Modeling crop land soil moisture and impacts of supplimental irrigaiton in a rainfed region of Bangladesh

A robust water balance model has been tested for predicting soil moisture levels and supplemental irrigation requirement of a rainfed region of Bangladesh. The predictions were used for improving the understanding of the impacts of rainwater harvesting on rainfed agriculture. The climate data (i.e., rainfall, temperature, evaporation, and evapotranspiration) were used as inputs for predicting the variations in soil moisture. Soil moisture levels under rainfed and supplementary irrigation conditions were compared. Results showed that rainwater harvesting i.e., rain water storage tanks during rainy seasons can be potentially useful for storing rainwater, which can be utilized for enhancing crop land soil moisture during dry seasons for enhancing crop yield. The study presented here will be useful for improving and disseminating rainwater harvesting approaches for enhancing water availability in rainfed regions.

Evaluation of a deep-learning model for multispectral remote sensing of land use and crop classification

High-resolution deep-learning-based remote-sensing imagery analysis has been widely used in land-use and crop-classification mapping. However, the influence of composite feature bands, including complex feature indices arising from different sensors on the backbone, patch size, and predictions in transferable deep models require further testing. The experiments were conducted in six sites in Henan province from2019 to 2021. This study sought to enable the transfer of classification models across regions and years for Sentinel-2 A(10-m resolution) and Gaofen PMS(2-m resolution) imagery. With feature selection and up-sampling of small samples, the performance of UNet++ architecture on five backbones and four patch sizes was examined. Joint loss, mean Intersection over Union(m Io U), and epoch time were analyzed, and the optimal backbone and patch size for both sensors were Timm-Reg Net Y-320 and 256 × 256, respectively. The overall accuracy and Fscores of the Sentinel-2 A predictions ranged from 96.86% to 97.72%and 71.29% to 80.75%, respectively, compared to 75.34%–97.72% and 54.89%–73.25% for the Gaofen predictions. The accuracies of each site indicated that patch size exerted a greater influence on model performance than the backbone. The feature-selection-based predictions with UNet++ architecture and upsampling of minor classes demonstrated the capabilities of deep-learning generalization for classifying complex ground objects, offering improved performance compared to the UNet, Deeplab V3+, Random Forest, and Object-Oriented Classification models. In addition to the overall accuracy, confusion matrices,precision, recall, and F1 scores should be evaluated for minor land-cover types. This study contributes to large-scale, dynamic, and near-real-time land-use and crop mapping by integrating deep learning and multi-source remote-sensing imagery.

Inventory of Atmospheric Pollutant Emissions from Burning of Crop Residues in China Based on Satellite-retrieved Farmland Data

The burning of crop residues emits large quantities of atmospheric aerosols.Published studies have developed inventories of emissions from crop residue burning based on statistical data.In contrast,this study used satellite-retrieved land-cover data(1 km×1 km)as activity data to compile an inventory of atmospheric pollutants emitted from the burning of crop residues in China in 2015.The emissions of PM10,PM2.5,VOCs,NOx,SO2,CO,and NH3 from burning crop straw on nonirrigated farmland in China in 2015 were 610.5,598.4,584.4,230.6,35.4,3329.3,and 36.1 Gg(1 Gg=109 g),respectively;the corresponding emissions from burning paddy rice residues were 234.1,229.7,342.3,57.5,57.5,1122.1,and 21.5 Gg,respectively.The emissions from crop residue burning showed large spatial and temporal variations.The emissions of particulate matter and gaseous pollutants from crop residue burning in nonirrigated farmland were highest in east China,particularly in Shandong,Henan,Anhui,and Sichuan provinces.Emissions from burning paddy rice residue were highest in east and central China,with particularly high levels in Shandong,Jiangsu,Zhejiang,and Hunan provinces.The monthly variations in atmospheric pollutant emissions were similar among different regions,with the highest levels observed in October in north,northeast,northwest,east,and southwest China and in June and July in central and south China.The developed inventory of emissions from crop residue burning is expected to help improve air quality models by providing high-resolution spatial and temporal data.

Characterizing historical(1992–2010) transitions between grassland and cropland in mainland France through mining land-cover survey data

Grassland, as one of the largest ecosystems on the earth, supports various goods and services to humanity.Historically, humans have increased agricultural output primarily by cropland expansion and agricultural intensification.The cropland area was primarily gained at the expense of grassland and forests.Apart from grassland conversion, increasing consumption of calorie- and meat-intensive diets drives the intensification of livestock systems, which is shifting steadily from grazing to feeding with crops.To cope with the environmental degradation due to agriculture, various forms of ‘green payment＇ were implemented to promote the adoption of sustainable farming practices over the last two decades in the European Union.The aim of this study is to monitor the recent transitions（1992–2010） between grassland and cropland during two Common Agricultural Policy（CAP） reforms at the French mainland scale.We proposed an innovative approach to link grassland conversion to agricultural commodities and farming systems practices.We first assessed the grassland-to-cropland conversion and further investigated the crop sequence patterns that were observed to be dominant after the conversion through mining land-cover survey data Teruti and Teruti-Lucas.We found the trends of the transitions between grassland and cropland over the two time intervals： The loss of grassland（1992–2003） and restoration or re-expansion of grassland（2006–2010） in mainland France.Our finding on the crop sequence patterns after the grassland conversion reveals two notable evolutions of agricultural production systems.These evolutions were related to the increase in the proportion of cropland in the total agricultural land use.One evolution was most likely influenced by the demand for fodder： The conversion from grazing livestock to feeding livestock.Another evolution was the conversion from livestock production to field crop production.Our results indicate that the intensification of livestock farming systems continued over the last two decades in France.We conclude that, the approach developed in this study can be considered as a generic method for monitoring the transitions between grassland and cropland and further identifying the crop sequence patterns after the grassland conversion from time-series land cover data.

A study on the bioenergy crop production function of land use in China

Based on the analysis of the bioenergy crop production function of land use,combined with the status quo of Chinese land use,the cultivation of energy plants and the bioenergy crop production function of land use had been analyzes and discusses in this paper.Results show that there were a lot of unused lands and marginal lands which can be planted bioenergy crops to perform the bioenergy crop production function of land use with great potentials;and currently there were no food production problems.Therefore,it was very important for China to emphasize bioenergy crops planting in order to fully use land resources in our country,moderate the energy crisis and increase peasants' income.

Comparison and Prediction of the above Ground Carbon Storage in Croplands on the Inhabited Slopes on Mount Kilimanjaro (Tanzania) and the Taita Hills (Kenya)

Mount Kilimanjaro and the Taita Hills are adjacent montane areas that experience similar climate and agricultural activity, but which differ in their geologic history, nature of elevation gradients and cultures. We assessed differences in cropland above ground carbon (AGC) between the two sites and against environmental variables. One hectare sampling plots were randomly distributed along elevational gradients stratified by cropland type;AGC was derived from all trees with diameter ≥ 10 cm at breast height in each plot. Predictor variables were physical and edaphic variables and human population. A generalized linear model was used for predicting AGC with AIC used for ranking models. AGC was spatially upscaled in 2 km buffer and visually compared. Kilimanjaro has higher AGC in cropped and agroforestry areas than the Taita Hills, but only significant difference in AGC variation in agroforestry areas (F = 9.36, p = 0.03). AGC in cropped land and agroforestry in Kilimanjaro has significant difference on mean (t = 4.62, p = 0.001) and variation (F = 17.41, p = 0.007). In the Taita Hills, significant difference is observed only on the mean AGC (t = 4.86, p = 0.001). Common tree species that contribute the most to AGC in Kilimanjaro are Albizia gummifera and Persea americana, and in the Taita Hills Grevillea robusta and Mangifera indica. Significant and univariate predictors of AGC in Mount Kilimanjaro are pH (R2 = 0.80, p = 0.00) and EVI (R2 = 0.68, p = 0.00). On Mount Kilimanjaro, the top multivariate model contained SOC, CEC, pH and BLD (R2 = 0.90, p = 0.00), whereas in the Taita Hills, the top multivariate model contained elevation, slope and population (R2 = 0.89, p = 0.00). Despite of the difference in land management history of Mount Kilimanjaro and the Taita Hills, mean of AGC in croplands does not differ significantly. Difference occurs on variation of AGC, type of trees contributing AGC, and environmental variables that explain AGC distribution. The research results provide reference for management of carbon sequestration on inhabited montane areas.

Effects of Crop Growth and Development on Land Surface Fluxes

In this study, the Crop Estimation through Resource and Environment Synthesis model （CERES3.0） was coupled into the Biosphere-Atmosphere Transfer Scheme （BATS）, which is called BATS CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes. For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China： one by BATS CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.

The Effect of Land Degradation on Farm Size Dynamics and Crop-Livestock Farming System in Ethiopia: A Review

Ethiopia is among the poorest countries in which poverty, land and resource degradation appear to feed off each other. The irony is that Ethiopia is a country with high biodiversity and distinctive ecosystems and the natural resource base is critical to the economy and the livelihood of a high percentage of the population. Being the owner of varying agro ecology, the country’s agricultural production system had practiced for decades with a maximum potential. However, because of the presence of interrelated problems, the productivity had not sustained as its potential. From the interrelated problems, land degradation takes the first and challengeable problem in many countries. Land degradation refers to a temporary or permanent decline in the productive capacity of the land, or its potential for environmental management as a result;the long-term biological and environmental potential of the land has been compromised. Land degradation in the Ethiopian highlands (i.e. areas above 1500 m.a.s.l.) has been a concern for many years and is a great threat for the future that requires great effort and resources to ameliorate. It had adverse effect on lowering of livestock production by shrinking grazing land, the fertile soil types were washed and the grazing land was dominantly covered by unpalatable pastures and grasses which had low nutritive value and fertility for crop-livestock production system. In other cases, degradation induces farmers to convert land to lower-value uses;for instance, cropland converted to grazing land, or grazing lands converted to shrubs or forests. Equitable and secure access to land is a critical factor for the rural poor, especially livestock owners, who depend on agriculture and animal-related activities for their livelihood. Having secure access to land for agriculture and pastoral activities reduces their vulnerability and enhances their opportunities to invest in land for agriculture and livestock activities. Historical patterns of feudal ownership of land followed by government ownership and despite policy change uncertain status of land ownership. These land distribution and ownership patterns coupled with continuous fragmentations and degradation disrupt the balance between crop, livestock, and forest production. These things nowadays enforce Ethiopian farmers to put more land into crop production than working on livestock sector. Livelihoods are complex, dependent on animal and crop production based on land and water resources, with emerging market opportunities. And from year to year, the size of farms is getting minimized because of land degradation and segmentations, and these make a change in farm size dynamics and farming shift. Currently, there is a great scenario towards the land policy pattern and agricultural production system, which is the backbone of the country’s economy. Therefore, the aim of this paper is to review the effect of land degradation on farm size dynamics and crop-livestock production since the impact of these things is not well measured.

多样化种植对提升耕地质量的作用:进展与展望

多样化种植是现代生态农业的重要举措之一,对提高生物多样性、生态服务功能和土壤质量等具有重要意义。在全球粮食供给紧张和耕地短缺背景下,多样化种植在提升我国耕地质量和保障粮食安全中将会发挥越来越重要的作用。但现有研究对多样化种植的理解多集中在提高生物多样性和发挥生态功能等方面,对其提升耕地质量的作用关注较少,特别是多样化种植如何通过改善土壤物理、化学、生物多样性来提高耕地质量和维持土壤健康方面的理解还较为局限。本文在总结多样化种植的内涵及对促进耕地土壤健康和提高生态服务功能作用的基础上,系统梳理了多样化种植对改善土壤物理、化学、生物多样性等方面的作用研究进展,展望了未来以提升耕地质量为核心发展多样化种植亟需关注的方向和研究重点,以期为多样化种植在我国耕地质量提升策略中发挥更大作用提供参考。

我国沿海滩涂盐碱地改良与综合利用现状与展望

沿海滩涂盐碱地是我国重要的后备土地资源,其生态生产力价值是沿海“蓝碳”的重要组成部分。针对长期以来沿海地区盐碱地综合利用效率低下和经济、生态、社会效益不高等问题,本文通过梳理沿海滩涂开发的历史和现状,总结不同改良方式主导的滩涂盐碱地利用方式的转变,评估滩涂盐碱地的生态生产力价值,分析滩涂盐碱地利用亟需解决的问题,以期为新时期我国沿海滩涂盐碱地的改良与综合利用提供参考。

Land Resource Areas and Spatial Analysis of Potential Location of Bioenergy Crops Production in Mississippi

Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops which generate both agricultural and economic benefits. Agricultural commodities play a key role in economic growth, therefore the ability to produce more would enhance development. This paper offers an analysis of the production of bioenergy crops in Mississippi. Relative measures, time series graphs and descriptive statistics coupled with geographic information systems (GIS) mapping using ArcMap were employed to generate the outcome of this research. The outcome of the statistical analysis indicated that corn and soybeans were the most produced crops in Agricultural Districts 10 and 40. These districts produced more bioenergy crops than the other districts. GIS mapping results also showed that the potential area for bioenergy crops is in zone 131 of the Mississippi Land Resource Area (MLRA). This zone has an absolute advantage in the production of these crops which includes the diversity of biomass production such as corn, cotton, soybeans, wheat, rice, barley, grain sorghum, canola, camelina, algae, hardwoods, and softwood. The paper recommends a constant GIS mapping and land management systems for each agricultural district in Mississippi to enable researchers and farmers to determine the factors which contribute towards the increasing and decreasing trends in the production of the bioenergy crops.

新时期我国麻类产业科技创新的重点任务

麻类作物是重要的特色经济作物,为高端纺织、食品医药、生物材料等领域提供重要工业原料,持续加强麻类产业科技创新对我国农业农村现代化建设具有重要意义。针对新时期麻类产业发展承担的新职能,文章梳理了近年来我国麻类产业技术研发重要进展,分析了麻类产业发展面临的新挑战,并结合新兴技术研发态势,提出了我国麻类产业科技创新的重点任务。研究建议:新时期我国麻类产业科技创新应进一步夯实种质资源研究,推进现代生物育种技术应用;加快抗逆丰产技术创新,在盐旱渍涝污染等边际土地中拓展种植空间;研发全产业链绿色低碳技术,促进麻类生产高产高质高效;创新加强麻类新材料创制,带动麻类产业创新发展,赋能粮食安全与重要农产品有效供给。

流动的非粮种植与二元土地流转市场——一项土地流转中农业经营模式的双案例分析

造成土地流转市场分化现象的因素不仅包括土地禀赋、流转主体和外在环境,农业经营模式本身也会产生影响。根据不同作物的种植特性,以作物-土地关联机制为切入点,对山东某地区的非粮种植及其参照案例进行比较。研究发现,非粮种植和粮食种植之间不同的作物-土地关联机制影响经营流动性,非粮作物需要流动经营,粮食作物采取固定经营。不同的作物类型和经营模式对土地流转市场产生影响,导致流转对象、合约形式和流转价格发生分化,呈现出二元土地流转市场形态。特别是非粮作物与粮食作物在土壤损害、种植风险、关系强度和交易成本等方面的差异,导致非粮种植的土地流转价格远高于粮食种植。

Land and Water Use in Rice-upland Crop Rotation Areas in Lower Ili River Basin, Kazakhstan

The lower Ili River Basin is located in semi-arid area, and the annual rainfall is 177mm. Therefore, the irrigation is inevitable for agriculture. Large-scale irrigated agriculture had been developed since 1960＇s in the lower parts of the river and the total irrigated area is about 32 000 hm2. In the project area, the paddy rice-upland crop rotation has been practiced. Due to the domestic water use for hydropower and agriculture as well as water use among riparian countries, the deficit of water for agriculture in the lower part has been concerned. The authors, therefore, conducted the field survey and water balance analysis of the Akdara irrigation project in the lower Ill River Basin in order to assess the land and water uses. Moreover, the impact of the water use on water environment to the basin was analyzed. The following results were obtained as following （1） the groundwater level in the irrigated district varied from 1.5 m to 3.5 m through year. （2） 1970＇s groundwater level was drastically raised from 8 m to 3 m and the groundwater had been recharged in this period. （3） Water use efficiency of agriculture, which is the ratio of total evapotranspiration to the total water withdrawal was as low as 0.23.

甜菜生产大幅波动的原因探究——基于199份农户调查问卷

2022/2023年榨季我国甜菜糖产量108万t,约占食糖产量的12%,比上年增长25%。甜菜作为我国重要的糖料作物,近几年种植面积和产量的大幅波动非常引人瞩目。为此,基于199份甜菜农户的调查问卷,探究甜菜种植面积和产量的影响因素就尤为重要,主要得出以下结论:(1)2022年受甜菜价格上涨提振,甜菜种植面积增加明显。其中,内蒙古受到轮作土地和成本限制,种植积极性不如新疆地区。2023年因缺乏轮作土地和成本上涨,甜菜扩种热情削减。从区域异质性来看,内蒙古受政策和轮作土地影响较大,新疆受成本和作物竞争影响较大。(2)甜菜收购价格是影响种植面积的最主要因素,其次是甜菜单产,甜菜成本变动对种植面积也产生较大影响。(3)影响甜菜成本的主要因素是地租和生产资料,生产资料成本主要受化肥和农药价格变动的影响。(4)竞争作物和粮食补贴对甜菜种植面积也带来明显影响。(5)甜菜单产主要受甜菜品种、化肥施用、轮作倒茬的影响。(6)从现存的问题来看,生产成本上涨过快最受关注,作物竞争和气候异常的影响也比较严峻。此外,甜菜户均生产规模明显提升,2022年户均甜菜规模41.67 hm2,较2018—2020年提升128.08%;机械化程度总体较高,仅育苗移栽机械化程度略低。规模经营提升和机械化程度较高使得甜菜农户种植行为更为理性,对甜菜比较收益的反应更为敏感。

旱区连作砂田土壤质量和土地生产力演变与调控研究进展

砾石覆盖在改变旱区水文循环和物质转化方面有着至关重要的作用。然而,长期连作给砂田土壤质量及土地生产力带来危机和不确定性。以连作砂田为研究对象,归纳总结了连作年限对砂层质地结构、土壤物理结构、土壤水盐热效应、土壤养分状况、土壤酶活性、土壤微生物特性、作物生长发育以及产量品质的影响效应和可能机制,发现砂田土壤生态环境和土地生产力在人类活动及自然侵蚀的扰动和破坏下整体呈现退化态势,但对不同覆盖条件、施肥水平和种植结构等农田管理措施的响应过程表现出差异性。继而,基于土壤质量和土地生产力的协同和互作效应深入揭示了砂田性能逐年退化机理,并简述了生物、农业及工程调控措施在砂田退化阻控和修复方面的应用进展。在此基础上,提出了砂田退化进程中急需解决的关键科学问题和未来发展方向,主要包括土壤质量演变的基本过程及其发生机制、“砾石-土壤-微生物-植物”系统的叠加和互作效应及其分子机理、土壤改良与生物防治措施的定量化及其调控机制三个方面。在气候变化、植被演替和土地退化背景下,废弃风化砾石的劣化增肥机制及其环境效应将是今后研究的重点。

不同连作年限设施农用地土壤有机碳与细菌群落功能特征

为探明不同连作年限设施农用地土壤有机碳(Soil organic carbon,SOC)与细菌群落功能变化及其动态响应关系,以北京市南郊设施农业集中地为研究区,采用时空替代法系统分析了未种植(CK)、连作年限0~5年(0~5 a)、5~10年(5~10 a)、10~20年(10~20 a)和20年以上(20 a+)SOC、细菌群落结构及其代谢功能的变化。结合冗余分析(RDA)、典型相关分析(CCA)、PICRUSt2功能预测及Mantel test探究了SOC及其活性组分与细菌优势菌群的动态响应,以及与细菌代谢功能的相互关系。结果表明:连作使研究区微生物生物量碳(Microbial biomass carbon,MBC)、易氧化有机碳(Easily oxidizes organic carbon,EOC)、SOC含量及土壤有机碳密度(Soil organic carbon density,SOCD)均随种植年限先增后减,可溶性有机碳(Dissolved organic carbon,DOC)含量在20 a+时最高,微生物熵(Q)随连作年限增加而减小。连作降低了土壤细菌的多样性,但提高了细菌种群间差异,PICRUSt2预测不同连作年限土壤细菌功能均以新陈代谢为主,5~20 a土壤细菌二级代谢功能丰度明显高于0~5 a、20 a+、CK。相对丰度前10的细菌群中Acidobacteriota与SOC及其活性组分含量均呈负相关,主导和参与SOC累积循环的关键菌群在连作20 a+后出现由富营养型菌群向寡营养和致病类菌群转变的趋势;Mantel分析显示,第3层级有53类与土壤有机碳含量呈显著相关的代谢功能(p<0.05),其中23类隶属于第1层级的新陈代谢,与EOC呈显著相关的代谢功能高达51类。本研究结果可为优化碳循环相关细菌功能群,提升小尺度设施农用地土壤碳汇功能提供参考。

中国耕地种植制度遥感探测及其时空特征

[目的]耕地种植制度是农业生产方式的具体体现,其形成受自然资源要素与人类土地利用行为综合影响,反映了“人类-自然”的耦合关系。本研究旨在科学掌握全国耕地种植制度格局,为优化农业生产布局、提高农业生产能力、推动农业可持续性发展提供依据。[方法]结合遥感监测与空间决策树模型等手段,构建适合我国农情的跨年度种植制度探测方法体系,并开展空间格局分析。首先,通过辨析种植强度、复种指数等概念,从长期性、周期性、稳定性等方面,定义种植制度的内涵;其次,构建连续度、频度指标,并利用基于时序遥感的2001—2018年中国复种指数监测结果,结合时间滑动窗口方法,在像元尺度分别计算两个指标的具体值;最后,评估耕地的种植强度与种植制度特征的显著性,利用决策树方法确定种植制度类型,从区域差异、动态规律等方面分析不同区域种植制度的时空异质特征。[结果](1)面积上看,一年一熟所占面积最大,占53.52%,超过耕地总面积的一半;其次是一年两熟,占23.28%,季节性休耕(如两年三熟)与年度休耕分别占12.80%和6.94%。(2)空间上看,一年一熟、一年两熟、季节性休耕与年度休耕的集中分布区分别为东北地区、华北地区、长江以南地区与“镰刀弯”地区。(3)时间上看,动态稳定的种植制度从时间维度上揭示了静态复种指数背后的异质性,例如,2018年复种指数为1的区域,其中75.18%属于一年一熟、6.60%属于一年两熟、8.92%属于季节性休耕、8.02%属于年度休耕。[结论]本研究提出了一种结合时序遥感监测与空间决策树模型的跨年度分类体系,揭示了中国耕地种植制度分区聚集、种植强度南高北低的空间格局,直观展现了松嫩平原、“镰刀弯”等空间聚集区;分析了耕地复种与种植制度的时空差异特征,主要表现在种植制度与年度复种指数的空间不一致性,以及种植制度特有的周期性。研究结果可为合理提高耕地复种强度、推动实施“藏粮于地”战略提供案例支撑。

改性生物炭作用滨海盐碱地的土壤微生物机理

为提高生物炭在盐碱地的适用性,研究改性生物炭对盐碱地的作用效果及微生态机理。通过2 a的大田试验,设置普通生物炭、富氮改性生物炭、富磷改性生物炭3种处理,3种生物炭用量分别为4.5,7.5,15.0 t/hm^(2),研究作物产量性状、土壤理化性质、土壤微生物多样性的响应情况。结果发现,添加生物炭可以改良土壤盐碱地,其中富氮改性生物炭和富磷改性生物炭效果更突出。生物炭可以提高盐碱地作物产量,降低土壤含盐量,改善土壤结构,降低土壤容重。3种生物炭影响并不一致,其中15.0 t/hm^(2)磷改性生物炭对作物增产效果最好,其产量为(8.92±0.12)t/hm^(2),比对照组提高了110%。生物炭影响土壤微生物多样性,普通生物炭增加了土壤微生物多样性,但磷改性生物炭降低土壤微生物多样性。随着生物炭施用量的增加,土壤理化性质对土壤微生物和植物结构关系受到影响,三者之间的联系被削弱。综上,推荐施用15 t/hm^(2)磷改性生物炭用于改善盐碱农田生态系统。

Crop Classification Using MODIS NDVI Data Denoised by Wavelet: A Case Study in Hebei Plain, China

Time-series Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data have been widely used for large area crop mapping.However,the temporal crop signatures generated from these data were always accompanied by noise.In this study,a denoising method combined with Time series Inverse Distance Weighted (T-IDW) interpolating and Discrete Wavelet Transform (DWT) was presented.The detail crop planting patterns in Hebei Plain,China were classified using denoised time-series MODIS NDVI data at 250 m resolution.The denoising approach improved original MODIS NDVI product significantly in several periods,which may affect the accuracy of classification.The MODIS NDVI-derived crop map of the Hebei Plain achieved satisfactory classification accuracies through validation with field observation,statistical data and high resolution image.The field investigation accuracy was 85% at pixel level.At county-level,for winter wheat,there is relatively more significant correlation between the estimated area derived from satellite data with noise reduction and the statistical area (R2 = 0.814,p < 0.01).Moreover,the MODIS-derived crop patterns were highly consistent with the map generated by high resolution Landsat image in the same period.The overall accuracy achieved 91.01%.The results indicate that the method combining T-IDW and DWT can provide a gain in time-series MODIS NDVI data noise reduction and crop classification.