Crop planting patterns are an important component of agricultural land systems.These patterns have been significantly changed due to the combined impacts of climatic changes and socioeconomic developments.However,the ...Crop planting patterns are an important component of agricultural land systems.These patterns have been significantly changed due to the combined impacts of climatic changes and socioeconomic developments.However,the extent of these changes and their possible impacts on the environment,terrestrial landscapes and rural livelihoods are largely unknown due to the lack of spatially explicit datasets including crop planting patterns.To fill this gap,this study proposes a new method for spatializing statistical data to generate multitemporal crop planting pattern datasets.This method features a two-level model that combines a land-use simulation and a crop pattern simulation.The output of the first level is the spatial distribution of the cropland,which is then used as the input for the second level,which allocates crop censuses to individual gridded cells according to certain rules.The method was tested using data from 2000 to 2019 from Heilongjiang Province,China,and was validated using remote sensing images.The results show that this method has high accuracy for crop area spatialization.Spatial crop pattern datasets over a given time period can be important supplementary information for remote sensing and thus support a wide range of application in agricultural land systems.展开更多
State farms,although a minority in China’s agricultural sector,play a critical role in regions like Heilongjiang,leading national food production.However,how state farms(SFs)and rural household farms(RFs)respond to f...State farms,although a minority in China’s agricultural sector,play a critical role in regions like Heilongjiang,leading national food production.However,how state farms(SFs)and rural household farms(RFs)respond to food policies,especially the 2017 soybean subsidy policy(post-Sino–U.S.trade war)and the 2019 soybean revitalization policy,remains unclear.This study examines changes in cropping patterns on SFs and RFs in Heilongjiang from 2013 to 2022 using annual crop maps.We find that SFs,with larger and more clustered fields,responded more effectively to the soybean policies:soybean acreage recovery(2019–2021)reached 91.51%of pre-trade war levels for RFs and 98.2%for SFs;following the revitalization policy,maize-soybean rotations were implemented four times in 62.3%of SFs and 45.4%of RFs.These results highlight the influence of global trade and agricultural policies on cropland management,providing critical insights into sustainable practices and food security across different agricultural systems.展开更多
The rapid identification of planting patterns for major crops in a large irrigated district has vital importance for irrigation management,water fee collection,and crop yield estimation.In this study,the OTSU algorith...The rapid identification of planting patterns for major crops in a large irrigated district has vital importance for irrigation management,water fee collection,and crop yield estimation.In this study,the OTSU algorithm and Mean-Shift algorithm were employed to automatically determine threshold values for mapping two main rotated crop patterns at the pixel scale.A time series analysis was conducted to extract the spatial distribution of rice-wheat and wheat-maize rotations in the Chuanhang irrigation district from 2016 to 2020.The results demonstrate that both threshold segmentation algorithms are reliable in extracting the spatial distribution of the crops,with an overall accuracy exceeding 80%.Additionally,both Kappa coefficients surpass 0.7,indicating better performance by OTSU method.Over the period from 2016 to 2020,the area occupied by rice-wheat rotation cropping ranged from 12500 to 14400 hm 2;whereas wheat-maize rotation cropping exhibited smaller and more variable areas ranging from 19730 to 34070 hm 2.These findings highlight how remote sensing-based approaches can provide reliable support for rapidly and accurately identifying the spatial distribution of main crop rotation patterns within a large irrigation district.展开更多
Mapping and monitoring the distribution of croplands and crop types support policymakers and international organizations by reducing the risks to food security,notably from climate change and,for that purpose,remote s...Mapping and monitoring the distribution of croplands and crop types support policymakers and international organizations by reducing the risks to food security,notably from climate change and,for that purpose,remote sensing is routinely used.However,identifying specific crop types,cropland,and cropping patterns using space-based observations is challenging because different crop types and cropping patterns have similarity spectral signatures.This study applied a methodology to identify cropland and specific crop types,including tobacco,wheat,barley,and gram,as well as the following cropping patterns:wheat-tobacco,wheat-gram,wheat-barley,and wheat-maize,which are common in Gujranwala District,Pakistan,the study region.The methodology consists of combining optical remote sensing images from Sentinel-2 and Landsat-8 with Machine Learning(ML)methods,namely a Decision Tree Classifier(DTC)and a Random Forest(RF)algorithm.The best time-periods for differentiating cropland from other land cover types were identified,and then Sentinel-2 and Landsat 8 NDVI-based time-series were linked to phenological parameters to determine the different crop types and cropping patterns over the study region using their temporal indices and ML algorithms.The methodology was subsequently evaluated using Landsat images,crop statistical data for 2020 and 2021,and field data on cropping patterns.The results highlight the high level of accuracy of the methodological approach presented using Sentinel-2 and Landsat-8 images,together with ML techniques,for mapping not only the distribution of cropland,but also crop types and cropping patterns when validated at the county level.These results reveal that this methodology has benefits for monitoring and evaluating food security in Pakistan,adding to the evidence base of other studies on the use of remote sensing to identify crop types and cropping patterns in other countries.展开更多
Through the pot experiment, the effects of different cropping patterns of soybean and maize seedlings on rhizosphere soil urease, catalase, polyphenol oxidase and invertase activities and microbial biomass carbon （MB...Through the pot experiment, the effects of different cropping patterns of soybean and maize seedlings on rhizosphere soil urease, catalase, polyphenol oxidase and invertase activities and microbial biomass carbon （MBC） and nitrogen （MBN） were studied. Six treatments of soybean-soybean, soybean-maize, soybean-mixed, maize-soybean, maize-maize and maize-mixed were conducted in pots. Results showed that catalase activity and invertase activity of maize-maize were the highest and significantly different from those of the other treatments except maize-soybean; soil polyphenol oxidase activity of soybean-maize was the highest, and reached significant level among the other treatments, but there was no significant difference of urease activity among treatment soils; MBC of maize-maize soil and MBN of maize-mixed soil reached the highest and significant levels compared with other treatments; MBC and C/N ratio had positive and very significant correlations with soil catalase activity and invertase activity, respectively. Therefore, different cropping patterns could affect rhizosphere soil enzyme activities and soil MBC and MBN, which influenced soil carbon and nitrogen mineralization.展开更多
Adequate freshwater supply has become an issue of increasing local and international concern. Reducing water use in agriculture, which is the largest water using sector of the economy, is both important and urgent. Th...Adequate freshwater supply has become an issue of increasing local and international concern. Reducing water use in agriculture, which is the largest water using sector of the economy, is both important and urgent. The aim of this paper was to quantify how recent cropping pattern changes have influenced water resources in the great Beijing metropolitan area, an expanding megacity which also includes rural counties. Crop production affects blue water use through water consumption and water pollution, the latter assessed here using a critical dilution method. From 1990 to 2010, the total blue water used by crop production declined due to a decrease in overall cropped area, initially in response to local government policies favouring urban development. However, the average blue water use per hectare increased from 2 112 m3 ha-~ yr-~ in 1990 to 2 764 m3 ha-1 yr-1 in 2003, largely as the result of a transition from cereal to vegetable crops, and in particular an increase in intensively managed plastic and glass covered vegetable production systems. Current policies aim to conserve agricultural land, in the interests of food security, and to stimulate cereal production systems with higher ecosystem services provision. As such, in 2010 the average blue water use was 2 425 m3 ha-~ yr-l. These results demonstrate that cropping pattern changes in peri-urban regions and rural communities surrounding the Beijing metropolitan area can have a substantial impact on water resources. They also highlight the tradeoffs between food production and urban and industrial water supply and the need for integrated policy development.展开更多
The study of the spatial patterns and temporal changes of cropland is important to understand the underlying factors and the functional effects of the agricultural landscape. On the other hand, crop dynamics mapping i...The study of the spatial patterns and temporal changes of cropland is important to understand the underlying factors and the functional effects of the agricultural landscape. On the other hand, crop dynamics mapping is essential to know the overall agro-spatial diversity of the area. Therefore, this paper addressed a spatio-temporal analysis of cropland and cropping pattern change in the Bogra district of Bangladesh over the last 16 years （between 1988/89 and 2004/05）. In this paper, crop mapping from multi-temporal and multi-sensor satellite images was described. Landsat TM and IRS P6 LlSS Ⅲ satellite images were used with GIS for spatial dynamics of cropland and cropping pattern change analysis. First, seasonal cropland maps were derived from object-based classification of satellite images, then two-date classified image differencing with GIS overlay technique and decision rules were applied. Cropping pattern change was analyzed in a spatial and quantitative way for the 16 years and for this, Integrated Land and Water Information System （ILWIS） and Land Change Modular （LCM） of IDRISl Andes were used. The results showed that in the area, mono crop cultivation was found in summer, but in winter, areas under different crop cultivation had changed dramatically. Change analysis showed that the changes mainly occurred in the north northwest and southwest of the areas, and during the time the highest change area was found under the rice-potato pattern.展开更多
Quantitative indexes such as land equivalent ratio, yield equivalent and value of output equivalent were used to evaluate output efficiencies of different cropping patterns, i.e., sequential cropping, intercrops and c...Quantitative indexes such as land equivalent ratio, yield equivalent and value of output equivalent were used to evaluate output efficiencies of different cropping patterns, i.e., sequential cropping, intercrops and crop rotation. Compared to single cropping, land use efficiencies under sequential cropping, intercrops and crop rotation were raised by 62, 38 and 21%, respectively. The unit area yield under sequential cropping, intercrops and crop rotation were raised by 63, 29 and 16%, respectively. The unit area value was also enhanced under sequential cropping and intercrops, 76 and 35% higher than that under single cropping. The paper provides a useful tool for comparing farm output efficiency and build up a theoretical basis for further research on output efficiency of various cropping patterns in the future.展开更多
It is of paramount importance to have sustainable agriculture since agriculture is the backbone of many nations’ economic development. Majority of agricultural professionals rarely capture the cropping patterns neces...It is of paramount importance to have sustainable agriculture since agriculture is the backbone of many nations’ economic development. Majority of agricultural professionals rarely capture the cropping patterns necessary to promote Good Agricultural Practises.Objective of this research is to explore the potential of mapping cropping patterns occurring on different field parcels on small-scale farmlands in Zimbabwe. The first study location under investigation are the International Maize and Wheat Improvement Center(CIMMYT) research station and a few neighboring fields, the second is Middle Sabi Estate. Fourier time series modeling was implemented to determine the trends befalling on the two study sites. Results reveal that Sentinel-1 synthetic aperture radar(SAR) time series allow detection of subtle changes that occur to the crops and fields respectively, hence can be utilized to detect cropping patterns on small-scale farmlands. Discrimination of the main crops(maize and soybean) grown at CIMMYT was possible, and crop rotation was synthesized where sowing starts in November. A single cropping of early and late crops was observed, there were no winter crops planted during the investigation period. At Middle Sabi Estate, single cropping on perennial sugarcane fields and triple cropping of fields growing leafy vegetables, tomatoes and onions were observed. Classification of stacked images was used to derive the crop rotation maps representing what is practised at the farming lands. Random forest classification of the multi-temporal image stacks achieved overall accuracies of 99% and 95% on the respective study sites. In conclusion, Sentinel-1 time series can be implemented effectively to map the cropping patterns and crop rotations occurring on small-scale farming land. We recommend the use of Sentinel-1 SAR multi-temporal data to spatially explicitly map cropping patterns of single-, double-and triple-cropping systems on both small-scale and large-scale farming areas to ensure food security.展开更多
In this paper, authors established a farmer crop selection model（FCS） for the three provinces of Liaoning, Jilin and Heilongjiang of the Northeast China. With linking to the environmental policy integrated climate m...In this paper, authors established a farmer crop selection model（FCS） for the three provinces of Liaoning, Jilin and Heilongjiang of the Northeast China. With linking to the environmental policy integrated climate model（EPIC）, the simulated results of FCS model for maize, rice and soybean were spatialized with 1 km×1 km grids to obtain cropping pattern. The reference map of spatial distribution for the three staple crops acquired by remote sensing imageries was applied to validate the simulated cropping pattern. The results showed that（1） the total simulation accuracy for the study area was 78.62%, which proved simulation method was applicable and feasible;（2） simulation accuracy for Jilin Province was the highest among the three provinces with a rate of 82.45% since its simple cropping system and not complex topography;（3） simulation accuracy for maize was the best among the three staple crops with a ratio of 81.14% because the study area is very suitable for maize growth. We hope this study could provide the reference for cropping pattern forecasting and decision-making.展开更多
Land use change and cropping patterns are important factors for controlling carbon sequestration in soils and they may also change the relative importance of different mechanisms of soil organic matter stabilization. ...Land use change and cropping patterns are important factors for controlling carbon sequestration in soils and they may also change the relative importance of different mechanisms of soil organic matter stabilization. The study was conducted to investigate the state of carbon sequestration in soil aggregates under different cropping patterns of Khulna, Jessore and Chapainawabganj districts in Bangladesh. Thirty-six soil samples were collected from (0 - 100 cm depth) above mentioned regions of three physiographic regions: Ganges Meander Floodplain, Ganges Tidal Floodplain and High Barind Tract. The texture of the samples varied within three soil texture groups, Silt Loam, Silty Clay Loam and Silty Clay. The highest NSI value (0.89) was found under Wheat-Fallow-T. Aman cropping pattern in Silty Clay soils (sample No 15) and lowest value (0.59) was found Vegetables/Mustard-Fallow-T. Aman cropping pattern in Silt Loam soils (sample No 17). The highest value (735.20 mg<span style="white-space:nowrap;"><span style="white-space:nowrap;">•</span></span>kg<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>1</sup>) of active C was observed under Chickpea/mustard-T. Aman (Sample No 31) and the lowest value (619.23 mg<span style="white-space:nowrap;"><span style="white-space:nowrap;">•</span></span>kg<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>1</sup>) was found in case of Wheat-Fallow-T. Aman cropping pattern (Sample No 30). The highest SOC stock (1.62 Kg C m<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>2</sup>) was found in Silty Clay Loam soil under Mungbean/Ash gourd-T. Aman cropping pattern (Sample no 4) and the lowest SOC stock (0.35 Kg C m<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>2</sup>) was found in Silt Loam soil under Cauliflower/Pumkin/Spinach-T. Aman Cropping pattern (Sample No 2). Soil organic carbon associated with different size aggregates was the highest (3.14%) under Mungbean/Ash gourd-T. Aman (Sample No 20) and was the lowest (0.36%) under Cauliflower/Pumkin/Spinach-T. Aman cropping pattern (Sample No 2). Organic carbon content in aggregate size ranges > 2000 μm (SOC1), 2000 - 250 μm (SOC2), 250-53 μm (SOC3), and <53 μm (SOC4) varied from 0.36% - 1.90%, 0.52% - 2.10%, 0.50% - 2.60% and 0.50% - 1.62%, respectively. The percentages of SOC associated with <53 μm aggregates were higher than those of >2000 μm, 2000 - 250 μm and 250 - 53 μm, aggregates. Significant positive correlations were found between SOC stock and SOC1, SOC stock and SOC2, SOC stock and SOC3, SOC stock and SOC4.展开更多
At the same time of tending forests,it is necessary to explore the under-forest economic development mode,bring into play production function of economic plants,establish cultivation mode of edible fungus,wild vegetab...At the same time of tending forests,it is necessary to explore the under-forest economic development mode,bring into play production function of economic plants,establish cultivation mode of edible fungus,wild vegetables and medicinal plants under forest,to obtain certain economic benefit in short period. This paper made a preliminary study on significance and existing problems of the under-forest economy,and came up with several interplanting patterns,in the hope of providing a comprehensive operation and cultivation approach for developing the under-forest economy.展开更多
The experiments were conducted at the Pulses Research Centre, Ishurdi, Pabna, Bangladesh during the 2005-2006 and 2006-2007 crop seasons to determine the economic viability of planting legumes for both vegetable and f...The experiments were conducted at the Pulses Research Centre, Ishurdi, Pabna, Bangladesh during the 2005-2006 and 2006-2007 crop seasons to determine the economic viability of planting legumes for both vegetable and forage purposes in the fallow period between monsoon-rice and spring-rice. The objectives were to ensure better land utilization, break up the mono cropping, improve soil health, and generate extra-income for small and resource-poor farmers of Bangladesh. Crop compositions used in the experiments were monsoon-rice （cv. BRRIdhan-32, BRRldhan-39 and BINAdhan-4） followed by pulses （grasspea, chickpea and field pea） followed by spring-rice （cv. BRRldhan-28, BRRldhan-29 and BINAdhan-6）. Based on the data from two years in a pooled analyses, it was observed that monsoon-rice variety BINAdhan-4, followed by field pea （as vegetable ＆ forage） and spring-rice variety BINAdhan-6 produced the highest yields of 5.0 t ha-1 rice grain, 3.25 t ha1 （green vegetable） ＋ 18.1 t hal （forage） legumes and 7.8 t ha~ rice grain, respectively. The cropping pattern of monsoon-rice （BINAdhan-4）-field pea （as vegetable ＋ forage）-spring-rice （BINAdhan-6） gave the highest net return of USD$1,705 hal year-~ compared to other patterns with different rice varieties and chickpea and grasspea. This is a new finding, and is being practiced by farmers of Bangladesh who have enhanced their farm income substantially. This has also generated job opportunities for rural women to pick the green vegetable of field pea.展开更多
The efficient cultivation technique of "rice-rice-potato" triple cropping rotation pattern is summarized by analyzing its characteristics and cultivation techniques in Yangjiang region of Guangdong Province,...The efficient cultivation technique of "rice-rice-potato" triple cropping rotation pattern is summarized by analyzing its characteristics and cultivation techniques in Yangjiang region of Guangdong Province,China,and machine-transplanted cultivation technique of double cropping rice and cultivation techniques of winter potato black film mulching are emphatically introduced,in order to promote the development of potato industry in Yangjiang City.The results will provide a scientific basis for the popularization and application of the "rice-rice-potato" triple cropping rotation pattern.展开更多
[Objective] To screen ratooning rice varieties for the ratooning rice-rape cropping planting pattern in Ganfu Plain. [Method] The growth period, plant morphology, yield and its component of 11 varieties at the first a...[Objective] To screen ratooning rice varieties for the ratooning rice-rape cropping planting pattern in Ganfu Plain. [Method] The growth period, plant morphology, yield and its component of 11 varieties at the first and rebirth season were compared and analyzed. [Result] The ratooning rice varieties such as Heliangyou -1, Y Liangyou 6, Zhunliangyou 608 and Jingliangyouhuazhan were suitable for the production and application in Ganfu Plain. Heliangyou 1 and Zhunliangyou 608 showed the characteristics of early maturity, easy to achieve high yield and stable production. [Conclusion] It suggests that Heliangyou 1 and Zhunliangyou 608 should be selected as preferred varieties for the planting pattern of ratooning rice-rape cropping.展开更多
Several whole-farm agro-economic optimization models have been developed to deal with lumped planning issues in the agriculture sector. However, these models cannot be used to devise appropriate management strategies ...Several whole-farm agro-economic optimization models have been developed to deal with lumped planning issues in the agriculture sector. However, these models cannot be used to devise appropriate management strategies at land parcel level, because of the differences between farm characteristics, and the increased complexity of the hydrological processes. Based on Spatial Farm Database (SFD) which is consisted of a number of farm-level spatial data, including location, paddock properties, owner specifications and budgets, it is possible to provide the farm manager with some suggestions regarding the optimal choice of crops and the area to be allocated for each one. To this end, genetic algorithm is used in order to cope with model nonlinearity and a large number of decision variables. In order to test the proposed model, the Mobarakabad district is modeled with 126 agriculture fields, and the optimization model is run for this area. Results showed that the optimization procedure can find more realistic farm-level optimal solutions due to its advantage in adequate modeling of field characteristics, common groundwater resources, and the associated constraints. The results of lumped optimizations could also be used as benchmarks for the purposes of comparison and interpretation.展开更多
Creation of a spectral signature reflectance data, which aids in the identification of the crops is important in determining size and location crop fields. Therefore, we developed a spectral signature reflectance for ...Creation of a spectral signature reflectance data, which aids in the identification of the crops is important in determining size and location crop fields. Therefore, we developed a spectral signature reflectance for the vegetative stage of the green gram (Vigna. radiata L.) over 5 years (2020, 2018, 2017, 2015, and 2013) for agroecological zone IV and V in Kenya. The years chosen were those whose satellite resolution data was available for the vegetative stage of crop growth in the short rain season (October, November, December (OND)). We used Landsat 8 OLI satellite imagery in this study. Cropping pattern data for the study area were evaluated by calculating the Top of Atmosphere reflectance. Farms geo-referencing, along with field data collection, was undertaken to extract Top of Atmosphere reflectance for bands 2, 3, 4 and 7. We also carried a spectral similarity assessment on the various cropping patterns. The spectral reflectance ranged from 0.07696 - 0.09632, 0.07466 - 0.09467, 0.0704047 - 0.12188,0.19822 - 0.24387, 0.19269 - 0.26900, and 0.11354 - 0.20815 for bands 2, 3, 4, 5, 6, and 7 for green gram, respectively. The results showed a dissimilarity among the various cropping patterns. The lowest dissimilarity index was 0.027 for the maize (Zea mays L.) bean (Phaseolus vulgaris) versus the maize-pigeon pea (Cajanus cajan) crop, while the highest dissimilarity index was 0.443 for the maize bean versus the maize bean and cowpea cropping patterns. High crop dissimilarities experienced across the cropping pattern through these spectral reflectance values confirm that the green gram was potentially identifiable. The results can be used in crop type identification in agroecological lower midland zone IV and V for mung bean management. This study therefore suggests that use of reflectance data in remote sensing of agricultural ecosystems would aid in planning, management, and crop allocation to different ecozones.展开更多
We studied a new grain-cash cropping pattern composed of "barley/watermelon + waize-rice", comparing with "barley / watermelon-rice" (CKI), "watermelon-rice", (CK2). The experiment was co...We studied a new grain-cash cropping pattern composed of "barley/watermelon + waize-rice", comparing with "barley / watermelon-rice" (CKI), "watermelon-rice", (CK2). The experiment was conducted in CNRRI’s field for 3 yr, employing completely randomized design with three replications, and each plot occupied 207 m~2. The soil in the experiment field contained: N, 2.48 g. kg, quick effective P 4 mg. kg, and quick effective K 53 mg·kg. The varieties tested were Zhemai 2 (barley), Zhemi 1 (watermelon), Suyu 1 (maize), and Shanyou 63 (hybrid rice).展开更多
China’s endeavors to mitigate recurrent crop residue burning(CRB)and improve air quality have yielded positive results owing to recent pollution prevention policies.Nonetheless,persistent challenges remain,particular...China’s endeavors to mitigate recurrent crop residue burning(CRB)and improve air quality have yielded positive results owing to recent pollution prevention policies.Nonetheless,persistent challenges remain,particularly in the Northeast China(NEC),where low temperature complicates crop residue management.Here,we examined the effects of cropping pattern adjustment on variations of CRB patterns in NEC during 2001-2021,utilizing the Moderate-resolution Imaging Spectroradiometer(MODIS)burned area dataset,the Visible Infrared Imaging Radiometer Suite(VIIRS)active fire dataset,and the high-accuracy crop planting area maps.Our results revealed an overall upward trend of 805.96 km^(2)/yr in NEC CRB from 2001 to 2021.The corn CRB area accounted for more than 50%of the total CRB area in each CRB-intensive year(2013-2021),and the increasing corn CRB generally aligns with the growing corn cultivation fields.A seasonal shift in CRB was found around 2017,with intensive CRB activities transitioning from both autumn and spring to primarily spring,particularly in the Songnen Plain and Sanjiang Plain.The changing trend of PM2.5 concentration aligned spatially with the shift.Moreover,the CRBs in spring of 2020 and 2021 were more severe than the major burning seasons in previous years,likely due to the disruptions during COVID-19 lockdowns.In certain years,the explanatory power of spring CRB on PM2.5 concentration was comparable to that of other natural factors,such as precipitation.This study underscores the critical need for sustained and region-specific strategies to tackle the challenges posed by CRBs.展开更多
基金supported and financed by the National key Research and Development Program of China(2019YFA0607400)the Fundamental Research Funds for the Central Universities, China (CCNU19TS045)
文摘Crop planting patterns are an important component of agricultural land systems.These patterns have been significantly changed due to the combined impacts of climatic changes and socioeconomic developments.However,the extent of these changes and their possible impacts on the environment,terrestrial landscapes and rural livelihoods are largely unknown due to the lack of spatially explicit datasets including crop planting patterns.To fill this gap,this study proposes a new method for spatializing statistical data to generate multitemporal crop planting pattern datasets.This method features a two-level model that combines a land-use simulation and a crop pattern simulation.The output of the first level is the spatial distribution of the cropland,which is then used as the input for the second level,which allocates crop censuses to individual gridded cells according to certain rules.The method was tested using data from 2000 to 2019 from Heilongjiang Province,China,and was validated using remote sensing images.The results show that this method has high accuracy for crop area spatialization.Spatial crop pattern datasets over a given time period can be important supplementary information for remote sensing and thus support a wide range of application in agricultural land systems.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFD1500200)the National Natural Science Foundation of China(Grants No.72221002,42271375,42461144212)+2 种基金the Informatization Plan of the Chinese Academy of Sciences(Grant No.CAS-WX2021PY-0109)the funding project of Northeast Geological S&T Innovation Center Zone of China Geological Survey(Grant No.QCJJ2022-9)the funding project of China Association for Science and Technology(Grant No.XMSB20240927024).
文摘State farms,although a minority in China’s agricultural sector,play a critical role in regions like Heilongjiang,leading national food production.However,how state farms(SFs)and rural household farms(RFs)respond to food policies,especially the 2017 soybean subsidy policy(post-Sino–U.S.trade war)and the 2019 soybean revitalization policy,remains unclear.This study examines changes in cropping patterns on SFs and RFs in Heilongjiang from 2013 to 2022 using annual crop maps.We find that SFs,with larger and more clustered fields,responded more effectively to the soybean policies:soybean acreage recovery(2019–2021)reached 91.51%of pre-trade war levels for RFs and 98.2%for SFs;following the revitalization policy,maize-soybean rotations were implemented four times in 62.3%of SFs and 45.4%of RFs.These results highlight the influence of global trade and agricultural policies on cropland management,providing critical insights into sustainable practices and food security across different agricultural systems.
基金Jiangsu Water Science and Technology Project(2021081)。
文摘The rapid identification of planting patterns for major crops in a large irrigated district has vital importance for irrigation management,water fee collection,and crop yield estimation.In this study,the OTSU algorithm and Mean-Shift algorithm were employed to automatically determine threshold values for mapping two main rotated crop patterns at the pixel scale.A time series analysis was conducted to extract the spatial distribution of rice-wheat and wheat-maize rotations in the Chuanhang irrigation district from 2016 to 2020.The results demonstrate that both threshold segmentation algorithms are reliable in extracting the spatial distribution of the crops,with an overall accuracy exceeding 80%.Additionally,both Kappa coefficients surpass 0.7,indicating better performance by OTSU method.Over the period from 2016 to 2020,the area occupied by rice-wheat rotation cropping ranged from 12500 to 14400 hm 2;whereas wheat-maize rotation cropping exhibited smaller and more variable areas ranging from 19730 to 34070 hm 2.These findings highlight how remote sensing-based approaches can provide reliable support for rapidly and accurately identifying the spatial distribution of main crop rotation patterns within a large irrigation district.
文摘Mapping and monitoring the distribution of croplands and crop types support policymakers and international organizations by reducing the risks to food security,notably from climate change and,for that purpose,remote sensing is routinely used.However,identifying specific crop types,cropland,and cropping patterns using space-based observations is challenging because different crop types and cropping patterns have similarity spectral signatures.This study applied a methodology to identify cropland and specific crop types,including tobacco,wheat,barley,and gram,as well as the following cropping patterns:wheat-tobacco,wheat-gram,wheat-barley,and wheat-maize,which are common in Gujranwala District,Pakistan,the study region.The methodology consists of combining optical remote sensing images from Sentinel-2 and Landsat-8 with Machine Learning(ML)methods,namely a Decision Tree Classifier(DTC)and a Random Forest(RF)algorithm.The best time-periods for differentiating cropland from other land cover types were identified,and then Sentinel-2 and Landsat 8 NDVI-based time-series were linked to phenological parameters to determine the different crop types and cropping patterns over the study region using their temporal indices and ML algorithms.The methodology was subsequently evaluated using Landsat images,crop statistical data for 2020 and 2021,and field data on cropping patterns.The results highlight the high level of accuracy of the methodological approach presented using Sentinel-2 and Landsat-8 images,together with ML techniques,for mapping not only the distribution of cropland,but also crop types and cropping patterns when validated at the county level.These results reveal that this methodology has benefits for monitoring and evaluating food security in Pakistan,adding to the evidence base of other studies on the use of remote sensing to identify crop types and cropping patterns in other countries.
基金Supported by the Scientific Research Foundation for Doctor of Northeast Agricultural UniversityInnovative Team Fund of Northeast Agricultural University
文摘Through the pot experiment, the effects of different cropping patterns of soybean and maize seedlings on rhizosphere soil urease, catalase, polyphenol oxidase and invertase activities and microbial biomass carbon （MBC） and nitrogen （MBN） were studied. Six treatments of soybean-soybean, soybean-maize, soybean-mixed, maize-soybean, maize-maize and maize-mixed were conducted in pots. Results showed that catalase activity and invertase activity of maize-maize were the highest and significantly different from those of the other treatments except maize-soybean; soil polyphenol oxidase activity of soybean-maize was the highest, and reached significant level among the other treatments, but there was no significant difference of urease activity among treatment soils; MBC of maize-maize soil and MBN of maize-mixed soil reached the highest and significant levels compared with other treatments; MBC and C/N ratio had positive and very significant correlations with soil catalase activity and invertase activity, respectively. Therefore, different cropping patterns could affect rhizosphere soil enzyme activities and soil MBC and MBN, which influenced soil carbon and nitrogen mineralization.
基金supported by the Special Fund for Agro-scientific Research in the Public Interest,China(201103001)the National Basic Research Program of China(2010CB951500)the CSIRO-Chinese Ministry of Education Ph D Research Fellowship Program
文摘Adequate freshwater supply has become an issue of increasing local and international concern. Reducing water use in agriculture, which is the largest water using sector of the economy, is both important and urgent. The aim of this paper was to quantify how recent cropping pattern changes have influenced water resources in the great Beijing metropolitan area, an expanding megacity which also includes rural counties. Crop production affects blue water use through water consumption and water pollution, the latter assessed here using a critical dilution method. From 1990 to 2010, the total blue water used by crop production declined due to a decrease in overall cropped area, initially in response to local government policies favouring urban development. However, the average blue water use per hectare increased from 2 112 m3 ha-~ yr-~ in 1990 to 2 764 m3 ha-1 yr-1 in 2003, largely as the result of a transition from cereal to vegetable crops, and in particular an increase in intensively managed plastic and glass covered vegetable production systems. Current policies aim to conserve agricultural land, in the interests of food security, and to stimulate cereal production systems with higher ecosystem services provision. As such, in 2010 the average blue water use was 2 425 m3 ha-~ yr-l. These results demonstrate that cropping pattern changes in peri-urban regions and rural communities surrounding the Beijing metropolitan area can have a substantial impact on water resources. They also highlight the tradeoffs between food production and urban and industrial water supply and the need for integrated policy development.
文摘The study of the spatial patterns and temporal changes of cropland is important to understand the underlying factors and the functional effects of the agricultural landscape. On the other hand, crop dynamics mapping is essential to know the overall agro-spatial diversity of the area. Therefore, this paper addressed a spatio-temporal analysis of cropland and cropping pattern change in the Bogra district of Bangladesh over the last 16 years （between 1988/89 and 2004/05）. In this paper, crop mapping from multi-temporal and multi-sensor satellite images was described. Landsat TM and IRS P6 LlSS Ⅲ satellite images were used with GIS for spatial dynamics of cropland and cropping pattern change analysis. First, seasonal cropland maps were derived from object-based classification of satellite images, then two-date classified image differencing with GIS overlay technique and decision rules were applied. Cropping pattern change was analyzed in a spatial and quantitative way for the 16 years and for this, Integrated Land and Water Information System （ILWIS） and Land Change Modular （LCM） of IDRISl Andes were used. The results showed that in the area, mono crop cultivation was found in summer, but in winter, areas under different crop cultivation had changed dramatically. Change analysis showed that the changes mainly occurred in the north northwest and southwest of the areas, and during the time the highest change area was found under the rice-potato pattern.
文摘Quantitative indexes such as land equivalent ratio, yield equivalent and value of output equivalent were used to evaluate output efficiencies of different cropping patterns, i.e., sequential cropping, intercrops and crop rotation. Compared to single cropping, land use efficiencies under sequential cropping, intercrops and crop rotation were raised by 62, 38 and 21%, respectively. The unit area yield under sequential cropping, intercrops and crop rotation were raised by 63, 29 and 16%, respectively. The unit area value was also enhanced under sequential cropping and intercrops, 76 and 35% higher than that under single cropping. The paper provides a useful tool for comparing farm output efficiency and build up a theoretical basis for further research on output efficiency of various cropping patterns in the future.
基金Under the auspices of Fundamental Research Funds for the Central Universities,China(No.2017TD-26)the Plan for Changbai Mountain Scholars of Jilin Province,China(No.JJLZ[2015]54)
文摘It is of paramount importance to have sustainable agriculture since agriculture is the backbone of many nations’ economic development. Majority of agricultural professionals rarely capture the cropping patterns necessary to promote Good Agricultural Practises.Objective of this research is to explore the potential of mapping cropping patterns occurring on different field parcels on small-scale farmlands in Zimbabwe. The first study location under investigation are the International Maize and Wheat Improvement Center(CIMMYT) research station and a few neighboring fields, the second is Middle Sabi Estate. Fourier time series modeling was implemented to determine the trends befalling on the two study sites. Results reveal that Sentinel-1 synthetic aperture radar(SAR) time series allow detection of subtle changes that occur to the crops and fields respectively, hence can be utilized to detect cropping patterns on small-scale farmlands. Discrimination of the main crops(maize and soybean) grown at CIMMYT was possible, and crop rotation was synthesized where sowing starts in November. A single cropping of early and late crops was observed, there were no winter crops planted during the investigation period. At Middle Sabi Estate, single cropping on perennial sugarcane fields and triple cropping of fields growing leafy vegetables, tomatoes and onions were observed. Classification of stacked images was used to derive the crop rotation maps representing what is practised at the farming lands. Random forest classification of the multi-temporal image stacks achieved overall accuracies of 99% and 95% on the respective study sites. In conclusion, Sentinel-1 time series can be implemented effectively to map the cropping patterns and crop rotations occurring on small-scale farming land. We recommend the use of Sentinel-1 SAR multi-temporal data to spatially explicitly map cropping patterns of single-, double-and triple-cropping systems on both small-scale and large-scale farming areas to ensure food security.
基金funded by the National Natural Science Foundation of China (41001049, 2011–2013)the China Regional Arable Land Resources Changes and its Warning-A Case Study in Northeast China, Ministry of Science and Technology of China (2004DIB3J092, 2003–2008)
文摘In this paper, authors established a farmer crop selection model（FCS） for the three provinces of Liaoning, Jilin and Heilongjiang of the Northeast China. With linking to the environmental policy integrated climate model（EPIC）, the simulated results of FCS model for maize, rice and soybean were spatialized with 1 km×1 km grids to obtain cropping pattern. The reference map of spatial distribution for the three staple crops acquired by remote sensing imageries was applied to validate the simulated cropping pattern. The results showed that（1） the total simulation accuracy for the study area was 78.62%, which proved simulation method was applicable and feasible;（2） simulation accuracy for Jilin Province was the highest among the three provinces with a rate of 82.45% since its simple cropping system and not complex topography;（3） simulation accuracy for maize was the best among the three staple crops with a ratio of 81.14% because the study area is very suitable for maize growth. We hope this study could provide the reference for cropping pattern forecasting and decision-making.
文摘Land use change and cropping patterns are important factors for controlling carbon sequestration in soils and they may also change the relative importance of different mechanisms of soil organic matter stabilization. The study was conducted to investigate the state of carbon sequestration in soil aggregates under different cropping patterns of Khulna, Jessore and Chapainawabganj districts in Bangladesh. Thirty-six soil samples were collected from (0 - 100 cm depth) above mentioned regions of three physiographic regions: Ganges Meander Floodplain, Ganges Tidal Floodplain and High Barind Tract. The texture of the samples varied within three soil texture groups, Silt Loam, Silty Clay Loam and Silty Clay. The highest NSI value (0.89) was found under Wheat-Fallow-T. Aman cropping pattern in Silty Clay soils (sample No 15) and lowest value (0.59) was found Vegetables/Mustard-Fallow-T. Aman cropping pattern in Silt Loam soils (sample No 17). The highest value (735.20 mg<span style="white-space:nowrap;"><span style="white-space:nowrap;">•</span></span>kg<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>1</sup>) of active C was observed under Chickpea/mustard-T. Aman (Sample No 31) and the lowest value (619.23 mg<span style="white-space:nowrap;"><span style="white-space:nowrap;">•</span></span>kg<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>1</sup>) was found in case of Wheat-Fallow-T. Aman cropping pattern (Sample No 30). The highest SOC stock (1.62 Kg C m<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>2</sup>) was found in Silty Clay Loam soil under Mungbean/Ash gourd-T. Aman cropping pattern (Sample no 4) and the lowest SOC stock (0.35 Kg C m<sup><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>2</sup>) was found in Silt Loam soil under Cauliflower/Pumkin/Spinach-T. Aman Cropping pattern (Sample No 2). Soil organic carbon associated with different size aggregates was the highest (3.14%) under Mungbean/Ash gourd-T. Aman (Sample No 20) and was the lowest (0.36%) under Cauliflower/Pumkin/Spinach-T. Aman cropping pattern (Sample No 2). Organic carbon content in aggregate size ranges > 2000 μm (SOC1), 2000 - 250 μm (SOC2), 250-53 μm (SOC3), and <53 μm (SOC4) varied from 0.36% - 1.90%, 0.52% - 2.10%, 0.50% - 2.60% and 0.50% - 1.62%, respectively. The percentages of SOC associated with <53 μm aggregates were higher than those of >2000 μm, 2000 - 250 μm and 250 - 53 μm, aggregates. Significant positive correlations were found between SOC stock and SOC1, SOC stock and SOC2, SOC stock and SOC3, SOC stock and SOC4.
基金Supported by Application Research Project of Bureau of Forest Industry in Heilongjiang Province(sgzjY2014027)
文摘At the same time of tending forests,it is necessary to explore the under-forest economic development mode,bring into play production function of economic plants,establish cultivation mode of edible fungus,wild vegetables and medicinal plants under forest,to obtain certain economic benefit in short period. This paper made a preliminary study on significance and existing problems of the under-forest economy,and came up with several interplanting patterns,in the hope of providing a comprehensive operation and cultivation approach for developing the under-forest economy.
文摘The experiments were conducted at the Pulses Research Centre, Ishurdi, Pabna, Bangladesh during the 2005-2006 and 2006-2007 crop seasons to determine the economic viability of planting legumes for both vegetable and forage purposes in the fallow period between monsoon-rice and spring-rice. The objectives were to ensure better land utilization, break up the mono cropping, improve soil health, and generate extra-income for small and resource-poor farmers of Bangladesh. Crop compositions used in the experiments were monsoon-rice （cv. BRRIdhan-32, BRRldhan-39 and BINAdhan-4） followed by pulses （grasspea, chickpea and field pea） followed by spring-rice （cv. BRRldhan-28, BRRldhan-29 and BINAdhan-6）. Based on the data from two years in a pooled analyses, it was observed that monsoon-rice variety BINAdhan-4, followed by field pea （as vegetable ＆ forage） and spring-rice variety BINAdhan-6 produced the highest yields of 5.0 t ha-1 rice grain, 3.25 t ha1 （green vegetable） ＋ 18.1 t hal （forage） legumes and 7.8 t ha~ rice grain, respectively. The cropping pattern of monsoon-rice （BINAdhan-4）-field pea （as vegetable ＋ forage）-spring-rice （BINAdhan-6） gave the highest net return of USD$1,705 hal year-~ compared to other patterns with different rice varieties and chickpea and grasspea. This is a new finding, and is being practiced by farmers of Bangladesh who have enhanced their farm income substantially. This has also generated job opportunities for rural women to pick the green vegetable of field pea.
基金Supported by Guangdong Provincial Special Fund for Modern Agriculture Industry Technology Innovation Teams (2019KJ111)。
文摘The efficient cultivation technique of "rice-rice-potato" triple cropping rotation pattern is summarized by analyzing its characteristics and cultivation techniques in Yangjiang region of Guangdong Province,China,and machine-transplanted cultivation technique of double cropping rice and cultivation techniques of winter potato black film mulching are emphatically introduced,in order to promote the development of potato industry in Yangjiang City.The results will provide a scientific basis for the popularization and application of the "rice-rice-potato" triple cropping rotation pattern.
文摘[Objective] To screen ratooning rice varieties for the ratooning rice-rape cropping planting pattern in Ganfu Plain. [Method] The growth period, plant morphology, yield and its component of 11 varieties at the first and rebirth season were compared and analyzed. [Result] The ratooning rice varieties such as Heliangyou -1, Y Liangyou 6, Zhunliangyou 608 and Jingliangyouhuazhan were suitable for the production and application in Ganfu Plain. Heliangyou 1 and Zhunliangyou 608 showed the characteristics of early maturity, easy to achieve high yield and stable production. [Conclusion] It suggests that Heliangyou 1 and Zhunliangyou 608 should be selected as preferred varieties for the planting pattern of ratooning rice-rape cropping.
文摘Several whole-farm agro-economic optimization models have been developed to deal with lumped planning issues in the agriculture sector. However, these models cannot be used to devise appropriate management strategies at land parcel level, because of the differences between farm characteristics, and the increased complexity of the hydrological processes. Based on Spatial Farm Database (SFD) which is consisted of a number of farm-level spatial data, including location, paddock properties, owner specifications and budgets, it is possible to provide the farm manager with some suggestions regarding the optimal choice of crops and the area to be allocated for each one. To this end, genetic algorithm is used in order to cope with model nonlinearity and a large number of decision variables. In order to test the proposed model, the Mobarakabad district is modeled with 126 agriculture fields, and the optimization model is run for this area. Results showed that the optimization procedure can find more realistic farm-level optimal solutions due to its advantage in adequate modeling of field characteristics, common groundwater resources, and the associated constraints. The results of lumped optimizations could also be used as benchmarks for the purposes of comparison and interpretation.
文摘Creation of a spectral signature reflectance data, which aids in the identification of the crops is important in determining size and location crop fields. Therefore, we developed a spectral signature reflectance for the vegetative stage of the green gram (Vigna. radiata L.) over 5 years (2020, 2018, 2017, 2015, and 2013) for agroecological zone IV and V in Kenya. The years chosen were those whose satellite resolution data was available for the vegetative stage of crop growth in the short rain season (October, November, December (OND)). We used Landsat 8 OLI satellite imagery in this study. Cropping pattern data for the study area were evaluated by calculating the Top of Atmosphere reflectance. Farms geo-referencing, along with field data collection, was undertaken to extract Top of Atmosphere reflectance for bands 2, 3, 4 and 7. We also carried a spectral similarity assessment on the various cropping patterns. The spectral reflectance ranged from 0.07696 - 0.09632, 0.07466 - 0.09467, 0.0704047 - 0.12188,0.19822 - 0.24387, 0.19269 - 0.26900, and 0.11354 - 0.20815 for bands 2, 3, 4, 5, 6, and 7 for green gram, respectively. The results showed a dissimilarity among the various cropping patterns. The lowest dissimilarity index was 0.027 for the maize (Zea mays L.) bean (Phaseolus vulgaris) versus the maize-pigeon pea (Cajanus cajan) crop, while the highest dissimilarity index was 0.443 for the maize bean versus the maize bean and cowpea cropping patterns. High crop dissimilarities experienced across the cropping pattern through these spectral reflectance values confirm that the green gram was potentially identifiable. The results can be used in crop type identification in agroecological lower midland zone IV and V for mung bean management. This study therefore suggests that use of reflectance data in remote sensing of agricultural ecosystems would aid in planning, management, and crop allocation to different ecozones.
文摘We studied a new grain-cash cropping pattern composed of "barley/watermelon + waize-rice", comparing with "barley / watermelon-rice" (CKI), "watermelon-rice", (CK2). The experiment was conducted in CNRRI’s field for 3 yr, employing completely randomized design with three replications, and each plot occupied 207 m~2. The soil in the experiment field contained: N, 2.48 g. kg, quick effective P 4 mg. kg, and quick effective K 53 mg·kg. The varieties tested were Zhemai 2 (barley), Zhemi 1 (watermelon), Suyu 1 (maize), and Shanyou 63 (hybrid rice).
基金supported by the National Key Research and Devel-opment Program of China(Grant No.2023YFD1500200)the funding project of Northeast Geological S&T Innovation Center of China Geologi-cal Survey(Grant No.QCJJ2022-9)+3 种基金the Strategic Priority Research Pro-gram of the Chinese Academy of Sciences(Grant No.XDA28060100)the Youth Interdisciplinary Team Project of the Chinese Academy of Sciences(JCTD-2021-04)the Informatization Plan of the Chinese Academy of Sciences(Grant No.CAS-WX2021PY-0109)the National Natural Science Foundation of China(Grants No.41971078,42271375,72221002,42001378).
文摘China’s endeavors to mitigate recurrent crop residue burning(CRB)and improve air quality have yielded positive results owing to recent pollution prevention policies.Nonetheless,persistent challenges remain,particularly in the Northeast China(NEC),where low temperature complicates crop residue management.Here,we examined the effects of cropping pattern adjustment on variations of CRB patterns in NEC during 2001-2021,utilizing the Moderate-resolution Imaging Spectroradiometer(MODIS)burned area dataset,the Visible Infrared Imaging Radiometer Suite(VIIRS)active fire dataset,and the high-accuracy crop planting area maps.Our results revealed an overall upward trend of 805.96 km^(2)/yr in NEC CRB from 2001 to 2021.The corn CRB area accounted for more than 50%of the total CRB area in each CRB-intensive year(2013-2021),and the increasing corn CRB generally aligns with the growing corn cultivation fields.A seasonal shift in CRB was found around 2017,with intensive CRB activities transitioning from both autumn and spring to primarily spring,particularly in the Songnen Plain and Sanjiang Plain.The changing trend of PM2.5 concentration aligned spatially with the shift.Moreover,the CRBs in spring of 2020 and 2021 were more severe than the major burning seasons in previous years,likely due to the disruptions during COVID-19 lockdowns.In certain years,the explanatory power of spring CRB on PM2.5 concentration was comparable to that of other natural factors,such as precipitation.This study underscores the critical need for sustained and region-specific strategies to tackle the challenges posed by CRBs.
