Aims Grasslands are the world’s most extensive terrestrial ecosystem,and are a major feed source for livestock.Meeting increasing demand for meat and other dairy products in a sustainable manner is a big challenge.At...Aims Grasslands are the world’s most extensive terrestrial ecosystem,and are a major feed source for livestock.Meeting increasing demand for meat and other dairy products in a sustainable manner is a big challenge.At a field scale,Global Positioning System and ground-based sensor technologies provide promising tools for grassland and herd management with high precision.With the growth in availability of spaceborne remote sensing data,it is therefore important to revisit the relevant methods and applications that can exploit this imagery.In this article,we have reviewed the(i)current status of grassland monitoring/observation methods and applications based on satellite remote sensing data,(ii)the technological and methodological developments to retrieve different grassland biophysical parameters and management characteristics(i.e.degradation,grazing intensity)and(iii)identified the key remaining challenges and some new upcoming trends for future development.Important Findings The retrieval of grassland biophysical parameters have evolved in recent years from classical regression analysis to more complex,efficient and robust modeling approaches,driven by satellite data,and are likely to continue to be the most robust method for deriving grassland information,however these require more high quality calibration and validation data.We found that the hypertemporal satellite data are widely used for time series generation,and particularly to overcome cloud contamination issues,but the current low spatial resolution of these instruments precludes their use for field-scale application in many countries.This trend may change with the current rise in launch of satellite constellations,such as RapidEye,Sentinel-2 and even the microsatellites such as those operated by Skybox Imaging.Microwave imagery has not been widely used for grassland applications,and a better understanding of the backscatter behaviour from different phenological stages is needed for more reliable products in cloudy regions.The development of hyperspect展开更多
Based on rural household survey data in Taipusi County in Inner Mongolia Autonomous Region, this article analyzes agricultural land use intensity and its determinants. The results reveal marked differences of agricult...Based on rural household survey data in Taipusi County in Inner Mongolia Autonomous Region, this article analyzes agricultural land use intensity and its determinants. The results reveal marked differences of agricultural land use intensity among households with different ages of householders, proportion of non-farm participants, total agricultural land area, land fragmentation and land utilization capacity. （i） Households with older householders and households with a smaller proportion of non-farming laborers generally spend more time on managing their land and invest less capital and materials than other households. The proportion of non-farming laborers within younger households is relatively high, and they tend to invest more capital and materials because the income derived from non-farm employment relaxes their financial constraints. （ii） Land fragmentation is an important determinant of land use intensity. Households with a bigger land size per plot usually spend less time and invest more capital and materials on their land; （iii） Land with better quality is usually managed intensively. The results suggest that labor has become an important constraint for local agricultural production, and there is the potential to improve land management scale and increase machinery input to substitute for labor. Furthermore, the effects of non-farm employment on land use intensity indicate that the establishment of a coordination mechanism between non-farm employment and agricultural land use is an important way to solve the conflict between ecological security and agricultural production in ecologically-vulnerable areas.展开更多
To determine the influence of agricultural meteorological disasters on agriculture in Heilongjiang Province,the disaster areas associated with different types of disasters and their variation characteristics were anal...To determine the influence of agricultural meteorological disasters on agriculture in Heilongjiang Province,the disaster areas associated with different types of disasters and their variation characteristics were analyzed based on the statistical data of agricultural disasters from 1983 to 2013 in Heilongjiang Province,China.The moving average and the Mann-Kendall test were applied to identify the variation trends of drought,flooding,hailstorms and freezing(based on the disaster ratio and the disaster intensity index).Then,the Morlet wavelet analysis method was used to identify the periodicity of these four kinds of agricultural meteorological disasters.Finally,a fuzzy comprehensive evaluation method was adopted to analyze the degrees of agricultural loss induced by these disasters.The following results were obtained:1)The disaster ratio and disaster intensity index for drought exhibited increasing trends;the disaster ratio and disaster intensity index for flooding exhibited decreasing trends;for hailstorms,the disaster ratio exhibited no obvious trend of change,whereas the disaster intensity index exhibited an increasing trend;and for freezing,the disaster ratio also exhibited no obvious trend of change,whereas the disaster intensity index exhibited a decreasing trend.2)Mutation points were observed in the disaster ratio series for drought,flooding and hailstorms,whereas no mutation point was evident in the disaster ratio series for freezing.3)Multiple time-scale characteristics were observed in the disaster ratio series for all four types of agricultural meteorological disasters.Furthermore,the disaster ratio series for the different types of disasters had different main periodicities.4)From the perspective of the degree of agricultural loss induced by each type of disaster,drought was identified as the most severe type of agricultural meteorological disaster,followed by flooding,freezing,and hailstorms.The degree of agricultural loss caused by each type of disaster was different during different periods.Finall展开更多
Peri-urban areas are playing an increasingly crucial role in the agricultural development and intensification in Indonesia.Peri-urban agriculture is highly vulnerable to change compared with urban and rural agricultur...Peri-urban areas are playing an increasingly crucial role in the agricultural development and intensification in Indonesia.Peri-urban agriculture is highly vulnerable to change compared with urban and rural agriculture,due to its location in transitional areas.Indicators of peri-urban agricultural intensity can help guide regional development.In this study,we assessed the sustainability of peri-urban areas based on agricultural intensity in Karawang Regency,Indonesia.We developed a village-based index to assess the region’s agricultural intensity by rescaling the village agriculture index(VAI)and combining the local sustainability index(LSI)with factor analysis.Since the unit of analysis is the village,we modified the LSI to the village sustainability index(VSI).In addition,we also developed a logical matrix analysis to determine the level of agricultural sustainability(LoAS)of each village.The combined results of the three indices(VAI,VSI,and LoAS)generated information about agricultural sustainability.The results indicated that peri-urban villages with high agricultural intensity tended to exhibit low levels of social welfare,economic development,and disaster risk.Moreover,high agricultural intensity did not necessarily ensure the prosperity of the people.Instead,there was the economic disparity among the villages in the study area.Encouraging diversity of agricultural intensity seems to be more critical than promoting agricultural intensity itself.Overall,this study highlights the distinctive characteristics and dynamic of peri-urban areas.New approaches,variables,and information regarding the combination of agricultural intensity and sustainability need to be developed as valuable tools for regional planning.展开更多
A surging population in Karnataka State,a semi-arid region in India,poses a threat to both food security and livelihood sustainability,necessitating a concentrated effort to bolster agricultural efficiency and achieve...A surging population in Karnataka State,a semi-arid region in India,poses a threat to both food security and livelihood sustainability,necessitating a concentrated effort to bolster agricultural efficiency and achieve United Naton’s Sustainable Development Goal 2(zero hunger).Therefore,in order to address the pressing issue of food scarcity in Karnataka,this study meticulously examined the spatio-temporal variation of agricultural efficiency and irrigation intensity in Karnataka,uncovering its significant dependence of agricultural efficiency on irrigation intensity.Specifically,this study used a one-way analysis of variance(ANOVA)to ascertain significant differences in the means of agricultural efficiency and irrigation intensity during 2004-2005 and 2018-2019.This study showed that the maximum improvement in agricultural efficiency index was recorded in Belgaum(40.24),Gulbarga(24.77),and Yadgir districts(22.92)between 2004-2005 and 2018-2019,which indicated the progressing trend and better scope for agriculture extension.On the contrary,some districts expressed threat(a decline of above 20.00 of agricultural efficiency index)and needed special care for the improvement of agricultural efficiency in four northern districts(Bagalkot,Bidar,Raichur,and Bijapur),three southern districts(Chitradurga,Chikballapur and Hassan),and two southern districts(Koppal and Gadag)in Karnataka.During 2004-2005,irrigation intensity varied from 3.19%to 56.39%,with the lowest irrigation intensity in Kodagu District and the highest irrigation intensity in Shimoga District.During 2018-2019,irrigation intensity changed from 0.77%to 72.77%,with the lowest irrigation intensity in Kodagu District and the highest in Dakshin Kannad District.Moreover,the research scrutinized the complex relationship between agricultural efficiency and irrigation intensity,with the correlation coefficient increased from 0.162 during 2004-2005 to 0.255 during 2018-2019.It implies that in both periods,a low positive correlation existed between these two variabl展开更多
Understanding the manifestations and underlying drivers of agricultural land use change in China is of great importance for both domestic and global food security. However, little is known about the holistic pattern o...Understanding the manifestations and underlying drivers of agricultural land use change in China is of great importance for both domestic and global food security. However, little is known about the holistic pattern of agricultural land use change across China, especially from the perspective of intensity since the evidence has been gathered mainly through case studies at local levels. This study conducts a systemic review of agricultural land use change and its underlying drivers in China by aggregating 169 relevant case studies from 123 publications. The cases related to intensification and disintensification, which are the two types of agricultural land use change, are generally equal, accounting for 50% of the total number of cases. Intensification and disintensification can be further divided into the same three categories: expansion/contraction of agricultural land, changes in agricultural land use activities and changes in land management intensity. Demographic, economic, technological, and institutional drivers, together with location factors, are frequently noted as significant underlying drivers, while sociocultural drivers and farm(er) characteristics are less frequently recognized. Finally, three major land use change trajectories are summarized mainly concerning rising labor costs and the concomitant increase in off-farm employment, the ecological improvement policy, and advances in agricultural technology.展开更多
An accurate prediction of peak discharge in watersheds is critical not only for water resource manage-ment,but also for understanding the complex relationships of hydrological processes.In this study,a modified peak d...An accurate prediction of peak discharge in watersheds is critical not only for water resource manage-ment,but also for understanding the complex relationships of hydrological processes.In this study,a modified peak discharge formula based on the Chemicals,Runoff,and Erosion from Agricultural Man-agement Systems(CREAMS)model was developed by introducing rainfall intensity and soil moisture factors.The reliability of the proposed method was tested with data from 1464 storm events in 41 watersheds and was applied to 256 storm events in five remaining typical watersheds using the opti-mized parameters.The results indicate that the proposed method is highly accurate in terms of model efficiency,as determined by Nash-Sutcliffe efficiencies(NSEs)of 88.60%,74.04%,and 90.12%during the calibration,validation,and application cases,respectively.Furthermore,it performed better than the original and modified CREAMS methods.Subsequently,using the parameters derived from the initial 41 watersheds and the runoff estimated using the modified Soil Conservation Service curve number(SCS-CN)method,the proposed method was used to predict the peak discharge from the last five typical watersheds.Large NSE(63.88-80.83%)and low root mean square error(RMSE)values(0.31-35.93 m^(3)s^(-1))were obtained for the five watersheds.Overall,the proposed peak discharge model,combined with the modified SCS-CN method,may accurately predict event-based peak discharge and runoff for general applications under various hydrological and geomorphic conditions in the Loess Plateau region.展开更多
Xinjiang Uygur Autonomous Region,the largest agricultural high-efficiency water-saving arid area in China,was adopted to explore the coupling relationship between agricultural water consumption and economic benefits,w...Xinjiang Uygur Autonomous Region,the largest agricultural high-efficiency water-saving arid area in China,was adopted to explore the coupling relationship between agricultural water consumption and economic benefits,which is of great significance to guiding the efficient utilization and sustainable development of agricultural water resources.This study utilizes an indicator,termed the Agricultural Water Footprint Intensity(short as AWFI,which means the amount of water resource consumed per unit of agricultural GDP),to study the economic benefits of agricultural water in Xinjiang from 1991-2018.In addition,the Theil index,a measure of the imbalance between individuals or regions,was used to study the evolution in the spatial differences in water efficiency,and the Logarithmic Mean Divisia Index(LMDI)method was applied to quantify the factors driving the AWFI.The results showed that AWFI in Xinjiang has experienced three stages:obvious decline,stable and slow decline,which decreased from 16114 m^(3)/10^(4) CNY to 2100 m^(3)/10^(4) CNY,decreasing by 86.97%.The Theil index indicated that the spatial evolution of 14 prefectures(cities)resembled an inverted N-shaped Kuznets curve over time.Among the influencing factors,the contributions of water-saving technology and planting structure to the change in the AWFI in Xinjiang,China from 1991 to 2018 were 154.03%and−37.98%,respectively.The total contribution to AWFI of the total population,urbanization rate,and production scale was−16.06%.This study concluded that further improvements in the economic benefits of agricultural water consumption can be obtained by continuing to promote more efficient or“water-conservation”irrigation technologies(engineering aspects),adjusting the planting structure(policy guidance aspects),and intensive management of cultivated land(management aspects).展开更多
基金Teagasc Walsh Fellowship Program for funding this research.
文摘Aims Grasslands are the world’s most extensive terrestrial ecosystem,and are a major feed source for livestock.Meeting increasing demand for meat and other dairy products in a sustainable manner is a big challenge.At a field scale,Global Positioning System and ground-based sensor technologies provide promising tools for grassland and herd management with high precision.With the growth in availability of spaceborne remote sensing data,it is therefore important to revisit the relevant methods and applications that can exploit this imagery.In this article,we have reviewed the(i)current status of grassland monitoring/observation methods and applications based on satellite remote sensing data,(ii)the technological and methodological developments to retrieve different grassland biophysical parameters and management characteristics(i.e.degradation,grazing intensity)and(iii)identified the key remaining challenges and some new upcoming trends for future development.Important Findings The retrieval of grassland biophysical parameters have evolved in recent years from classical regression analysis to more complex,efficient and robust modeling approaches,driven by satellite data,and are likely to continue to be the most robust method for deriving grassland information,however these require more high quality calibration and validation data.We found that the hypertemporal satellite data are widely used for time series generation,and particularly to overcome cloud contamination issues,but the current low spatial resolution of these instruments precludes their use for field-scale application in many countries.This trend may change with the current rise in launch of satellite constellations,such as RapidEye,Sentinel-2 and even the microsatellites such as those operated by Skybox Imaging.Microwave imagery has not been widely used for grassland applications,and a better understanding of the backscatter behaviour from different phenological stages is needed for more reliable products in cloudy regions.The development of hyperspect
基金National Science Foundation of China (Grant No.40971062)
文摘Based on rural household survey data in Taipusi County in Inner Mongolia Autonomous Region, this article analyzes agricultural land use intensity and its determinants. The results reveal marked differences of agricultural land use intensity among households with different ages of householders, proportion of non-farm participants, total agricultural land area, land fragmentation and land utilization capacity. （i） Households with older householders and households with a smaller proportion of non-farming laborers generally spend more time on managing their land and invest less capital and materials than other households. The proportion of non-farming laborers within younger households is relatively high, and they tend to invest more capital and materials because the income derived from non-farm employment relaxes their financial constraints. （ii） Land fragmentation is an important determinant of land use intensity. Households with a bigger land size per plot usually spend less time and invest more capital and materials on their land; （iii） Land with better quality is usually managed intensively. The results suggest that labor has become an important constraint for local agricultural production, and there is the potential to improve land management scale and increase machinery input to substitute for labor. Furthermore, the effects of non-farm employment on land use intensity indicate that the establishment of a coordination mechanism between non-farm employment and agricultural land use is an important way to solve the conflict between ecological security and agricultural production in ecologically-vulnerable areas.
基金This work was supported by the National Key R&D Program of China(No:2017YFC0406004)the National Natural Science Foundation of China(No:51109036,51179032)+5 种基金the Natural Science Foundation of Heilongjiang Province of China(No:E2015024)the Research Fund for the Doctoral Program of Higher Education of China(No:20112325120009)the Foundation for Reserve Academic Leader in Province Lead Team of Heilongjiang Province of China(No:500001)the Research Foundation for Postdoctors of Heilongjiang Province of China(No:LBH-Q12147)the Projects for Science and Technology Development of Water Conservancy Bureau in Heilongjiang Province of China(No:201402,No:201404,No:201501)the Academic Backbones Foundation of Northeast Agricultural University(No.16XG11).
文摘To determine the influence of agricultural meteorological disasters on agriculture in Heilongjiang Province,the disaster areas associated with different types of disasters and their variation characteristics were analyzed based on the statistical data of agricultural disasters from 1983 to 2013 in Heilongjiang Province,China.The moving average and the Mann-Kendall test were applied to identify the variation trends of drought,flooding,hailstorms and freezing(based on the disaster ratio and the disaster intensity index).Then,the Morlet wavelet analysis method was used to identify the periodicity of these four kinds of agricultural meteorological disasters.Finally,a fuzzy comprehensive evaluation method was adopted to analyze the degrees of agricultural loss induced by these disasters.The following results were obtained:1)The disaster ratio and disaster intensity index for drought exhibited increasing trends;the disaster ratio and disaster intensity index for flooding exhibited decreasing trends;for hailstorms,the disaster ratio exhibited no obvious trend of change,whereas the disaster intensity index exhibited an increasing trend;and for freezing,the disaster ratio also exhibited no obvious trend of change,whereas the disaster intensity index exhibited a decreasing trend.2)Mutation points were observed in the disaster ratio series for drought,flooding and hailstorms,whereas no mutation point was evident in the disaster ratio series for freezing.3)Multiple time-scale characteristics were observed in the disaster ratio series for all four types of agricultural meteorological disasters.Furthermore,the disaster ratio series for the different types of disasters had different main periodicities.4)From the perspective of the degree of agricultural loss induced by each type of disaster,drought was identified as the most severe type of agricultural meteorological disaster,followed by flooding,freezing,and hailstorms.The degree of agricultural loss caused by each type of disaster was different during different periods.Finall
文摘Peri-urban areas are playing an increasingly crucial role in the agricultural development and intensification in Indonesia.Peri-urban agriculture is highly vulnerable to change compared with urban and rural agriculture,due to its location in transitional areas.Indicators of peri-urban agricultural intensity can help guide regional development.In this study,we assessed the sustainability of peri-urban areas based on agricultural intensity in Karawang Regency,Indonesia.We developed a village-based index to assess the region’s agricultural intensity by rescaling the village agriculture index(VAI)and combining the local sustainability index(LSI)with factor analysis.Since the unit of analysis is the village,we modified the LSI to the village sustainability index(VSI).In addition,we also developed a logical matrix analysis to determine the level of agricultural sustainability(LoAS)of each village.The combined results of the three indices(VAI,VSI,and LoAS)generated information about agricultural sustainability.The results indicated that peri-urban villages with high agricultural intensity tended to exhibit low levels of social welfare,economic development,and disaster risk.Moreover,high agricultural intensity did not necessarily ensure the prosperity of the people.Instead,there was the economic disparity among the villages in the study area.Encouraging diversity of agricultural intensity seems to be more critical than promoting agricultural intensity itself.Overall,this study highlights the distinctive characteristics and dynamic of peri-urban areas.New approaches,variables,and information regarding the combination of agricultural intensity and sustainability need to be developed as valuable tools for regional planning.
文摘A surging population in Karnataka State,a semi-arid region in India,poses a threat to both food security and livelihood sustainability,necessitating a concentrated effort to bolster agricultural efficiency and achieve United Naton’s Sustainable Development Goal 2(zero hunger).Therefore,in order to address the pressing issue of food scarcity in Karnataka,this study meticulously examined the spatio-temporal variation of agricultural efficiency and irrigation intensity in Karnataka,uncovering its significant dependence of agricultural efficiency on irrigation intensity.Specifically,this study used a one-way analysis of variance(ANOVA)to ascertain significant differences in the means of agricultural efficiency and irrigation intensity during 2004-2005 and 2018-2019.This study showed that the maximum improvement in agricultural efficiency index was recorded in Belgaum(40.24),Gulbarga(24.77),and Yadgir districts(22.92)between 2004-2005 and 2018-2019,which indicated the progressing trend and better scope for agriculture extension.On the contrary,some districts expressed threat(a decline of above 20.00 of agricultural efficiency index)and needed special care for the improvement of agricultural efficiency in four northern districts(Bagalkot,Bidar,Raichur,and Bijapur),three southern districts(Chitradurga,Chikballapur and Hassan),and two southern districts(Koppal and Gadag)in Karnataka.During 2004-2005,irrigation intensity varied from 3.19%to 56.39%,with the lowest irrigation intensity in Kodagu District and the highest irrigation intensity in Shimoga District.During 2018-2019,irrigation intensity changed from 0.77%to 72.77%,with the lowest irrigation intensity in Kodagu District and the highest in Dakshin Kannad District.Moreover,the research scrutinized the complex relationship between agricultural efficiency and irrigation intensity,with the correlation coefficient increased from 0.162 during 2004-2005 to 0.255 during 2018-2019.It implies that in both periods,a low positive correlation existed between these two variabl
基金National Key Research and Development Program of China,No.2017YFE0104600National Natural Science Foundation of China,No.41930757。
文摘Understanding the manifestations and underlying drivers of agricultural land use change in China is of great importance for both domestic and global food security. However, little is known about the holistic pattern of agricultural land use change across China, especially from the perspective of intensity since the evidence has been gathered mainly through case studies at local levels. This study conducts a systemic review of agricultural land use change and its underlying drivers in China by aggregating 169 relevant case studies from 123 publications. The cases related to intensification and disintensification, which are the two types of agricultural land use change, are generally equal, accounting for 50% of the total number of cases. Intensification and disintensification can be further divided into the same three categories: expansion/contraction of agricultural land, changes in agricultural land use activities and changes in land management intensity. Demographic, economic, technological, and institutional drivers, together with location factors, are frequently noted as significant underlying drivers, while sociocultural drivers and farm(er) characteristics are less frequently recognized. Finally, three major land use change trajectories are summarized mainly concerning rising labor costs and the concomitant increase in off-farm employment, the ecological improvement policy, and advances in agricultural technology.
基金supported by the National Natural Science Foundation of China(42107351)China Postdoctoral Science Foundation(2019M663917XB)+2 种基金Natural Science Fund of Shaanxi Province(2021JQ-227)Fundamental Research Funds for the Central Universities,CHD(300102291104 and 300102291507)Programme of Introducing Talents of Discipline to Universities(B08039).
文摘An accurate prediction of peak discharge in watersheds is critical not only for water resource manage-ment,but also for understanding the complex relationships of hydrological processes.In this study,a modified peak discharge formula based on the Chemicals,Runoff,and Erosion from Agricultural Man-agement Systems(CREAMS)model was developed by introducing rainfall intensity and soil moisture factors.The reliability of the proposed method was tested with data from 1464 storm events in 41 watersheds and was applied to 256 storm events in five remaining typical watersheds using the opti-mized parameters.The results indicate that the proposed method is highly accurate in terms of model efficiency,as determined by Nash-Sutcliffe efficiencies(NSEs)of 88.60%,74.04%,and 90.12%during the calibration,validation,and application cases,respectively.Furthermore,it performed better than the original and modified CREAMS methods.Subsequently,using the parameters derived from the initial 41 watersheds and the runoff estimated using the modified Soil Conservation Service curve number(SCS-CN)method,the proposed method was used to predict the peak discharge from the last five typical watersheds.Large NSE(63.88-80.83%)and low root mean square error(RMSE)values(0.31-35.93 m^(3)s^(-1))were obtained for the five watersheds.Overall,the proposed peak discharge model,combined with the modified SCS-CN method,may accurately predict event-based peak discharge and runoff for general applications under various hydrological and geomorphic conditions in the Loess Plateau region.
基金This work was financially supported by the Third Xinjiang Scientific Expedition(Grant No.2022xjkk0103,2021xjkk0406)the National Natural Science Foundation of China(Grant No.52179028)+1 种基金the Water Conservancy Science and Technology Project of Hunan Province(Grant No.XSKJ2019081-02)the Xinjiang Water Conservancy Science and technology project(Grant No.XSKJ-2021-01).
文摘Xinjiang Uygur Autonomous Region,the largest agricultural high-efficiency water-saving arid area in China,was adopted to explore the coupling relationship between agricultural water consumption and economic benefits,which is of great significance to guiding the efficient utilization and sustainable development of agricultural water resources.This study utilizes an indicator,termed the Agricultural Water Footprint Intensity(short as AWFI,which means the amount of water resource consumed per unit of agricultural GDP),to study the economic benefits of agricultural water in Xinjiang from 1991-2018.In addition,the Theil index,a measure of the imbalance between individuals or regions,was used to study the evolution in the spatial differences in water efficiency,and the Logarithmic Mean Divisia Index(LMDI)method was applied to quantify the factors driving the AWFI.The results showed that AWFI in Xinjiang has experienced three stages:obvious decline,stable and slow decline,which decreased from 16114 m^(3)/10^(4) CNY to 2100 m^(3)/10^(4) CNY,decreasing by 86.97%.The Theil index indicated that the spatial evolution of 14 prefectures(cities)resembled an inverted N-shaped Kuznets curve over time.Among the influencing factors,the contributions of water-saving technology and planting structure to the change in the AWFI in Xinjiang,China from 1991 to 2018 were 154.03%and−37.98%,respectively.The total contribution to AWFI of the total population,urbanization rate,and production scale was−16.06%.This study concluded that further improvements in the economic benefits of agricultural water consumption can be obtained by continuing to promote more efficient or“water-conservation”irrigation technologies(engineering aspects),adjusting the planting structure(policy guidance aspects),and intensive management of cultivated land(management aspects).
