黄河三角洲耕地变化及其驱动力的卫星遥感分析

Taking Kenli County in the Yellow River Delta, China, as the study area and using digital satellite remote sensing techniques, cultivated land use changes and their corresponding driving forces were explored in this study. An interactive interpretation and a manual modification procedure were carried out to acquire cultivated land information. An overlay method based on classification results and a visual change detection method which was supported by land use maps were employed to detect the cultivated land changes. Based on the changes that were revealed and a spatial analysis between cultivated land use and related natural and socio-economic factors, the driving forces for cultivated land use changes in the study area were determined. The results showed a decrease in cultivated land in Kenli County of 5321.8 ha from 1987 to 1998, i.e., an average annual decrement of 483.8 ha, which occurred mainly in the central paddy field region and the northeast dry land region. Adverse human activities, soil salinization and water deficiencies were the driving forces that caused these cultivated land use changes.     

岷江上游1974-1995年间景观变化

Landscape changes were traced over the 20 years from 1974 to 1995 in the upper Minjiang River basin, one of the most important forest regions in China, based on satellite image interpretation to provide basic data for local decision-making as well as sustainable landscape use and management. Results revealed that landscape from 1974 to 1995 changed at the regional scale as the area of forestland decreased, while cropland, shrubland, economic forest, grassland, and built-up land increased. Landscape changes mainly occurred in forestland, shrubland, grassland, economic forest, and built-up land. Moreover, the changes among forestland, shrubland, and grassland were the largest, influencing the whole characteristics of the changes in the basin. Analysis of the changes between 1974 and 1995 in the study area indicated that landscape heterogeneity and fragmentation increased, whereas landscape connectivity decreased. There were multiple reasons for landscape changes. A principal component analysis （PCA） was used to quantitatively study driving forces of landscape changes. The PCA results showed that economic and population factors were the principal driving forces of landscape changes from 1974 to 1995 in the upper Minjiang River basin, and that PCA was a suitable method for investigating driving forces of landscape changes.     

厦门市土地利用变化的时空格局及驱动力

Using Landsat TM data of 1988, 1998 and 2001, the dynamic process of the spatial-temporal characteristics of land use changes during 13 years from 1988 to 2001 in the special economic zone of Xiamen, China was analyzed to improve understanding and to find the driving forces of land use change so that sustainable land utilization could be practiced. During the 13 years cropland decreased remarkably by nearly 11 304.95 ha. The areas of rural-urban construction and water body increased by 10 152.24 ha and 848.94 ha, respectively. From 1988 to 2001, 52.5% of the lost cropland was converted into rural-urban industrial land. Rapid urbanization contributed to a great change in the rate of cropland land use during these years. Land-reclamation also contributed to a decrease in water body area as well as marine ecological and environmental destruction. In the study area 1） urbanization and industrialization, 2） infrastructure and agricultural intensification, 3） increased affluence of the farming community, and 4） policy factors have driven the land use changes. Possible sustainable land use measures included construction of a land management system, land planning, development of potential land resources, new technology applications, and marine ecological and environmental protection.     

中国坡耕地分布特征与退耕还林草政策影响分析

The Grain-for-Green Policy in China could not only improve China's ecological quality, but also influence grain supplies for a short term. Based on data from the detailed nationwide land use survey in 1996 and the steep cultivated land survey update in 2000, a regression model for the driving forces affecting steep cultivated lands was developed, and cluster analysis was used to identify seven steep cultivated land types in order to analyze the grain availability impact of the project with land usage estimates for 2010 and 2030. The results suggested that consecutive days with minimum daily temperature over 10 ℃ and the dominant slope in a county constrained the spatial distribution of steep cultivated lands. In terms of socioeconomic factors, steep cultivated land was a complex interaction of population size, gross domestic production level, and the richness and quality of cultivated lands having slopes less than 15°. The trends for steep cultivated land in 2010 and 2030 were forecast using a driving forces model and China's grain security criteria and showed that the Grain-for-Green Policy at the national level would not cause a grain shortage or threaten food security criteria. However, if steep sloped lands were to be retired from production, some regions would need grain supplements as early as 2010. Also, assuming that only 60% of the cultivated land at the national level was needed, population and economic development pressures in 2030 would require some steep cultivated lands to be used for grain production.     

多源卫星遥感影像进行土地利用变化监测

Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in developed urban area in the coastal regions; therefore, there is an urgent need to effectively detect and monitor the land use changes and provide accurate and timely information for planning and management. In this study a method combining principal component analysis (PCA) of multisensor satellite images from SPOT (systeme pour l'observation de la terre or earth observation satellite)-5 multispectral (XS) and Landsat-7 enhanced thematic mapper (ETM) panchromatic (PAN) data, and supervised classification was used to detect and analyze the dynamics of land use changes in the city proper of Hangzhou. The overall accuracy of the land use change detection was 90.67% and Kappa index was 0.89. The results indicated that there was a considerable land use change (10.03% of the total area) in the study area from 2001 to 2003, with three major types of land use conversions: from cropland into built-up land, construction site, and water area (fish pond). Changes from orchard land into built-up land were also detected. The method described in this study is feasible and useful for detecting rapid land use change in the urban area.     

基于多时相TM/ETM+数据的浙江省沿海地区土地利用变化研究

Landsat Thematic Mapper （TM） and Enhanced Thematic Mapper Plus （ETM＋） images in 1985, 1986, 1993, 1994 and 2001 were used to quantify the land use and land cover changes （LUCC） in the Zhejiang coastal region with a stratified unsupervised classification technique in conjunction with visual interpretation and to attempt an identification of the socioeconomic driving forces. In level I an overall accurate classification was achieved using a modified Anderson＇s Ⅰ/Ⅱ/Ⅲ-level classification scheme. The overall accuracy of the land use classification at Anderson level Ⅰ were 89.7% （1985）, 91.6% （1993）, and 90.4% （2001）. The most rapid land use change was a dramatic increase in urban or built-up areas, which quadrupled from 1985 to 2001. Over 90% of this newly expanded built-up area was originally paddy fields or other croplands. In different parts of the Zhejiang coastal region, urban land expansion was spatially uneven. Temporally, land use development did not stabilized, and the two study periods of time （1985-1993 and 1993-2001） had different transition styles. Socioeconomic factors, such as gross domestic product, total population, and financial expenditure, were all highly correlated with the expansion of urban or built-up areas. Based on the degree of urban sprawl and socioeconomic factors, cities and towns were further divided into six subgroups, which may help decision makers improve land use for the region.     

应用数字遥感图像对泰国Chanthaburi省土地利用动态的监测

A comprehensive method of image classification was developed for monitoring land use dynamics in Chanthaburi Province of Tailand.RS(Remote Sensing),GIS(Geographical Information System),GPS (Global Positioning System) and ancillary data were combined bythe method which adopts the main idea of classifying images by stekps from decision tree method and the hybridized supervised and unsupervised classification.An integration of automatic image interpretation,ancillary materials and expert knowledge was realized.Two subscenes of Landsat 5 Thematic Mapper(TM) images of bands 3,4 and 5 obtained on December 15,1992,and January 17,1999,were used for image gprocessing and spatial data analysis in the study.the overall accuracy of the results of classification reached 90%,which was verified by field check.Results showed that shrimp farm land,urban and traffic land,barren land,bush and agricultural developing area increased in area,mangrove,paddy field,swamp and marsh land,orchard and plantation,and tropical grass land decreased,and the forest land kept almost stable.Ecological analysis on the land use changes showed that more attentions should be paid on the effect of land development on ecological environment in the future land planning and management.     

黄河流域生态环境脆弱性评价

Using remote sensing （RS） data and geographical information system （GIS）, eco-environmental vulnerability and its changes were analyzed for the Yellow River Basin, China. The objective of this study was to improve our understanding of eco-environmental changes so that a strategy of sustainable land use could be established. An environmental numerical model was developed using spatial principal component analysis （SPCA） model. The model contains twelve factors that include variables of land use, soil erosion, topography, climate, and vegetation. Using this model, synthetic ecoenvironmental vulnerability index （SEVI） was computed for 1990 and 2000 for the Yellow River Basin. The SEVI was classified into six levels, potential, slight, light, medium, heavy, and very heavy, following the natural breaks classification. The eco-environmental vulnerability distribution and its changes over the ten years from 1990 to 2000 were analyzed and the driving factors of eco-environmental changes were investigated. The results show that the eco-environmental vulnerability in the study area was at medium level, and the eco-environmental quality had been gradually improved on the whole. However, the eco-environmental quality had become worse over the ten years in some regions. In the study area, population growth, vegetation degradation, and governmental policies for eco-environmental protection were found to be the major factors that caused the eco-environmental changes over the ten years.     

应用遥感技术对中国亚热带地区坡地利用及土壤侵蚀的研究

This paper introduces briefly two remote sensing case studies on land use in the subtropic region of China. One is on slope land use in the Yangtze River Three Gorges area. This is a large area of 60497 km². First of all, geometric correction and supervised classification were conducted for ten scenes of Landsat-5 TM or MSS images. The resolution of the processed images is 50 m × 50 m on ground. By the classification the land use/cover categories in this area were discriminated. Then the croplands including rice fields and upland fields were extracted from the land use/cover maps. Simultaneously the slope grade maps were prepared based on the topographic maps. Overlaying the slope grade maps and the cropland maps, the area and percentage of the croplands in different slope grades were determined. This case study indicated that 71.5% of the uplands was situated on the slope above 150 and 25% on the slope above 250 in this area. It is dangerous, and urgent cultivation or engineering measures should be taken. Another case study is on soil erosion in Linshan County of Guangxi Province. Airphoto interpretation and supervised classification of a Landsat TM image were carried out for discriminating land cover/use categories in an area of 3 557.8 km². And the soil erosion intensity grades were determined according to the land cover/use maps and slope maps. It wad discovered that the land suffering soil erosion accounted for 2404.0 km², 67.6% of the total area of the county. Necessary measures to control soil erosion should be taken also.     

一种新的辨别土地利用/覆被的遥感图像融合方法

In China, accelerating industrialization and urbanization following high-speed economic development and population increases have greatly impacted land use/cover changes, making it imperative to obtain accurate and up to date information on changes so as to evaluate their environmental effects. The major purpose of this study was to develop a new method to fuse lower spatial resolution multispectral satellite images with higher spatial resolution panchromatic ones to assist in land use/cover mapping. An algorithm of a new fusion method known as edge enhancement intensity modulation (EEIM) was proposed to merge two optical image data sets of different spectral ranges. The results showed that the EEIM image was quite similar in color to lower resolution multispectral images, and the fused product was better able to preserve spectral information. Thus, compared to conventional approaches, the spectral distortion of the fused images was markedly reduced. Therefore, the EEIM fusion method could be utilized to fuse remote sensing data from the same or different sensors, including TM images and SPOT5 panchromatic images, providing high quality land use/cover images.     

基于TM数字图像的耕地变化检测及其驱动力分析

以黄河三角洲垦利县为研究靶区，采用多时相陆地卫星TM 数据，对耕地的动态变化及其驱动力进行了系统研究。采用人机交互式的目视解译和人工修正方法提取耕地信息，以分类后比较法和历史土地利用专题图支持下的目视检测方法进行耕地变化信息的获取。在此基础上，建立了基于TM数字图像的耕地变化及其自然和人为驱动力指标，通过耕地变化及其相关因素分析、空间一致性分析等，确定了耕地变化的驱动因子。结果表明：从1987年至1998年，垦利县耕地面积减少了5 321.8 hm²，平均每年减少483.8 hm²，耕地的减少主要分布于中部稻田区和东北部旱区。不良的人为活动、土壤盐渍化和水源的匮乏是该区耕地动态变化的驱动因子。     

岷江上游汶川县耕地变化及驱动力研究

该文研究了汶川县的耕地变化情况，并运用定性与定量结合的方法分析了导致耕地变化的原因。研究结果表明：汶川县在过去的几十年里耕地的数量发生了变化，呈现一种在波动中缓慢变化的趋势；其变化除了受政策和自然因素影响外，人口和经济增长对耕地变化也起到了进一步的促进作用。在此基础上，对该区耕地资源的利用提出了建议，以促进地方土地资源的可持续利用。     

松嫩高平原黑土区耕地资源安全及其驱动力分析——以黑龙江省巴彦县为例

耕地资源安全是保护耕地和保障国家粮食安全的基础。选取我国重要的商品粮食基地——松嫩高平原黑土区巴彦县为研究区,从自然、经济、社会和生态共4个方面构建耕地资源安全评价指标体系,运用最优组合赋权法确定指标权重,利用综合指数法定量评价巴彦县2000—2009年间耕地资源安全状态,并采用SPSS软件对耕地资源安全驱动力进行主成分分析,引入Cubic曲线,通过非线性回归分析建立耕地资源安全变化模型,对研究区耕地资源安全值及其驱动力进行结果验证。研究结果表明,2000—2009年,巴彦县耕地资源安全状态存在一定差异。2000年研究区耕地资源安全处于较不安全等级;2001—2003年处于极不安全等级;2004—2005年处于较不安全等级;2006年处于稍不安全等级;2007—2009年处于相对安全等级。研究期间耕地资源安全级别转换呈先负向后正向发展。科技经济社会发展动力、自然干扰力和生态质量影响力是促使巴彦县耕地资源安全变化的驱动力。巴彦县耕地资源安全与3类驱动力表现出非常显著的Cubic曲线关系,说明构建的耕地资源安全变化模型符合研究区实际。     

黄河口耕地遥感动态监测及其生态环境安全分析

采用多时相陆地卫星TM数据，以分类后比较法和历史土地利用专题图支持下的目视检测方法进行黄河口耕地变化动态监测。建立了基于TM数字图像的耕地变化及其相关自然和人为因素变化的指标，对与耕地变化相关的自然环境要素变化及人为影响进行了分析。结果表明：从1987∽1998年，垦利县耕地增减变化较大，面积减少了5321．8hm^2，平均每年减少483．8hm^2。耕地的变化反映出该区土壤盐渍化的加重和水源的匮乏，以及人为不良活动的影响。在此基础上提出了该区生态环境安全的对策措施。     

东北地区县域耕地利用系统安全驱动力因子及其空间分异

[目的]确定耕地利用系统安全变化的驱动力空间差异,为保护耕地和保障粮食安全服务。[方法]以东北区典型区域巴彦县为研究区,运用"3S"技术,采用相关分析和Logistic回归模型,对影响耕地利用系统安全的驱动力因子进行识别和分析;采用单因子评价法和Kriging插值法分析驱动因子影响程度及其空间分布,揭示空间分异规律。[结果](1)地貌类型、土壤类型、土壤质地、速效磷、排涝能力和政策法规对系统安全具有促进作用,高程、比值植被指数、人口密度和水土流失对系统安全具有抑制作用。(2)各驱动力因子在空间上打破了原来的耕地利用分区,呈现出以地理空间为基础的空间分异特征。[结论](1)各驱动因子对研究区耕地利用系统安全均有不同程度的影响。(2)各驱动因子对耕地利用系统安全的影响程度在地域空间上有明显的分异规律。     

国家尺度耕地变化驱动力的定量分析方法

该文使用中国1987～1989年和2000年两期土地利用遥感调查数据,探索了国家尺度土地利用变化驱动力分析的定量研究方法。以全国耕地变化为例,首先通过GIS和遥感技术对全国耕地变化与自然、社会经济状况进行综合分区,然后利用人工神经网络对各类型区的耕地变化的主导因素进行了分析。研究发现,东部沿海地区及四川盆地自1987年到2000年发生的耕地流失严重,城市化导致的城镇人口增长进而导致城镇扩张、市场经济条件下区域经济之间的相互作用、第二、三产业的迅速发展是其主导原因。在变量选取中大样本的神经网络训练得到较好结果,表明神经网络在土地利用变化驱动力研究中具有强大能力,并说明了先分区后筛选变量的研究思路的合理性。该研究方法对其他类型的土地利用变化驱动力研究以及全球变化研究具有借鉴作用。     

黄河口生态脆弱区土地利用时空变化及驱动因素分析

黄河三角洲是典型的生态环境脆弱区,在人类活动及自然环境相互作用下土地利用变化剧烈,是研究土地利用变化的热点地区。该文以黄河口垦利县为研究区,选用1989年、1995年、2000年、2005年及2011年5个时相的遥感影像,获取各时相土地利用信息,利用土地利用变化相关模型,分析了研究区20余年来土地利用的时空变化特点,并对其驱动因素进行了探讨。结果表明:研究区土地利用变化的主要特征是旱地、林草地面积减少和建设用地、水域、盐荒地、滩涂面积的大幅增加。2000年之前总体土地利用变化程度高于后期,单一土地利用动态度,河流水面、水域及建设用地表现较明显。研究时段内旱地、盐荒地、水田、建设用地重心均向西南方向迁移,林草地、河流水面、滩涂重心则向东北方向迁移,水域重心转向西南,但整体地域分布特点变化不大。蒸降比大、偏砂质地土壤、地下水埋深浅且矿化度高、黄河断流等气候水文因素是该区土地利用覆盖变化的主导自然驱动,人类不合理的农业开发活动是主要人为驱动。该研究为黄河口生态脆弱区资源环境的利用保护和社会经济的可持续发展提供依据。     

浮梁县土地利用变化及驱动力分析

以江西省浮梁县作为研究区域,采用浮梁县1996-2005年的土地利用变更数据及社会经济统计数据,从土地利用数量变化、土地利用程度变化、土地利用效益变化3方面探讨了研究区域的土地利用变化特征,并运用主成分分析法对引起这些变化的驱动力进行了分析。研究结果表明:（1）耕地和建设用地是浮梁县土地利用数量变化的主要类型,土地利用程度和效益都有一定程度的提高,土地利用总体态势较好;（2）工业化、城市化水平的提高及人口的增长是引起土地利用变化的主要社会经济驱动力,但是城市化和工业化水平的提高是最为主要的驱动因素。     

黄三角濒海区土壤水盐时空分异特征及耦合关系分析

选择黄河三角洲代表区域垦利区和无棣县，将野外调查与室内分析得到的土壤表层水盐数据，按照季节、植被类型、与渤海距离进行归类，利用经典统计分析、耦合度模型、缓冲区分析、Origin三维关系分析等方法，分析研究区土壤表层（0—15 cm）水盐时空分异特征及其耦合关系。结果表明：研究区土壤水盐含量总体较高，含盐量以中度盐渍化为主，垦利土壤表层水盐含量整体高于无棣；不同季节土壤含水量排序为夏季>春季>秋季>冬季，土壤含盐量排序为春季>秋季>冬季>夏季，耦合度关系比较为春季>秋季>冬季>夏季；不同植被类型土壤含水量排序为荒草地>光板地>耕地>林地，土壤含盐量排序为光板地>荒草地>耕地>林地，耦合度关系比较为光板地>荒草地>耕地>林地；由近海到内陆，研究区土壤表层含水量、含盐量以及水盐耦合度呈现逐步递减的趋势，其中无棣变化趋势较为平缓，垦利土壤含盐量在距海40~50 km处上升，土壤含水量在距海30~40 km处明显上升，表层水盐耦合度也有所提高。研究结果为黄三角濒海区土壤资源的合理规划利用提供理论依据。