will decrease in the downstream area. The above methods and rules will be of great help to future land use planning.

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