城市局部气候分区对地表温度的影响 ——以大连市区为例

以大连市区建筑数据、SPOT 5和Landsat 8遥感数据为基础，运用局部气候带分类、地表温度反演方法，研究大连市局部气候带分区类型和特征，进而分析不同局部气候带对城市地表温度的影响。研究结果表明：①大连市建筑类型高度主要为低层建筑、多层建筑和中高层建筑，建筑密度为中密度和较高密度，甘井子区分布大量森林绿地，中山区具有丰富的公园绿地；②地表温度整体偏高，空间上呈现东高西低的趋势，其中半数以上地区地表温度达到28℃~31℃，并且有超过1%的地区地表温度大于38℃，该区域出现极端高温；③同一建筑高度上，密度越大的建筑区域，地表温度越高；同一建筑密度，多层建筑高度覆盖区地表温度较高。森林绿地地表温度最低，公园绿地和社区绿地地表温度几乎一致，附属绿地地表温度最高。     

塔里木河流域2000-2014年地表覆盖动态变化监测

针对塔里木河流域脆弱的生态环境,该文采用地理信息系统、遥感技术手段提取2000年、2006年、2009年、2012年以及2014年塔里木河流域地表覆盖分类数据并对其变化特征进行分析.结果表明:2000-2014年塔里木河流域除水域、荒漠与裸露地表面积减少外,其余地表类型均呈增加趋势,其中变化量最大的为荒漠与裸露地表、冰川与积雪、耕地、草地,其变化量分别为-34 558.1 km2、14 351.15 km2、6 471.79 km2、6 383.94 km2.2000-2014年塔里木河流域荒漠与裸露地表面积减小,主要转变为了草地、林地与耕地;耕地面积增加主要来自于林地、草地、荒漠与裸露地表;冰川和积雪的面积增加主要增加来源为林地、草地和荒漠与裸露地表.     

一种极干旱区水热通量遥感模型反演

针对极干旱的土壤水热通量遥感估算研究少和缺乏模型验证分析的不足,该文选取新疆塔克拉码干沙漠东南缘米兰绿洲,借助2010年8月7日TM影像数据,结合地面观测数据和土地覆盖类型解译,利用SEBAL模型反演了研究区地表通量。结果表明:该方法在极干旱区的模拟精度较高,研究区地表能量平衡各分量具有明显的时空分布特征。地表通量参数的遥感反演估算对极干旱区的生态保护、灾害监测和地区水资源管理具有重要现实意义。     

2000—2020年亚马孙流域地表覆盖时空变化分析

针对亚马孙流域地表覆盖变化对当地生态系统以及全球气候变化具有重要意义这一问题，该文基于国家基础地理信息中心牵头研制的、经一致性处理的全球30 m地表覆盖产品(GlobeLand30)三期地表覆盖数据产品，采用景观格局指数和转移矩阵，分析了2000—2020年亚马孙流域地表覆盖的空间格局分布以及时空变化，并对其变化原因做出分析。结果表明：2000—2020年亚马孙流域林地和湿地面积逐渐减少，耕地、草地和人造地表的面积逐渐增加，水体先减少后增加。亚马孙流域2000—2010年和2010—2020年的地表覆盖类型转变方向基本保持一致；人造地表在地表覆盖类别中破碎现象最为显著，但其破碎化指数持续降低。亚马孙流域地表覆盖的变化主要受人类活动的影响，其中城市扩张和人口增加是林地减少的最主要因素。相关研究成果可为亚马孙流域未来的社会经济发展和生态系统保护提供重要支撑。     

近30年长江中下游平原典型区耕地覆盖变化

以长江中下游平原苏皖边界的10个县市为研究区,利用1984,1990,1995,2000,2005和2010年6期的TM/ETM+图像提取土地覆盖信息,从时间和空间2个方面研究耕地覆盖变化。结果表明:①从时间变化来看,研究区近30 a耕地总体呈减少趋势,经历了快速减少、缓慢减少和急剧减少3个过程,1984—1990年、1990—2000年及2000—2010年耕地分别减少了374.10 km2,66.09 km2及1 724.33 km2,主要表现为城镇和水体侵占耕地,但林地开垦使耕地增加;②从空间变化上看,沿江城市周围大面积耕地转变为建设用地,以1984年的南京市区、马鞍山市区和芜湖市区为主,且城镇化速度在加快;1990年以来沿石臼湖和固城湖周边地区的部分耕地转变成养殖塘,其西部地区转换较频繁;1984—2000年耕地沿山体和耕地交界处增加,2000年之后又因实施退耕还林和营造经济林而有所减少。     

2019年中国陆表定量遥感发展综述

为了更好地了解中国定量遥感的发展态势和加强同行之间的信息交流，根据中国学者2019年发表的SCI检索论文和部分中文论文，对陆表定量遥感的核心进展进行了总结，涉及数据预处理（云及其阴影识别，大气与地形校正）、陆表辐射传输建模、不同变量的反演方法、产品生产评价与精度验证，以及相关应用等内容。陆表变量产品较多，本文概要介绍了反射率、下行太阳辐射、反照率、地表温度、长波辐射、总净辐射、荧光遥感、植被生化参数、叶面积指数、光合有效辐射比、植被覆盖度、森林高度、森林生物量、植被生产力、土壤水分、雪水当量、雪盖、蒸散发、地表与地下水量等最新进展，也一并介绍了2019年与定量遥感相关的科研项目、学术交流会与暑假培训班等内容。     

玛河流域景观生态风险评价与时空分异

以玛纳斯河流域作为研究区,结合特殊的干旱区山地-绿洲-荒漠系统(Mountain-Oasis-Desert System简称MODS),综合考虑遥感影像数据光谱信息和纹理特征,将研究区分为耕地、林地、草地、水体、裸地、居民地、工业用地和冰川/永久积雪等8个景观类型,利用FRAGSTATS软件计算景观指数,引入生态风险的指数,将研究区划为低、较低、中、较高、高生态风险区五级,评估其景观格局的生态风险时空变化特征。结果表明:1)1990—2015年间,玛纳斯河流域景观变化主要表现为耕地、建设用地的增加以及水体、冰川/永久积雪面积的缩减;2)玛纳斯河流域的景观生态风险等级空间分布具有明显的差异,较低风险区的面积变化较为明显,低、较低生态的风险区比重有所上升,除此以外,林、草地类型各生态风险的等级所占比重的起伏波动具有明显的差异。建议应当合理地利用土地资源,尽量保护林地、草地等景观脆弱行较低的原生景观类型,禁止为开垦耕地而破坏林地、草地;增加土地的利用效率,更要对高等、较高生态风险区加强监管。     

基于GlobeLand30的番禺区地表覆盖时空变化分析

本文基于全球30 m地表覆盖数据(GlobeLand30),采用地表覆盖转移矩阵、重心迁移方法，分析了番禺区2000—2020年不同地表覆盖类型的相互转化及其空间分布。结果表明：过去20年间，人造地表持续占用耕地、森林和草地，其中耕地最为明显。同时，2010—2020年人造地表扩张速度较2000—2010年更为迅速。从相互转化的空间分布上看，番禺区人造地表在2000—2010年呈点状增加，之后10 a快速蔓延至全区。人造地表和水体的重心向东迁移，耕地的重心转移则逐步西移，呈“一进一退”的趋势。     

基于GlobeLand 30的山东省地表覆盖时空变化与分析

以山东省为研究区域,利用2000年、2010年和2020年的GlobeLand 30数据,综合采用用地面积、构成占比、增量占比以及地表覆盖转移矩阵等分析方法,研究了山东省各地市地表覆盖的空间格局、变化幅度、区域差异,并从人口、经济、政策等方面对山东省各地级市的地表覆盖变化驱动力、变化特点等进行了分析.研究结果表明山东省地表覆盖在过去的20 a中发生了较大的变化.耕地呈现较大幅度的减少,其减少率为11.63％;人造地表扩张速度较快,增长率高达80.92％,其他地类也有不同程度的变化.山东省地表覆盖变化具有显著的区域差异性,草地和森林的变化主要集中在鲁东丘陵的东北部地区和鲁中南山地丘陵中部区域,湿地和水体的变化主要集中在鲁西北平原北部沿海地区和南四湖地区.山东省地表覆盖变化是由多种驱动力因素共同影响的结果,如经济的增长、人口的流动、政策的实施等.     

抚顺矿区1989-2019年土地利用/覆盖变化分析

为探讨抚顺矿区土地利用/覆盖变化及驱动力,该文以1989-2019年6期Landsat系列遥感影像为数据源,设计支持向量机(SVM)多分类器进行土地利用/覆盖分类,通过土地利用/覆盖格局分析、动态度分析和转移矩阵分析,探究类型结构的变化规律,并运用主成分分析法,揭示其主要驱动力.研究表明:1989-2019年,抚顺矿区土地利用/覆盖发生了明显的变化.在整体结构中,土地利用/覆盖类型以建设用地和耕地为主;土地利用/覆盖变化呈现出采矿用地和林地减少,建设用地和水域增加,耕地先增加后减少的趋势;采矿用地和建设用地的动态度分别在[-4％,1％]和[0,3％]内,表明采矿用地和建设用地变化较为显著.根据转移矩阵可知,采矿用地主要向耕地和林地转移,同时耕地和林地被建设用地占用.利用主成分分析方法对选取的12个驱动因子进行定量分析,得出主要驱动力为人口城镇化、经济发展水平的提升和原煤产量的降低.     

Quantifying Four Decades of Changes in Land Use and Land Cover in India’s Kailash Sacred Landscape: Suggested Option for Priority Based Patch Level Future Forest Conservation

Effective quantification of land cover changes remains a challenge in Himalayan hills and mountains, and has a colossal value addition for natural resource management. Here we present a new robust method for classifying land cover vegetation at physiognomic scale along steep elevational gradients from ~?200 to ~?7000 masl in the Kailash Sacred Landscape, Western Himalaya, India along with four decades of land use and land cover changes (1976–2011) using remote sensing techniques coupled with intensive ground surveys. Results show that forest cover loss was minimum ca 7.14% of existing forest in 1976; but, however forest fragmentation is high especially in montane broad-leaved and subtropical needle leaved forests. This change largely impacted the quality of valuable tree species such as Quercus spp. Post 1976, continuous migration forced conversion of high altitude agricultural lands into grasslands and scrublands. Human settlement expansion was high especially in low altitudinal range valleys between 1000 and 2000 masl and has increased 6.76 fold since 1976, leading to high forest fragmentation in spite of reduced agriculture area in the landscape. Our physiognomic level classified land cover map will be a key for forest managers to prioritize conservation zones for protecting this unique forest land.     

中国陆地生态系统脆弱带遥感模型

本研究通过对我国陆地生态系统8个典型样地的植被指数取样实验和图像计算结果发现，这8个样地植被指数随着水、热因子的季节变化，在时间和空间上具有一定的“绿波推移”和“景观更替”规律。在中国东部湿润的季风区（样地1－3），随着纬度的增高，其月平均植被指数与月平均气温有较大的相关。发现降水相对丰沛的地带，热量和光照条件的变化成为植被生长和变化的自然限制因子；而在中国北方森林－森林草原－典型昌原－荒漠草原－荒漠地带上，随着从东部（湿润地区）到西部（干旱地区）干湿条件的更替，月平均植被指数与降水多寡有较大的正相关关系。在8个样地上都呈现出共同的规律，即定向风的分布与植被指数的分布在时间和空间上具有逆相分布的“套合关系”。尤其在时间上有相逆套合关系，这正是中国北方沙尘暴和沙漠化加剧的自然原因。本研究定量地给出了我国陆地不同经纬度带生态系统脆弱季节和累积时间的分布。     

Albedo-rainfall Feedback Over Indian Monsoon Region Using Long Term Observations Between 1981 to 2000

Albedo determines radiation balance of land (soil-canopy complex) surface and influence boundary layer structure of the atmosphere. Accurate surface albedo determination is important for weather forecasting, climate projection and ecosystem modelling. Albedo-rainfall feedback relationship has not been studied so far using observations on spatial scale over Indian monsoon region due to lack of consistent, systematic and simultaneous long-term measurements of both. The present study used dekadal (ten-day) composite of satellite (e.g. NOAA) based Pathfinder AVHRR Land (PAL) datasets between 1981 and 2000 over India (68–100°E, 5–40°N) at 8 km spatial resolution. Land surface albedo was computed using linear transformation of red and near infrared (NIR) surface reflectances. The cloud effects were removed using a smoothening filter with harmonic analysis applied to time series data in each year. The monthly, annual and long term means were computed from dekadal reconstructed albedo. The mean per year and coefficient of variation (CV) of surface albedo over seventeen years, averaged over Indian land region, were found to show a significantly decreasing (0.15 to 0.14 and 60 to 40%, respectively) trend between 1981 and 2000. Among all the land use patterns, the inter-annual variation of albedo of Himalayan snow cover showed a significant and the steepest reducing trend (0.42 – 0.35) followed by open shurbland, grassland and cropland. No significant change was noticed over different forest types.. This could be due to increase in snow melting period and snow melt area. A strong inverse exponential relation (correlation coefficient r = 0.95, n = 100) was found between annual rainfall and annual albedo over seven rainfall zones. The decreasing trend in snow-albedo of accumulation period (September to March) follows the declining trend in measured south-west monsoon rainfall between 1988 (980 mm) to 1998 (880 mm) over India. This finding perhaps suggests the possible reversal of reported coupling of increased snowfall followed by lower monsoon rainfall.     

Estimating carbon sequestration in the piedmont ecoregion of the United States from 1971 to 2010

Human activities have diverse and profound impacts on ecosystem carbon cycles. The Piedmont ecoregion in the eastern United States has undergone significant land use and land cover change in the past few decades. The purpose of this study was to use newly available land use and land cover change data to quantify carbon changes within the ecoregion. Land use and land cover change data (60-m spatial resolution) derived from sequential remotely sensed Landsat imagery were used to generate 960-m resolution land cover change maps for the Piedmont ecoregion. These maps were used in the Integrated Biosphere Simulator (IBIS) to simulate ecosystem carbon stock and flux changes from 1971 to 2010. Results show that land use change, especially urbanization and forest harvest had significant impacts on carbon sources and sinks. From 1971 to 2010, forest ecosystems sequestered 0.25 Mg C ha?1 yr?1, while agricultural ecosystems sequestered 0.03 Mg C ha?1 yr?1. The total ecosystem C stock increased from 2271 Tg C in 1971 to 2402 Tg C in 2010, with an annual average increase of 3.3 Tg C yr?1. Terrestrial lands in the Piedmont ecoregion were estimated to be weak net carbon sink during the study period. The major factors contributing to the carbon sink were forest growth and afforestation; the major factors contributing to terrestrial emissions were human induced land cover change, especially urbanization and forest harvest. An additional amount of carbon continues to be stored in harvested wood products. If this pool were included the carbon sink would be stronger.     

Spatial and Temporal Relationships among NDVI,Climate Factors,and Land Cover Changes in Northeast Asia from 1982 to 2009

This study uses a multiple linear regression method to composite standard Normalized Difference Vegetation Index (NDVI) time series (1982-2009) consisting of three kinds of satellite NDVI data (AVHRR, SPOT, and MODIS). This dataset was combined with climate data and land cover maps to analyze growing season (June to September) NDVI trends in northeast Asia. In combination with climate zones, NDVI changes that are influenced by climate factors and land cover changes were also evaluated. This study revealed that the vegetation cover in the arid, western regions of northeast Asia is strongly influenced by precipitation, and with increasing precipitation, NDVI values become less influenced by precipitation. Spatial changes in the NDVI as influenced by temperature in this region are less obvious. Land cover dynamics also influence NDVI changes in different climate zones, especially for bare ground, cropland, and grassland. Future research should also incorporate higher-spatial-resolution data as well as other data types (such as greenhouse gas data) to further evaluate the mechanisms through which these factors interact.     

城市不透水表面遥感估算研究

作为城市化水平的关键指示因子，不透水表面已经被广泛应用在城市生态环境评估中。利用TM影像，采用附有限制条件的线性光谱混合模型对北京城区的不透水表面分布进行空间分析。通过高反照率、低反照率、植被及土壤4类光谱端元的线性组合表征城市土地覆盖类型，综合剔除噪声影响后的高、低反照率分量，估算北京城区不透水表面分布。研究结果表明：利用附有限制条件的线性光谱分解得到的RMS平均值为0．003428。其不透水表面分布结果与同期spot-5对比验证，R2为0．932，均方根误差为0．086，结果令人满意。     

Linear unmixing of MODIS albedo composites to infer subpixel land cover type albedos

We use a linear unmixing approach to test how land use and forestry maps, in combination with the MODIS BRDF/albedo product, can be used to estimate land cover type albedos in boreal regions. Operational land use maps from three test areas in Finland and Canada were used to test the method. The resulting endmember albedo estimates had low standard errors of the mean and were realistic for the main land cover types. The estimated albedos were fairly consistent with albedo measurements conducted with a telescope mast and pure pixel albedos. Problems with the method are the possible errors in the land cover maps, lack of good quality winter MODIS albedo composites and the mismatch between the MODIS pixels and the true observation area. The results emphasize the role of tree species as determinant of forest albedo. Comprehensive spatial and temporal measurements of land cover albedo are usually not possible with in situ mast measurements, and the spatial resolution of MODIS albedo product is often too low to allow direct comparison of pixel albedos and land cover types in areas with heterogeneous vegetation. Hence, and since local forestry maps exist for most temperate and boreal regions, we believe that the proposed method will be useful in estimating average regional land cover type albedos as well as in tracking changes in them.     

Determination of land degradation causes in Tongyu County,Northeast China via land cover change detection

Tongyu County in Northeast China is highly prone to land degradation due to its fragile physical settings characterized by a flat topography, a semi-arid climate, and a shallow groundwater table. This study aims to determine the causes of land degradation through detecting the long-term trend of land cover changes. Degraded lands were mapped from satellite images recorded in 1992 and 2002. These land cover maps revealed that the area subject to land degradation in the form of soil salinization, waterlogging and desertification increased from 2400 to 4214 km², in sharp contrast to most severely degraded land that decreased by 122.5 km². Newly degraded land stems from productive farmland (263 km²), harvested farmland (551 km²), and grassland (468 km²). Therefore, the worsened degradation situation is attributed to excessive reclamation of grassland for farming, over cultivation, overgrazing, and deforestation. Mechanical, biological, ecological and engineering means should be adopted to rehabilitate the degraded land.     

四川省江油市2004～2020年土地利用动态分析及预测

基于2004、2010、2015年Landsat-5 TM、Landset-80LI遥感影像土地利用现状解译数据,分析了江油市近11年土地利用动态变化;同时,利用元胞自动机-马尔科夫(CA-Markov)模型,模拟预测了2020年江油市土地利用空间分布格局.结果表明,2004 ～ 2015年期间,江油市耕地、草地、水域面积总体减少,建设用地和林地面积总体呈增加趋势.2015 ～2020年期间,江油市土地利用变化较快,与上一个五年相比,建设用地、耕地和草地面积将有所增加,林地面积有所减少,水域面积基本不变;建设用地从原有基础往外围耕地扩张,耕地面积则主要由林地转入.     

遥感与GIS支持下近十年中国草地变化空间格局分析

以遥感与GIS为技术支撑，动态监测我国草地资源近十年的变化情况，为草地资源的可持续利用与管理提供科学依据。近十年来，我国的草地资源变化在空间上有明显的地域差异。表现为草地变耕地主要分布于我国的东北三省，与内蒙古的东部地区；草地变为城镇交通用地在很大程度上与区域的人口、经济发展有联系；草地变林地分布主要集中于沿海地区；草地退化集中于内蒙古、新疆、青海。草地变化虽然与自然条件有关，但人类活动对草地变化有很大影响。同时草地的退化对我国的生态环境，尤其是北方将产生不良的作用，在一定程度上制约区域经济发展。