Urban expansion or poor productivity: Explaining regional differences in cropland abandonment in China during the early 21st century

Qiu, Bingwen; Yang, Xin; Tang, Zhenghong; Chen, Chongcheng; Li, Haiwen; Berry, J. A.

doi:10.1002/ldr.3617

Cited by 31 publications

(13 citation statements)

References 48 publications

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“…For example, the out-migration of agricultural labor [55,56]. As a result of rural-to-urban population migration, the double-cropping system of cropland decreased along with cropland abandonment, especially in low-quality croplands in the hilly rural and mountainous regions [55,57]. It is difficult to implement mechanized operations in mountainous and hilly terrain [58,59].…”

Section: Analysis Of Driving Factors For Shifts Of the Nldcmentioning

confidence: 99%

“…A series of agricultural stimulation policies since the start of the 21st century have also helped drive the movement of NLDC, including the elimination of the agricultural tax, increased agricultural subsidies, and increased grain price [4,57]. Since 2002, China has carried out agricultural tax reform in Hebei, Shandong, Henan, and Hubei provinces, which to some extent increased farmers' production enthusiasm [60] and caused the NLDC to move slightly westward after 2005.…”

Section: Analysis Of Driving Factors For Shifts Of the Nldcmentioning

confidence: 99%

“…The NLDC movement in Beijing and Tianjin may be attributed to socioeconomic factors [59,62]. In the past 20 years, the cropland abandonment process was spatial-temporally coupled with urbanization, and urbanization has been found to be the main cause of farmland abandonment in suburban fields, especially high-quality cropland [57]. Shaanxi and Shanxi provinces are inland of northwest China, where the climate is dry and ecosystems are fragile.…”

Section: Analysis Of Driving Factors For Shifts Of the Nldcmentioning

confidence: 99%

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Mapping the Northern Limit of Double Cropping Using a Phenology-Based Algorithm and Google Earth Engine

et al. 2022

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Double cropping is an important cropping system in China, with more than half of China’s cropland adopting the practice. Under the background of global climate change, agricultural policies, and changing farming practices, double-cropping area has changed substantially. However, the spatial-temporal dynamics of double cropping is poorly understood. A better understanding of these dynamics is necessary for the northern limit of double cropping (NLDC) to ensure food security in China and the world and to achieve zero hunger, the second Sustainable Development Goal (SDG). Here, we developed a phenology-based algorithm to identify double-cropping fields by analyzing time-series Moderate Resolution Imaging Spectroradiometer (MODIS) images during the period 2000–2020 using the Google Earth Engine (GEE) platform. We then extracted the NLDC using the kernel density of pixels with double cropping and analyzed the spatial-temporal dynamics of NLDC using the Fishnet method. We found that our algorithm accurately extracted double-cropping fields, with overall, user, and producer accuracies and Kappa coefficients of 95.97%, 96.58%, 92.21%, and 0.91, respectively. Over the past 20 years, the NLDC generally trended southward (the largest movement was 66.60 km) and eastward (the largest movement was 109.52 km). Our findings provide the scientific basis for further development and planning of agricultural production in China.

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Section: Analysis Of Driving Factors For Shifts Of the Nldcmentioning

confidence: 99%

Section: Analysis Of Driving Factors For Shifts Of the Nldcmentioning

confidence: 99%

Section: Analysis Of Driving Factors For Shifts Of the Nldcmentioning

confidence: 99%

See 1 more Smart Citation

Mapping the Northern Limit of Double Cropping Using a Phenology-Based Algorithm and Google Earth Engine

et al. 2022

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“…Changes in socioeconomic elements, such as urbanization and industrialization, are considered to be the main driving force behind abandoned cropland [14,49,50]. With the development of urbanization and industrialization, the surplus rural labor force is gradually transferred to non-agricultural industries [51].…”

Section: Introductionmentioning

confidence: 99%

Degree of Abandoned Cropland and Socioeconomic Impact Factors in China: Multi-Level Analysis Model Based on the Farmer and District/County Levels

Jiang

Song

2021

Land

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At present, abandoned cropland has become a common phenomenon spreading to countries around the world. China has seen widespread abandoned cropland in recent years. However, there are extremely few empirical studies of cropland abandonment and influencing factors nationwide. In this study, survey data from 8071 farmer households in 14 Chinese provinces were used to analyze the degree of cropland abandonment in China and its spatial distribution. A multi-level model was constructed to quantitatively explore the socioeconomic factors affecting the degree of cropland abandonment, at both the farmer and district/county levels. The results show that: (1) the proportion of farmers and the spatial distribution of abandoned cropland are consistent. (2) Chongqing City, Guangdong Province, and Shanxi Province are high-value areas of abandoned cropland, while Shandong, Liaoning, Henan and Jiangsu provinces are low-value areas. (3) Among the differences in cropland abandonment, 68.5% and 31.5% can be explained at the farmer and district/county level, respectively. (4) At the farmer level, all labor and cropland transfer indicators, including land labor quantity per unit area, male agricultural labor ratio, farmers mainly of middle-aged labor, cropland transfer area and cropland subcontract amount, have significant negative effects on the degree of abandoned cropland. There is a significant negative correlation between the value of agricultural operating fixed assets in the agricultural input indicators and the degree of abandoned cropland, but participation in professional, cooperative, economic, agricultural organizations has no significant impact on the degree of abandoned cropland. The per capita disposable income, which represents the quality of life indicator, has a significant positive impact on the degree of abandoned cropland. (5) At the district/county level, the proportion of the total co-working labor force and the transfer rate of cropland are negatively related to the degree of cropland abandonment, and the proportion of the co-working labor force outside the district/county is positively related to the degree of cropland abandonment. In addition, we briefly analyzed the mechanism and process of cropland abandonment from the perspective of farmers’ decision-making. Finally, the policy suggestions to alleviate the abandonment of cropland were put forward from the district/county and farmer level, respectively.

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“…The direct effects resulted from the urbanization process led to a large amount of land converted to construction land and the migration of a large number of rural population to cities [16]. Urbanization leads to the separation of labor and cultivated land, and the emergence of "concurrent farming" or "abandonment of agriculture", which leads to the abandonment of cultivated land [17][18][19]. Based on a sample survey, the researchers found that the rate of cultivated land abandonment in mountainous areas of China was 14.32% from 2014 to 2015, the abandonment rate was the highest in the mountainous areas along the Yangtze River Basin [20]; at the same time, some scholars used meta-analysis to reveal the spatial and temporal characteristics of cultivated land abandoned at the national scale in China, and found that the abandoned land was mainly concentrated in southern China [21].…”

Section: Introductionmentioning

confidence: 99%

Impact of Economic Development Level and Agricultural Water Use on Agricultural Production Scale in China

Pang

Wang

Xue

et al. 2021

IJERPH

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The change of agricultural production scale is directly related to food security and the stable development of social economy. Particularly, the influence of economic development level and agricultural water use on agricultural production scale cannot be ignored. Therefore, this paper uses the fully modified ordinary least squares (FMOLS) and the Dumitrescu–Hurlin panel causality test models to discuss the effects of the level of economic development, agricultural water use, the level of urbanization, and the market price of agricultural products on the scale of agricultural production in China. The analysis results indicated that agricultural water use, the level of urbanization, and the market price of agricultural products promoted an increase of the scale of agricultural production at the total sample level; a 1% increase for these three variables will result in an increase of the scale of agricultural production of 0.634%, 0.377%, and 0.292%, respectively. The influence of economic development level on agricultural production scale accords with Kuznets curve. However, at the regional level, the influence of each variable on the eastern region is consistent with the trend of the total sample. In the central region, the impact of economic development on agricultural production scale shows a U-shaped curve, and the improvement of urbanization level inhibits the expansion of agricultural production scale. In the western region, all variables failed to pass the significance test. The results of the FMOLS model were validated by the fixed effects model. The results of causality tests showed that bidirectional causality existed between the scale of agricultural production and the level of economic development, the scale of agricultural production and agricultural water use, the level of economic development and the market price of agricultural products, and the level of urbanization and the market price of agricultural products. In different regions, there were differences in causality between variables. Therefore, based on the empirical results, we put forward some policy suggestions to maintain the scale of agricultural production.

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Urban expansion or poor productivity: Explaining regional differences in cropland abandonment in China during the early 21st century

Cited by 31 publications

References 48 publications

Mapping the Northern Limit of Double Cropping Using a Phenology-Based Algorithm and Google Earth Engine

Mapping the Northern Limit of Double Cropping Using a Phenology-Based Algorithm and Google Earth Engine

Degree of Abandoned Cropland and Socioeconomic Impact Factors in China: Multi-Level Analysis Model Based on the Farmer and District/County Levels

Impact of Economic Development Level and Agricultural Water Use on Agricultural Production Scale in China

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