Construction of the Classification and Grading Index System of Cultivated Land Based on the Viewpoint of Sustainable Development

In order to objectively and reasonably evaluate the actual and potential value of cultivated land, both social and ecological values are introduced into the classification and grading index system of cultivated land based on the viewpoint of sustainable development, after considering the natural and economic values of cultivated land. Index system construction of the sustainable utilization of cultivated land should follow the principles of economic viability, social acceptability, and ecological protection. Classification of cultivated land should take into account the soil fertility of cultivated land. Then, grading of cultivated land is carried out from the practical productivity (or potential productivity) of cultivated land. According to the existing classification index system of cultivated land, the soil, natural and environmental factors in plains, mountains and hills are mainly modified in the classification index system of cultivated land. And index systems for the cultivated land classification in plains, mountains and hills are set up. The grading index system of cultivated land is established based on the economic viability (economic value), social acceptability (social value) and protection of cultivated land (ecological value). Quantitative expression of cultivated land grading index is also carried out.

Classification and Gradation of Cultivated Land Quality in Bishan County of Chongqing, China

The conflicts among food security, economic development and ecological protection are the “sticking point” of undeveloped southwestern mountainous areas of China. The objectives of this study are to identify appropriate inte- grated indicators influencing the classification and gradation of cultivated land quality in the southwestern mountainous area of China based on semi-structure interview, and to promote the monitoring of cultivated land quality in this region. Taking Bishan County of Chongqing as a study case, the integrated indicators involve the productivity, protection, ac- ceptability, and stability of cultivated land. The integrated indicators accord with the characteristics of land resources and human preference in southwestern mountainous area of China. In different agricultural zones, we emphasize different indicators, such as emphasizing productivity, stabilization and acceptability in low hilly and plain agricultural integrative zone (LHP-AIZ), protection, productivity and stability in low mountain and hill agro-forestry ecological zone (LMH-AEZ), and acceptability in plain outskirts integrative agricultural zone (PO-IAZ), respectively. The pronounced difference of classification and gradation of cultivated land, regardless of inter-region or intra-region, is observed, with the reducible rank from PO-IAZ, LHP-AIZ to LMH-AEZ. Research results accord with the characteristics of assets management and intensive utilization of cultivated land resources in the southwestern mountainous area of China. Semi-structure interview adequately presents the principal agent of farmers in agricultural land use and rural land market. This method is very effective and feasible to obtain data of the quality of cultivated land in the southwestern mountainous area of China.

Analysis on the Application of Quality Classification of Cultivated Land Resources in Municipal Land Space Planning:A Case Study of Chongzuo City

Cultivated land is the most important strategic resource to ensure food security.The newly constructed quality classification system of cultivated land resources considers the cultivated land health index for the first time.How the new classification and grading index system and the quality classification results of cultivated land resources to effectively guide the preparation of municipal land space planning has become a key research direction.This paper expounds the overall design idea for quality classification of cultivated land resources and classification index system.Taking Chongzuo City as an example,through the analysis of the quality classification results of cultivated land resources in the study area,using GIS spatial analysis and factor pairwise comparison method,this paper explores the application ideas and methods of quality classification research results of cultivated land resources in the formulation of cultivated land retention target,the delineation of dominant areas of cultivated land protection,the delineation of three control lines,the comprehensive improvement of land,and ecological restoration zoning in the municipal land space planning.

Cultivated land information extraction in UAV imagery based on deep convolutional neural network and transfer learning

The development of precision agriculture demands high accuracy and efficiency of cultivated land information extraction. As a new means of monitoring the ground in recent years, unmanned aerial vehicle(UAV) low-height remote sensing technique, which is flexible, efficient with low cost and with high resolution, is widely applied to investing various resources. Based on this, a novel extraction method for cultivated land information based on Deep Convolutional Neural Network and Transfer Learning(DTCLE) was proposed. First, linear features(roads and ridges etc.) were excluded based on Deep Convolutional Neural Network(DCNN). Next, feature extraction method learned from DCNN was used to cultivated land information extraction by introducing transfer learning mechanism. Last, cultivated land information extraction results were completed by the DTCLE and e Cognition for cultivated land information extraction(ECLE). The location of the Pengzhou County and Guanghan County, Sichuan Province were selected for the experimental purpose. The experimental results showed that the overall precision for the experimental image 1, 2 and 3(of extracting cultivated land) with the DTCLE method was 91.7%, 88.1% and 88.2% respectively, and the overall precision of ECLE is 90.7%, 90.5% and 87.0%, respectively. Accuracy of DTCLE was equivalent to that of ECLE, and also outperformed ECLE in terms of integrity and continuity.

Research on Extraction Method of Surface Information Based on Multi-Feature Combination Such as Fractal Texture

Because of the developed economy and lush vegetation in southern China, the following obstacles or difficulties exist in remote sensing land surface classification: 1) Diverse surface composition types;2) Undulating terrains;3) Small fragmented land;4) Indistinguishable shadows of surface objects. It is our top priority to clarify how to use the concept of big data (Data mining technology) and various new technologies and methods to make complex surface remote sensing information extraction technology develop in the direction of automation, refinement and intelligence. In order to achieve the above research objectives, the paper takes the Gaofen-2 satellite data produced in China as the data source, and takes the complex surface remote sensing information extraction technology as the research object, and intelligently analyzes the remote sensing information of complex surface on the basis of completing the data collection and preprocessing. The specific extraction methods are as follows: 1) extraction research on fractal texture features of Brownian motion;2) extraction research on color features;3) extraction research on vegetation index;4) research on vectors and corresponding classification. In this paper, fractal texture features, color features, vegetation features and spectral features of remote sensing images are combined to form a combination feature vector, which improves the dimension of features, and the feature vector improves the difference of remote sensing features, and it is more conducive to the classification of remote sensing features, and thus it improves the classification accuracy of remote sensing images. It is suitable for remote sensing information extraction of complex surface in southern China. This method can be extended to complex surface area in the future.

Monitoring the Cultivated Slope Land in the Three Gorges Reservoir Area Based on Remote Sensing and GIS

By means of combining auto-extraction with manual interpretation, the current distribution information about cultivated land is obtained. The distribution information of 1992 is extracted from the dynamic polygons of 2002. The monitoring mini-system of the cultivated slope land is established. In the system, detailed surveys, focused on the resources of cultivated slope land, are carried out. The results indicate that the area of the cultivated slope land is very large. Meanwhile, there are lots of cultivated steep slopes with gradient above 35°. The areas of steep land cultivated had been slowly reduced from 1992 to 2002. At the same time, the pressures of returning farm land to forestry are great in all counties. The conflicts between population growth, insufficient grain supply and stagnant economic development sharpen increasingly. It is inevitable to improve the agricultural structure.

Evaluation of Land Use &Land Cover Change Using Multi-Temporal Landsat Imagery: A Case Study Sulaimaniyah Governorate, Iraq

Land use & land cover change detection in rapid growth urbanized area have been studied by many researchers and there are many works on this topic. Commonly, settlement sprawl in area depends on many factors such as eco-nomic prosperity and population growth. Iraq is one of the countries which witnessed rapid development in the settlement area. Remote sensing and geographic information system (GIS) are analytical software technologies to evaluate this familiar worldwide phenomenon. This study illustrates settlement development in Sulaimaniyah Governorate from 2001 to 2017 using Landsat satellite imageries of different periods. All images had been classified using remote sensing software in order to proceed powerful mapping of land use classification. Maximum likelihood method is used in the accurately extracted solution information from geospatial imagery. Landsat images from the study area were categorized into four different classes. These are: forest, vegetation, soil, and settlement. Change detection analysis results illustrate that in the face of an explosive demographic shift in the settlement area where the record + 8.99 percent which is equivalent to 51.80 Km2 over a 16-year period and settlement area increasing from 3.87 percent in 2001 to 12.86 percent in 2017. Accuracy assessment model was used to evaluate (LULC) classified images. Accuracy results show an overall accuracy of 78.83% to 90.09% from 2001 to 2017 respectively while convincing results of Kappa coefficient given between substantial and almost perfect agreements. This study will help decision-makers in urban plan for future city development.

交叉学科视角下的信息资源管理创新人才培养

当前,新一轮科技革命和产业变革突飞猛进,科学研究范式加速演进,学科交叉融合已经成为学科发展的必然趋势。“信息资源管理”一级学科更名后,站在新的历史交汇期,如何开展学科创新人才培养成为重要课题。学科人才是学科发展重要的拉动力,人才培养工作是学科建设的重要环节。本文通过梳理信息资源管理产生和发展进路,阐明信息资源管理从诞生之日起就具有多领域融合、多学科交叉的特质,进而从交叉学科视角切入,从本科和研究生两个培养层次分析信息资源管理人才培养趋势,最后提出交叉学科视角下信息资源管理学科“根植课程体系、立足学科前沿、拓宽交叉领域”的创新人才培养路径。

东北典型黑土区耕地侵蚀沟形态系统分类方法构建

侵蚀沟形态分类是认识其发展现状和潜在危害的重要方法,探究耕地侵蚀沟形态分类特征和分布特征对把握耕地侵蚀沟防治重点,预防坡耕地水土流失具有重要意义。针对现有侵蚀沟形态分类体系指标获取难、分类结果不完整等问题,利用遥感解译数据,根据系统分类和信息科学理论,结合东北黑土区现实需求,构建了耕地侵蚀沟系统分类方法,并在典型黑土耕作区海伦市进行了验证。结果表明:1)海伦市耕地侵蚀沟具有小面积、大宽度、短长度的特点,Ⅰ类和Ⅱ类为数量最多的一级分类;Ⅱ类四等微型沟(Ⅱ4T)和Ⅱ类四等小型沟(Ⅱ4S)在二级和三级分类中数量居多,易通过高标准农田建设进行治理。2)地形要素下耕地侵蚀沟形态分布差异明显,需要特别关注在高程180~<240 m,坡长35~<55 m,坡度2°~6°,西南坡区域内的Ⅰ4T、Ⅱ4S、Ⅱ4T等发育程度较低的侵蚀沟向更高发育程度的Ⅳ4M、Ⅴ4M等类型转变,建议结合农田建设及时采取综合防治措施,以防止耕地侵蚀沟的潜在破坏。3)构建的“类+等+型”耕地侵蚀沟分类定级方法,兼顾指标的易获取性和方法的易操作性,能够精准、直观地揭示耕地侵蚀沟的形态特征及其危害情况,可为侵蚀沟和黑土耕地的协同综合治理提供方法借鉴。

基于耕地资源质量分类监测的土壤条件变化对粮食产量的影响——以河南省兰考县为例

为突出土壤条件变化对粮食产量的影响,采用趋势分析法和对比分析法,以兰考县耕地资源质量分类监测工作为例,分析土壤监测样点不同年份的土壤条件变化对当地粮食产量造成的影响。研究表明,土壤有机质含量的增加和土壤pH在合理范围内的增加都能够提升粮食产量。建议以测土配方施肥为基础,增加有机肥的使用量,提升土壤有机质含量,并针对当地土壤的实际情况和主要作物类型,提出有针对性的改良土壤pH的措施,以提升粮食产量。

POI辅助下的城市国土空间地类信息细化研究

为提升城市国土空间地类信息细化工作效率,将POI数据、国土变更调查数据与行业专题资料相结合,利用分类映射、数据匹配、空间叠置等关键技术,研究形成了一套POI辅助下的城市国土空间地类信息细化技术流程。通过搭建FME模板,实现了城镇住宅、医疗机构、学校等各细化地类的快速自动定位与信息细化补充,在一定程度上减少了人工工作量,提升了工作效率。以徐州市为例,统计了POI对于不同细化地类的利用率。结果表明,分类映射提取后的POI专题数据整体利用率较好;但由于不同数据标准的差异性,对于部分细化类型,POI数据需进一步结合其他数据来提升其可用性。

规划管控约束下耕地细碎化评价与整治分区

科学评估耕地细碎化治理的适宜性与必要性,并进行合理的整治分区有利于耕地资源的高效利用与空间布局,促进三生空间协调发展。该研究以典型山区县及资源型城市江西省德兴市为例,基于村域尺度,从生产适宜性、空间集聚性、管控约束性3个视角构建评价体系,采用多因素综合叠加评价法对耕地细碎化进行评价,借助三维魔方空间分类法开展整治分区研究。结果表明:1)各村耕地资源生产适宜性良好,均值为0.558;空间集聚性一般,均值为0.350;管控约束性标准差大于均值,各村差异较大;耕地细碎化治理适宜性较高,均值为0.711。2)统筹评价结果将德兴市划分为高质保障区、综合整治区、设施优化区、集约整合区以及现状维持区5区,基于各区生产适宜性、空间集聚性与管控约束性差异制定差别化整治措施与治理策略。研究结果可为耕地细碎化整治提供有益的参考借鉴。

基于Landsat8 OLI数据的山东省耕地信息提取研究

为了探讨美国最新发射的陆地卫星Landsat8 OLI影像在耕地信息提取方面的效果,为了解该影像的应用潜力提供一些信息,采用遥感图像处理软件ENVI,对覆盖山东省区域的12幅Landsat8 OLI影像进行了计算机校正和增强处理,通过目视解释、监督分类和非监督分类交互式的分类方法提取山东省的耕地信息。结果表明,基于Landsat8 OLI数据提取耕地信息适宜波段是543波段和652波段组合,提取精度达到91.8%,Landsat8 OLI数据可以满足耕地利用及管理中对耕地信息适时获取的要求。

基于GeoSOS-FLUS模型的桂林市耕地变化趋势

为探讨桂林市耕地时空变化格局、促进土地资源合理配置,本文基于Google Earth Engine(GEE)云平台,以多时相的Landsat遥感影像为数据源,综合比较5种分类方法在桂林市土地利用分类中的适用性;分析了桂林市2000—2020年土地利用变化,尤其是耕地时空变化格局;并利用GeoSOS-FLUS模型模拟预测在自然发展、耕地保护和生态控制等不同情景下,2030年桂林市耕地时空变化趋势。结果表明:①随机森林算法对桂林市土地利用类型提取的总体精度及Kappa系数均最高;②2000—2020年耕地面积逐年减少,其中2010—2015年流失情况最为严重,耕地主要表现为与建设用地和林地的相互转化,退耕还林、旅游业快速发展及建设用地扩张等是影响耕地时空变化格局的关键因素;③自然发展情景下,耕地面积将继续大幅减少,建设用地扩张和耕地减少将对生态环境产生一定影响。耕地保护和生态控制情景中,耕地面积将有所上升,其减少趋势有所缓解,对维护桂林市粮食安全、旅游业持续发展及生态系统的稳定性具有重要意义。

新形势下耕地资源质量分类与等别转换的应用研究——以济南市为例

以济南市为研究区域,在2021年度耕地资源质量分类成果的基础上,运用改进的灰靶模型和指标赋分求和法2种等别转换方式将济南市耕地资源质量分类成果转换为等别数据。结果表明:改进的灰靶模型兼顾了耕地的自然本底特征和耕地的粮食产能,在赋权和评价过程更为客观、科学,转换后的等别成果更为合理,济南市质量较好的耕地主要位于中部和北部平原地区以及沿黄地区,等别主要为3等和4等地,占总耕地面积的77%,符合济南市实际情况;采用指标赋分求和法转换的等别整体较为合理,但主观性较强,评价结果区域内部差异性较小。因此,改进的灰靶模型在耕地资源质量分类与等别衔接研究中应用性更强,转换成果可为耕地占补平衡与进出平衡等实践应用提供参考。

基于模糊数学方法的金昌市耕地质量评价及土壤养分空间特征分析

本研究以金昌市为研究区,通过对市域范围内耕地质量等级、土壤养分特征和空间分异的分析,在保障精度的条件下,为耕地的科学施肥和提高土壤养分区域化管理水平提供依据。模糊数学作为一种对模糊现象进行定量分析的方法,在许多领域都有广泛的应用价值。基于地理信息系统技术,阐述了该方法如何对耕地质量进行评价。本研究以金昌市为例,以《耕地质量等级》国家标准为依据,采用县域耕地资源管理信息系统和GIS技术相结合的方法,对该地区耕地质量等级与养分含量的空间分布进行了分析与研究。结果表明:金昌市耕地质量等级处于一至六等地,无七至十等地,一等地为金昌市耕地主体,面积为80024.40 hm^(2),占金昌市总耕地的64.35%;金昌市耕地养分整体水平较为中等,土壤有机质含量多属中低等水平,总体呈现西高东低趋势;全氮含量多属低等水平,总体呈现西南高东北低的趋势;有效磷含量多属较高水平,总体呈现西南地区高于东北地区;速效钾含量多属中低等水平,总体呈现西高东低趋势。金昌市耕地质量总体状况较好,可以通过增施有机肥,提高土壤肥力,加大灌溉力度、加大节水技术推广力度,使土壤保水保肥。

Spatio-temporal characteristics and typical patterns of eco-efficiency of cultivated land use in the Yangtze River Economic Belt, China

Identifying the dynamics of the eco-efficiency of cultivated land use(ECLU)is important to balance food security and environmental protection.The Yangtze River Economic Belt(YREB)is a vital region of national strategic development in China.However,the spatio-temporal characteristics and typical patterns of the ECLU in the YREB remain unclear.This study aims to reveal the spatio-temporal characteristics of the ECLU by using the super-efficiency slack-based measure(SBM)and a spatial autocorrelation model.The typical patterns of the ECLU were classified based on a decision tree algorithm.The results indicate that the overall ECLU increased from 0.78 to 0.87 from 2000 to 2019,dropping sharply in 2003 before rising again.Different reaches had similar trends.The local indicators of spatial association(LISA)cluster reflect that the spatial distributions of high-high and low-low agglomeration varied dramatically among these years.The ECLU was divided into three typical patterns considering the restriction of agrochemicals and water resources(RAW),cultivated land and agrochemicals(RCA),as well as technology(RT).Most cities belonged to the low ECLU category in RT pattern.Fully understanding the spatio-temporal characteristics and classification of the ECLU will provide a reference for decision-makers to improve the ECLU in different regions.

上海市耕地后备资源宜耕性分析评价

以上海市9个涉农郊区的未利用地作为评价对象,依托国家统一部署耕地后备资源调查评价工作指标体系,收集相关规划、测绘、土地、生态数据,针对体系内不同指标开展宜耕性分析,形成上海市耕地后备资源综合评价成果,并采用不同地理分析手段对全市后备资源分布情况进行分析及研究。结果表明:上海市耕地后备资源总量仅占调查面积的32%,且土地集中连片度较低,呈不均匀碎片式分布,主要集中分布于浦东、崇明、奉贤、青浦等少数几个郊区。针对耕地后备资源开发利用,从全域土地综合整治、低效建设用地复垦等方面提出了提升全市耕地后备资源的对策建议。

基于地理信息系统的农业耕地土壤污染源检测方法研究

基于地理信息系统的农业耕地土壤污染源检测方法,在整个研究区3亩区域,采集了研究区土壤样品,并采用相关性分析、富集因子及评价、正定矩阵因子分析模型(PMF)解析了重金属污染来源及其贡献率,并且用指数法评价了重金属污染水平及其生态风险。结果表明:As、Pb、Cd数据呈现正态性分布,Zn、Cr、Cu、Ni污染物特征相对比较集中,呈现均匀性分布。其余重金属除了Ni以外,评价结果都属于安全等级。经PMF模型源解析可知研究区域农业耕地土壤中重金属的主要来源依次是:自然土壤来源>农业污染来源>工业活动来源>地下径流和大气沉降来源。

韩江中上游地区的崩岗分布特征

选取韩江中上游地区2016—2022年的Sentinel-1/2卫星星座遥感影像和其他辅助数据,基于机器学习方法进行区域尺度的崩岗识别和崩岗影响因子测度。结果表明:1)分类模型的总体精度达到84%,Kappa系数为0.8。其中,崩岗识别的用户精度和生产者精度都超过95%,且其FScore为0.97。2)截至2022年,韩江中上游地区的崩岗侵蚀面积共有435.5 km^(2),各县(市、区)崩岗侵蚀面积差异明显,年变化趋势不一。其中,五华县崩岗侵蚀面积最多(199.2 km^(2)),其年平均变化率为16.29 km^(2)/a。梅江区崩岗侵蚀面积最少(1.6 km^(2)),其年平均变化率为0.18 km^(2)/a。3)韩江中上游地区崩岗发生概率与高程、坡度、植被覆盖、地质类型、人口密度、大气压、降雨量、经向风速、纬向风速和风速等10个因素存在显著相关性(P<0.001)。在一定的变化范围内,高程、坡度、地质类型、大气压、经向风速、纬向风速和风速对研究区崩岗发生为正向影响,植被覆盖、人口密度和降雨量对崩岗发生为负向影响。