基于Landsat8影像估算新安江水库光合有效辐射漫射衰减系数

光合有效辐射(photosynthetically active radiation,PAR)是指可以被植物利用并进行光合作用的那部分太阳辐射,其进入湖水后受光学组分(悬浮颗粒、有色可溶性有机物和浮游植物)的吸收和散射作用发生衰减,对湖泊生物的密度和分布具有重要影响.本研究构建了基于Landsat 8影像数据的较为清洁的新安江水库PAR漫衰减系数的遥感估算模型,进而分析其时空分布特征及主要影响因素.结果表明,利用Landsat 8的第二、三和第八波段构建的多元回归模型能够得到较为准确的估算结果,模型决定系数为0.87.利用独立样本对构建的模型验证,预测值和实测值相对误差绝对值均值为9.16%,均方根误差为0.06 m~(-1),由此可见利用Landsat 8数据的3个波段,采用多元回归模型能够较好地估算较清洁水体的PAR漫射衰减系数.基于14景Landsat 8影像发现,新安江水库PAR漫射衰减系数季节差异性明显,秋季(9~11月)和夏季(6~8月)PAR漫射衰减系数较高,分别为(0.82±0.60)m~(-1)和(0.77±0.41)m~(-1),而冬季(12~次年2月)和春季(3~5月)PAR漫射衰减系数相对较低,分别为(0.56±0.50)m~(-1)和(0.40±0.45)m~(-1).新安江水库PAR漫射衰减系数空间差异性显著,全湖PAR漫射衰减系数变化范围为(0.002~13.86)m~(-1),均值为(0.64±0.49)m~(-1).漫射衰减系数的季节变化主要是由季节性降雨和浮游植物季节性生长引起,空间差异性主要由外源河流输入和部分水域采砂过程导致悬浮物浓度变化引起.     

西安地区城镇扩展及其生态环境效应研究

论文以西安地区为研究区,基于1988年和2003年两期LandsatTM影像,采用监督分类法提取了该区15年间城镇扩展变化,并利用土地利用面积转移矩阵分析了城镇用地与其它土地利用类型转化的关系,此外,结合社会经济统计资料探讨了城镇扩展的生态环境效应。结果表明:①城镇面积1988年为59711.31hm₂,而到了2003年为75043.53hm₂,其增幅达25.68%;②城镇的新增面积主要是由耕地、未利用地、果园和水体转化而来;③城镇扩展的生态环境效应在该地区集中表现为水资源污染、城市“热岛效应”、地面沉降以及地裂缝等环境问题。     

Estimating Annual Groundwater Evapotranspiration from Phreatophytes in the Great Basin Using Landsat and Flux Tower Measurements

Escalating concerns about water supplies in the Great Basin have prompted numerous water budget studies focused on groundwater recharge and discharge. For many hydrographic areas (HAs) in the Great Basin, most of the recharge is discharged by bare soil evaporation and evapotranspiration (ET) from phreatophyte vegetation. Estimating recharge from precipitation in a given HA is difficult and often has significant uncertainty, therefore it is often quantified by estimating the natural discharge. As such, remote sensing applications for spatially distributing flux tower estimates of ET and groundwater ET (ET_g) across phreatophyte areas are becoming more common. We build on previous studies and develop a transferable empirical relationship with uncertainty bounds between flux tower estimates of ET and a remotely sensed vegetation index, Enhanced Vegetation Index (EVI). Energy balance‐corrected ET measured from 40 flux tower site‐year combinations in the Great Basin was statistically correlated with EVI derived from Landsat imagery (r² = 0.97). Application of the relationship to estimate mean‐annual ET_g from four HAs in western and eastern Nevada is highlighted and results are compared with previous estimates. Uncertainty bounds about the estimated mean ET_g allow investigators to evaluate if independent groundwater discharge estimates are “believable” and will ultimately assist local, state, and federal agencies to evaluate expert witness reports of ET_g, along with providing new first‐order estimates of ET_g.     

Retrieving leaf area index for coniferous forest in Xingguo County, China with Landsat ETM+ images

Spatial distributions of the leaf area index (LAI) needed for carbon cycle modeling in Xingguo County, China were estimated based on correlations between the field-measurements and vegetation indices (VIs). After making geometric and atmospheric corrections to two Landsat ETM+ images, one in January 2000 and the other in May 2003, three VIs (SR, NDVI, and RSR) were derived, and their separate correlations with ground LAI measurements were established. The correlation with RSR was the highest among the three VIs. The retrieved LAI values for January 2000 were lower than those for May 2003 because of a small seasonal variation in the coniferous forests (predominantly masson pine) and the decrease in the understorey vegetation during winter.     

利用多信息源提高半干旱地区TM影像的森林类型制图精度:以北京西部山区为例

以地处半干旱地区的北京西部山区为例,利用研究区森林类型的季相特征、已有的少部分林相图、Google Earth免费影像数据等信息选择不同坡向的相同森林类型做训练样本,通过加入其他辅助数据(海拔和坡向数据),来提高Landsat TM影像的森林类型分类精度,同时对比了基于像元和面向对象方法提取森林类型的效果。结果表明:1)就半干旱山区的森林类型划分来说,TM影像的TM4、TM5、TM4-TM2及辅助数据DEM和坡向可作为TM影像森林类型划分的最佳数据源。2)单独加入海拔信息,阔叶林的提取精度提高23%,针叶林和混交林的分类精度只提高了4%~5%;单独加入坡向信息,阔叶林的提取精度只提高21%,但是针叶林和混交林的分类精度则分别提高了13%、18%,显著优于单独加入海拔信息的效果。同时加入海拔信息和坡向信息,至少可以准确区分出约70%以上的针叶林、阔叶林和混交林。3)就本研究区而言,坡向比海拔更有效地辅助提高森林分类精度。4)就混淆矩阵数据而言,面向对象的分类方法比基于像元分类结果总体精度低3%,Kappa系数低4%,但面向对象的分类结果更加符合研究区实际情况。该研究对中分辨率影像应用于半干旱山区森林类型划分具有一定的借鉴意义。     

成都市热力景观空间格局分析

城市热力景观空间格局是城市附属物和城市活动性在热场方面的综合表现。使用2008年11月23日的Landsat5/TM数据,将第6波段反演为亮温,并按温度值的高低把热力景观分为7个类型;借鉴景观生态学的原理和方法,以破碎度指数、多样性指数、均匀度指数和优势度指数为评价指标,对成都市三环路内约200km2热力景观空间格局的研究结果表明：5个行政区的热力景观格局指数存在显著差别,如锦江区的破碎度指数最大,为0.924,成华区的最小,为0.559,指数大小与城市热力景观类型的分布特点密切相关。这些结果对于分析和研究城市整体格局、城市规划和环境保护等具有应用意义。     

Comparing the utility of image algebra operations for characterizing landscape changes: the case of the Mediterranean coast

The aim of this study is to compare various image algebra procedures for their efficiency in locating and identifying different types of landscape changes on the margin of a Mediterranean coastal plain, Cukurova, Turkey. Image differencing and ratioing were applied to the reflective bands of Landsat TM datasets acquired in 1984 and 2006. Normalized Difference Vegetation index (NDVI) and Principal Component Analysis (PCA) differencing were also applied. The resulting images were tested for their capacity to detect nine change phenomena, which were a priori defined in a three-level classification scheme. These change phenomena included agricultural encroachment, sand dune afforestation, coastline changes and removal/expansion of reed beds. The percentage overall accuracies of different algebra products for each phenomenon were calculated and compared. The results showed that some of the changes such as sand dune afforestation and reed bed expansion were detected with accuracies varying between 85 and 97% by the majority of the algebra operations, while some other changes such as logging could only be detected by mid-infrared (MIR) ratioing. For optimizing change detection in similar coastal landscapes, underlying causes of these changes were discussed and the guidelines for selecting band and algebra operations were provided.     

Visual interpretation of satellite imagery for monitoring floods in Bangladesh

This article presents the methods and results of visual interpretation of NOAA AVHRR imagery for mapping flood areas in Bangladesh. Color composites of channels 1 and 2 for 18 August 1987 and 10, 15, and 24 September 1988 were interpreted visually for delineating flood boundaries. On such imagery flood areas appear in dark tones and are separated from land (light tones) owing to the absorption of near infrared by water and its reflectance by land and non-waterbodies. Visual interpretation was aided by the use of ground information, such as physiographic and river maps, previous flood maps, newspaper reports, and other published and unpublished documents on the 1987 and 1988 floods. Interpreted flood areas on selected images ranged from 31% to 43% of the total area of Bangladesh. Visual interpretation overestimated flood areas by 5%–10%, compared to the digitally analyzed data. The main advantage of visual analysis lies in the cost effectiveness of AVHRR photographic products, which make them more accessible than the digital image analysis of computer-compatible tapes.     

鄱阳湖天然湖面遥感监测及其与水位关系研究

以1989—2010年鄱阳湖100期(景)Landsat TM/ETM+影像为数据源,对比分析了水体指数法和谱间关系法两种主要的水体提取方法,利用水体指数法提取了天然湖体水面面积,揭示了不同水位下鄱阳湖天然湖体水面的空间扩展过程与特征,建立了汛期与非汛期水面-水位关系模型并确定了相应代表性水位站。结果表明:①在鄱阳湖,水体指数法水体提取精度优于谱间关系法;②受地形影响,不同水位条件下鄱阳湖天然水面的空间扩展特征大致呈"菱形"沿湖岸以顺时针方向(即:北→东→南→西→北)推进;③水位为6~15 m时,鄱阳湖天然湖体水面随水位变化呈线性变化,水面变化显著;而在水位介于15~22 m时,天然湖体水面随水位变化则呈对数变化。基于水面-水位关系模型,确定汛期代表性水位站为星子站、都昌站与吴城站;而非汛期代表性水位站为棠荫站。     

Tracking land cover change along the western edge of the U.S. Corn Belt from 1984 through 2016 using satellite sensor data: observed trends and contributing factors

The Cropland Data Layers (CDL) are high-resolution geo-referenced data products made available by the U.S. Department of Agriculture. However, the CDL lacks in its ability to be employed as a tool to identify the impact of the gradually evolving drivers of land use change, e.g., climate change, due to its limited historical depth. We implement a robust, phenology-based satellite image classification algorithm to identify historical cropland allocation in eastern South Dakota and North Dakota predating the initial CDL by 13 and 22 years, respectively. Five major land covers, i.e., corn, soybeans, wheat, alfalfa and grass (including native grass, hay and pasture) are identified using archived Landsat-5 surface reflectance data, while achieving CDL-like accuracy. The long-term rate of grassland loss during 1985–2011 is found to be significantly lower (26,781 hectares or 1.5% annually) relative to the near-term rate of grassland loss during 2006-’11 (84,545 hectares or 5.2% annually). We find similar discrepancy in regional corn expansion rates. Our value-added raster data provide opportunities for improved identification of land use drivers, whereas relying solely on the CDL’s restricted historical extent may lead to biased land use change estimates and misguide policy.