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农户的耕地非农转换价值及态度模型——基于西宁市的实证研究
陈琼1,2,, 蔡运龙3,, 刘峰贵1, 魏晓燕1, 周强1, 张海峰1
1. 青海师范大学地理科学学院,西宁 810008
2. 青海省地理空间信息技术与应用重点实验室,西宁 810001
3. 北京大学城市与环境学院,地表过程分析与模拟教育部实验室,北京 100871

作者简介:陈琼(1975- ),女,浙江诸暨人,博士研究生,研究方向为土地科学。E-mail: qhchenqiong@163.com

通讯作者:蔡运龙(1948- ),男,贵州贵阳人,教授,博士生导师,研究方向为综合自然地理学。E-mail: caiyl@urban.pku.edu.cn
摘要

耕地非农转换是城市化进程中的必然过程,并对城乡不同农户产生差异性影响。立足农户层面,针对耕地非农转换过程的特征,建立多元情景,分析基于农户视角的耕地非农转换价值及差异性,构建农户的耕地非农转换态度模型。并以西宁市市区为例,完成22个村812户农户的入户调查,建立了耕地征用程度、土地开发方向、空间区位和城市位置4个分析框架,形成13种情景农户的耕地非农转换价值及态度模型。结果表明:农户的耕地非农转换价值内容呈现多元化特征,影响农户征用态度和生活满意度的因素较为复杂多样,经济来源增加成为耕地非农转化农户生活满意度和征用态度模型中最为主要的影响因素。提高对耕地价值的全面系统认知,可为丰富和完善土地利用政策提供借鉴。

关键词: 耕地非农转换价值; 态度模型; 农户调查; 西宁市区;
Farmers' value and attitude model of farmland non-agriculture conversion: A questionnaire from farmers in Xining city
CHEN Qiong1,2,, CAI Yunlong3,, LIU Fenggui1, WEI Xiaoyan1, ZHOU Qiang1, ZHANG Haifeng1
1. College of Geographic Sciences, Qinghai Normal University, Xining 810008, China
2. Geospatial information technology and Application Key Laboratory of Qinghai Province, Xining 810008, China
3. College of Urban and Environmental Sciences, the Center for Land Study, Peking University; Laboratory for Earth Surface Processes, the Ministry of Education, Beijing 100871, China
Abstract

Farmland non-agricultural conversion is a common phenomenon during urbanization and it has different influences on farmers. According to different situations, this study, from a perspective of farmers, examines farmers' value and attitudes of farmland non-agricultural conversion. A case study is from 812 households of 22 villages in Xining city. Four analytical frameworks of land acquisition degree, land development direction, spatial location and administrative region and 13 conditions are built. The results are showed as follows: (1) The farmers' value of farmland non-agricultural conversion varies from person to person; (2) The factors that affect the farmers' attitude toward expropriation and life satisfaction are complicated and diverse; (3) At different situations of cultivated land non-agricultural conversion, there are significant differences in farmers' perceptions on economic value, happiness, and attitude toward expropriation; (4) Increasing economic source is the major factor that affect farmers' satisfaction and attitude toward expropriation. Through this questionnaire research, we can attain the comprehensive acknowledge about the value of cultivated land. It is helpful for us to enrich and complete the land-use policies.

Keyword: farmers' value of farmland non-agricultural conversion; attitude measuring model; questionnaire from farmers; Xining city;
1 引言

城市及其周边土地利用变化是土地变化科学近年来高度关注的热点问题[1]。随着城市化和工业化过程不断推进,城镇周边耕地大量非农化,具有全球普遍性[2,3,4,5,6]。伴随中国经济的快速发展,工业和城镇建设用地大量增加,耕地急剧减少。1990-2000年全国145个重要城市70%新增建设用地来自于耕地[7,8];2000-2014年全国建成区面积由2.24×104 km2增加到4.98×104 km2[9]。耕地非农化一方面促进了地区经济的发展,但同时也出现了建设用地快速扩张与宅基地低效利用并存,耕地质量退化与高度集约利用并存等土地利用管理的重大问题[10,11],出现一系列社会和生态等不利于可持续发展的问题[12,13]

作为一个复杂过程,耕地非农化研究方法从以自然科学家为代表的“地”的研究和以社会科学家为代表的“人”的研究相融合,逐步与空间技术(RS、GIS)、计量经济学、环境学、地理学等更多理论和方法融合,加深了对耕地非农化问题的理解,但依然缺乏统一的理论指导[14]。耕地非农化受多重因素的综合作用,主要包含基础设施建设和城市扩张等导致的表层原因(proximate drivers),以及人口、经济、技术、制度、文化和区位等深层原因(underlying drivers)[15,16,17,18,19],且各因素具有显著的级联效应,进一步增加其复杂性。因此,寻求新的途径揭示耕地非农过程产生问题的根源,成为解决失地农民困境和实现耕地可持续管理的重要关键。

蔡运龙等提出耕地的经济产出价值、生态服务价值和社会保障价值[20],为系统认识耕地价值提供了基础。借鉴行为地理学研究方法,通过探究重要利益主体的主观意象,从人的主体角度理解行为与所处自然社会地理环境的关系[21,22],揭示影响行为发生的主要因素,探寻人类主观模型及假设[23],能够更好地解释行为决策。本文从农户视角,调查分析耕地非农转换价值体系及其差异性,构建农户对耕地非农化价值和态度模型,进而解释耕地非农过程中产生的问题根源,以期为改变快速城镇化背景下城乡结合部农业地域功能受到忽视与低估[24]的现象提供支持,为耕地保护和利用决策提供科学依据。

2 耕地非农转换价值及其态度关系假设
2.1 农户耕地非农转换价值

耕地非农转换过程对农户家庭的收入来源、种植效益、生活保障、就业以及周边环境等方面产生直接影响。因此,在农户耕地非农转换价值内容分为经济价值、社会价值和生态价值框架下,系统梳理耕地非农转换给农户带来的多元化影响结果,结合实地与农户和地方官员的访谈,最终辨识和筛选出农户的耕地非农转换价值体系指标(表1)。

表1 农户的耕地非农转换价值体系指标 Tab. 1 Indicators of farmer's value for farmland non-agricultural conversion
2.2 农户的耕地非农转换价值体系与态度关系结构

耕地征用是中国目前耕地非农化最主要的方式。耕地征用导致农户土地利用和生产生活发生变化。用生活满意状况和对土地征用的态度来表征这种变化的综合影响。

然而,农户的耕地非农转换价值与态度意愿存在显著差异,究其原因主要与区域经济社会发展阶段和自然地理背景密切相关。空间区位、耕地被征用程度、耕地征用后的土地开发方向、区域的经济发展背景以及农户的经济社会特征等因素都深刻影响着农户的价值体系。据此,从影响因素到农户对耕地非农转换价值及态度分为三层结构,各个层次之间存在复杂的交互关系(图1)。

图1 农户耕地非农转换价值、态度与影响因素的结构关系 Fig. 1 Relationships among farmers' value, attitudes and influencing factors of farmland conversion

3 耕地非农转换的农户态度模型
3.1 模型选择

在以上关系假设的基础上,为评价和识别不同影响因素对农户非农转换价值和态度的影响程度,试图建立关系模型。从研究问题的性质看,可以将影响因子、农户非农转换价值与态度之间关系界定为驱动因素与效应。综合考虑到数据可得性、数据类型和研究者对模型的解释能力,并结合所涉及数据类型,即定距、定序和定类三种类型,选择二值逻辑斯蒂回归模型(Binary Logistic Model)作为量化农户耕地非农转换价值与影响因素关系的计算模型。

以农户对耕地非农转换价值评价模型为例,假设p为耕地非农转换生活满意的概率值,则1-p为不满意的发生概率,X为影响满意态度的各项因素,则逻辑斯蒂回归模型建立满意度测度基本模型,具体可用如下方程表示:

ln p 1 - p = B 0 + B 1 X 1 + B 2 X 2 + + B n X n (1)

p = 1 1 + exp [ - ( B 0 + B 1 X 1 + B 2 X 2 + + B n X n ) ] (2)

式中:B为待定系数;X为自变量。采用最大似然估计法(Maximum Likelihood Estimation, MLE)进行参数估计获得因变量的待定系数。根据待定系数的取值判断不同因子对事件发生概率的影响方向与强度。用比数比exp(B)来表征因变量的影响程度,其值以1为界,当exp(B)>1时,说明该自变量取值的增加有利于事件发生概率的提高,可定性为正效应指标;反之为负向,提高该指标的取值将降低事件发生概率。

3.2 情景设置

总体评价往往掩盖了局部的差异性,不同地域由于社会经济发展的基础、区位条件、资源禀赋的差异,其主导优势功能存在较大的差异[25]。为此,在系统掌握城市周边农户土地征用、价值和态度基础上,分别从空间区位、耕地征用程度、土地开发利用方向及行政分区四个方面对农户进行分类,实现农户耕地转换价值的差异性分析。耕地征用程度主要考虑农户在不同农业生产和生活资源条件下的价值认知及差异,分为部分耕地、全部耕地以及全部耕地和宅基地被征用三种情况。土地开发利用反映政府土地政策的差异性,探测农户对城市化过程造成农村周边环境变化的响应,主要分为:住宅区、开发区、基础设施建设和服务设施四种类型。城市内部在土地资源、经济发展定位等方面存在空间异质性,城市下属的行政区作为分析框架。近、远郊反映不同空间位置农户对耕地转换价值的影响。结合研究区实际,形成如下情景模式(图2)。

图2 农户的耕地非农转换价值与态度模型情景设置 Fig. 2 Scenarios of farmer' value and attitudes

根据图2,构成13种情景,每种情景下分别建立农户生活满意度模型和土地征用满意度模型2种模型,共26个情景。考察各种情景的影响因素差异,识别影响农户耕地非农转换态度的关键要素。

4 农户耕地非农转换的价值研究:以西宁市区为例

西宁市属于河谷型城市,南北宽25.5 km,东西长32 km,是青藏高原发展最快的城市,土地利用格局在21世纪初发生转型,由耕地主导型转变为多元化城市土地利用格局。自2004年后,土地利用变化相对平缓,以耕地非农转换为主[26]。选择城区内22个村进行农户耕地非农转换价值认知进行入户调查(图3),获得问卷812份,有效797份,有效率为98.2%。

图3 西宁市22个调查村空间分布示意图 Fig. 3 Location of 22 villages for questionnaire in Xining

4.1 西宁市耕地非农转换的情景解释

基于图1中的情景分类,结合西宁市区实际,具体解释如下(表2)。

表2 西宁市耕地非农转换情景解释 Tab. 2 Intruduction of 13 scenarios for farmer's perception in Xining city
4.2 西宁市农户的耕地非农转换价值

对西宁市农户进行耕地非农转换价值调查,并对选择项从“非常同意,同意,一般,不同意和非常不同意”分别从5~1打分,形成表3结果。

表3 农户的耕地非农转换价值 Tab. 3 Farmers' value of farmland non-agricultural conversion

耕地非农化后,农户总体认为家庭生活费用增加,土地种植效益逐渐变好,土地发生增值。虽然农户获得了更多就业机会,但57%的农户认为这并不会增加赚钱机会,家庭收入反而因失去了种植而减少;农户居住环境明显改善,农民可享受到更多的城市基础设施和公共服务设施;耕地非农化改善了农村道路设施,加强了居住区的统一规划,使农户普遍认为居住区周围整洁度显著提高。尤其是城区化和土地开发区利用的农户,满意度最高,但96.1%的农户依然渴望农田景观。

空间位置、开发方向、征用程度和行政分区对家庭收入、生活费用、耕地增值的农户、生活保障、工作机会等不同而产生显著差异。近郊和耕地宅基地全被征用农户产生了更大的经济和生活保障压力。

4.3 西宁市耕地非农转换农户态度模型构建

选择耕地非农转换的农户生活满意状态和征用态度为因变量,研究区农户耕地非农转换价值内容、经济社会与环境特点等为自变量,分别建立农户生活满意度和耕地征用态度模型(表4)。

表4 耕地非农转换态度的逻辑斯蒂回归模型的变量说明 Tab. 4 Logistic variables of perceptions to farmland conversion

为避免自变量之间存的共线性问题,先进行相关性分析,剔除相关性较高的指标。并考虑自变量中有较多的定序类型,选择非参数检验法,Spearman秩次相关检验法,剔除α显著性水平0.01,相关系数达到0.5以上的变量。采用二值逻辑斯蒂回归模型分别建立农户生活满意度与征地态度与12项自变量之间的定量关系。

4.4 西宁市耕地非农转换的农户生活满意度模型

农户生活满意度模型各情景的有效样本量范围为40~432个,平均为240个。使用的样本数量平均为自变量的20倍,样本数量满足逻辑斯蒂回归建模需要。表5中对生活满意度模型的有效性检验与方程的预测能力结果表明,除土地开发方向的基础设施建设情景(A4)和空间位置的城北区情景(C1)的检验值小于0.05外,其他均高于阈值,最高达到0.962,各个模型的预测正确率为64.2%~90.0%不等,即模型有效。

表5 西宁市耕地非农化农户生活满意度、征用态度回归模型有效性检验与预测能力结果表 Tab. 5 Validity test and predictive ability of Logistic of farmers' satisfaction and attitude

模型运算后得出相关性较高的指标主要为家庭劳动力比例、劳动力数量、户均收入、家庭收入。构建的13种情景二值逻辑斯蒂回归模型分别如下:

A1: ln p 1 - p = - 0.149 X 2 - 0.105 X 7 + 0.266 X 8 - 0.129 X 10 + 0.176 X 11 + 0.197 X 12 - 1.194

A2: ln p 1 - p = 1.069 X 5 - 0.233 X 9 + 0.389 X 11 - 3.034

A3: ln p 1 - p = 0.427 X 8 + 0.368 X 11 - 4.667

A4: ln p 1 - p = 0.182 X 4 - 2.999

B1: ln p 1 - p = 0.189 X 8 + 0.201 X 11 + 0.365 X 12 - 3.399

B2: ln p 1 - p = 0.217 X 7 + 0.213 X 8 + 0.140 X 9 + 0.184 X 11 - 1.298

B3: ln p 1 - p = 0.192 X 4 + 0.380 X 11 - 0.887

C1: ln p 1 - p = - 0.281 X 2 - 0.156 X 4 - 0.321 X 7 + 0.358 X 8 + 0.242 X 9 + 0.203 X 11 - 0.019

C2: ln p 1 - p = 0.424 X 5 - 0.084 X 7 + 0.196 X 8 + 0.147 X 11 0.308 X 12 - 2.746

C3: ln p 1 - p = 1.133 X 5 + 0.219 X 11 - 1.327

D1: ln p 1 - p = - 0.144 X 7 + 0.281 X 8 + 0.220 X 9 + 0.156 X 11 - 2.834

D2: ln p 1 - p = - 0.181 X 2 + 0.377 X 5 + 0.137 X 11 0.217 X 12 - 0.928

D3: ln p 1 - p = - 0.509 X 1 - 0.183 X 4 + 4.088

从进入回归方程的变量看,4个分析框架,13种情景农户对耕地非农转换生活满意度回归模型存在较大差异。耕地用于住宅开发、近郊、城北区、城西区、耕地和宅基地全部被征用以及耕地被征用这6种情景的影响因素最为复杂,其中,耕地种植满意度、收入来源增加和生活环境条件改善较为一致的影响因素。耕地用于基础设施建设、远郊农户、城东区和部分耕地被征用四种情景的回归模型最为简单,并且普遍受到人均耕地非农化补偿的影响。

收入来源增加成为农户耕地非农转换生活满意度的最主要因素,除土地基础设施开发和部分耕地征用情景外,其他11种情景中都进入了回归模型。其次为生活环境条件改善,是7种情景的影响因素。

根据比数比(图4),可判断各个因素对生活满意度的影响效应,对于大于1的因子可以界定为促进因素,反之为抑制因子。在土地开发利用方向类型中,生活满意度的促进因子有:家庭人均收入、生活环境改善、收入来源增加、空气改善、生活压力减轻;抑制因子为:人均耕地征用补偿、家庭人数、耕地增值、耕地种植满意。在农户类型中,促进因子为:收入来源增加、生活压力减轻、生活环境改善、空气改善;抑制因子包括:耕地种植满意、人均耕地征用补偿。在空间位置类型中,促进因子:家庭人均收入、生活环境改善、生活压力减轻、空气改善、收入来源增加;抑制因子:耕地种植满意、家庭人数、人均耕地征用补偿。在征用程度类型中,促进因子有:家庭人均收入、生活环境改善、空气改善、生活压力减轻、收入来源增加;抑制因子:劳动力人数、人均耕地征用补偿、家庭人数、耕地种植满意。

图4 农户耕地非农转换生活满意度逻辑斯蒂回归模型的比数比 Fig. 4 Odds ratios of Logistic of farmers' satisfaction

4.5 西宁市农户耕地征用态度模型

与西宁市农户生活满意度模型构建过程类似,耕地征用态度回归模型使用的有效样本量在不同情景中有所差异,总体范围为37~384个,平均达到224个,满足逻辑斯蒂回归建模的需要。除土地开发方向的基础设施建设情景(A4)和空间位置的城北区情景(C1)的检验值小于0.05外,其他均高于阈值,最高达到0.96,各个模型的预测正确率为60.6~90.7%不等,模型有效(表5)。

与西宁市农户非农转换生活满意度模型构建方法相同,建立耕地征用态度回归模型,先进行相关性检验后,对13种情景进行二值逻辑斯蒂回归。

A1: ln p 1 - p = 0.598 X 5 - 0.202 X 7 + 0.181 X 10 + 0.193 X 11 - 1.647

A2: ln p 1 - p = 0.579 X 1 + 0.278 X 9 + 0.456 X 10 + 0.613 X 11 - 10.144

A3: ln p 1 - p = 1.978 X 8 + 0.474 X 9 - 0.467 X 10 + 0.635 X 11 - 19.573

A4: ln p 1 - p = - 0.498 X 9 + 2.089

B1: ln p 1 - p = 0.478 X 5 - 0.583

B2: ln p 1 - p = - 0.245 X 7 + 0.235 X 8 + 0.328 X 10 + 0.345 X 11 + 0.177 X 12 - 5.442

B3: ln p 1 - p = 0.242 X 9 + 0.289 X 11 - 3.642

C1: ln p 1 - p = 0.896 X 8 + 0.277 X 9 - 0.193 X 10 + 0.202 X 11 - 8.756

C2: ln p 1 - p = 0.515 X 5 + 0.249 X 10 + 0.178 X 11 + 0.252 X 12 - 4.737

C3: ln p 1 - p = - 0.333 X 7 + 0.389 X 10 + 0.479 X 11 - 3.308

D1: ln p 1 - p = 0.173 X 10 + 0.286 X 11 - 3.434

D2: ln p 1 - p = 0.467 X 5 - 0.199 X 7 + 0.420 X 8 + 0.183 X 10 + 0.181 X 11 + 0.313 X 12 - 6.585

D3: ln p 1 - p = - 0.137 X 4 + 0.298 X 9 + 0 . 305 X 11 - 3.252

4个类型13种情景的耕地征用态度模型存在较大差异,影响耕地被征用和近郊农户征用态度的因素最为复杂,且较为一致,主要为:耕地种植满意、生活环境条件改善、耕地增值、收入来源增加和生活压力减轻。影响城区化农户和土地基础设施建设开发农户征用态度的因素最为简单,分别为家庭人均收入和空间质量改善。

从进入回归方程的变量看,收入来源增加依然成为影响农户征用态度的最为主要因素,除城区化农户和土地基础设施建设开发情景外,其他11种情景中都进入了回归模型。耕地增值和空气质量改善也成为重要影响因素,分别在9种和6种情景进入模型。

根据比数比(图5)看出,在土地开发利用方向类型中,促进农户对耕地征用满意的因子有:生活环境改善、收入来源增加、家庭人均收入、劳动力人数、空气改善、耕地增值;主要的抑制因子是耕地种植满意。在农户类型中,促进因子:家庭人均收入、收入来源增加、耕地增值、空气改善、生活环境改善、生活压力减轻;抑制因子同样为耕地种植满意。在空间位置类型中,促进征用态度满意的因子包括:生活环境改善、家庭人均收入、收入来源增加、耕地增值、空气改善、生活压力减轻;抑制因子为耕地种植满意。在征用程度类型中,促进因子有家庭人均收入、生活环境改善、生活压力减轻、收入来源增加、空气改善、耕地增值;抑制因子包括耕地种植满意、人均耕地征用补偿。

图5 农户耕地征用态度逻辑斯蒂回归模型的比数比 Fig. 5 Odds ratio of Logistic of farmers' attitude

5 结论与讨论

随着城市化和工业化发展,耕地大量非农转换,尤其在城市周边,受比较利益影响,城市扩张迅速。然而,对耕地功能、农民需求、农村发展等问题重视不足,一系列经济、社会和环境问题出现。单一的经济补偿方式已远远不能满足耕地非农转换中出现的新问题。通过实地入户调查,系统剖析农户的耕地非农转换价值及其差异性,深入了解农户多样化需求,提高耕地功能的认识,对丰富和完善土地利用政策具有重要的意义。

农户的耕地非农转换价值呈现多元化特征。耕地非农化用后,农户才能真实感受和判别耕地非农转化价值,普遍认为生活费用增加、生活和养老保障降低、收入来源和就业机会少,并受区位条件、耕地征用程度和土地开发方向等因素影响而多样化。城区化农户已逐渐适应城市生活,近郊农户在耕地非农转换中感受到经济和社会压力最大,而远郊农户的经济和生活保障压力相对较小,希望能通过打工增加收入;对于耕地和宅基地被征用农户而言,失去家庭农产品的生产能力,同时受城市发展影响,生活方式被改变,农户反而因失去了农业种植机会,面临家庭低收入减少、工作不稳定、生活费用增加的困境;随着土地开发,农户感到耕地种植效益的提高和土地增值。

影响城市周边农户征用态度和生活满意度的因素较为复杂多样。家庭人均收入、收入来源、环境质量因素促进了农户生活满意的增加,而家庭人数、耕地种植满意度、人均耕地补偿数成为抑制因素。生活环境改善、收入来源增加、家庭人均收入促进农户征用积极性,成为征用态度的其促进因子;耕地种植满意度为抑制因子。

经济来源增加成为耕地非农转化农户生活满意度和征用态度模型中最为主要的影响因素,在13种情境得到普遍反映。在实际入户调查中,经济来源增加解释为农户因失去部分和全部农业生产资料后,是否因劳动力解放有更多机会参加非农工作,使得家庭劳动人员的就业多元化,经济来源增加,属于农户非农转换社会价值的内容。从结果看出,影响农户非农转换后生活满意度和征用态度最重要因素并非耕地补偿所获得的经济价值,而是耕地的社会价值。

耕地非农化对农户造成的困境在于失去土地的同时,又失去生活保障和工作机会。因此,如何在土地被征用后,使农民能拥有城市居民一样的保障体系,既有稳定的收入来源,又能享有城市居民享受城市福利和待遇,这是从根本上解决城市居民身份外衣下失地农民的关键。地方政府应因地制宜积极为农户创造长远生计的机会,一方面集约利用土地,在保证城市发展的土地需求基础上,发展生态、观光等多元化、多功能的农业经济,提高失地农民的就业机会;另一方面,积极进行土地制度创新,增加农户参与土地增值收益分配的途径。

The authors have declared that no competing interests exist.

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Swat is part of the high mountain Hindu-Kush Himalayan region of Pakistan, with diverse biophysical and socio-economic characteristics. The region is endowed with many fragile and fragmented ecosystems, and land use and land cover changes have accelerated destructive processes with irreversible effects on ecosystems. The paper aims to (I) find proximate and underlying causes of land use and land cover changes; (2) analyse the drivers of change; and (3) reflect on the role of governance and policy.We used land use maps for the years 1968 and 2007 to highlight the extent and type of land use changes, and household surveys and expert interviews were conducted to collect quantitative and qualitative data for detecting and analysing the drivers of change.Results of household surveys and expert interviews show that technological and environmental factors, accessibility and proximity to local markets, immense use of firewood, conflicting property rights and other institutional weaknesses, and over-grazing of alpine pastures were the main driving forces for agriculture expansion and deforestation.Given the present governance structure of forest management in Pakistan a multi-sectoral and multi-scale framework is required to conserve the Swat's natural landscape and associated ecosystem services. A carefully crafted reform programme is required to clarify and assign unambiguous property rights, provisions for communal management and market-based incentives, depending on the social, economic, and ecological characteristics of the different zones under consideration. Only with such policies in place can the current rapid rate of deforestation be avoided and sustainable natural resources use be ensured. (C) 2013 Elsevier Ltd. All rights reserved.
DOI:10.1016/j.landusepol.2013.02.008      [本文引用:1]
[20] 蔡运龙, 霍雅勤. 中国耕地价值重建方法与案例研究. 地理学报, 2006, 61(10): 1084-1092.
耕地不断流失的根本原因在于耕地农业利用的比较收益低下,所以建立耕地保护机制的主要途径在于:一方面提高耕地利用的比较收益,另一方面通过提高耕地征用的价值补偿来抑制乱占耕地行为.这两条途径归结于重建耕地资源的价值.本文提出耕地资源具有经济产出价值、生态服务价值和社会保障价值,并尝试用市场价格分别加以评估.耕地资源的经济产出价值为耕地年收益与贴现率之商,生态服务价值为耕地生态服务年价值与贴现率之商,社会保障价值是耕地提供的养老保险和就业保障价值之和.分别选择广东省潮安县、河南省淮阳县和甘肃省会宁县三个县作为案例的评价,以显示我国东、中、西部之间的区域差异.结果表明:耕地资源价值量在各地区之间呈现东高西低的差异;在耕地资源价值构成中,社会保障价值在三个案例区都占60%以上,但所占比重从东到西渐增,说明农民对耕地资源的依赖程度与社会经济发展水平呈反相关.耕地资源的经济产出价值在总价值中所占比重则从东到西递减,主要源于自然和经济生产率的差异.生态服务价值所占比重也表现出东低西高的特点,反映出生态系统从复杂到简单的变化使得农田生态系统对于西部地区生态环境显得更加重要.农业用地为社会提供了大量外部效益,这可成为实行农业补贴的一大理由,也是计算补贴量的一种依据;更可作为提高征地补偿标准的依据.在我国现阶段,耕地是大多数农民赖以生存的主要资源,在农村社会保障体系不完善甚至不存在的情况下,耕地的社会保障功能不可忽视.
DOI:10.3321/j.issn:0375-5444.2006.10.008      [本文引用:1]
[Cai Yunlong, Huo Yaqin.Reevaluating cultivated land in China: Method and case studies. Acta Geographica Sinica, 2006, 61(10): 1084-1092.]
[21] Golledge R G, Timmermans H.Applications of behavioural research on spatial problems I: Cognition. Progress in Human Geography, 1990, 14(1): 57-100.
DOI:10.1177/030913259001400104      [本文引用:1]
[22] Harvey D.Conceptual and measurement problems in the cognitive-behavioral approach to location theory. In: Cox K R, Golledge R G. Behavioral Problems in Geography Revisited. London and New York: Routledge, 1981: 18-42.
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[23] 龙花楼, 李婷婷. 中国耕地和农村宅基地利用转型耦合分析. 地理学报, 2012, 67(2): 201-210.
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[Long Hualou, Li Tingting.Analysis of the coupling of farmland and rural housing land transition in China. Acta Geographica Sinica, 2012, 67(2): 201-210.]
[24] 刘玉, 冯健. 城乡结合部农业地域功能实现程度及变化趋势: 以北京为例. 地理研究, 2017, 36(4): 673-682.
城乡结合部农业因其所处的独特区位而具有非常显著与多元的地域功能.基于构建城乡结合部农业地域功能评价指标体系,以北京为例测算了城乡结合部农业地域功能的实现程度.结果表明:近十年来,城乡结合部农业地域功能实现程度整体上呈现波动变化趋势,经历了下降—反弹—下降的变化过程.具体分析,受宏观经济、社会、技术等因素影响较显著的农业劳动生产率、收入等指标上升明显,生态建设成效较突出;而农产品生产与供给、满足城镇居民休闲与娱乐消费需求和拉动就业等方面的功能较为薄弱且持续下降,城乡结合部农业融入现代城市产业体系,促进城乡经济交流等方面的功能与现实需求也不相符.
DOI:10.11821/dlyj201704006      [本文引用:1]
[Liu Yu, Feng Jian.Analysis on execution and change of regional function of agriculture in rural-urban fringe: A case study of Beijing. Geographical Research, 2017, 36(4): 673-682.]
[25] 安悦, 周国华, 贺艳华. 基于“三生”视角的乡村功能分区及调控: 以长株潭地区为例. 地理研究, 2018, 37(4): 695-703.
随着城镇化的快速推进,中国社会经济发展进入转型期,乡村功能发展的多元化和空间分异特征日益明显。以长株潭地区23个县市区为研究地域单元,构建乡村功能评价指标体系及评价模型,揭示长株潭地区"生产—生活—生态"功能分异特征并进行功能分区与调控路径研究。结果表明:(1)长株潭地区乡村"三生"功能空间分异特征明显,耕地资源丰富的醴陵市、浏阳市等地区生产功能较强,基础设施较为完善的荷塘区、岳塘区等地区生活功能较强,生态环境较好的茶陵县等地区生态功能较强。(2)基于评价结果将研究区共划分为东部平原生产区、中部丘陵生活区、南部山地生态区、中部丘陵生态生活区和北部丘陵生态生产区5种类型功能区,其中东部平原生产区、中部丘陵生活区、南部山地生态区为长株潭地区的三生功能优势发展区,基于"优化主导优势功能、提升中等功能、改善弱势功能"的原则,提出各功能分区的调控路径与发展策略,从而为长株潭地区乡村功能转型发展与主导功能的识别及确定提供理论依据。
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[An Yue, Zhou Guohua, He Yanhua.Research on the functional zoning and regulation of rural areas based on the production-life-ecological function perspective: A case study of Changsha-Zhuzhou-Xiangtan area. Geographical Research, 2018, 37(4): 695-703.]
[26] 陈琼, 周强, 梁生甫, . 西宁市主城区城市土地利用格局变化分析. 经济地理, 2010, 30(2): 244-248.
西宁市是西部大开发战略实施以来在西部地区城市化水平提高较陕的城市之一。西宁市主城区城市土地利用变化的格局显示出西宁市城市发展的基本阶段。文章利用1996-2008年西宁市主城区城市土地利用数据,对西宁市土地利用格局变化进行了分析,结果表明:西宁市主城区城市土地利用格局在1996-2003年发生较大转变,土地利用格局由耕地主导型转变为多元化城市土地利用格局,说明西部大开发、青藏铁路等国家重大战略措施对西宁城市发展具有十分重要的影响,西宁市高原区域现代化中心城市的土地利用格局在2003年前后才基本形成,表现出青藏高原落后地区中等城市城市化过程的滞后性;2004-2008年各类土地利用变化相对平稳,但耕地、林草地、未利用土地的面积减少和空间变化揭示出西宁市等典型河谷型城市的地形和河流对城市建设和发展控制性作用明显,城市土地利用紧张。
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[Chen Qiong, Zhou Qiang, Liang shengfu, et al. An analysis of land use pattern change of Xining city based on GIS. Economic Geography, 2010, 30(2): 244-248.]
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