1990~2015年吉林省西部耕地变化与“旱改水”时空特征研究

以Landsat遥感影像为数据源,利用面向对象和决策树方法获得多期土地覆被数据;以此为基础,分析了1990~2015年吉林省西部耕地变化与旱田水田转化特征及驱动因素。结果表明：1990~2015年期间,吉林省西部耕地面积增加了2159.33 km²,增速逐渐变缓。旱田面积在1990~2000和2000~2010年期间有小幅增加,但在2010~2015年期间呈减少趋势。水田面积持续扩张,25年间增加了1139.39 km²（51.7%）,旱田净转化为水田的面积不断增加,1990~2000年为69.13 km²,2000~2010年为156.19 km²,2010~2015年为288.27 km²。人口和经济的增长是导致耕地面积迅速增长的主要原因,影响水田面积扩张和旱田向水田转化的驱动因素有：科技进步、水利设施建设、政策倾向和利益驱动。最后提出了吉林省西部地区耕地保护的建议,为区域农业生产和生态建设提供科学借鉴。     

1990~2015年吉林省西部耕地变化与“旱改水”时空特征研究

以Landsat遥感影像为数据源，利用面向对象和决策树方法获得多期土地覆被数据；以此为基础，分析了1990~2015年吉林省西部耕地变化与旱田水田转化特征及驱动因素。结果表明：1990~2015年期间，吉林省西部耕地面积增加了2159.33 km²，增速逐渐变缓。旱田面积在1990~2000和2000~2010年期间有小幅增加，但在2010~2015年期间呈减少趋势。水田面积持续扩张，25年间增加了1139.39 km²（51.7%），旱田净转化为水田的面积不断增加，1990~2000年为69.13 km²，2000~2010年为156.19 km²，2010~2015年为288.27 km²。人口和经济的增长是导致耕地面积迅速增长的主要原因，影响水田面积扩张和旱田向水田转化的驱动因素有：科技进步、水利设施建设、政策倾向和利益驱动。最后提出了吉林省西部地区耕地保护的建议，为区域农业生产和生态建设提供科学借鉴。     

基于多源时空信息的西宁和拉萨近70年来城市扩展过程重现及地表覆盖变化分析

西宁和拉萨城市作为青藏高原人类活动的热点地区,其发展历程对青藏高原社会经济发展具有重要影响。研究基于遥感影像、城市规划图和历史地图等资料重建了西宁和拉萨城市1949基准年、1978基准年、1990年、2000年、2010年和2018年城市扩展及2000年以来城市不透水层和绿地空间组分数据,分析了1949基准年以来西宁和拉萨主城区城市扩展的时空特征,揭示了社会经济因素和政策因素对城市土地利用/覆盖变化的影响。研究结果表明：(1)新中国成立以来,西宁和拉萨主城区持续扩展,均呈现非线性的增长态势,城市土地面积分别从1949基准年的1.98 km²和1.10 km²增长到2018年的75.65 km²和76.04 km²;西宁主城区城市扩展呈现十字状的扩展态势,拉萨呈现出圈层外延式的扩展模式;(2)自2000年来,西宁和拉萨城市绿化水平显著提升。2000～2018年,西宁和拉萨城市不透水层面积分别从36.91 km²和21.56 km²增加到55.34 km     

基于GeoSOS-FLUS模型的乌鲁木齐主城区扩张情景模拟分析

乌鲁木齐市作为新疆首府、“一带一路”中的中亚区域经济中心,其土地资源的合理利用、城市形态的健康发展则显得尤为重要。本研究首先基于乌鲁木齐主城区1990～2018年遥感影像解译出的土地利用分类对其土地利用时空演变情况加以分析,1990～2018年乌鲁木齐主城区急剧扩张,2010年以来交通网络铺设完善,主城区快速扩张,周遭耕地、林地、草地等萎缩95.12 km²、6.49 km²、52.37 km²,重心呈现出向东与向北扩张趋势,主城区农用与绿化面积萎缩,无法兼顾经济与生态效益协调可持续发展。接着,遴选自然与社会经济等影响主城区扩张的驱动因素,结合乌鲁木齐主城区扩张历史特点设计第一产业优先、第二三产业优先、生态优先情景,利用Geo SOS-FLUS模型对不同情景下的主城区扩张情景进行模拟预测,研究发现第二三产业优先情景下建设用地明显增加1 142.94 km²;生态优先情景下生态效益高的林地、草地、水域面积显著增加281.59、651.38、7.29 km²;第一产业优先情景下,建...     

中国超大城市建设用地遥感监测与时空格局

针对超大城市的快速发展对生态环境、资源分配及人类生活等方面带来的问题,监测城市发展模式成为迫切需求,鉴于建设用地可以作为城市范围的直观指示器,监测了中国7座超大城市建设用地的时空变化格局,并分析了其扩张情况及驱动机制。研究基于长时间序列的Landsat TM/OLI数据,使用支持向量机方法提取了各城市1990—2015年的建设用地分布,并分析了景观格局变化和建设用地扩张的内外在驱动因素。研究结果表明:各城市25年间建设用地均存在不同程度、不同模式的扩张,普遍表现为从城市中心向四周、从沿海向内陆扩张;各城市建设用地逐渐趋于集中、分离度降低,在城市景观中的主导程度加大;城市人口增长、经济转型升级是促进城市扩张的主要驱动力。研究结果有助于认知中国超大城市的空间扩张模式,并为其他城市的生态环境治理及区域发展规划提供科学的理论依据。     

基于MODIS的黄土高原土地荒漠化动态监测

以2001年和2009年8月MODIS卫星影像为数据源,基于归一化植被指数和像元二分原理,通过建立科学的荒漠化土地分类系统,对黄土高原地区近8 a的荒漠化土地进行了动态变化监测,分析了2个时期荒漠化土地的空间分布特征和面积变化情况。结果表明:黄土高原荒漠化土地面积整体呈明显的减少态势,但类型转化结构表明荒漠化土地强度却处于不断发展阶段。8 a间,极重度荒漠化土地面积增加了16.53 km²,增长率为28.36%,重度和中度荒漠化土地面积均有不同程度减少,分别减少了1.2×10⁴ km²和7.0×10⁴ km²,变化率分别为32.97%和29.19%;分别有9.0×10^4 km²和1.2×10⁴ k²的轻度和潜在荒漠化土地转化为其他类型荒漠化土地,并分别增加了9.3×10³ km²和7.3×10⁴ km²,增长率分别为4.2%和57.3%。发展区面积为1.9×10⁵ km²,稳定区面积为4.0×10⁵ km²,逆转区面积为2.8×10⁴ km²,发展区面积比逆转区面积大1.6×10⁵ km²,表明黄土高原环境质量不断下降,荒漠化强度不断扩张的趋势。     

基于线性光谱混合分析的乌鲁木齐不透水层提取及其时空变化分析

利用Landsat TM、OLI多光谱卫星遥感数据,采用VIS（植被－不透水层－土壤）模型和线性光谱混合分析法对丝绸之路经济带核心区乌鲁木齐建城区及其周边进行丰度估算,并针对红色彩钢板屋顶在不透水层丰度图像上低亮度特点,进行改进处理,提高了不透水层丰度估算精度。研究结果表明：1994~2018年的24年间乌鲁木齐市不透水层呈现出显著扩展的特点,其面积从140.41 km²扩大到462.62 km²;扩展速率在1994~2005年间缓慢上升,2005年之后迅速上升;扩展强度先上升,2010~2015年达到最大,之后出现下降;同时,城市不透水层的空间扩展具有明显差异,向西和东北方向扩展最为显著。综合分析指出：乌鲁木齐城市不透水层的空间扩展受到周边山体地形和煤矿开采等因素的限制,而“乌昌一体化”政策是城市扩展的主要助力因素。     

1985～2020年上海市不透水面时空特征演化分析

不透水地表的分布与变化是城市发展过程的直观标志和重要指示因子,在城市生态功能、城市规划和可持续发展研究等方面发挥着重要作用。利用中国科学院空天信息创新研究院研发的1985～2020年长时序30m不透水面动态数据集(GISD30),结合GIS空间统计方法,研究分析了过去35 a上海市不透水面时空特征演化。结果表明：(1)35 a来,上海市不透水面面积从878.07 km²增长至2 849.90 km²,面积扩张到原来的3.25倍,随着1990年浦东新区的开发开放,上海城市化进程明显加快,1990～2010年上海市不透水面扩张最为显著,2010年以后不透水面扩张速度和扩张强度开始显著下降。(2)从区位分异特征来看,不透水面迅速扩张的行政区主要位于城市郊区,其中,浦东新区在各个研究时段的扩张速度均大于其他区划。(3)基于紧凑度和分形维数发现,中心城区不透水面空间分布结构趋于疏散,上海市整体不透水面边界复杂程度降低,城市空间形态更加规则。(4)“南北两翼”的上海城市扩张特点较为明显,南部郊区的高强度扩张带动了不透水面空间重心的持续南移,发展至2010...     

通过不透水面聚集密度法提取城市建成区

针对已有基于不透水面提取城市建成区的方法无法保证建成区连续性的问题,提出了一种基于对象不透水面聚集密度的城市建成区提取方法。该方法计算了不透水面聚集密度并进行分级,提取聚集程度高的区域为输入对象,并将被建成区完全包围的绿地水体也包含在内;利用长时序遥感影像建成区提取结果,使用城市空间形态扩展指标对济南市1997—2017年城市时空演化特征进行分析。结果表明,该方法提取精度达到93.5%,能准确刻画出城市形态,保持建成区的完整性;1997—2017年间,济南市建成区面积不断扩张,扩张速度与强度分别达到10.48km~2/a、0.32%,呈现带状轴向扩展模式;1997—2013年,建成区扩展的不规则程度在逐年减少,2013年以后建成区形状变得复杂。     

21世纪以来西安城乡梯度土地覆盖变化及对城市热岛影响时空特征

城市快速扩张导致城乡梯度土地覆盖发生显著的变化,引发不透水地表的增加,植被覆盖的减少,从而加剧了城市热岛强度。研究城乡梯度土地覆盖变化引起的城市热岛效应,并揭示城市热岛的时空特征及强度的变化,对城市规划建设、人居环境改善及提升城市生态系统服务功能具有重要的意义。基于Landsat系列4期影像,利用单窗算法反演西安市地表温度,计算热场变异指数得到热力场强度图并对其进行等级划分,结合土地利用/覆盖类型数据分析城乡梯度土地覆盖变化对城市热岛强度的影响。结果表明：①2000年西安市极强热岛效应区占研究区面积的10.58%,逐渐增加到2011年极强热岛效应区域的面积占比达到16.14%,而后到2015年降低为9.00%,整体上西安市城市热岛效应呈现出了先增长后降低的趋势;②2000年到2015年城乡建设用地面积增加了412.76 km2,极强热岛强度的范围随城市建成区的扩张逐年向外扩展;③无热岛效应区约70%位于耕地和林地,水域在无热岛效应中的占比也在逐年增多,从31%增加到了47%。不透水地表面积占比与地表温度有显著相关性,城乡梯度植被和水体面积的增加可以有效地缓解城市热岛强度。     

Remote Sensing Monitoring and Comparison of Urban Land Cover Changes in Typical Cities in China-Kazakhstan Arid Region based on Cloud Platform

Urban land cover composition is the key factor affecting the living environment and urban ecosystem service. Based on the Google Earth Engine platform, Landsat 5/8 remote sensing image data were used to adopt the improved "Vegetation-Impervious Surface-Soil" model and linear spectral mixed decomposition method. The variation characteristics of land cover in Nur-Sudan, Almaty, Urumqi cities from 1990 to 2015 were compared and analyzed. The results show that the urban built-up area of Urumqi city expanded the largest area of the three cities from1990 to 2015, with an expansion of 349.81 km², followed by Nur-Sultan, with a city expansion area of 158.16 km². As the capital of Kazakhstan was relocated from Almaty to Nur-Sultan, the city of Almaty expanded the slowest during the entire period, with a total expansion of 126.23 km². In the urban built-up area, the urban surface in Urumqi increased by 7.10% from 1990 to 2015, and the Nur-Sultan and Almaty decreased by 14.9% and 4.49%，respectively. The green space component of the built-up area, Nur-Sultan increased by 6.68% from 1990 to 2015, while Urumqi and Almaty decreased by 6.65% and 2.75%，respectively. The different surface cover patterns of cities are different for different reasons. Urumqi is mainly supported by national policies, and Almaty is known for its historical background and urban planning, while the rapid development of Nur-Sudan was affected by the relocation of Kazakhstan.     

Analyzing Temporal-spatial Change of Urumqi Impervious Surface using Linear Spectral Mixture Analysis

The method of linear spectral mixture analysis combined with V-I-S model(Vegetation-Imperious surface-Soil) is used to estimate the impervious surface abundance of Urumqi city, which is in the core area of the Silk Road Economic Belt, using Landsat OLI and TM multi-spectral data. Because the red color steel shed has low brightness on the impervious surface brightness image, an improvement was proposed, and then verify the accuracy through the interpretation of high-resolution satellite imagery. The results show that: the impervious surface area in Urumqi displayed a significant expansion from 140.41 km² to 462.62 km² during past 24 years (1994 to 2018). It expanded slowly during 1994 to 2005, and increased rapidly since 2005. The expansion intensity increased during 1994~2015 and decreased after 2015; and the spatial expansion of urban impervious surface is significantly different, with the largest expansion area in the west and northeast direction. The comprehensive analyses suggested that the expansion of the impervious surface of Urumqi city is limited by the surrounding mountain topography and coal mining, and the “Urumqi-Changji integration” policy is the major driving factor for urban expansion in the past 24 years.     

Remote Sensing Monitoring and Spatiotemporal Pattern of Land Use/Cover Change in Built-up Area of Tianjin in the Past 70 Years

Urban land use/cover changes have an important impact on urban ecosystem services functions and the environmental quality of human settlements. This study mapped urban expansion process using the historical data, remote sensing images and urban planning maps, and acquired the urban impervious surface and green space fraction based on big data platform. We analyzed the process of Tianjin urban expansion rate, intensity and urban land cover change since 1949, and revealed the driving factors in the process of urban expansion with social economic and policy factors. The results showed that the built-up area increased from 49.15 km² in 1949 to 663.39 km² in 2015. The expansion has undergone four stages of "acceleration – deceleration – acceleration - deceleration"; the urban expansion mode presents the filled with built-up area and along with the neighboring transportation trunk lines. The proportion of green space in the built-up area is increasing, indicating that the urban ecological greening in the main urban area of Tianjin has been improved.     

Spatiotemporal Pattern of Urban-rural Aradient Land Cover Changes and Their Impact on Urban Heat Island in Xi′an City Since the 21st Century

Rapid urban expansion had a significant impact in land use/cover change along urban-rural gradient, and the increase of impervious construction land and the reduction of vegetation cover had induced and aggravated the urban heat island effect. Studying the impact of urban-rural gradient land cover change on urban heat island effect was significant for urban planning and construction, improving the comfort of human settlements and enhancing the function of urban ecological services. The surface temperature of Xi'an city was retrieved by mono-window algorithm based on Landsat images, and the thermal field intensity map was obtained by calculating the thermal field variation index, and the gradient land cover changes in urban and rural areas were analyzed with land use data. The results showed that: ①The urban heat island effect in Xi'an showed a trend of first increasing and then decreasing from 2000 to 2015. In 2000, the extremely strong heat island effect area accounted for 10.58% of the research area, and gradually increased to 16.14% in 2011, and then decreased to 9.00% in 2015. ②From 2000 to 2015, the area of construction land increased 412.76 km² and the intensity of extremely strong heat island expanded year by year with the expansion of urban built-up areas. ③About 70% of the non-heat island effect areas were located on farmland and forest land, and the proportion of water area in the non-heat island effect was increasing year by year from 31% to 47%, which showed that the increase of vegetation and water area could effectively alleviate the urban heat island effect.     

Spatio-temporal Characteristics of Urban Land Cover Structures in Prefecture-level Cities of Inner Mongolia Autonomous Region based on Remote Sensing Imagery

The urban land cover structures play an important role in providing urban ecological service and altering the quality of human settlements environment.In this study,2000~2015 Landsat TM series satellite data along with fine resolution remote sensing images were used to capture information of each 5-year land cover structures in 12 prefecture-level cities of Inner Mongolia Autonomous Region.Subsequently,there land cover information was used to monitor and analyze the spatiotemporal dynamics of urban expansion,and differences of land cover structures and expansion types.The results showed that：in 2000~2015,the overall changes of land cover structures in 12 prefecture level cities of Inner Mongolia Autonomous Region were rapid.Specifically,the urban area expanded by 278.93 km².By comparison,the proportion of urban area expansion in 2010~2015 was 1.61 times and 1.91 times than that of the first two periods (in 2000~2005 and in 2005~2010).Since 2010,the most dramatic changes has been observed.Particularly,obvious urban impervious surface expansion was found.Also urban vegetation showed obviously increased with varying degrees.At the past decade,urban expansion has undergone three stages.Specifically,the main process experienced from urban interior filling to urban interior filling and then to urban extension,of which Baotou and Hulunbeier belonging to the internal filling city.Population growth and socio-economic development are responsible for these differences.     

IBI and CA Model based Extraction of Urban Built\|up Areaand Its Application：A Case Study in Shanghai

At present,the automatic extraction of urban built\|up area is still a problem.Taking Shanghai city as an example,this research uses the binary image,which was derived from an IBI(index\|based built\|up index)image,as the geographical cellular automaton initial input data.This was then imported to the extended cellular automata model for further processing.After a series of processing such as thresholding,corrosion and connectivity test,the urban built\|up area was simulated and can be extracted.Based on this method,the urban built\|up area of Shanghai in five different years between 1987 and 2015 was extracted using multi\|temporal Landsat images of Shanghai.In addition,the urban growth intensity index,the concentric buffers analysis and radar chart analysis were calculated and used to analysis spatiotemporal pattern of Shanghai urban expansion in the 28 study years.The result shows that the built\|up area of Shanghai was expanded from 195 km² in 1987 to 1759 km² in 2015,which is eight times as large as that in 1987.In the period between 1987 and 2002,the urban built\|up area expanded mainly along the North\|South axis of the Huangpu River.However,after 2002 the expansion rate was increased more quickly,and the direction of the expansion was shifted to an east to west direction.Generally speaking,Shanghai has experienced a rapid urban expansion in the recent three decades.     

哈尔滨城乡梯度建设用地结构变化及不透水面遥感监测分析

在快速城镇化背景下,客观掌握城市扩张进程中的城乡建设用地及内部不透水面变化特征,有利于优化大都市城乡用地结构及空间融合发展。基于城乡建设用地及不透水面遥感监测数据集,应用空间分析模型,对哈尔滨2000~2015年城乡建设用地规模、结构及内部不透水面时空演变特征进行分析,探究城市扩张格局、区位差异、建设用地利用强度及城乡之间的差异。结果表明：①2000年以来城乡建设用地快速扩张了158.32 km²,年变化率和动态度均呈先增大后减小趋势;从城市核心区至远郊区方向其扩张规模依次增大,建设重点不断向城市周边推移,呈现出较明显的空间异质性;②城镇建设用地和独立工矿用地面积及占比逐年增加,扩张来源均以耕地为主;农村居民点占比降低了13.14%,城乡建设用地结构特征发生了较明显变化;③2000~2015年城乡建设用地内部不透水面面积和比例分别增加了145.32 km²和10.04%,城镇建设用地利用强度已达到较高水平,农村居民点用地利用强度快速提高,城市和农村之间的差距不断缩小;自城市核心区至远郊区方向不透水面比例不断降低,可利用潜力越大,不透水面面积增量、比例增量、比例增长率及扩张强度大体呈增加趋势,不透水面与城乡建设用地规模变化趋势相近,可在一定程度上揭示城市扩张轨迹。