Effects of Soil Improver on Wheat in Saline-Alkali Lands in the Yellow River Delta

Field experiment carried out to test the effects of soil improver on wheat yield and soil physical-chemical properties. The results indicated that soil improver could optimize soil aggregates structure, decrease soil bulk density, soil pH and soil salt content, increase soil organic matter and 1 000-grain weight, thereby enhancing wheat yield. With the increase of soil improver application amount, soil physical-chemical properties became better and wheat yield increased. However, there was no significant difference in the treatments with the application amounts of 3%, 4% and 5%. In addition, the treatment of reducing nitrogen showed no superiority in soil physical-chemical properties and wheat yield, indicating that sufficient nitrogen was essential for the growth of wheat.

Bohai Granary:Harnessing the Saline-Alkali Lands

Agriculture forms the backbone of a nation,and food security is essential for social stability and sustainable economic growth.In China,ensuring adequate food production is not only critical for national well-being but also a strategic priority for maintaining self-sufficiency.To enhance food security,two key approaches are increasing yields from the existing agricultural lands and improving the productivity of low-and medium-yield farmland.One of China’s major underutilized resources is its extensive saline-alkali lands,which,despite historically low productivity due to poor soil conditions and scarce freshwater resources,hold immense potential for boosting grain output.Recognizing this,the Chinese Academy of Sciences,in collaboration with the Chinese Ministry of Science and Technology(MOST),initiated the“Bohai Granary Scientific and Technological Demonstration Project”(Bohai Granary Project for short)in partnership with three provinces and one municipality-Hebei,Shandong,Liaoning,and Tianjin.This project represents a landmark effort to rehabilitate saline-alkali lands and transform them into highly productive grain-producing regions,thereby contributing significantly to China’s food security strategy.In this article,the author revisits the key milestones,technological breakthroughs,and outlook on the future potential of this project.

Study on the Landscaping Technologies for Coastal Saline-Alkali Land in Tanghai County of Tangshan City

Tanghai County is one of the counties in Tangshan City with the highest saline-alkali degree, with 80% of its land being covered by saline-alkali soils. Through studying landscaping technologies for coastal saline-alkali land in Tanghai County, 3 dominant modes for landscaping engineering in such land were summarized as shallow underground pipe desalination technology, banding soil replacement technology and hole membrane soil replacement technology, which are different in application scope and also in cost (respectively 260, 210 and 170 yuan). 3 landscaping measures were also proposed, including promotion of suitable plant cultivation technologies, application of saline-alkali tolerant plants and biological improvement of soils. To explore economic and practical planting patterns for saline-alkali land, low-cost landscaping tests were conducted from the perspectives of improving landscaping engineering mode and optimizing landscaping measures, and the results showed that it was practical to apply low-cost landscaping patterns, and comprehensive ecological measures should be adopted to realize the sustained utilization of soil.

基于Landsat影像的城市土地利用动态监测

土地是自然界不可或缺的资源,土地利用反映了人地关系。随着人口数量的持续增加和社会工业化、城市化的持续推进,如何科学地开发利用宝贵的土地资源越来越受到人们的重视。本文通过2013年和2023年的Landsat影像数据,结合遥感与GIS,对10年间合肥市土地资源进行监测与分析,结果表明,经过10年的城市发展,合肥市耕地面积减少了65707.92 hm 2,建设用地增长了39181.05 hm 2,林地减少了1728.27 hm 2,水域增加了28255.14 hm 2。

Effects of Microbial Fertilizers on Soil Improvement and Wheat Growth Characteristics in Saline-alkali Land

[Objectives]This study was conducted to further enrich the research on saline-alkali land improvement,and explore the effects of biological bacterial fertilizers containing Bacillus subtilis and Bacillus velezensis HM-3 in saline-alkali land improvement and crop growth promotion.[Methods]Wheat was planted in saline-alkali land in Huanghua City,Hebei Province,and a mixed application experiment was carried out using biological agents from Hemiao Biotechnology Co.,Ltd.[Results]Compared with the field of control check(CK),water-soluble salts and pH value in the experimental fields decreased,and living bacteria count in the soil increased.Meanwhile,the economic characters of wheat in the experimental fields showed excellent performance,with yields increasing by 39.09%and 27.49%compared with the CK.It could be seen that the application of biological bacterial fertilizers achieved obvious effects of improving saline-alkali soil and increasing wheat yield.[Conclusions]In this study,the effects of biological bacterial fertilizers on saline-alkali land and wheat growth characters were clarified,providing some technical support and theoretical guidance for wheat planting in Huanghua saline-alkali land.

Spatiotemporal landscape pattern changes and their effects on land surface temperature in greenbelt with semi-arid climate:A case study of the Erbil City,Iraq

Urban expansion of cities has caused changes in land use and land cover(LULC)in addition to transformations in the spatial characteristics of landscape structure.These alterations have generated heat islands and rise of land surface temperature(LST),which consequently have caused a variety of environmental issues and threated the sustainable development of urban areas.Greenbelts are employed as an urban planning containment policy to regulate urban expansion,safeguard natural open spaces,and serve adaptation and mitigation functions.And they are regarded as a powerful measure for enhancing urban environmental sustainability.Despite the fact that,the relation between landscape structure change and variation of LST has been examined thoroughly in many studies,but there is a limitation concerning this relation in semi-arid climate and in greenbelts as well,with the lacking of comprehensive research combing both aspects.Accordingly,this study investigated the spatiotemporal changes of landscape pattern of LULC and their relationship with variation of LST within an inner greenbelt in the semi-arid Erbil City of northern Iraq.The study utilized remote sensing data to retrieve LST,classified LULC,and calculated landscape metrics for analyzing spatial changes during the study period.The results indicated that both composition and configuration of LULC had an impact on the variation of LST in the study area.The Pearson's correlation showed the significant effect of Vegetation 1 type(VH),cultivated land(CU),and bare soil(BS)on LST,as increase of LST was related to the decrease of VH and the increases of CU and BS,while,neither Vegetation 2 type(VL)nor built-up(BU)had any effects.Additionally,the spatial distribution of LULC also exhibited significant effects on LST,as LST was strongly correlated with landscape indices for VH,CU,and BS.However,for BU,only aggregation index metric affected LST,while none of VL metrics had a relation.The study provides insights for landscape planners and policymakers to not only develop more green spaces in greenbelt but also optimize the spatial landscape patterns to reduce the influence of LST on the urban environment,and further promote sustainable development and enhance well-being in the cities with semi-arid climate.

Soil Carbon, Nitrogen and Phosphorus Concentrations and Stoichiometries Across a Chronosequence of Restored Inland Soda Saline-Alkali Wetlands, Western Songnen Plain, Northeast China

Soil carbon(C), nitrogen(N) and phosphorus(P) concentrations and stoichiometries can be used to evaluate the success indicators to the effects of wetland restoration and reflect ecosystem function. Restoration of inland soda saline-alkali wetlands is widespread, however, the soil nutrition changes that follow restoration are unclear. We quantified the recovery trajectories of soil physicochemical properties, including soil organic carbon(SOC), total nitrogen(TN), and total phosphorus(TP) pools, for a chronosequence of three restored wetlands(7 yr, 12 yr and 21 yr) and compared these properties to those of degraded and natural wetlands in the western Songnen Plain, Northeast China. Wetland degradation lead to the loss of soil nutrients. Relative to natural wetlands, the mean reductions of in SOC, TN, and TP concentrations were 89.6%, 65.5% and 52.5%, respectively. Nutrients recovered as years passed after restoration. The SOC, TN, and TP concentrations increased by 2.36 times, 1.15 times, and 0.83 times, respectively in degraded wetlands that had been restored for 21 yr, but remained 29.2%, 17.3%, and 12.8% lower, respectively, than those in natural wetlands. The soil C∶N(RC N), C∶P(R CP), and N∶P(R NP) ratios increased from 5.92 to 8.81, 45.36 to 79.19, and 7.67 to 8.71, respectively in the wetland that had been restored for 12 yr. These results were similar to those from the natural wetland and the wetland that had been restored for 21 yr(P > 0.05). Soil nutrients changes occurred mainly in the upper layers(≤ 30 cm), and no significant differences were found in deeper soils(> 30 cm). Based on this, we inferred that it would take at least 34 yr for SOC, TN, and TP concentrations and 12 yr for RC N, R CP, and RN P in the top soils of degraded wetlands to recover to levels of natural wetlands. Soil salinity negatively influenced SOC(r =-0.704, P < 0.01), TN(r =-0.722, P < 0.01), and TP(r =-0.882, P < 0.01) concentrations during wetland restoration, which indicates that reducing salinity is beneficial to SOC, TN, and TP recovery. Moreover, plants were an important source of soil nutrients and vegetation restoration was conducive to soil nutrient accumulation. In brief, wetland restoration increased the accumulation of soil biogenic elements, which indicated that positive ecosystem functions changes had occurred.

Assessing Spatio-Temporal Land Cover Changes in Dhund River Basin, Eastern Rajasthan (India), Using Multi-Temporal Landsat Data

Land cover is an impression of natural cover on surface of earth such as bare soil, river, grass etc. and utilization of these natural covers for various human needs and purposes by mankind is defined as land use. Land cover identification, delineation and mapping is important for planning activities, resource management and global monitoring studies while baseline mapping and subsequent monitoring is done by application of land use to get timely information about quantity of land that has been used. The present study has been carried out in Dhund river watershed of Jaipur, Rajasthan which covers an area of about 1828 sq∙km. The minimum and maximum elevation of the area is found to be 214 m and 603 m respectively. Land use and land cover changes of three decades from 1991 to 2021 have been interpreted by using remotes sensing and GIS techniques. ArcGIS software (Arc map 10.2), SOI topographic map, Cartosat-1 DEM and satellite data of Landsat 5 and Landsat 8 have been used for interpretation of eleven classes. The study shows an increase in cultivated land, settlement, waterbody, open forest, plantation and mining due to urbanization because of increasing demands of food, shelter and water while a decrease in dense forest, river, open scrub, wasteland and uncultivated land has also been marked due to destruction of aforementioned by anthropogenic activities such as industrialization resulting in environmental degradation that leads to air, soil and water pollution.

Landsat和GF数据面向对象土地覆盖分类研究

针对中分辨率遥感数据面向对象分类,以河北省北部山区和南部平原Landsat8 OLI,Landsat5 TM及高分一号(GF1)数据为研究对象,对支持向量机(support vector machine,SVM)、随机森林(random forest,RF)、决策树(decision tree,DT)及朴素贝叶斯(naive Bayes,NB)4种分类器的土地覆盖分类效果进行对比,并分析SVM,RF和DT中关键参数对分类结果的影响。结果表明:在2个研究区,各分类器结果略有差异,从整体上看其优劣排序为SVM,NB,RF和DT。其中SVM和DT分类精度随参数变化波动较大:对于SVM,当参数C取值不小于103且gamma不大于10^(-1)时,无论哪种情况其分类精度均优于90%;对于DT,当参数树深(Depth)大于3时,各情况下的分类精度相对较高且趋于稳定。RF分类精度随参数变化波动较小且没有明显的变化规律。研究结果可为中分辨率遥感数据面向对象土地覆盖分类研究提供参考。

To Uplift the Profitability of Marginal Lands by Cassava Cultivation

Expanding the utilization of marginal land resources in rural areas is regarded as a significant supplement for the sustainable development of modern agriculture for its yield, economic and ecological good. Marginal areas, due to their natural limitations, are only productive for energy crops with strong resistance and tolerance. Cassava, in its longstanding cultivation practices, has marked its adaptability in tropical and subtropical regions. Farmers are allowed to improve reclaimed soils’ fertility, while plants’ canopy coverage could reduce soil erosion. Besides, cassava tubers to be produced as food or fodder can be counted as soil productivity. Breeding advanced cassava varieties on marginal land under proper intensification management and facilitating policies can indeed increase farmers’ income. Some of the projects implemented outside of China speak quite well on that. Additionally, intercropping modes for cassava bring higher incomes than monocropping mode, which simultaneously improves the ecosystem structure and soil conditions. The interspecific cooperation brought by the intercropping pattern has its buffering function and antagonistic effects to counter against plant diseases, pest attacks and weed infestations. It performs as a natural alternative for pesticides and fertilizers with minimal inputs and safe and productive outputs. Although a complete cassava industrial chain has been formed nationwide, there are still challenges like the inadequate use of marginal areas and risks triggered by unfavorable climate, changeable commodity markets, and the composition of the labor force. However, there will still be ample room for further growth of cassava, for recent years have witnessed the acceleration in the circulation of rural land management rights and the stratification of Chinese farmers, which gives an impetus to household management’s dominance as well as the improvements of rural social welfare systems for the overall agricultural efficiency.

Landscape ecological risk assessment and its driving factors in the Weihe River basin,China

Weihe River basin is of great significance to analyze the changes of land use pattern and landscape ecological risk and to improve the ecological basis of regional development.Based on land use data of the Weihe River basin in 2000,2010,and 2020,with the support of Aeronautical Reconnaissance Coverage Geographic Information System(ArcGIS),GeoDa,and other technologies,this study analyzed the spatial-temporal characteristics and driving factors of land use pattern and landscape ecological risk.Results showed that land use structure of the Weihe River basin has changed significantly,with the decrease of cropland and the increase of forest land and construction land.In the past 20 a,cropland has decreased by 7347.70 km2,and cropland was mainly converted into forest land,grassland,and construction land.The fragmentation and dispersion of ecological landscape pattern in the Weihe River basin were improved,and land use pattern became more concentrated.Meanwhile,landscape ecological risk of the Weihe River basin has been improved.Severe landscape ecological risk area decreased by 19,177.87 km2,high landscape ecological risk area decreased by 3904.35 km2,and moderate and low landscape ecological risk areas continued to increase.It is worth noting that landscape ecological risks in the upper reaches of the Weihe River basin are still relatively serious,especially in the contiguous areas of high ecological risk,such as Tianshui,Pingliang,Dingxi areas and some areas of Ningxia Hui Autonomous Region.Landscape ecological risk showed obvious spatial dependence,and high ecological risk area was concentrated.Among the driving factors,population density,precipitation,normalized difference vegetation index(NDVI),and their interactions are the most important factors affecting the landscape ecological risk of the Weihe River basin.The findings significantly contribute to our understanding of the ecological dynamics in the Weihe River basin,providing crucial insights for sustainable management in the region.

Characteristics and drivers of the soil multifunctionality under different land use and land cover types in the drylands of China

The drylands of China cover approximately 6.6×106 km2 and are home to approximately 5.8×10^(8)people,providing important ecosystem services for human survival and development.However,dryland ecosystems are extremely fragile and sensitive to external environmental changes.Land use and land cover(LULC)changes significantly impact soil structure and function,thus affecting the soil multifunctionality(SMF).However,the effect of LULC changes on the SMF in the drylands of China has rarely been reported.In this study,we investigated the characteristics of the SMF changes based on soil data in the 1980s from the National Tibetan Plateau Data Center.We explored the drivers of the SMF changes under different LULC types(including forest,grassland,shrubland,and desert)and used structural equation modeling to explore the main driver of the SMF changes.The results showed that the SMF under the four LULC types decreased in the following descending order:forest,grassland,shrubland,and desert.The main driver of the SMF changes under different LULC types was mean annual temperature(MAT).In addition to MAT,pH in forest,soil moisture(SM)and soil biodiversity index in grassland,SM in shrubland,and aridity index in desert are crucial factors for the SMF changes.Therefore,the SMF in the drylands of China is regulated mainly by MAT and pH,and comprehensive assessments of the SMF in drylands need to be performed regarding LULC changes.The results are beneficial for evaluating the SMF among different LULC types and predicting the SMF under global climate change.

Rainfall Dynamics and Landslides in Urban Areas of Gabon: The Case of Libreville-Est (Gabon)

Due to its abundant rainfall, the city of Libreville, which concentrates more than half of Gabon’s population, is frequently confronted with the impacts of natural disasters such as floods and landslides. This study attempts to identify the complex relationships between the dynamics of land use and the role of rainfall in the occurrence of landslides. On the one hand, it uses statistics on landslides compiled from information taken from general news bulletins and, on the other, daily rainfall data obtained from the National Meteorological Department. The study revealed that the Libreville East sector, dominated by Mount Nkol Ogoum, one of Libreville’s most prominent landforms, is affected by a land-use dynamic in which human settlement has been progressing for some thirty years, to the detriment of the original vegetation which, among other things, helped to stabilise the soil on the hillsides and the marshy areas at the foot of the slopes. The result is not only an uncontrolled occupation of the land, but also a major landslide every two years in this part of the city, causing significant loss of life and property. However, an analysis of the time series shows little rainfall variability, marked in particular by a predominance of negative anomalies, and the occurrence of a few exceptional daily rainfall peaks. Similarly, the period from 20 October to 20 November, which receives the most rainfall, also appears to be the most conducive to landslides.

基于Landsat8遥感影像的巢湖及周围地区土地利用变化研究

随着我国经济快速发展,人地矛盾日益突出,巢湖及周围地区作为安徽省中部的重要生态区和重要经济区,土地利用类型的变化影响着该区域的社会、政治、经济和生活。通过地理空间数据云官网获取Landsat8遥感影像数据,运用遥感技术(RS)和地理信息技术(GIS),针对研究区2017年、2019年和2021年三个时期的土地利用变化进行研究,分别从土地利用的变化幅度、土地利用的数量关系、土地利用动态度、土地利用程度分析研究区的土地利用类型的变化过程,分析该变化的驱动因子并提出对策,为今后该地区的经济建设和区域规划提供参考。

Extensive identification of landslide boundaries using remote sensing images and deep learning method

The frequent occurrence of extreme weather events has rendered numerous landslides to a global natural disaster issue.It is crucial to rapidly and accurately determine the boundaries of landslides for geohazards evaluation and emergency response.Therefore,the Skip Connection DeepLab neural network(SCDnn),a deep learning model based on 770 optical remote sensing images of landslide,is proposed to improve the accuracy of landslide boundary detection.The SCDnn model is optimized for the over-segmentation issue which occurs in conventional deep learning models when there is a significant degree of similarity between topographical geomorphic features.SCDnn exhibits notable improvements in landslide feature extraction and semantic segmentation by combining an enhanced Atrous Spatial Pyramid Convolutional Block(ASPC)with a coding structure that reduces model complexity.The experimental results demonstrate that SCDnn can identify landslide boundaries in 119 images with MIoU values between 0.8and 0.9;while 52 images with MIoU values exceeding 0.9,which exceeds the identification accuracy of existing techniques.This work can offer a novel technique for the automatic extensive identification of landslide boundaries in remote sensing images in addition to establishing the groundwork for future inve stigations and applications in related domains.

Decoding vegetation's role in landslide susceptibility mapping:An integrated review of techniques and future directions

Rainfall-induced landslides,exacerbated by climate change,require urgent attention to identify vulnerable regions and propose effective risk mitigation measures.Extensive research underscores the significant impact of vegetation on soil properties and slope stability,emphasizing the necessity to incorporate vegetation effects into regional landslide susceptibility mapping.This review thoroughly examines research integrating vegetation into landslide susceptibility mapping,encompassing qualitative,semi-quantitative,and quantitative forecasting methods.It highlights the importance of incorporating vegetation aspects into these methods for comprehensive and accurate landslide susceptibility assessment.This review explores the diverse roles of vegetation in slope stability,covering both aggregated impacts and individual influences,including mechanical and hydrological effects on soil properties,as well as the implications of evapotranspiration and rainwater interception on slope stability.While aggregated roles are integrated into non-deterministic methods as input layers,individual roles are considered in deterministic methods.In the application of deterministic methods,it is noteworthy that a considerable number of studies primarily concentrate on the mechanical impact,particularly the reinforcement provided by root cohesion.The review also explores limitations and highlights future research prospects.In the context of mapping landslide susceptibility amid changing climatic conditions,data-driven techniques encounter challenges,while deterministic methods present their advantages.Stressing the significance of hydrological impacts,the paper recommends incorporating vegetation influences on unsaturated soil properties,including the soil water characteristic curve and soil permeability,along with pre-wetting suction due to evapotranspiration and potential rainwater interception.

基于Landsat数据的衡阳市主城区热岛效应研究

由于城市化快速发展,致使城市热岛成为重要的城市生态环境问题之一。以衡阳市主城区为研究区,利用辐射传输方程法、均值-标准差、标准差椭圆分析和相关分析等方法,分析了2000年-2021年的地表温度和热岛效应的时空变化,并研究了NDVI指数与地表温度的相关性。结果表明:地表温度在2000年-2021年间高温集中分布在中心城区的湘江两岸,但随着时间的推移,逐渐向四周扩散;热岛分布存在三个时间段的规律性,以2004年、2009年为时间分割点;热岛的标准差椭圆的面积在扩大,且重心向西南方向移动;NDVI指数与地表温度呈现出明显的负相关关系。

基于Landsat8的凤永高速地表温度反演

在隧道建设过程中,高地温热害会影响机械设备效率和施工进度,还会恶化作业环境、对人员安全造成威胁,因此,精准识别地热异常区对隧道建设非常重要。热红外遥感是用遥感的方法探测地球表面的温度,以此为基础利用遥感技术反演地表温度愈发可靠。以云南省凤永高速凤庆-领岗地隧道为研究区域,采用Landsat8影像数据,运用大气校正法对研究区进行地表温度反演,再利用DEM数据制作地形坡向文件,按阳坡、阴坡分布提取地表温度,结合地质构造对地表温度异常进行分析,圈定地热异常区。

基于Landsat-8的湛江东海岛地物分类研究

“宝钢湛江项目”的实施对近十年湛江东海岛的地物分布产生剧烈影响,尤其是工业用地。本文基于2013年、2017年和2021年的陆地卫星8号(Landsat-8)数据对湛江东海岛进行地物分类,研究该区域近十年的用地变化趋势。以2013年数据为参照:采用归一化水体指数(Normalized Difference Water Index,NDWI)模型和谱间关系模型实现水陆分离,比对选择分离效果较优者以提取东海岛岸线;对比最大似然法、神经网络法和支持向量机法3种监督分类方法,选择提取地物效果最优者应用于其余数据。基于Google earth在线地图及无人机实测数据构建验证点集,使用混淆矩阵进行精度评价。结果表明:谱间关系模型的水陆分离效果较优,提取海岛岸线的精确度有明显提升;支持向量机法的分类总体精度和Kappa系数最高,分类结果能较好地反映研究区的真实地物分布;汇总三年数据的分类结果,发现用于发展工业的土地面积增长突出且处于持续增长趋势。谱间关系模型与支持向量机法分别实现了对东海岛岸线和地物类型的准确提取,得出近十年研究区的用地变化趋势,能为研究区的用地规划提供参考。

基于Landsat影像的雄安新区2013−2021年土地利用变化检测和生态政策评估

利用2013−2021年共9期Landsat8影像,采用面向对象的监督分类方法,得到新区逐年土地利用与覆盖分类结果,进行LUCC分析及生态品质评价.结论:1)分类结果总体精度>86.8%,K为0.81~0.88,优于同期FROM-GLC及GLC_FCS全球分类产品;2)雄安新区设立至今耕地面积减少,不透水面和林地面积增长,蓝绿空间面积占比由12%增加至30%,雄安3县(雄县、容城县和安新县)建设严格遵循了新区《规划纲要》中植树造林、城市发展、湿地涵养3项不同的建设任务,各县主要土地利用覆盖变化分别为耕地向林地的转变、耕地与不透水面的相互转变以及耕地向水体和水生植被的转变;3)不透水面扩张与城市建设对生态品质的负面影响正逐步被森林覆盖率、蓝绿空间面积增加带来的正面影响所抵消.总体看,雄安新区土地利用/覆盖变化遵循新区规划要求,体现了经济社会发展和生态建设的成果.