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Land
Special Issues
Arable Land Quality: Observation, Estimation, Optimization and Application
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Arable Land Quality: Observation, Estimation, Optimization and Application

A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: closed (15 September 2023) | Viewed by 24641

Special Issue Editors

Prof. Dr. Changqing Song

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Guest Editor
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Interests: synthetic ggeography; human-earth System Coupling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yakov Kuzyakov

E-Mail Website
Guest Editor
Department of Soil Science of Temperate Ecosystems, University of Göttingen, 37077 Göttingen, Germany
Interests: priming effects; stable and radioactive isotopes; climate change and land use effect
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Feng Cheng

E-Mail Website
Guest Editor
China Land Surveying and Planning Institute, Beijing 100035, China
Interests: arable land quality assessment
Prof. Dr. Xiangbin Kong

E-Mail Website
Guest Editor
College of Land Science and Technology, China Agricultural University, Beijing 100193, China
Interests: arable land quality; LUCC; land ecology
Special Issues, Collections and Topics in MDPI journals
Dr. Zhe Feng

E-Mail Website
Guest Editor
School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China
Interests: ecosystem service; landscape ecology; land resources management; land policy
Special Issues, Collections and Topics in MDPI journals
Dr. Peichao Gao

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Guest Editor
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Interests: sustainable land use; geographic trade-offs; geographic complexity; spatial entropy as applied in landscapes and image analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Sijing Ye

E-Mail Website
Guest Editor
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Interests: arable land monitoring; evaluation and protection; geographic spatiotemporal data analysis; land use change simulation and evaluation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sustainable use of arable land plays an important role in reducing soil erosion, eliminating hunger and coping with climate change. Cognition of regional arable land quality and its leading factors is crucial for planning sustainable arable land use path that protect the stability of farmland ecosystems while meeting the growing demand for food.

Arable land quality is driven by interaction between the natural system and the utilization system, and is the comprehensive expression of the farmland ecosystem functions. In recent decades, national governments attach importance to protect arable land quality. For instance, protect arable land quality become core compositions of China’s arable land protection strategy. Without the considering of arable land quality status, it will be hard to systematically implement farmland red line control and high-standard farmland construction, and to trade off appropriate local path between “land sharing” and “land sparing”. Meanwhile, researches on arable land quality has developed from farmland productivity and cultivation suitability assessment to coupling intensive use of arable land with healthy development of farmland ecosystem. The theoretical connotation has been greatly enriched, observation techniques and calculation models have been steadily improved, and scientific data and practical experience have been gradually accumulated. Whereas, there are still challenges in study of arable land quality, related to cognition of regional leading factors; indicators’ observation and simulation techniques; comprehensive evaluation theories and methods. Explore these issues is of great significance for the sustainable development of mankind.

This special issue on “arable land quality: observation, estimation, optimization and application” is dedicated to bring advances on our understanding of the patterns, regional leading factors, and influences of arable land quality.

We therefore invite contributions covering, but not limited to, papers on the following topics:

  1. Theories and methods for arable land quality evaluation and its regional practice;
  2. Observation and simulation of arable land quality indicators;
  3. Spatio-temporal variation of regional arable land quality and its leading factors;
  4. Arable land quality and ecosystem health;
  5. Arable land quality and agricultural intensification;
  6. Landscape optimization considering arable land quality;
  7. Applications of arable land quality in land use and restoration;
  8. Paths for protecting arable land quality;

Prof. Dr. Changqing Song
Prof. Dr. Yakov Kuzyakov
Prof. Dr. Feng Cheng
Prof. Dr. Xiangbin Kong
Dr. Zhe Feng
Dr. Peichao Gao
Dr. Sijing Ye
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • arable land quality
  • ecosystem health
  • LUCC
  • land use intensity
  • soil properties
  • landscape optimization
  • arable land health
  • land-computing

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Published Papers (12 papers)

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Editorial

Jump to: Research

9 pages, 802 KiB  
Editorial
Arable Land Quality in Developing China: An Integrated Exploration from Global Challenges to Localized Solutions
by Sijing Ye, Changqing Song, Yakov Kuzyakov, Feng Cheng, Xiangbin Kong, Zhe Feng and Peichao Gao
Land 2024, 13(3), 350; https://doi.org/10.3390/land13030350 - 8 Mar 2024
Viewed by 1882
Abstract
Ensuring global food security and sustainable development remains a top priority at present [...] Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)
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5 pages, 198 KiB  
Editorial
Preface: Arable Land Quality: Observation, Estimation, Optimization, and Application
by Sijing Ye, Changqing Song, Yakov Kuzyakov, Feng Cheng, Xiangbin Kong, Zhe Feng and Peichao Gao
Land 2022, 11(6), 947; https://doi.org/10.3390/land11060947 - 20 Jun 2022
Cited by 9 | Viewed by 2007
Abstract
Food security is a worldwide challenge that is related to the basic human needs of sustainable development [...] Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)

Research

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20 pages, 9499 KiB  
Article
A Big Data Grided Organization and Management Method for Cropland Quality Evaluation
by Shuangxi Miao, Shuyu Wang, Chunyan Huang, Xiaohong Xia, Lingling Sang, Jianxi Huang, Han Liu, Zheng Zhang, Junxiao Zhang, Xu Huang and Fei Gao
Land 2023, 12(10), 1916; https://doi.org/10.3390/land12101916 - 13 Oct 2023
Viewed by 1334
Abstract
A new gridded spatio-temporal big data fusion method is proposed for the organization and management of cropland big data, which could serve the analysis application of cropland quality evaluation and other analyses of geographic big data. Compared with traditional big data fusion methods, [...] Read more.
A new gridded spatio-temporal big data fusion method is proposed for the organization and management of cropland big data, which could serve the analysis application of cropland quality evaluation and other analyses of geographic big data. Compared with traditional big data fusion methods, this method maps the spatio-temporal and attribute features of multi-source data to grid cells in order to achieve the structural unity and orderly organization of spatio-temporal big data with format differences, semantic ambiguities, and different coordinate projections. Firstly, this paper constructs a dissected cropland big data fusion model and completes the design of a conceptual model and logic model, constructs a cropland data organization model based on DGGS (discrete global grid system) and Hash coding, and realizes the unified management of vector data, raster data and text data by using multilevel grids. Secondly, this paper researches the evaluation methods of grid-scale adaptability, and generates distributed multilevel grid datasets to meet the needs of cropland area quality evaluation. Finally, typical data such as soil organic matter data, road network data, cropland area data, and statistic data in Da’an County, China, were selected to carry out the experiment. The experiment verifies that the method could not only realize the unified organization and efficient management of cultivated land big data with multimodal characteristics, but also support the evaluation of cropland quality. Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)
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22 pages, 42937 KiB  
Article
Evaluation of Spatiotemporal Changes in Cropland Quantity and Quality with Multi-Source Remote Sensing
by Han Liu, Yu Wang, Lingling Sang, Caisheng Zhao, Tengyun Hu, Hongtao Liu, Zheng Zhang, Shuyu Wang, Shuangxi Miao and Zhengshan Ju
Land 2023, 12(9), 1764; https://doi.org/10.3390/land12091764 - 12 Sep 2023
Cited by 3 | Viewed by 1408
Abstract
Timely cropland information is crucial for ensuring food security and promoting sustainable development. Traditional field survey methods are time-consuming and costly, making it difficult to support rapid monitoring of large-scale cropland changes. Furthermore, most existing studies focus on cropland evaluation from a single [...] Read more.
Timely cropland information is crucial for ensuring food security and promoting sustainable development. Traditional field survey methods are time-consuming and costly, making it difficult to support rapid monitoring of large-scale cropland changes. Furthermore, most existing studies focus on cropland evaluation from a single aspect such as quantity or quality, and thus cannot comprehensively reveal spatiotemporal characteristics of cropland. In this study, a method for evaluating the quantity and quality of cropland using multi-source remote sensing-derived data was proposed and effectively applied in the black soil region in Northeast China. Evaluation results showed that the area of cropland increased significantly in the study area between 2010 and 2018, and the proportion of cropland increased by 1.17%. Simultaneously, cropland patches became larger and landscape connectivity improved. Most of the gained cropland was concentrated in the northeast and west, resulting in a shift in the gravity center of cropland to the northeast direction. Among land converted into cropland, unused land, grassland, and forest were the main sources, accounting for 36.38%, 31.47%, and 16.94% respectively. The quality of cropland in the study area generally improved. The proportion of low-quality cropland decreased by 7.17%, while the proportions of high-quality and medium-quality cropland increased by 5.65% and 5.17%, respectively. Specifically, the quality of cropland improved strongly in the east, improved slightly in the southwest, and declined in the north. Production capacity and soil fertility were key factors impacting cropland quality with obstacle degrees of 36.22% and 15.64%, respectively. Overall, the obtained results were helpful for a comprehensive understanding of spatiotemporal changes in cropland and driving factors and can provide guidance for cropland protection and management. The proposed method demonstrated promising reliability and application potential, which can provide a reference for other cropland evaluation studies. Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)
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22 pages, 4077 KiB  
Article
Input Flux and the Risk of Heavy Metal(Loid) of Agricultural Soil in China: Based on Spatiotemporal Heterogeneity from 2000 to 2021
by Wenyu Ma, Yuchun Pan, Zaijin Sun, Changhua Liu, Xiaolan Li, Li Xu and Yunbing Gao
Land 2023, 12(6), 1240; https://doi.org/10.3390/land12061240 - 16 Jun 2023
Cited by 4 | Viewed by 1449
Abstract
Identifying the current status of the heavy metal(loid) input of agricultural soils is vital for the soil ecological environment of agricultural-producing areas. Most previous studies have typically carried been out in small regions with limited sampling sites, which is insufficient to reveal the [...] Read more.
Identifying the current status of the heavy metal(loid) input of agricultural soils is vital for the soil ecological environment of agricultural-producing areas. Most previous studies have typically carried been out in small regions with limited sampling sites, which is insufficient to reveal the overall status of China. This study reviewed publications from over the past 20 years and calculated the input fluxes of heavy metal(loid)s in agricultural soil via atmospheric deposition, fertilizer, manure, and irrigation in different regions of China based on spatiotemporal heterogeneity using a meta-analysis, providing more accurate and reliable results. It was found that the heavy metal(loid) input flux of atmospheric deposition in China is large, while that of fertilizer and manure is relatively low compared to Europe. The major sources of As, Cd, Cr, Ni, and Pb entering the soil was atmospheric deposition, which accounted for 12% to 92% of the total input. Manure was responsible for 19% to 75% of the Cu and Zn input. Cd is the element presenting the most significant risk to the environment of agricultural soils in China and its safety limit will be reached within 100 years for most regions. The region we need to be concerned about is Huang-Huai-Hai due to its comprehensive pollution. Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)
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14 pages, 3783 KiB  
Article
Distribution Characteristics and Influencing Factors of Soil Biological Indicators in Typical Farmland Soils
by Long Kang, Rui Zhao, Kening Wu, Zhe Feng, Huafu Zhao and Sicheng Zhang
Land 2023, 12(4), 755; https://doi.org/10.3390/land12040755 - 27 Mar 2023
Cited by 1 | Viewed by 2167
Abstract
Soil biodiversity drives soil-based ecosystem services and is an important indicator of soil health. To understand the responses of important soil biological indicators to different farmland use contexts, 72 fields in three agricultural regions of China were used as research objects. The distribution [...] Read more.
Soil biodiversity drives soil-based ecosystem services and is an important indicator of soil health. To understand the responses of important soil biological indicators to different farmland use contexts, 72 fields in three agricultural regions of China were used as research objects. The distribution characteristics and the factors influencing six indicators (carbon and nitrogen contents of soil microbial biomass (MBC, MBN, respectively), soil respiration (SR), soil catalase activity (CAT), soil acid phosphomonoesterase activity (APA), and soil earthworms) were investigated using field monitoring and indoor analysis. The MBC, SR, CAT, and APA indicators showed significant differences among the regions (p < 0.05). Correlation and redundancy analyses indicated that the important factors affecting MBC, MBN, and soil respiration were cation exchange capacity, total N, organic matter, hydrolytic N, and soil bulk density, whereas the important factors affecting APA and earthworms were total phosphorus, available phosphorus, and available potassium. None of these factors had a significant effect on CAT. Climatic conditions, soil types, and farmland practices all have complex impacts on soil biodiversity. The results showed that attention should be paid to improving the physical conditions of the soil and to increasing soil fertility levels when establishing sustainable farm management patterns. Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)
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19 pages, 12765 KiB  
Article
Spatial Differentiation and Influencing Mechanisms of Farmland Transfer Rents in Mountainous Areas: Evidence from Chongqing and Its Surrounding Areas
by Ting Du, Chao Li and Zhaolin Wang
Land 2023, 12(3), 699; https://doi.org/10.3390/land12030699 - 16 Mar 2023
Cited by 1 | Viewed by 1905
Abstract
This study used Chongqing, a municipality in mountainous southwest China, and its surrounding areas as a case study to explore the spatial differentiation of farmland transfer rents in mountainous areas, with the aim of serving as a theoretical and practical reference to realize [...] Read more.
This study used Chongqing, a municipality in mountainous southwest China, and its surrounding areas as a case study to explore the spatial differentiation of farmland transfer rents in mountainous areas, with the aim of serving as a theoretical and practical reference to realize the value of farmland, ensure regional food security, and promote stable and sound development of the farmland transfer market. In doing so, we applied the GIS spatial analysis method to explore the spatial differentiation and influencing mechanisms of farmland transfer rents in mountainous areas. Our results indicate that farmland transfer rents in mountainous areas have a significant high and low clustering tendency. The high-value areas of farmland transfer rents are mainly located in the downtown area and the west of Chongqing, while the low-value areas are mainly distributed in the Daba Mountains and Wuling Mountains, which are two national contiguous areas of dire poverty. Location and terrain factors are the main driving forces for the spatial differentiation of farmland transfer rents in mountainous areas. Specifically, a 1% increase in farmland mean slope and farmland supply-demand ratio in the study area will lead to a 0.13 and 0.15% decrease in farmland transfer rents, respectively, while a 1% increase in GDP will drive up farmland transfer rents by 0.09%. The policy factor is not significant. The influence of terrain and farmland supply and demand on transfer rents increased from west to east, whereas the influence of traffic location on transfer rents decreased in an outward direction from the southwest of the study area. It is concluded that local governments should objectively view the spatial differentiation of farmland transfer rents in mountainous areas and avoid the blind comparison of transfer rents between regions. Mountainous areas with low transfer rents should focus on increasing the intrinsic value of farmland assets by stimulating effective demand for farmland and improving farming conditions, while mountainous areas with high transfer rents in major grain-producing counties should be wary of their impact on grain production to ensure regional food security. Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)
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22 pages, 13096 KiB  
Article
Spatio-Temporal Analysis of Cultivated Land from 2010 to 2020 in Long’an County, Karst Region, China
by Jianhui Dong, Wenju Yun, Kening Wu, Shaoshuai Li, Bingrui Liu and Qiaoyuan Lu
Land 2023, 12(2), 515; https://doi.org/10.3390/land12020515 - 20 Feb 2023
Cited by 3 | Viewed by 1909
Abstract
Spatio-temporal changes in cultivated land have a profound impact on food security and sustainable development. However, existing studies on spatio-temporal changes in cultivated land mostly focus on single factors, for instance quantity, quality and ecology, that cannot comprehensively reflect the changes in total [...] Read more.
Spatio-temporal changes in cultivated land have a profound impact on food security and sustainable development. However, existing studies on spatio-temporal changes in cultivated land mostly focus on single factors, for instance quantity, quality and ecology, that cannot comprehensively reflect the changes in total production capacity and the sustainability of cultivated land. This study aims to construct a comprehensive analysis approach and to provide a reference basis for a comprehensive analysis of the extent of changes in overall cultivated land food-production capacity and the formulation of cultivated land conservation-related policies. This comprehensive analysis method constructed from three dimensions: quantity, production capacity and ecology, fully reflects the changes in the total amount, structure, rate of change, spatial distribution, quality, total production capacity and sustainability of cultivated land. The results from the application of this approach to Long’an County, Guangxi Province, China demonstrate that: (a) from 2010 to 2020, the total amount of cultivated land in Long’an County decreased sharply by 30.83%, accounted for mainly by the conversion into orchards, forest land and other garden land; (b) the quality of cultivated land improved by 2.71% on average, mostly in relation to natural factors; (c) the total food-production capacity of cultivated land decreased by 28.96% on average, mainly due to the decrease in the area of cultivated land; (d) both the ecological grade and the sustainability of cultivated land decreased slightly; (e) the barycenter of cultivated land migrated 3.3 km to the ecologically sensitive areas in the west, and the patch size of cultivated land decreased from an average of 2.60 hectares/pc in 2010 to that of 1.34 hectares/pc in 2020, suggesting increased fragmentation of cultivated land; and (f) the patch regularity of cultivated land decreased from 2.08 in 2010 to 1.76 in 2020, showing improved patch regularity and slightly better adaptability to mechanization. There were two main reasons for the lower, total food production capacity in Long’an County: first, the low comparative income of grain cultivation, because of which farmers spontaneously adjusted the agricultural cultivation structure to pursue high returns; and second, the lack of targeted government policies to protect cultivated land. In general, this comprehensive analysis method is applicable to other provinces in China or other regions abroad to provide a reference basis for a comprehensive understanding of changes in the food production capacity of cultivated land and the formulation of policies on cultivated land protection. Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)
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14 pages, 4782 KiB  
Article
Quantitative Study on Agricultural Premium Rate and Its Distribution in China
by Yaoyao Wu, Hanqi Liao, Lei Fang and Guizhen Guo
Land 2023, 12(1), 263; https://doi.org/10.3390/land12010263 - 16 Jan 2023
Viewed by 2504
Abstract
In recent years, with the deepening of the reform of rural economic systems, the demand for disaster risk governance in land production and management is increasing, and it is urgent for the state to develop agricultural insurance to improve land production recovery capacity [...] Read more.
In recent years, with the deepening of the reform of rural economic systems, the demand for disaster risk governance in land production and management is increasing, and it is urgent for the state to develop agricultural insurance to improve land production recovery capacity and ensure national food security. The study develops a quantitative model to determine the agricultural premium rate for each county in China based on disaster risk level in order to refine agricultural insurance. The results show that: (a) in terms of the disaster situation, most of northeast and central China, part of southwest, north, and northwest China are seriously affected; (b) regarding the integrated natural disaster risk level, there are 129 counties with extremely high disaster risk in China; (c) as for agricultural premium rates based on the integrated natural disaster risk index, some counties in Inner Mongolia, Shanxi, Liaoning, Jilin, Shandong, Anhui, Jiangxi, Zhejiang, Guangdong, Hubei, and Hunan Province had extremely high rates, out of a total of 63 counties. The above results reveal regional differences in disaster risk levels and premium rates between counties, providing a reference for improving the accuracy of agricultural premium rates. This contributes to the creation of security for further improving land production capacity and promoting the intensification and sustainable development of agricultural production. Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)
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17 pages, 3069 KiB  
Article
System Cognition and Analytic Technology of Cultivated Land Quality from a Data Perspective
by Huaizhi Tang, Jiacheng Niu, Zibing Niu, Qi Liu, Yuanfang Huang, Wenju Yun, Chongyang Shen and Zejun Huo
Land 2023, 12(1), 237; https://doi.org/10.3390/land12010237 - 12 Jan 2023
Cited by 8 | Viewed by 2481
Abstract
As cultivated land quality has been paid more and more scientific attention, its connotation generalization and cognitive bias are widespread, bringing many challenges to the investigation and evaluation of regional cultivated land quality and its data analysis and mining. Establishing a systematic and [...] Read more.
As cultivated land quality has been paid more and more scientific attention, its connotation generalization and cognitive bias are widespread, bringing many challenges to the investigation and evaluation of regional cultivated land quality and its data analysis and mining. Establishing a systematic and interdisciplinary cognitive approach to cultivated land quality is urgent and necessary. Therefore, we explored and developed a conceptual framework of the model for the cultivated land quality analysis from the data perspective, including cultivated land quality ontology, mapping, correlation, and decision models. We identified the primary content of cultivated land quality perceptions and four cognitive mechanisms. We built vital technologies, such as the collaborative perception of the quality of cultivated land, intelligent treatment, diagnostic evaluation, and simulation prediction. Applying this analysis framework, we sorted out the frequency of indicators that characterize the function of cultivated land according to the literature in recent years and have built the cognitive system of cultivated land quality in the black soil region of Northeast China. The system’s central component was production capacity and it had three components: a foundation, a guarantee, and an effect. The black soil region cultivated land quality evaluation system has seven purposes involving 20–31 key indicators: production supply, threat control, farmland infrastructure regulation, cultivated land ecological maintenance, economics, social culture, and environmental protection. In various application contexts, the system had many critical supporting technologies. The results demonstrate that the framework has strong adaptability, efficiency, and scalability, which might offer a theoretical direction for further studies on the evaluation of the quality of cultivated land in the area. The analysis framework established in this study is helpful to deepen the understanding of cultivated land quality systems from the perspective of big data. Taking the big data of cultivated land quality as the driving force, combined with the technical methods of cultivated land quality analysis, the evaluation results of cultivated land quality under different scenarios and different objectives are optimized. In addition, the framework can serve the practice of farmland management and engineering improvement, adapt to the management needs of different objects and different scales, and achieve the combination of theory and practice. Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)
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14 pages, 2772 KiB  
Article
Is Cultivated Land Increased by Land Consolidation Sustainably Used in Mountainous Areas?
by Jian Zhou, Chao Li, Xiaotong Chu and Chenying Luo
Land 2022, 11(12), 2236; https://doi.org/10.3390/land11122236 - 8 Dec 2022
Cited by 9 | Viewed by 1627
Abstract
Land consolidation (LC) in China is an important means by which we can increase the quantity and improve the quality of cultivated land. At present, large areas of cultivated land are abandoned in mountainous areas. It is unclear whether the increased cultivated land [...] Read more.
Land consolidation (LC) in China is an important means by which we can increase the quantity and improve the quality of cultivated land. At present, large areas of cultivated land are abandoned in mountainous areas. It is unclear whether the increased cultivated land from LC in mountainous areas is sustainably used. Data from 64 land consolidation zones completed in 2016 in the Qinba Mountain Area were collected. The land-use status was obtained from high-resolution remote sensing images by the method of visual interpretation, and land-use changes were analyzed. According to our results, the increased cultivated land by LC is mainly terrace, accounting for 92.22% of the total area of increased cultivated land. The increased cultivated land is mainly distributed in the Qinba Mountainous Area, and terrace is the main type of increased cultivated land in both the Hanzhong Basin Area and Qinba Mountainous Area. The transformation rate of cultivated land from LC, especially terrace, is small. The transformation rates of terrace in the Hanzhong Basin Area and Qinba Mountainous Area are 0.36% and 0.09%, respectively. The socioeconomic development in mountainous areas is relatively lagging, and the per capita cultivated land area is small. Many farmers are still engaged in agricultural production and earn a basic income. Thus, high-quality cultivated land with convenient transportation is sustainably used. LC remains a key avenue for increasing cultivated land area, improving agricultural productivity, increasing farmers’ incomes, and promoting rural development in the mountainous areas. Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)
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19 pages, 3015 KiB  
Article
A Cooperative-Dominated Model of Conservation Tillage to Mitigate Soil Degradation on Cultivated Land and Its Effectiveness Evaluation
by Yubo Liao, Bangbang Zhang, Xiangbin Kong, Liangyou Wen, Dongheng Yao, Yuxuan Dang and Wenguang Chen
Land 2022, 11(8), 1223; https://doi.org/10.3390/land11081223 - 3 Aug 2022
Cited by 8 | Viewed by 2038
Abstract
Sustainable agricultural production systems are important for ensuring food security. However, they are severely threatened by soil degradation and carbon emissions resulting from traditional farming practices. A cooperative-dominated conservation tillage model attempts to mitigate these issues, yet it is not clear how this [...] Read more.
Sustainable agricultural production systems are important for ensuring food security. However, they are severely threatened by soil degradation and carbon emissions resulting from traditional farming practices. A cooperative-dominated conservation tillage model attempts to mitigate these issues, yet it is not clear how this model has been implemented and how well it performs in practice. This study takes Lishu County in Jilin Province in Northeast China as a case study to explore the implementation of a cooperative-dominated conservation tillage (CDCT) model and its practical effectiveness. In contrast to the traditional production model, this model uses cooperatives as the direct managers of cultivated land and promotes the construction of new production units and large-scale and mechanized operations to standardize the application of conservation tillage technology in agricultural production. Scientific research institutes, governments, and enterprises are supporters of cooperatives, empowering them in terms of technology, capital, products, and services. The evaluation results show that, unlike the traditional production model, which caused a decrease in the soil organic carbon content, the organic carbon content of the topsoil of cultivated land under this model increased by an average of 6.17% after 9 years of conservation tillage application. Furthermore, the soil structural stability index of the cultivated land increased from 3.35% to 3.69%, indicating that the degree of soil structural degradation was alleviated to a certain extent. The CDCT model effectively enhanced the operational efficiency and fertilizer use efficiency, and the carbon footprint of maize production was also reduced by 15.65% compared to the traditional production model. In addition, the total production cost was reduced by 1449 CNY/ha and profit increased by 2599 CNY/ha on average, indicating higher economic returns under the CDCT model due to increased yields and lower input costs. Farmers who are freed from agricultural production activities by transferring their farmland can also gain two types of income—land revenue and labor wagesi—thus mproving their living conditions. The CDCT model can deliver multigoal benefits and be of great value in its extension to other regions. This study may provide lessons for the sustainable use of cultivated land in China and other developing countries, contributing to agricultural development with lower environmental costs. Full article
(This article belongs to the Special Issue Arable Land Quality: Observation, Estimation, Optimization and Application)
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