Evaluating the suitability of different terrains for sustaining human settlements according to the local elevation range in China using the ASTER GDEM

The topographical suitability assessment of human settlements(SAHS) creates a solid foundation for regional population distribution and socio-economic development. Local elevation range(LER) is an important factor that can be used to assess the suitability of different terrains for sustaining human settlements. However, current digital elevation model(DEM)-based LER products suffer from some challenges typically because of their subjectively selected neighborhood scales and coarser spatial resolution. In this study, we initially determined the optimal statistical window and then calculated the appropriate LER with the finer resolution data of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM(ASTER GDEM) products for China. Then, the appropriate LER was used to evaluate the topographical SAHS and its correlations with the national gridded population distribution(1 km × 1 km) in 2010. The results show that the optimal statistical window for calculating a 1 arc-second(about 30 m) resolution GDEM LER for China can be determined using a 51 × 51 grid unit(width × height) within a rectangular neighborhood, corresponding to an area of about 2.34 km~2. Secondly, the LER values in the southern and western China were greater than those of the north and east, showing a trend which consistently reflects the general spatial features of landforms. Finally, the relationship between GDEM LER and population density was highly correlated with the R~2 value of 0.81. It showed that 85.22% of the Chinese population was located in areas where the LER is lower than 500 m. The topographically suitable area within China decreased from the southeastern coastal zone towards the northwestern inland areas due to transition from plains and basins to plateaus and mountains. The total area of moderate to high suitable level was 423.84 × 10~4 km~2, or 44.15% of the total land area, with 88.17% of the national population. Our study demonstrates the usefulness of appropriate LER in evaluating the topographical SAHS as well as its significant impact on population distribution.     

SRTM1 DEM与ASTER GDEM V2数据的对比分析

本文以山西省为实验区,基于ICESat/GLA14测高数据对SRTM1 DEM和ASTER GDEM V2数据的垂直精度进行了对比,分析了其在坡度、土地利用类型和地貌类型中的误差分布情况,并基于地形剖面方法分析了2种DEM数据在地形表达上的差异。研究结果表明：① 在垂直精度上,SRTM1 DEM数据要明显高于ASTER GDEM V2数据,其绝对误差均值分别为4.0 m和7.8 m,标准偏差分别为6.0 m和10.7 m,均方根误差分别为6.1 m和10.7 m。② 这2种DEM数据的精度受坡度影响严重,随坡度值的升高误差增大;SRTM1 DEM的绝对误差均值、标准偏差和均方根误差在水田最小,在林地最大,而ASTER GDEM V2的这3种误差在居民用地最小,在林地最大;SRTM1 DEM 和ASTER GDEM V2的绝对误差均值、标准偏差和均方根误差在平原地区最小,在大起伏山地最大。③ 在平原和台地地区,ASTER GDEM V2数据高程值有异常波动,SRTM1 DEM在起伏山地存在对山谷过高估计。总体上,SRTM1 DEM比ASTER GDEM V2对地形的表达准确,与ICESat/GLA14对地形的描述基本相一致。     

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基于ICESat/GLAS的山东省SRTM与ASTER GDEM高程精度评价与修正

SRTM3和ASTER GDEM V2数据具有较高的空间分辨率和广泛的覆盖范围,对于地学研究具有重要意义;但在不同地形复杂度和地面覆盖物区域,两类数据的误差分布并不均匀。SRTM3和ASTER GDEM V2数据自公布以来,其精度修正一直是研究热点。然而大范围区域精度验证缺乏有效手段,传统方法可靠性差且数据获取成本较高。自ICESat-1数据公开以来,它们已成为SRTM3和ASTER GDEM V2精度评定的主要检核点。为此,本文以山东省为研究区域,借助ICESat-1评估了SRTM3和ASTER GDEM V2的高程精度,并根据插值误差曲面对两种DEM进行了修正。分析表明,原始SRTM和ASTER高程中误差分别为5.57 m和7.20 m,均高于标称精度;随着坡度的增大,高程精度呈降低的趋势。通过分析土地覆盖类型与误差分布关系表明:农田、灌丛土地类型精度较高;森林、湿地精度较低。分别采用反距离加权、普通克里金、地形转栅格和自然邻域插值方法构建误差曲面。结果表明:不同的插值方法构建的误差曲面的特征和精度也不同。其中,反距离加权修正的效果最佳,其次是地形转栅格和自然邻域,而普通克里金修正的效果最差。     

An automated method for glacial lake mapping in High Mountain Asia using Landsat 8 imagery

Glacial lakes in the High Mountain Asia (HMA) are sensitive to global warming and can result in much more severe flood disasters than some largesized lakes. An accurate and robust method for the extraction of glacial lakes is critical to effective management of these natural water resources. Conventional methods often have limitations in terms of low spectral contrast and heterogeneous backgrounds in an image. This study presents a robust and automated method for the yearly mapping of glacial lake over a large scale, which took advantage of the complementarity between the modified normalized difference water index (MNDWI) and the nonlocal active contour model, required only local homogeneity in reflectance features of lake. The cloud computing approach with the Google Earth Engine (GEE) platform was used to process the intensive amount of Landsat 8 images from 2015 (344 path/rows and approximately 7504 scenes). The experimental results were validated by very high resolution images from Chinese GaoFen-1 (GF-1) panchromatic multi-spectral (PMS) and appeared a general good agreement. This is the first time that information regarding the spatial distribution of glacial lakes over the HMA has been derived automatically within quite a short period of time. By integrating it with the relevant indices, it can also be applied to detect other land cover types such as snow or vegetation with improved accuracy.     

典型山区SRTM3与ASTER GDEM数据精度对比分析——以青藏高原东麓深切河谷区为例

目前广泛应用的数字高程模型(DEM)包括SRTM和ASTER GDEM,但在地形影响下,两类数据的误差分布并不均匀。本文选用1:5万地形图DEM及河流要素作为参照,在青藏高原东麓山区开展实验,分别采用"河流-河谷"位置偏移量与高程中误差来评价两类数据的平面精度与垂直精度,结果表明:(1)实验区内SRTM3存在向西南方向的水平位置偏移,平均偏移量为127.8 m,ASTER GDEM则以正西方向偏移为主,平均偏移量为104.1 m,该区域ASTER GDEM的总体平面精度较好;(2)SRTM3数据样本的绝对误差分布相对集中,高程中误差为35.3 m,小于ASTER GDEM样本的高程中误差50.2 m,总体垂直精度优于ASTER GDEM;(3)在平均高程大于4500 m的高海拔区域,两类数据的中误差与高程值正相关,SRTM3中误差随高程增速较慢,垂直精度较ASTER GDEM高;(4)两组数据垂直精度对坡度有较大依赖性,中误差随坡度近似指数曲线增长,在平缓区域SRTM3中误差小于ASTER GDEM。本研究为该类数据在山区的选用及误差修正提供依据。     

Using Landsat images to monitor changes in the snow-covered area of selected glaciers in northern Pakistan

Landsat satellite images were used to map and monitor the snow-covered areas of four glaciers with different aspects(Passu: 36.473°N, 74.766°E;Momhil: 36.394°N, 75.085°E; Trivor: 36.249°N,74.968°E; and Kunyang: 36.083°N, 75.288°E) in the upper Indus basin, northern Pakistan, from 1990-2014. The snow-covered areas of the selected glaciers were identified and classified using supervised and rule-based image analysis techniques in three different seasons. Accuracy assessment of the classified images indicated that the supervised classification technique performed slightly better than the rule-based technique. Snow-covered areas on the selected glaciers were generally reduced during the study period but at different rates. Glaciers reached maximum areal snow coverage in winter and premonsoon seasons and minimum areal snow coverage in monsoon seasons, with the lowest snow-covered area occurring in August and September. The snowcovered area on Passu glacier decreased by 24.50%,3.15% and 11.25% in the pre-monsoon, monsoon and post-monsoon seasons, respectively. Similarly, the other three glaciers showed notable decreases in snow-covered area during the pre-and post-monsoon seasons; however, no clear changes were observed during monsoon seasons. During pre-monsoon seasons, the eastward-facing glacier lost comparatively more snow-covered area than the westward-facing glacier. The average seasonal glacier surface temperature calculated from the Landsat thermal band showed negative correlations of-0.67,-0.89,-0.75 and-0.77 with the average seasonal snowcovered areas of the Passu, Momhil, Trivor and Kunyang glaciers, respectively, during pre-monsoon seasons. Similarly, the air temperature collected from a nearby meteorological station showed an increasing trend, indicating that the snow-covered area reduction in the region was largely due to climate warming.     

Estimation of vegetative surface albedo in the Kushiro Mire with Landsat TM data

A method has been developed for estimating the filtered narrow band surface albedo with Landsat/TM data. In this method, the surface albedo from filtered range of Landsat/TM is converted to the surface albedo with unfiltered spectral range. The atmospheric effects on each channel are systematically different, because of the different spectral behavior of atmospheric parameters. As a result, in this study, atmospheric correction has been done respectively in different parameters for visible and infrared channels. The surface albedos of the Kushiro Mire gotten with this method were compared with the observed data there. The results show that the satellite inferred albedos have a good agreement to the diurnal mean of ground observed albedos with 3% systematic error. There is a seasonal variation of albedo in high and low mires, the albedo decreased gradually from April to July and reached its minimum in July, further it rose gradually from August to October. It is also clear that there is a characteristic pattern of surface distribution according to the vegetation types of this area. The average surface albedos of each type of community are 0.164 for Sphagnum, 0.175 for Carex, 0.179 for Pragmites and 0.166 for Alnus. In the other words, the albedo in high mire (mainly covered by Sphagnum) is lower than that in low mire (mainly covered by Phragmites and Carex).     

结合ICESat-2和GEDI的中国东南丘陵地区ASTERGDEM高程精度评价与修正

星载激光雷达ICESat-2和GEDI可以为数字高程模型产品的精度评价与修正提供全球覆盖的、可靠的高精度参考数据源。然而,现有的DEM修正方法主要是针对DEM误差中的植被高信号且多采用线性回归模型。为此,本文分析了ASTER GDEM v3精度与土地覆盖类型、高程、坡度、起伏度及植被覆盖率的关系。在此基础上,提出了一种考虑上述多种精度影响因素并结合XGBoost和空间插值的DEM误差修正方法。结果分析表明:原始ASTER GDEM的误差整体呈正态分布,平均误差为-3.463 m,存在较大负偏差,高程精度随着高程、坡度、起伏度及植被覆盖率VCF的增大呈降低趋势;经过修正后,ASTER GDEM平均误差降低到了-0.233 m,负偏差得到有效改善,整体平均绝对误差降低了26.04%,整体均方差降低了23.56%,耕地、林地、草地、湿地、水域及人造地表的DEM平均绝对误差和均方差都有不同程度的降低;本文提出的方法对多种特征要素与地形误差间的非线性关系进行拟合建模,在研究区取得了较好的修正效果。     

三峡库区典型样带潜热通量遥感反演与验证

本文以三峡库区腹地的部分地区为典型样带,利用遥感数据的时效性和区域性优势,结合常规气象数据,定量反演样带地表潜热通量,并对比验证遥感反演方法的可行性和可靠性。结果表明：潜热通量在不同地表覆被状况下呈现较大差异,城镇居民区和无植被覆盖区一般在20~80W·m^-2;人工林场、山区森林及草灌和山前农作区在180~280W·m^-2;水体则分布在420~470W·m^-2,潜热通量整体呈现出随地表覆被变化而变化的空间异质性。此外,由于库区地表覆被类型多样,并受到山区起伏地形地貌的影响,潜热通量在空间分布上的地形分异特征也较显著。     

TM热波段图像的地表温度反演算法与实验分析

目前利用LandsatTM热波段数据反演地表温度有3种算法:辐射传导方程法、单窗算法和单通道算法。辐射传导方程法由于计算过程复杂且需要实时大气剖面数据,因而实际应用较为困难。单窗算法和单通道算法对Landsat热波段反演地表温度能获得较高精度。单窗算法所需的大气参数包括近地表气温和大气水分含量,单通道算法所需的大气参数仅为大气水分含量。地表辐射率为这两种算法共有的关键参数。本文以福建省福州市为研究区,使用1989年6月15日LandsatTM数据,利用单窗算法和单通道算法对研究区进行地表温度反演,并将这两种算法的反演结果与研究区反演的亮度温度进行了比较,结果表明:(1)两种算法反演的结果总体趋势比较接近,但单窗算法的结果相对于单通道算法较低,二者相差约2.45℃;(2)两种算法的结果与亮度温度相比,单窗算法要高出约2.84℃,而单通道算法则要高出约5.28℃。     

基于Landsat TM和ENVISAT ASAR数据的鄱阳湖湿地植被生物量的反演

作为湿地生态系统的重要组成部分,湿地生物量是衡量生态系统健康状况的关键指标。由于光学遥感对植被垂直分布探测的局限,使得植被指数反映生物量变化的灵敏度下降。利用C波段SAR反演生物量时,对于低中等生物量,含水量高的湿地地表的后向散射对总雷达后向散射的影响会在雷达图像上出现类似光学遥感中异物同谱的现象。本文用光学遥感中NDVI、RVI和DVI三种植被指数对生物量变化的敏感性,利用改进的MIM-ICS模型,对湿地植被各散射分量进行模拟分析,建立符合湿地植被类型的各散射分量模拟数据库,以LandsatTM和Envisat ASAR交替极化数据为基础,选择植被指数DVI=0.45为阈值,将湿地植被分割为低叶片密度植被区和高叶片密度植被区,分别应用统计回归模型和半经验微波散射模型,对两个区域植被生物量进行反演。最后,得到整个鄱阳湖湿地生物量为2.1×10⁹kg。研究表明,对于生物量动态范围较大的地区,采用光学和雷达遥感相结合可以有效地提高湿地植被生物量反演的精度,克服光学遥感探测植被垂直分布能力有限和雷达遥感受背景影响大的不足。     

集成夜间灯光数据与Landsat TM影像的不透水面自动提取方法研究

利用多源遥感数据提取不透水面信息是一个重要的研究方向。针对以往研究中多需要人工选取不透水面样本进行模型训练的问题,本文通过整合夜间灯光遥感与Landsat TM影像中的空间和光谱信息实现了不透水面覆盖范围（Impervious Surface Area,ISA）的自动提取。首先根据夜间灯光的分布来定位ISA聚集的城市区域的位置,分别在城市区域内部和外部自动提取可靠性高的ISA及非ISA样本,然后通过迭代分类提取城市区域的ISA,再以此为样本对城市区域外部进行分类,最后将分类结果整合完成整幅影像的ISA提取流程。应用本方法对美国雪城地区的DMSP/OLS夜间灯光影像上提取了84个城市区域,提取精度大于95%。从中分别选择高ISA密度和低ISA密度的2个城市区域作为ISA提取的测试区,本文方法在城市区域内的ISA提取总体精度与kappa系数分别为88.23%和0.63;在城市区域外部为78.6%和0.54,均优于人工样本选取方法的提取精度,表明该方法能够实现精度稳定且高效的ISA自动提取。     

State and fate of the remaining tropical mountain glaciers in australasia using satellite imagery

Tropical glaciers are extremely sensitive to a warming climate. In this paper, the evolution of the remaining tropical glaciers in Australasia(Irian Jaya, Indonesia) during the period 1988-2015 was quantified. Landsat series images, a digital elevation model from SRTM, and previously published data were used. Estimated total glacier area in 1988, 1993, 1997 and 2004 was 3.85 km2±0.13 km2, 3.01 km2±0.08 km2, 2.49 km2±0.07 km2 and 1.725 km2 ±0.042 km2, respectively. Only 0.58 km2±0.016 km2 glacierized area remained in 2015 in Puncak Jaya, which is about 84.9% loss in just 27 years. If this rate continued, the remaining tropical glaciers in Australasia would disappear in the 2020 s. Timeseries analysis of climate variables showed significant positive trends in air temperature(0.009°C per year) and relative humidity(0.43% per year) but no considerable tendency was observed for precipitation. Warming climate together with mining activities would accelerate loss of glacier coverage in this region.     

Improvement of glacial lakes detection under shadow environment using ASTER data in Himalayas, Nepal

The detection of glacial lake change in the Himalayas, Nepal is extremely significant since the glacial lake change is one of the crucial indicators of global climate change in this area, where is the most sensitive area of the global climate changes. In the Himalayas, some of glacial lakes are covered by the dark mountains′ shadow because of their location. Therefore, these lakes can not be detected by conventional method such as Normalized Difference Water Index (NDWI), because the reflectance feature of shadowed glacial lake is different comparing to the ones which are located in the open flat area. The shadow causes two major problems: 1) glacial lakes which are covered by shadow completely result in underestimation of the number of glacial lakes; 2) glacial lakes which are partly identified are considered to undervalue the area of glacial lakes. The aim of this study is to develop a new model, named Detection of Shadowed Glacial Lakes (DSGL) model, to identify glacial lakes under the shadow environment by using Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) data in the Himalayas, Nepal. The DSGL model is based on integration of two different modifications of NDWI, namely NDWIs model and NDWI she model. NDWIs is defined as integration of the NDWI and slope analysis and used for detecting non-shadowed lake in the mountain area. The NDWIshe is proposed as a new methodology to overcome the weakness of NDWIs on identifying shadowed lakes in highly elevated mountainous area such as the Himalayas. The first step of the NDWIshe is to enhance the data from ASTER 1B using the histogram equalization (HE) method, and its outcome product is named ASTER he . We used the ASTER he for calculating the NDWI he and the NDWIshe . Integrated with terrain analysis using Digital Elevation Model (DEM) data, the NDWI she can be used to identify the shadowed glacial lakes in the Himalayas. NDWIs value of 0.41 is used to identify the glacier lake (NDWIs≥0.41), and 0.3 of NDWIshe is used to identify the shadowed glacier lake (NDWIshe≤0.3). The DSGL model was proved to be able to classify the glacial lakes more accurately, while the NDWI model had tendency to underestimate the presence of actual glacial lakes. Correct classification rate regarding the products from NDWI model and DSGL model were 57% and 99%, respectively. The results of this paper demonstrated that the DSGL model is promising to detect glacial lakes in the shadowed environment at high mountains.     

Impacts of park landscape structure on thermal environment using QuickBird and Landsat images

Urban parks composed mostly of vegetation and water bodies can effectively mitigate the urban heat island effect. Many studies have investigated the cooling effects of urban parks; however, little attention has been given to park landscape structure. Based on landscape metrics, this study has explored the influences of the park landscape structure on its inner thermal environment, taking heavily urbanized Beijing Municipality in China as the study area. Three indices, including the percentage of landscape (PLAND), landscape shape index (LSI) and aggregation index (AI), were used to measure the composition and configuration characteristics of the landscape components inside the parks. The indices were calculated for five landscape types being interpreted from Quickbird images. Urban thermal conditions were measured using the land surface temperature (LST) derived from Landsat TM images. The results showed that the park LST had a negative relationship with the park size, but no significant relationship was found with park shape. For the park’s interior landscape, however, the configuration and composition characteristics of the landscape components inside the park explained 70% of the park LST variance. The area percentage of water bodies and the aggregation index of woodland were identified as the key influencing characteristics. In addition, when the composition and configuration characteristics of the park landscape components were separately considered, the configuration characteristics (LSI and AI) explained approximately 54% of the variance in park LST, which was comparable with that explained by the composition characteristics (PLAND). Thus, this study suggested that an effective and practical way for urban cooling park design is the optimization of spatial configuration of landscape components inside the park.     

Assessing the influence of highway and high-speed railway construction on local climate using Landsat images in karst areas

Large-scale transportation infrastructure construction in ecologically vulnerable areas such as the karst region of Southwest China requires estimation method for better project design. This research was carried out on a four-lane highway(the Guilin-Guiyang highway, G76) and a two-lane highspeed railway(the Guilin-Guiyang high-speed railway,GGHSR) in karst areas in Guizhou and Guangxi provinces. The highway and high-speed railway were constructed in the 2010 s and covered by Landsat images whose multispectral information could be used for research purposes. In this study, the severity of the impact and the CO_2 emissions from the G76 and GGHSR construction were evaluated. Landsat images and field meteorological measurements were applied to calculate the surface functional parameters(surface temperature and surface wetness) and heat fluxes(latent, sensible and ground heat flux) before and during the highway and high-speed railway construction; the amount of CO_2 emissions during the G76 and GGHSR construction were determined by using budget sheets, which record the detail consumptions of materials and energy. The results showed that the decrease of water evaporation from the highway and high-speed railway construction can reach up to 26.4 m~3 and 20.1 m~3 per kilometer, which corresponds to an average decrease in the vegetation cooling effect of 18.0 MWh per day per highway kilometer and 13.7 MWh per day per high-speed railway kilometer, respectively. At the meantime, the average CO_2 emission densities from the G76 and GGHSR construction can reach up to 24813.7 and 36921.1 t/km, respectively. This study implied that extensive line constructions have a significant impact on the local climate and the energy balance, and it is evident that selecting and planting appropriate plant species can compensate for the adverse effects of line constructions in karst mountain regions.     

CLIMATIC TREND INDICATED BY VARIATIONS OF GLACIERS AND LAKES IN THE TIANSHAN MOUNTAINS

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Remote sensing classification of western Sierra Leone using landsat TM and ETM +

The study examines the changes of land cover/use resources for the period under investigation.An unsupervised vegetation classification is being performed that provides five distinctive classes and thus assesses these changes in five broad land cover classes-high/moist forests,forest regrowth,mixed savanna,bare land/ grass and water.The remote sensing images used in this work are both images of TM and ETM+in different time periods(1986 to 2001)to determine land cover/use changes.A fairly accuracy report is recorded after performing the unsupervised classification,which shows vegetation has been depleted for over the years.Changes created are mostly human and to a lesser extent environment.Human activities are mainly encroachment thus altering the landscape through activities such as population growth,agriculture,settlements,etc.and environment due to some perceive climatic changes.This vegetation classification highlights the importance to acquire and publish information about the country’s partial vegetation cover and vegetation change including vegetation maps and other basic vegetation influencing factors,leading to an understanding of its evolution for a period.     

ASTER数据地表温度反演算法的MATLAB实现

基于ASTERTES算法的思想,用ADE、RATIO和MMD3个模块计算地表温度,并在MATLAB环境下编程实现了该算法。结果表明：该程序简单明了,便于操作,可以在无人为干预下快速实现ASTER数据地表温度反演,非常适合其他领域非遥感专业人员的使用。