Exploitation of Landsat data for snow zonation mapping in the Hindukush,Karakoram and Himalaya (HKH) region of Pakistan

Abstract

In the Hindukush, Karakoram and Himalaya (HKH) region of Pakistan, many glaciological variables are still not known due to the remoteness and harsh weather conditions of the area. A remote sensing technique is therefore applied to map the snow zonation in the HKH region. Landsat 7 ETM+ data for the year 2003 are used in this study. Image classification and image processing techniques are applied to map, for the first time, the major snow zones in the HKH region. Six classes are identified: the results show that the area covered by the highest-altitude snow (Snow I), lower-altitude snow (Snow II), bare ice, debris-covered ice, wet snow and shadow is 21 529.42, 22 472.58, 8696.41, 8038.75, 12 159.37 and 7322.30 km², respectively. The study also indicates that the equilibrium line altitude (ELA) lies between 5000 and 5500 m above sea level, with an accumulation area ratio (AAR) of 0.60.

Citation Butt, M.J., 2013. Exploitation of Landsat data for snow zonation mapping in the Hindukush, Karakoram and Himalaya (HKH) region of Pakistan. Hydrological Sciences Journal, 58 (5), 1088–1096.     

Comparison between four methods for data fusion of ETM+ multispectral and pan images

Four data fusion methods, principle component transform (PCT), brovey transform (BT), smoothing filter-based intensity modulation (SFIM), and hue, saturation, intensity (HSI), are used to merge Landsat—7 ETM+ multispectral bands with ETM+ panchromatic band. Each of them improves the spatial resolution effectively but distorts the original spectral signatures to some extent. SFIM model can produce optimal fusion data with respect to preservation of spectral integrity. However, it results the most blurred and noisy image if the coregistration between the multispectral and pan images is not accurate enough. The spectral integrity for all methods is preserved better if the original multispectral images are within the spectral range of ETM+ pan image.     

Using remote sensing and GIS to investigate the impacts of tourism on forest cover in the Annapurna Conservation Area,Nepal

Tourism is Nepal's largest industry, giving people in rural areas an alternative to subsistence farming. Tourism can have an impact on the forest cover of a region as trees provide firewood for cooking and heating and timber for building accommodation. In 1986 the Annapurna Conservation Area Project was established to ensure that tourism was managed more sustainably, which includes minimising its impact on the forest cover. This study assesses the impacts of tourism on the forest cover in the Annapurna region by comparing Landsat images from 1999 to 2011. This was achieved through spectral classification of different land cover and by assessing the change in forest cover in relation to increasing distances from tourism villages. A major problem with remote sensing in mountainous regions such as Nepal is shadow caused by the relief. This issue was addressed by only assessing areas which were free from shadow, which in effect meant a sample was used rather than the whole study region. The results indicate that there has been an 8 percent reduction in overall forest extent, but this change varies by region. In the northern, drier regions there has been a net increase in forest cover, while in the southern regions there has been a net reduction in forests. The influence of tourism facilities on forest is also variable. Around each of the tourism villages sampled there was a general trend of forest removal decreasing as the distance from each village increased, which indicates tourism does have a negative impact on forests. However, there was an opposite trend in the northern villages that were well inside the conservation area.     

基于Landsat-7ETM+SLC-OFF影像的山地冰川流速提取与评估——以Karakoram锡亚琴冰川为例

Landsat-7机载扫描行校正器（Scan Line Corrector,SLC）失效后的ETM+影像（SLC-OFF影像）约有22%的数据缺失,严重限制了该影像在冰川研究中的应用,特别对长期缺乏高质量遥感影像的高亚洲地区冰川运动连续监测产生较大影响。以Karakoram 中部最大的锡亚琴冰川为例,初步评估了Landsat-7 ETM+SLC-OFF影像在山地冰川表面流速提取方面的适用性和可行性。选取2009年和2010年两景SLC-OFF影像,运用局部直方图匹配法（Local Linear Histogram Match,LLHM）和加权线性回归法（Weighted Liner Regression,WLR）修复缺失数据条带,并利用亚像元互相关方法对修复后两景影像进行冰川表面流速估算。结果表明,LLHM和WLR两种方法均能有效修复冰川区Landsat-7 SLC-OFF影像,其冰流估算结果与同期Landsat-5TM 影像的冰流结果较为一致,三者冰流速估算精度分别为±5.9m ·a^-1、±6.3m ·a^-1和±4.0m ·a^-1,验证了Landsat-7 SLC-OFF 影像在山地冰川流速监测中的应用潜力。     

ETM+影像IHS融合算法改进及其土地覆盖分类实验比较

在总结PCA、IHS融合算法优缺点的基础上,发展了一种改进的IHS融合算法。利用HPF、Brovery、PCA、IHS及改进的IHS融合算法对ETM+全色和多光谱影像进行了融合实验。通过定性、定量分析比较融合影像的质量,并分别对融合后影像和原始影像进行土地覆盖非监督分类实验。选取原始影像和非监督分类精度最高的一种融合影像进行监督分类实验与比较,发现无论是非监督分类还是监督分类,改进的IHS融合影像精度均较高。     

Mapping badland areas using LANDSAT TM/ETM satellite imagery and morphological data

Soil erosion is the most influential component of land degradation for its strong impacts on both natural and agricultural environments. In order to support effective intervention and recovery policies for eroded areas, monitoring techniques should take into account the space–time variability of the processes involved, and make use of assessed mapping methodologies as baseline criteria for studying the dynamics of landform development. When using multispectral data for mapping eroded areas, low spectral separability is a significant limit in areas with complex features, where soil materials are frequently remixed by surface runoff. Since multispectral satellite images are a valuable data source for multi-temporal analyses of erosion processes at the medium scale, we assessed how accurately a badland area can be identified from LANDSAT TM and ETM data. A protocol for an optimal mapping was built up by testing the performance of different supervised algorithms and input layers (spectral and morphological). Tests were carried out in a well-known badland area of Basilicata, Italy, with an extension of  8000 ha. Results obtained from the use of spectral bands (with and without thermal channel) and principal components returned an overall accuracy ranging from 53% (for classification on first three components) to 72% (for classification on all bands from TM), with low values for the kappa coefficient (0.30–0.50), showing that the spectral information alone are insufficient to accurately identify badland areas. In order to improve mapping, we found that the integration of slopes and aspects derived from a Digital Elevation Model (DEM) can overcome problems inherent to the low separability of spectral signatures. The use of morphological data was tested for different classification algorithms and integration approaches. In discriminating badlands, the better performing algorithm was MLC (Maximum Likelihood Classifier) and the best results were obtained by integrating all seven bands (including TIR) with slope and aspect maps as input within the classifier (A > 0.85 and K  0.75 for both the sensors). We selected such parameters because they play an important role in characterising badlands of study area from a morphological perspective but the proposed approach is also conceptually simple and can be easily exported to other areas. The obtained results support the hypothesis that the combined use of remote sensing imagery and auxiliary morphological data significantly improves the mapping of badlands over large areas with heterogeneous features, thus providing a useful methodology for long-term studies on soil erosion processes.     

Retrieval of suspended sediment concentrations in large turbid rivers using Landsat ETM+: an example from the Yangtze River,China

Suspended sediment concentration (SSC) is a critical parameter in the study of river sediment transport and water quality variation, but traditional measurement methods are costly and time‐consuming. This paper is focused on presenting a methodology that may be useful in estimating SSC which is of key importance in process geomorphology and hydrology. In previous studies, remote sensing has been applied to estimate the SSC of sea waters as well as low turbid inland waters like lakes, reservoirs and short river reaches visible within a single Landsat satellite image coverage. Rivers, especially highly turbid large rivers, have largely been ignored. The dataset used in this paper includes measured SSC and multi‐temporal Landsat ETM+ images covering most part of the Yangtze River. Using an effective easy‐to‐use atmospheric correction method that does not require in situ atmospheric conditions, retrieved water reflectance of Band 4 was found to be a good SSC indicator within the large SSC range 22–2610 mg l^–1. The newly developed regression relation between SSC and water reflectance of Band 4 appears to be able to provide a relatively accurate SSC estimate directly from Landsat ETM+ images for the Yangtze River from the upper, the middle to the lower reaches. With the relation it is possible to estimate or map out SSC dynamics of large rivers which lack SSC data due to constraints of conventional measurements. Copyright © 2009 John Wiley & Sons, Ltd.     

ETM和SPOT融合影像制作土地利用分类图

以辽阳地区为试验区,采用ETM多波段和SPOT全色遥感影像为主要信息源。利用遥感图像处理软件ERDAS对影像进行几何配准、图像增强等一系列处理。利用HIS变换和主成分分析法进行影像融合试验,对比分析融合结果,融合后影像同时具有多光谱和高分辨率的特性,提高了影像解译度。参考国家分类标准,选取农村、水体、旱地、林地、菜地、城市和水田七大类进行分类试验。采用监督分类的方法对主成分变换融合后的影像进行土地利用分类。最后,在ArcGIS软件中进行矢量化处理,制作土地利用分类图。使用该方法制作的辽阳地区土地利用分类图,可以满足一般用户对土地利用分类图的要求。     

Comparison Between Four Methods for Data Fusion of ETM＋ Multispectral and Pan Images

Four data fusion methods, principle component transform (PCT), brovey transform (BT), smoothing filter-based intensity modulation(SFIM), and hue, saturation, intensity (HSI), are used to merge Landsat--7 ETMq- multispectral bands with ETM panchromatic band. Each of them improves the spatial resolution effectively but distorts the original spectral signatures to some extent. SFIM model can produce optimal fusion data with respect to preservation of spectral integrity. However, it results the most blurred and noisy image if the coregistration between the multispectral and pan images is not accurate enough. The spectral integrity for all methods is preserved better if the original multispectral images are within the spectral range of ETM pan image.     

喀喇昆仑山厦呈、吕莫慕士塔格山段现代冰川分布及变化特征

在全球气候普遍变暖、冰川大面积退缩的大背景下,为揭示山岳冰川十分发育的喀喇昆仑山脉现代冰川分布及变化特征,以中等空间分辨率(ETM和Landsat 8)卫星数据为主要数据源,采用人机交互式解译方法完成了厦呈慕士塔格山、吕莫慕士塔格山段冰川变化遥感调查,基本查明了区内冰川面积、分布特征和变化状况,共调查1 373处冰川,其中中国境内有554处,境外克什米尔印控区有819处; 同时对区内典型冰川变化进行了2期对比分析,得出冰舌退缩、前进或稳定现象同时存在的结论,为喀喇昆仑山脉冰川变化研究提供了参考依据,为我国西部边海防地区水资源的开发利用和冰雪灾害的防治等提供了科学依据。