井冈山地形特征与土地利用类型分布相关性研究

针对土地覆被类型在不同高程、坡度、地形起伏度等地形地貌特征下,差异性明显的问题,提出了一种分析和研究地形地貌特征与土地覆被类型相关性的方法。通过数学分析与计算,将土地覆被类型在不同地形景观下的分布情况进行了统计分析。引入高程、坡度、坡向等地形因子信息,通过将地形因子通过一定规则进行分级,并进行统计、计算,分析了不同地形特征下土地利用类型的分布规律、变化趋势和成因,说明了地形对土地利用分类的重要性。研究发现,土地利用类型在不同高程、坡度、地形起伏度上,呈现出阶梯状变化的特征。在较低的高程、坡度、地形起伏度区域内,主要分布着与人类的生产、生活密切相关的土地利用类型,如水田、旱地、果园、茶园、水田、坑塘水面、内陆滩涂、城市、建制镇、村庄、采矿用地等。有林地等则主要分布在高程、坡度、地形起伏度较高的区域。这些地区人类活动少,土地开发程度也较弱,因而多是自然植物覆被。     

GEDI地面高程和森林冠层高度的精度评价与影响分析

精确地提取地面高程和植被冠层高度,对于地形地貌、生态学等方面的研究具有重要意义。2018年12月发射的新一代全球生态系统动力学调查雷达（GEDI）为地面高程和植被冠层高度大范围精确提取提供了前所未有的机会。研究旨在利用机载激光雷达数据验证GEDI提取的地面高程和冠层高度精度,并探讨地理定位误差、地形坡度、坡向、植被覆盖度、方位角、采集时间、光束类型和不同森林类型因素对其精度的影响。结果表明：通过校正GEDI数据地理定位误差,可以明显提高其提取的地面高程和冠层高度精度;影响冠层高度提取精度最主要的因素是植被覆盖度,其次是坡度;影响地面高程提取精度的主要因素为坡向、坡度。植被覆盖度大于25%时,数据精度更高;坡度为0°—5°的缓坡地区地面高程和冠层高度精度最高。该研究结果将为GEDI数据筛选与应用提供依据。     

基于DEM的土地利用空间格局分析——以大连市普兰店为例

为了了解普兰店市景观类型变化与地形分布的关系,本文利用2000和2010年Landsat5TM遥感影像,在ENVI5.3软件的支持下,获取普兰店土地利用类型,并基于DEM数据获取高程、坡度、坡向,将土地利用数据与三者相叠加分析,研究发现:(1)2000～2010年普兰店市土地利用类型变化具有主明显的坡向型特征,集中在半阴坡、阴坡、半阳坡上。(2)2000～2010年普兰店市土地利用类型变化量随着坡度增加而减少。(3)2000～2010年普兰店市土地利用类型变化量主要集中在0～200m高程级别上。该研究结果可为普兰店市土地利用规划部们提供帮助。     

三峡库区巴东段地质灾害因子关联规则挖掘

选择地质灾害较为发育的巴东县为研究区,并以该区灾害点为数据样本,利用GIS将灾害点与地层岩性、高程、坡度、坡向、水系组合、遥感影像土地利用分类结果等6个影响因子进行叠加分析,选取灾害点的灾害类型、灾害规模、灾害体的物质类型、高程差、水系岸别等5个属性与叠加分析结果利用Apriori算法进行关联规则挖掘,最后挖掘出灾害规模与水系组合间关系等单因素间关联以及不同灾害属性与各因子间的关系等多因素间关联。通过与前人的相关研究成果对比分析,证明得出的规则具有合理性并符合实际情况,可为地质灾害分析决策提供先验知识。     

基于MODIS数据的玛纳斯河山区雪盖年内变化特征研究

基于2000年～2010年的MODIS/Terra积雪8d合成数据(MOD10A2)与DEM数据,通过计算和分析不同高程带、不同坡向和不同坡度的积雪覆盖率,研究了新疆玛纳斯河山区雪盖的年内变化特征。结果表明:①研究区平均积雪覆盖率最高为一月中旬的67.8%,最低为七月中旬的11.9%,年内变化总体上呈V字型,积雪分布与气温关系密切;②可将研究区雪盖年内分布情况归纳为1600m以下、1600m～3800m和3800m以上共三个高程带,各高程带内雪盖分布的年内变化较为相似,不同高程带则差异明显。从年内波动情况来看,低海拔地区年内波动幅度最大,随着海拔上升,波动幅度逐渐减小;③3800m以下各坡向和坡度地区积雪覆盖率均表现为一月最高,七月最低,四月和十月介于二者之间,而3800m以上地区积雪覆盖率全年最高值则出现在四月和十月;④各坡度和坡向区域雪盖的年内变化与所在高程带的总体情况基本相似,说明坡度和坡向对雪盖分布的影响是在高程影响的基础上产生的。     

甘肃省榆中县地形对耕地分布影响

针对现有研究在地形对耕地分布影响中较少考虑地形因子间交互作用,且忽视了沟壑密度等因子影响的问题,以甘肃省榆中县为例,在地貌分区基础上利用分形指数分析了耕地分布特征,并通过地理探测器分析高程、坡度、坡向和沟壑密度对耕地分布的影响。结果表明,河谷平原区与黄土塬区耕地连片性较好,河谷平原区、黄土丘陵区和北部石质低山丘陵区耕地空间分布较稳定;各地貌区影响耕地分布的主导因子不同,南部石质山地和黄土丘陵区是高程,黄土塬和河谷平原区是坡度,北部石质低山丘陵区是沟壑密度;地形因子交互作用均表现为增强,其中沟壑密度影响作用不可忽略。     

安徽省土地利用地形梯度格局变化分析

针对研究土地利用变化方面基于非空间属性数据库的数据研究方法在空间位置和形象思维方面的不足,综合分析高程、坡度等多重因素研究不足的问题,提出了一种基于地形梯度的土地利用格局变化分析方法。以安徽省2000年、2005年和2010年Landsat TM影像为主要数据源,利用遥感和地理信息系统方法,探讨了安徽省2000~2010年,不同地形条件下自然因素以及人文因素对土地利用格局时空演变过程中的影响;基于数字高程模型,结合地学信息图谱理论,通过等间距(Equal Interval)分类方法,计算土地利用图谱类型的地形梯度分布。研究结果表明:安徽省土地利用结构以林地、耕地和建设用地为主,2000~2010年,未利用地和耕地面积呈不断减少趋势,建设用地面积由2000年的26 270.67km2增加到2010年的38 996.49km2,呈现不断增加的趋势,且增加幅度较大,破碎度也随之加重。前期变化型的优势分布区是地形位等级1~2级,后期变化型的分布指数总体呈增加趋势,持续变化型的分布指数变化呈现波动起伏的曲线,稳定型分布指数在1~6级呈现减小趋势,在6~10级呈现增加趋势。     

天山典型区卫星雪盖的年内变化特征分析

利用2000年1月~2001年5月位于天山中段的Landsat TM及ETM+卫星遥感数据,提取逐月雪盖信息,结合研究区数字高程模型数据获取不同地形条件、不同垂直带上的雪盖逐月分布状况,从而分析雪盖的空间分布特征和时间变化规律。研究结果表明,年内雪盖面积与海拔带、坡向带、坡度带之间呈现一定的相关性。总体而言雪盖比率随海拔上升而增大,随坡度增大而减小;雪盖边界高度呈现明显夏秋高、冬春低的变化规律;雪盖面积在特定时间段存在东西坡向上的差异,总体差异小于南北坡向的差异。研究结论为天山水资源的合理利用以及气候与环境变化研究提供科学依据。     

汶川震后地质灾害遥感信息提取及分布特征分析

以汶川县为研究区,利用遥感、GIS和计算机三维可视化技术,对地质灾害进行了信息提取和解译,共解译滑坡53个,崩塌1 575个,地质灾害面积76.58 km2,并建立了相应的数据库。利用GIS空间分析功能,结合高程、坡度、坡向、地层岩性、地震烈度和水系等因子对研究区地质灾害的空间分布特征进行了分析,并采用层次分析法对研究区地质灾害易发性预测进行了分区研究。研究结果表明,本数据与分析对安置地的重建和地震灾害预测具有很好的参考价值。     

特征控制下的多样图地形纹理合成算法

针对三维虚拟室外场景的建模与绘制需求,提出一种多样图地形纹理合成算法。以地形数字高程模型数据和样图集为基础,根据用户自定义的纹理合成规则控制地形的高程值和坡度特征,并自动合成地形纹理。实验结果表明,利用该算法合成的纹理能够较好地反映自然界地形的分布情况,增强三维场景绘制的真实感。     

基于Landsat8热红外遥感数据的山地地表温度地形效应研究

地表温度是影响地表能量收支平衡的重要参量,能够综合反演地表的水热交换过程。虽然当前在基于地表温度开展全球或者区域尺度的地表能量平衡研究方面取得一系列的进展,但是面向山地区域尺度的类似研究仍然面临较大的挑战。为分析山地复杂地形对山地地表温度时空分布的影响规律,基于具有较高空间分辨率的Landsat 8热红外数据,以我国西南典型山地为研究对象,定量反演该区域的地表温度空间分布状况,结合SRTM90DEM数据,选择从海拔、坡度和坡向3个关键地形因子角度分析山地地表温度的地形效应特征。结果发现:山地地表温度随地形因子均呈现出十分显著的变化特征。总体而言,地表温度均随着海拔和坡度的升高而降低,而在坡向方面,南坡的温度相比北坡的温度要高。在地形效应分析的基础上,通过开展1km空间尺度地形和地表温度的空间统计分析发现,山地1km尺度下地表温度存在较大的空间异质性,且其影响不可忽略。研究结果表明:开展山地地表水热过程遥感动态监测需高空间分辨率地表温度作为数据支持,以准确描述山地地形因素对地表能量交换过程的影响。     

Parametrized BRDF for atmospheric and topographic correction and albedo estimation in Jiangxi rugged terrain,China

A method is presented for bi‐directional reflectance distribution function (BRDF) parametrization for topographic correction and surface reflectance estimation from Landsat Thematic Mapper (TM) over rugged terrain. Following this reflectance, albedo is calculated accurately. BRDF is parametrized using a land‐cover map and Landsat TM to build a BRDF factor to remove the variation of relative solar incident angle and relative sensor viewing angle per pixel. Based on the BRDF factor and radiative transfer model, solar direct radiance correction, sky diffuse radiance and adjacent terrain reflected radiance correction were introduced into the atmospheric‐topographic correction method. Solar direct radiance, sky diffuse radiance and adjacent terrain reflected radiance, as well as atmospheric transmittance and path radiance, are analysed in detail and calculated per pixel using a look‐up table (LUT) with a digital elevation model (DEM). The method is applied to Landsat TM imagery that covers a rugged area in Jiangxi province, China. Results show that atmospheric and topographic correction based on BRDF gives better surface reflectance compared with sole atmospheric correction and two other useful atmospheric‐topographic correction methods. Finally, surface albedo is calculated based on this topography‐corrected reflectance and shows a reasonable accuracy in albedo estimation.     

Land surface phenology of North American mountain environments using moderate resolution imaging spectroradiometer data

Monitoring and understanding plant phenology is becoming an increasingly important way to identify and model global changes in vegetation life cycle events. High elevation biomes cover twenty percent of the Earth's land surface and provide essential natural resources. These areas experience limited resource availability for plant growth, development, and reproduction, and are one of the first ecosystems to reflect the harmful impact of climate change. Despite this, the phenology of mountain ecosystems has historically been understudied due to the rough and variable terrain and inaccessibility of the area. In addition, although numerous studies have used synoptically sensed data to study phenological patterns at the continental and global scales, relatively few have focused on characterizing the land surface phenology in mountainous areas. Here we use the MODIS/Terra + Aqua satellite 8-day 500 m Nadir BRDF Adjusted Reflectance product to quantify the land surface phenology. We relate independent data for elevation, slope, aspect, solar radiation, and temperature as well as longitude and latitude with the derived phenology estimates. We present that satellite derived SOS can be predicted based on topographic and weather variables with a significant R²adj between 0.56 and 0.62 for the entire western mountain range. Elevation and latitude exhibit the most significant influences on the timing of SOS throughout our study area. When examined at both the local and regional scales, as well as when accounting for aspect and temperature, SOS follows closely with Hopkins' Bioclimatic Law with respect to elevation and latitude.     

TM遥感影像的地形辐射校正研究

从地面所接收到的太阳直接辐射、天空散射辐射和临近地形反射附加的辐射三个方面分析计算地面每个像元的太阳总辐射,并在此基础上建立地表真实反射率恢复模型,实现对地形的辐射校正。在算法实现上,采用交互式数据语言（Interactive Data Language,IDL）,结合6S大气校正模型和数字高程模型（DEM）进行编程实现。利用北京山区的TM遥感影像所做的实验表明该方法能有效地消除卫星影像中地形的影响,为影像的后续处理提供更真实的信息。     

Siberian silkmoth outbreak pattern analysis based on SPOT VEGETATION data

The spatial pattern of Siberian silkmoth outbreak in south Siberian mountains was analysed based on SPOT VEGETATION data. A digital elevation model (DEM) was also used to relate outbreak area dynamics with topographic elements (elevation, azimuth and slope steepness). To avoid bias of spatial pattern data, areas with a given damage category and with given azimuth, slope steepness and elevation were referenced to the areas with similar parameters within the entire study area. The outbreak began between the elevations of ～430–480 m and on south‐west slopes with steepness <5°; these conditions appear to be the most favourable pest habitat. As the pest searched for food it moved up and down slope, resulting in an elevation distribution split within a range of ～390–540 m and slope steepness up to 15°. In the final phase the azimuth distribution of damaged stands became even, showing that pests at this phase settle in non‐optimal habitat. The final outbreak area was ～20 000 ha, which is in good agreement with on‐ground data. The correlation between the initial phase of infestation and topographic features can be used to prioritize pest monitoring. Data obtained show that the SPOT VEGETATION sensor is applicable for monitoring taiga landscapes vulnerable to Siberian silkmoth outbreaks.     

Estimating surface net solar radiation by use of Landsat-5 TM and digital elevation models

The ground surface net solar radiation is the energy that drives physical and chemical processes at the ground surface. In this paper, multi-spectral data from the Landsat-5 TM, topographic data from a gridded digital elevation model, field measurements, and the atmosphere model LOWTRAN 7 are used to estimate surface net solar radiation over the FIFE site. Firstly an improved method is presented and used for calculating total surface incoming radiation. Then, surface albedo is integrated from surface reflectance factors derived from remotely sensed data from Landsat-5 TM. Finally, surface net solar radiation is calculated by subtracting surface upwelling radiation from the total surface incoming radiation.     

Estimating surface solar radiation over complex terrain using moderate‐resolution satellite sensor data

It is well known that taking into account the influence of complex terrain is essential when using high‐resolution satellite remotely sensed data to estimate surface net solar radiation. This paper investigates whether this is also the case when using moderate‐resolution satellite remotely sensed data, such as Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR). Firstly, topographic data from a gridded digital elevation model, field measurements from the Tibetan Plateau, and results from the atmospheric 6S model are used to estimate surface incoming solar radiation over complex terrain. The associated error caused by not taking into account terrain complexity is then calculated, and the relative radiation error is estimated by standardizing the error. The results show that the standard deviation of the relative radiation error depends on the solar zenith angle, standard deviation of the height, and resolution of the digital elevation model (or resolution of the satellite sensor data). A single regression equation describes the change in the standard deviation of the relative radiation error with solar zenith angle, standard deviation of height, and resolution of the digital elevation model. This demonstrates that it is necessary to consider terrain complexity when using moderate‐resolution remotely sensed data.     

The influence of meteorological conditions and topographic parameters on the beech forest microclimate of Simbruini Mountains,central Italy

The relation between vegetation surface temperature and remotely sensed spectral vegetation indices has been examined by a number of authors. The observed linear decrease in surface temperature with the increase in vegetation cover density has generally been explained in terms of the increase in latent heat flux associated with greater amounts of transpirationally active vegetation. However, these investigations have initially concentrated in spatially uniform crop or pasture targets on level terrain, excluding more complex forested environments with variable Sun-sensor-surface geometry. In irregular terrains, the vegetation surface temperature may be strongly influenced by topographic parameters, such as altitude and insulation angle, so that the actual forest microclimate is often difficult to evaluate. Moreover, in the thermal regime, the emission of radiative flux within the canopy element is very tightly coupled to the environment through driving mechanisms such as meteorological conditions. In fact, the allocation of absorbed solar radiation into sensible heat flux and latent heat flux is dominated by the availability of water at the Earth's surface and thus by precipitations and air temperature conditions. In this paper, which uses remotely sensed inputs of surface temperature and vegetation fractional cover, the effects of topographic parameters and vegetation cover density on surface temperature of vegetation are investigated based on Landsat 5 satellite images obtained in the daytime of two clear summer days with different antecedent meteorological conditions. For both scenes analysed, results indicate that altitude as well as the orientation of the surface relative to the Sun were the most important factors controlling surface temperatures of beech forests of Simbruini Mountains, in central Italy.     

Topographic correction algorithm for remotely sensed data accounting for indirect irradiance

The solar irradiance incidents upon terrain surface are composed of three parts, i.e. direct solar irradiance, diffuse sky irradiance and reflected irradiance from the adjacent surface, respectively. Most of the topographic correction models only account for the topographic effect induced from direct solar irradiance, and few models take the topographic effects from the last two components of solar irradiance into account. A physically based topographic correction algorithm aiming to overcome this shortcoming, called a three-factor correction model, was developed based on theoretical analysis of radiation transferring processes along an undulating surface, atmosphere and satellite sensor geometry under the assumption of Lambertian surface. On the basis of this three-factor correction model, an advanced algorithm accounting for the bidirectional reflectance distribution function (BRDF) nature of non-Lambertian surface, called the three-factor+C topographic correction model, was developed by introducing an empirical parameter C to approximate the indirect irradiance contribution of non-Lambertian surface. Performances of these two newly developed algorithms were tested and compared with those of Cosine and C correction algorithms for a selected rugged terrain on the south flank of the Qinling Mountain, China. Visual comparison and statistical analysis were adopted for quantitative evaluation on topographic corrections of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) image in the study. The results suggested that the general performance of the algorithms for topographic correction ranks the three-factor+C correction, C correction, three-factor correction and Cosine correction from excellent to poor in order, which implies the promising potential of the proposed algorithms in effective topographic correction applications in remote sensing techniques.