Is PPGIS good enough? An empirical evaluation of the quality of PPGIS crowd-sourced spatial data for conservation planning

A significant barrier to the use of public participation GIS (PPGIS) and crowd-sourcing for conservation planning is uncertainty about the quality of the spatial data generated. This study examines the quality of PPGIS data for use in conservation planning. We evaluate two dimensions of spatial data quality, positional accuracy and data completeness using empirical PPGIS data from a statewide study of public lands in Victoria, Australia. Using an expert-derived spatial conservation model for Victoria as a benchmark, we quantify the performance of a crowd-sourced public in their capacity to accurately and comprehensively identify areas of high conservation importance in the PPGIS process. About 70% of PPGIS points that identified biological/conservation values were spatially coincident (position accurate) with modeled areas of high conservation importance, with greater accuracy associated with locations in existing protected areas. PPGIS data had less positional accuracy when participants identified biological values in urban areas and on non-public lands in general. The PPGIS process did not comprehensively identify all the largest, contiguous areas of high conservation importance in the state, missing about 20% of areas, primarily on small public land units in less densely populated regions of the state. Preferences for increased conservation/protection were over-represented in areas proximate to the Melbourne urban area and under-represented in more remote statewide locations. Our results indicate that if PPGIS data is to be integrated into spatial models for conservation planning, it is important to account for the spatial accuracy and completeness limitations identified in this study (i.e., urban areas, non-public lands, and smaller remote locations). The spatial accuracy and completeness of PPGIS data in this study suggests spatial data quality may be “good enough” to complement biological data in conservation planning but perhaps not good enough to overcome the mistrust associated with crowd-sourced knowledge. Recommendations to improve PPGIS data quality for prospective conservation planning applications are discussed.     

A note on synthetic data for replication purposes in agricultural economics

Empirical studies in agricultural economics usually involve policy implications. In many cases, such studies rely on proprietary or confidential data that cannot be published along with the article, challenging the replicability and credibility of the results. To overcome this problem, the use of synthetic data—that is, data that do not contain a single unit of the original data—has been proposed. In this note, we illustrate the utility of synthetic data generation methods for replication purposes using a range of methods from agricultural production analysis. More specifically, we compare input elasticities and technical efficiency scores based on different farm-level production data between original data and synthetic data. We generate synthetic data using a non-parametric method of classification and regression trees (CART) and parametric linear regressions. We find synthetic data result in elasticities and technical efficiency distributions that are very similar to the original data, especially when generated with CART, and conclude with implications for the research community.     

基于关联规则的耕地质量评价数据检错方法研究 ——以广州市为例

研究目的:从数据项之间关联关系的角度切入,探索一种新的耕地数据质量检错方法,以期更有效地提高耕地数据库的质量。研究方法:通过数据挖掘算法寻找耕地数据库中的关联关系,计算这些关联关系的发生频率,从中提取低频发生的关联关系作为检测规则(关联规则),最后利用这些关联规则识别耕地数据库中的错误记录(包含或符合关联规则的耕地数据记录为错误记录)。研究结果:(1)该方法有能力识别耕地数据库中的错误,可以做到有效提高耕地参评数据库的正确性;(2)经计算,与耕地领域现有的传统数据检错方法相比,同等条件下该方法可将检错效率提高11倍,甚至更多;(3)该方法可以针对不同的数据库迅速挖掘关联规则,灵活地应对不同的耕地数据库和层出不穷的错误类型。研究结论:基于关联规则的耕地数据库质量检测方法高效、便捷,为耕地领域现有的数据检错方法开辟了一个新的角度和思路,可以在地学领域广泛应用。     

A robust house price index using sparse and frugal data

In this article, we describe a house price index algorithm which requires only sparse and frugal data, namely house location, date of sale and sale price, as input data. We aim to show that our algorithm is as effective for predicting price changes as more complex models which require detailed or extensive data. Although various methods are employed for determining house price indexes, such as hedonic regression, mix-adjusted median or repeat sales, there is no consensus on how to determine the robustness of an index, and hence no agreement on which method is the best to use. We formalise an objective criterion for what a house price index should achieve, namely consistency between time periods. Using this criterion, we investigate whether it is possible to achieve strong robustness using frugal data covering only 66 months of transactions on the Irish property market. We develop a simple multi-stage algorithm and show that it is more robust than the complex hedonic regression model currently employed by the Irish Central Statistics Office.     

Modelling the supply of ecosystem services from agriculture: a minimum‐data approach*

We argue that to support agriculture–environmental policy decision making, stakeholders need ‘quantitative back‐of‐the‐envelope’ analysis that is timely and sufficiently accurate to make informed decisions. We apply this concept to the analysis of the supply of ecosystem services from agriculture. We present a spatially explicit production model and show how it can be used to derive the supply of ecosystem services in a region. This model shows that the supply of ecosystem services can be derived from the spatial distribution of opportunity cost of providing those services. We then show how this conceptual model can be used to develop a minimum‐data (MD) approach to the analysis of the supply of ecosystem services from agriculture that can be implemented with the kinds of secondary data that are available in most parts of the world. We apply the MD approach to simulate the supply of carbon that could be sequestered in agricultural soils in the dryland grain‐producing region of Montana. We find that the supply curve derived from the MD approach can approximate the supply curve obtained from a more elaborate model based on site‐specific data, and can do so with sufficient accuracy for policy analysis.     

基于时空数据模型的土地地籍管理研究

土地是最基础与最重要的资源与资产,是国家经济政策拟定的依据,是实施规划纲要与落实方针政策的基础。土地是人类生存的基础,而且是不可再生的,只有加大土地管理的力度,高效合理地利用土地,才能实现我国可持续发展的目标。地籍管理是土地管理工作的重点领域,是土地产权得到保障的前提。目前的土地管理集中在对土地产权的管理,土地产权变化会涉及到地理实体时间、空间及属性的变化,时态GIS正好反映了此变化。目前时态GIS的研究集中在对时空数据模型的建构。时空数据模型决定了时态GIS系统的运行效率。无论是国内还是国外均对时空数据模型进行了研究,通过模型的构建的相应地提出了超过20种模型,而在实际的应用中,不同的模型有不同的特点。文章对典型的6种时空数据模型进行了分析,从模型的建模思路出发,分别探讨了模型的适合环境与优缺点,可以为人们在应用时空数据模型进行土地管理时提供帮助,有利于研究者对模型的进一步研究。     

Towards integration of 3D legal and physical objects in cadastral data models

Digital 3D cadastres are often envisaged as the visualisation of 3D property rights (legal objects) and to some extent, their physical counterparts (physical objects) such as buildings and utility networks on, above and under the surface. They facilitate registration and management of 3D properties and reduction of boundary disputes. They also enable a wide variety of applications that in turn identify detailed and integrated 3D legal and physical objects for property management and city space management (3D land use management).Efficient delivery and implementation of these applications require many elements to support a digital 3D cadastre, such as existing 3D property registration laws, appropriate 3D data acquisition methods, 3D spatial database management systems, and functional 3D visualisation platforms. In addition, an appropriate 3D cadastral data model can also play a key role to ensure successful development of the 3D cadastre.A 3D cadastral data model needs to reflect the complexity and interrelations of 3D legal objects and their physical counterparts. Many jurisdictions have defined their own cadastral data models for legal purposes and have neglected the third dimension, integration of physical counterparts and semantic aspects.To address these problems, this paper aims to investigate why existing cadastral data models do not facilitate effective representation and analysis of 3D data, integration of 3D legal objects with their physical counterparts, and semantics. Then, a 3D cadastral data model (3DCDM) is proposed as a solution to improve the current cadastral data models. The data model is developed based on the ISO standards. UML modelling language is used to specify the data model. The results of this research can be used by cadastral data modellers to improve existing or develop new cadastral data models to support the requirements of 3D cadastres.     

Alternative models of input allocation in multicrop systems: Irrigation water in the Central Plains,United States

This paper compares three models of input allocation in multicrop systems. In addition to the variable input and satisficing models analyzed in previous research, an allocatable fixed input model of short-run input use is derived. The empirical application studies irrigation water use in the Central Plains region of the United States. Based on results from model specification tests and prediction accuracy measures, the allocatable fixed input model dominates both other models in explaining multicrop water allocation. In addition, the paper presents an alternative approach to the study of deficient data on multicrop production. By transferring econometric results from analysis of ‘non-deficient’ crop-level data, input allocations in deficient data sets can be predicted.     

数据融合算法在土地评估中的应用

研究目的:基于专家的主观信息在当前土地评估中的关键作用,对专家主观信息的置信度和评估数据进行分组融合,以提高评估精度和评估结果的可信度。研究方法:基于模糊测度理论,分析土地评估中"专家信息"融合需要解决的问题,建立融合准则和信息融合模型。研究结果:推导了专家评估信息融合基本算法,对专家的评估信息进行了有效的建模和融合,并在实际土地评估中进行了应用。研究结论:该方法能增加专家主观评估的可信性,提高估价精度,在更高层次上实现对专家信息价值的挖掘与利用。     

FAO/UNEP土地覆被分类系统及其借鉴

研究目的:介绍FAO/UNEP土地覆被分类系统(LCCS)的产生背景、分类理念、框架体系结构及应用前景,为同行提供学习和借鉴国际研究经验.研究方法:比较研究法、对比分析法,对比分析FAO/UNEP LCCS与美国、欧洲等国际知名机构,用于遥感监测和制图而建立的土地利用/覆被分类体系.研究结果:在各个分类体系之间,无论是分类命名、类型划分、详细程度、彼此间兼容性等方面,都存在很大差异且很难统一.研究结论:基于遥感数据建立土地覆被/利用分类体系并标准化是顺利开展各种遥感调查的前提和保证.在建立和完善中国标准化的土地覆被/利用分类体系基础上,应研究如何使中国的土地覆被/利用分类体系与国际接轨,在全球或区域实现信息共享.     

粮食产量空间化中4种误差修正方法的对比与分析

[目的]空间化作为一种常用的地学数据处理方法,必然会存在一定的误差,而对空间化结果进行误差修正,可以降低空间化误差。[方法]文章以2005年粮食产量空间化为例,以各地市不同农田类型(水田、水浇地、旱地)面积数据为自变量,以各地市粮食产量统计数据为因变量,进行多元线性回归分析建模。在具体建模时,令常数项为0,将全国分为7个区,各区分别建立回归方程。然后分别利用4种误差修正方法对空间化初步结果进行修正。选取4种误差评价因子,对修正前后的空间化结果的精度进行对比和分析。[结果](1)均值法不能被用于修正空间化初步结果;(2)比例系数法、权重系数法Ⅰ(不同农田类型同一权重)和权重系数法Ⅱ(不同农田类型不同权重)3种方法都可以被用于修正空间化初步结果;(3)利用权重系数法Ⅰ修正后的空间化结果的精度最高,比例系数法次之,权重系数法Ⅱ最差。[结论]误差修正方法对提高空间化精度具有重要影响。该研究虽以粮食产量空间化为例,但所得结论同样适用于其他社会经济统计数据的空间化研究,对以后统计型数据空间化研究具有一定的参考价值和指导作用。     

Joint estimation using revealed and stated preference data: An application using a national forest

We combine contingent behaviour with travel cost data to estimate the change in the recreational use value of a National Forest due to quality and price changes. Instead of the usual improvement scenario, a hypothetical deterioration in the conditions of the forest due to a fire is considered. A dataset containing five observations for each respondent enabled the estimation of three models for which the number of scenarios differed. The results show that visitors are sensitive to price and quality changes and that in the forest fire scenario the intended number of trips would be reduced and that respondents would experience a welfare loss. Signs of inconsistency between preferences expressed by revealed and intended behaviour were found. This research also provides some indications that strategic bias affects answers to price changes.     

中国耕地利用变化的研究方法分析：立足驱动与模拟研究

[目的]分析2000—2018年中国耕地利用变化的文献,对学者在研究耕地利用变化驱动和模拟方面所使用的方法进行对比分析,系统梳理各种方法在应用上存在的优势与不足,为未来学者开展相关研究提供方法参考。[方法]文献分析法、分类统计法等。[结果]对于耕地利用变化驱动研究而言,与主成分分析法组合的方法使用频率较高,基本适用于所有尺度,该方法可使复杂系统简单化、提高精度、有利于确定主要驱动因子,但一些重要的驱动因子难以经过统计学检验进入回归模型。对于耕地利用变化模拟研究而言,BP神经网络模型适合于大尺度的模拟研究,该方法预测能力强但精度一般;灰色动态模型GM(1,1)进行模拟所需的数据量较少、精度高,但受随机因素影响较大。CLUE-S模型已经比较成熟,在中小尺度上得到了很好的应用。[结论]耕地利用变化驱动与模拟的研究方法众多,但使用时相对单一且方法适用尺度的局限性较大。耕地利用变化驱动研究中学者们更倾向于使用定性与定量相结合的研究方法,未来耕地利用变化驱动的研究方法将逐渐朝着全定量的方向发展。耕地利用变化模拟研究中学者们更倾向于单一模型的使用,未来综合模型跨尺度融合将成为耕地利用变化模拟研究方法的发展方向。总体来看,未来耕地利用变化驱动与模拟研究方法将朝着双向、动态的复合型研究方法方向发展。     

耕地质量监测预警研究进展

耕地质量是人类社会赖以生存与发展的物质基础,是农业发展的基本生产资料。为发挥监测预警体系在耕地质量建设中的主体作用,实现耕地质量的可持续利用,本文采用文献综述法和系统分析法综述了耕地质量监测和预警体系在国内外的研究进展,并着重对时间序列分析模型、灰色预测模型和回归分析模型三种耕地质量预警模型进行阐述。耕地质量监测预警体系具有实时、动态、全方位的监测与预警功能,对监测预警指标体系、方法、周期、模型和理论实践探究还需要进一步完善,同时还需要借助应用大数据,以期为耕地质量精准化监测预警提供实时的数据及模型支持服务。     

基于SAR提高喀斯特地区LUCC光谱分类精度研究

喀斯特地区复杂地表形态导致地面调查可深入性差、精度不高,遥感则作为该区有效监测与研究人类活动对土地利用(LUCC)方式与利用程度影响的主要手段。文章利用ALOS多光谱数据与Terra SARX的数据进行融合,讨论了HH极化微波后向散射数据用于改善多光谱遥感数据LUCC分类的精度,并比较了不同融合方法对地物识别。结果表明:2种数据之间的融合充分利用了多光谱的光谱信息与HH极化数据丰富的结构与纹理的特征,增强了不同地物之间的光谱差异,提高地物可分性;PC法融合、IHS法融合分类精度较单独使用ALOS多光谱数据分类精度分别提高了8%与13%,而且由于HH极化对植被含水量的敏感性,提高了"插花"分布的旱地与草地、林地等由植被覆盖的土地利用类型的区分精度。通过该研究探讨了HH极化数据与多光谱数据融合在地表信息提取中的应用,拓展了遥感数据在喀斯特地区土地利用领域应用的范围。     

GNSS信号估算大气可降雨系统原理及应用进展

目的 通过分析机器学习方法与传统方法各自的优势和缺陷,可以融合机器学习方法和传统方法各自的优势,有效克服经验模型的缺陷,同时提高降雨估算精度,增强了降雨预测的可靠性,从而预防自然灾害。方法 文章指出将人工智能等相关算法引入GNSS大气可降水量的反演过程成为了当前研究的重要方向,特别是将深度学习神经网络等模型运用到GNSS大气可降水量的探测实验中不仅能够提高实验运算效率及反演精度,还可以在一定程度上减少工作量。结果 根据系统组合的PPP模式实验数据显示运用北斗系统进行大气可降水量反演具有可行性,反演结果与探空数据有很好的一致性,且将机器学习方法运用到多系统组合的PPP模型的精度更高,能够为天气预测提供技术支撑。结论 通过对GNSS反演大气可降水量发展的分析,归纳了当前利用GNSS反演大气可降水量的研究方法,对GNSS的大气水汽含量反演从理论到技术应用进行了梳理。同时研发基于约束下的GPS系统和我国北斗卫星系统的联合大气水汽反演系统对于进一步推动GNSS技术在气象和农业方面的应用具有重要作用。     

Can mobile phones improve nutrition among pastoral communities? Panel data evidence from Northern Kenya

The digital revolution and the ongoing dissemination of mobile phones carry several prospects for smallholder farmers in sub-Saharan Africa. Food insecurity and low dietary quality remain major issues among African smallholders. Mobile phones could potentially facilitate access to food markets and thus improve food security and nutrition, but research on such types of effects remains scarce. In this study, we analyze whether mobile phones improve dietary quality among pastoral communities in Northern Kenya. We use six rounds of household panel data covering the period between 2009 and 2015. During this period, mobile phone ownership in the sample increased from less than 30% to more than 70%. Regression models with household fixed effects allow robust estimation while reducing potential issues of unobserved heterogeneity. The estimates show that mobile phone adoption and use are positively and significantly associated with dietary diversity. The effects are particularly large for frequent mobile phone users. We also examine the underlying mechanisms. Mobile phone use improves dietary diversity mainly through better access to purchased foods. These results encourage the promotion of mobile phone technologies as a valuable tool for nutritional improvements, especially in remote rural settings with poor access to food markets.     

基于多维城乡差异化人地特征的城区范围识别方法 ——面向中国多样本城市的实践探索

研究目的：基于概念辨析与方法演进分析，从城乡差异化人地特征入手，构建指标量化下的城区范围识别方法并应用于107个样本城市进行准确度校验。研究方法：文献资料法、归纳演绎法、实证分析法。研究结果：（1）城区概念中的实体地域认知日益深化，现有多类指标筛选法、遥感影像识别法、大数据与人工智能识别法三类识别方法且具有差异化应用特征；（2）可从人口、土地、产业、环境4个维度选取差异化特征要素并确定指标条件，构建以实体地域为基础的城区范围识别方法；（3）借助影像数据、矢量数据和统计数据，依次通过初步筛选获得城区初始范围，通过图斑功能、连接度、边界核查等判断获得城区实体地域范围，通过图斑占比、市政公用和公共服务设施等分析获得城区范围；（4）在方法准确度校验中，105个样本城市的城区实体地域范围面积与同年度建成区面积平均偏差为21.2%，趋势线斜率为0.825，判定方法有效。研究结论：本方法可应用于全国各区域城市的城区范围识别，未来可在人口指标增补、统计精度提升等方面进行优化并开展镇区、乡村空间识别的延续性研究。     

Estimation of input-oriented technical efficiency using a nonhomogeneous stochastic production frontier model

Technical inefficiency can be modeled as either input‐oriented (IO) or output‐oriented (OO). However, in the estimation of parametric stochastic production frontier models which use maximum likelihood method only the OO measure is used. In this article we consider a simple nonhomogeneous production function and estimate it with both IO and OO specifications. A sample of 80 Spanish dairy data (1993–1998) is used to estimate both models. We consider one output (liters of milk) and four variable inputs (viz., number of cows, kilograms of concentrates, hectares of land, and labor [measured in man‐equivalent units]). We find that returns to scale (RTS) and technical efficiency results derived from these models are different because either estimated technologies are different, or they are evaluated at different points. Using a Monte Carlo analysis we show that if RTS is close to unity differences in the estimates of RTS and technical efficiency are smaller. This holds true for estimates of both RTS and technical efficiency.     

半城市化对中国农村土地利用效率的影响——基于CHIP数据的实证分析

研究目的:考察中国半城市化现状对农村土地利用效率的影响。研究方法:基于中国家庭收入调查(CHIP)2013年数据,采用二元logistic模型对半城市化水平与农村土地利用效率进行实证研究。研究结果:半城市化水平与土地资源的利用效率成明显负相关,半城市化程度越高,农村土地有效利用就越低。研究结论:半城市化现象的突出后果就是土地资源没有得到有效配置,即农村人口的减少并没有带来土地利用效率的提高。基于此,提出在半城市化背景下,要改变土地利用水平不高的问题,其前提是解决好城市化中的农民工问题,要让只是名义农民的农民工真正进城,实现农民工权益保障与农村土地配置优化双赢。