塔里木盆地周边地区泥石流灾害的遥感分析

本文以MSS图像和TM图像为基本信息源,从影响泥石流灾害形成的自然要素,如地质（岩性、构造）、地形地貌、植被、水文（河流、冰川、雪被）、地面物质组成以及泥石流沟的遥感判读入手,结合气象资料分析,对塔里木盆地周边地区泥石流灾害的类型、分布状况、孕育和诱发条件进行探讨,进一步对该区泥石流灾害发育程度进行区划,并对危险区进行预测。     

A GIS-based glacier inventory for the Antarctic Peninsula and the South Shetland Islands —A first case study on King George Island

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A GIS-based glacier inventory for the Antarctic Peninsula and the South Shetland Islands —A first case study on King George Island

The aim of the international project “Global Land Ice Measurements from Space (GLIMS)” headed by the US Geological Survey is to establish a world wide glacier inventory based on satellite imagery. This data set will form a first digital baseline study for future glacier monitoring. The presented GIS-based glacier inventory for King George Island is a case study for the area of the Antarctic Peninsula. In the database of the glacier inventory topographic information, specific glaciological parameters as well as metadata will be included. The topographic data consists of drainage basin limits, basin areas, altitudinal ranges, perimeters and mean lengths. Glaciological data sets should comprise information on glacier retreat in different periods, glacier velocities, ice thickness and bedrock topography as well as derived parameters. Modelled and measured mass balance parameters could be included as additional data layers. In particular, these metadata records must comprise background information on data accuracy and data sources and should be compatible with a future data model for the King George Island GIS (KGIS). Three examples illustrate that the GLIMS database will not only contain information valuable for glaciological applications, but also other environmental studies on the island will benefit from this standardised remote sensing data sets. Therefore, a very close link between the data models of KGIS and GLIMS has to be established to enable these synergisms. Finally, better access to historic aerial photography would enable a continuous record of glacier retreat from the beginning of the 1950's onward.     

A GIS-BASED GLACIER INVENTORY FOR THE ANTARCTIC PENINSULA AND THE SOUTH SHETLAND ISLANDS——A FIRST CASE STUDY ON KING GEORGE ISLAND

1　ＩｎｔｒｏｄｕｃｔｉｏｎＴｈｅＷｏｒｋｉｎｇＧｒｏｕｐｏｎＧｅｏｄｅｓｙａｎｄＧｅｏｇｒａｐｈｉｃＩｎｆｏｒｍａｔｉｏｎ (ＷＧ＿ＧＧＩ)ｏｆｔｈｅＳｃｉｅｎｔｉｆｉｃＣｏｍｍｉｔ ｔｅｅｏｎＡｎｔａｒｃｔｉｃＲｅｓｅａｒｃｈ (ＳＣＡＲ )ｌａｕｎｃｈｅｄｔｈｅｐｒｏｊｅｃｔＫｉｎｇＧｅｏｒｇｅＩｓｌａｎｄＧＩＳ (ＫＧＩＳ) .Ｉｎｏｒｄｅｒｔｏｐｒｏｖｉｄｅａｎｏｐｅｒａｔｉｏｎａｌｓｙｓｔｅｍ ,ａｄａｔａｍｏｄｅｌ,ｄａｔａａｃｃｕｒａｃｙｓｔａｎｄａｒｄｓａｎｄａｄａｔａｉｎｖｅｎｔｏｒｙｈａｖ…     

Estimation of Snow Cover Area,Snow Physical Properties and Glacier Classification in Parts of Western Himalayas Using C-Band SAR Data

Snow physical properties, snow cover and glacier facies are important parameters which are used to quantify snowpack characteristics, glacier mass balance and seasonal snow and glacier melt. This study has been done using C-band synthetic aperture radar (SAR) data of Indian radar imaging satellite, radar imaging satellite-1 (RISAT)-1, to estimate the seasonal snow cover and retrieve snow physical properties (snow wetness and snow density), and glacier radar zones or facies classification in parts of North West Himalaya (NWH), India. Additional SAR data used are of Radarsat-2 (RS-2) satellite, which was used for glacier facies classification of Smudra Tapu glacier in Himachal Pradesh. RISAT-1 based snow cover area (SCA) mapping, snow wetness and snow density retrieval and glacier facies classification have been done for the first time in NWH region. SAR-based inversion models were used for finding out wet and dry snow dielectric constant, dry and wet SCA, snow wetness and snow density. RISAT-1 medium resolution scan-SAR mode (MRS) in HV polarization was used for first time in NWH for deriving time series of SCA maps in Beas and Bhagirathi river basins for years 2013–2014. The SAR-based inversion models were implemented separately for RISAT-1 quad pol. FRS2, for wet snow and dry snow permittivity retrieval. Masks for layover and shadow were considered in estimating final snow parameters. The overall accuracy in terms of R² value comes out to be 0.74 for snow wetness and 0.72 for snow density based on the limited ground truth data for subset area of Manali sub-basin of Beas River up to Manali for winter of 2014. Accuracy for SCA was estimated to be 95 % when compared with optical remote sensing based SCA maps with error of ±10 %. The time series data of RISAT-1 MRS and hybrid data in RH/RV mode based decompositions were also used for glacier radar zones classification for Gangotri and Samudra Tapu glaciers. The various glaciers radar zones or facies such as debris covered glacier ice, clean or bare glacier ice radar zone, percolation/refreeze radar zone and wet snow, ice wall etc., were identified. The accuracy of classified maps was estimated using ground truth data collected during 2013 and 2014 glacier field work to Samudra Tapu and Gangotri glaciers and overall accuracy was found to be in range of 82–90 %. This information of various glacier radar zones can be utilized in marking firn line of glaciers, which can be helpful for glacier mass balance studies.     

Snow and glacier melt runoff model to estimate hydropower potential

Himalayan region has high concentrations of mountain glaciers. Large extent of this region is covered by seasonal snow during winter. Runoff generates from melting of these snow and glaciers is one of the important sources of water for the Himalayan Rivers. Glaciers and snowfields are distributed throughout the Himalayas and form a source of numerous streams. Due to steep slopes, all such streams have potential sites for hydropower generation. If this potential is fully utilized, it will help in generating power from environmentally friendly Run-of-River (RoR) hydropower stations. Considering these aspects, a stream flow simulation model was developed for small streams. This will help in estimation of average seasonal unrestricted hydropower potential of snow and glaciated streams for winter, summer, monsoon and autumn seasons. Information generated through remote sensing technique as glacier, permanent snow cover, seasonal snow cover, altitude of snow and glaciers were used in conjunction with daily maximum and minimum temperature, rainfall and discharge. The model was developed for Malana nala located in Parbati River basin near Kullu in Himachal Pradesh. It was validated at adjacent Tosh nala in the same basin. Seasonal runoff computed from the model is comparable with observed data for all seasons except Monsoon. Good results in autumn, winter and summer seasons demonstrates usefulness of runoff model to assess hydropower potential of snow and glaciated streams and therefore, the model was applied to ungauged Sorang Gad and Kirang Khad. In winter runoff was estimated as 1.8 and 1.69 cumecs for Kirang Khad and Sorang Gad, respectively. This is important, as viability of hydropower station depends upon winter stream runoff. These results suggest that the model is useful tool to assess initial estimate of hydropower potential for large number of snow and glaciated streams, for which no hydrological data is available.     

Mass Balance Estimation of Dokriani Glacier in Central Indian Himalaya Using Remote Sensing Data

Dokriani Glacier is regarded as one of the important glaciers of Bhagirathi River basin, which fed river Ganges. The length of the glacier is about 4.6 km, and snout elevation is about 4028 m m.s.l. The mass balance of this glacier was calculated using field-based measurements for few years during 1994 to 2000. However, due to remote and poor accessibility, the field-based measurements could not continue; thus, remote sensing-based methods become useful tool to estimate the long-term mass balance of the glacier. In this study, glacier mass balance has been determined using accumulation area ratio (AAR) method. Remote sensing data sets, e.g. Landsat TM, ETM?+?and OLI, have been used to estimate AAR for different years from 1994 to 2014. An attempt has also been made to develop a mathematical relationship between remote sensing-derived AAR and field-observed mass balance data of the glacier. Further, this relationship has been used to estimate mass balance of the glacier for different years using remote sensing-derived AAR. Estimated mass balance was validated from ground-observed mass balance for few years. The field-observed and remote sensing-derived mass balance data are compared and showed high correlation. It has been observed that AAR for the Dokriani Glacier varies from 0.64 to 0.71. Mass balance of the glacier was observed between ??15.54 cm and ??50.95 cm during the study period. The study highlights the application of remote sensing in mass balance study of the glaciers and impact of climate change in glaciers of Central Indian Himalaya.     

基于遥感和GIS的洪水坝河流域冰川变化研究

以洪水坝河流域为例,利用1956年的地形图和2003年的ASTER遥感影像及数字高程模型,在GIS的支持下对两期数据进行统计分析,结果表明:近47年来,洪水坝河流域冰川面积减少了14.04%,长度退缩了17.28%,储量减少了2.26%。研究认为,气温显著升高是洪水坝河流域冰川快速萎缩的主要原因。在和祁连山地区、西藏以及天山地区的冰川进行对比后,发现研究区冰川消融的速率介于三地之间,初步推测是由研究区所在区域的气候和自身属性共同作用的结果。     

中国西部喀喇昆仓明铁盖多金属矿化区的卫星遥感勘查

成矿环境的地质分析与遥感探测标志是矿产遥感定位的     

Role of satellite remote sensing in land system mapping,land resources inventory and land use planning: A sample study of kemang river basin,Arunachal Pradesh

Here an attempt has been made to highlight the importance of satellite remote sensing in land system mapping, land resources inventory and land use planning of a sample river basin (in Arunachal Pradesh) covering an area of 10,186 sq. km. The (Kemang) river basin has been divided intofour land systems viz : structural, denudational, piedmont and fluvial. Each system has been analysed with respect toeight land water-land use (resource) parameters for proper land use and environmental management of the river basin. A tentative‘productivity/development strategy ranking’ is also given for optimum planning of the basin.     

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。     

高山冰川多时相多角度遥感信息提取方法

提出一种多角度遥感影像的冰川信息提取方法。通过"全域—局部"的阈值分割方法获取短时期内不同时相的遥感影像的冰雪边界,结合地形信息和多时相遥感影像的太阳角度信息,联合消除山体阴影对冰川的遮挡,并以多期影像的最小冰雪边界作为最佳冰川边界。以托木尔峰西侧冰川为研究对象,采用2009—2010年4个时相的遥感影像提取冰川信息。结果表明多角度遥感提取的冰川边界效果好,能有效地排除积雪与山体阴影的干扰。     

Variation of Snowline and Mass Balance of Glaciers of Warwan and Bhut Basins of Western Himalaya Using Remote Sensing Technique

Glaciers are natural reservoirs of fresh water in frozen state and sensitive indicators of climate change. Among all the mountainous glaciated regions, glaciers of Himalayas form one of the largest concentrations of ice outside the Polar Regions. Almost all the major rivers of northern India originate from these glaciers and sustain perennial flow. Therefore, in view of the importance and role of the glaciers in sustaining the life on the Earth, monitoring the health of glaciers is necessary. Glacier??s health is monitored in two ways (i) by mapping the change in extent of glaciers (ii) by finding variation in the annual mass balance. This paper has been discussed the later approach for monitoring the health of glaciers of Warwan and Bhut basins. Mass balance of glaciers of these two basins was determined based on the extraction of snow line at the end of ablation season. A series of satellite images of AWiFS sensor were analysed for extraction of snowline on the glaciers for the period of 2005, 2006 and 2007. The snow line at the end of ablation season is used to compute accumulation area ratio (AAR = Accumulation area/Glacier area) for each glacier of basins. An approach based on relationship of AAR to specific mass balance (computed in field) for glaciers of Basapa basin was employed in the present study. Mean of specific mass balance of individual glacier for the year 2005, 2006 and 2007 of Warwan basin was found to be ?ve 0.19?m, ?ve 0.27?m and ?ve 0.2?m respectively. It is 0.05?m, ?ve 0.11?m and ?ve 0.19?m for Bhut basin. The analysis suggests a loss of 4.3 and 0.83?km3 of glacier in the monitoring period of 3?years for Warwan and Bhut basins respectively. The overall results suggest that the glaciers of Warwan basin and Bhut basins have suffered more loss of ice than gain in the monitoring period of 3?years.     

遥感技术在小流域水土流失快速调查中的应用——以老高川地区为例

以SPOT与TM融合图像为遥感信息源,对孤山川流域老高川地区进行1:5万比例尺水土流失遥感调查,分析了小流域水土流失的主要影响因素,指出了遥感技术与地理信息系统结合是遥感技术在小流域水土流失快速调查的发展方向.     

Snow cover area variability assessment in the upper part of the Satluj river basin in India

In high-altitude areas, snow cover plays a significant role in mountainous hydrology. Satluj, which is a snow-fed river, is a part of the Indus River system in the western Himalayas. Snow cover area (SCA) variability in this river basin affects the spatio-temporal flow availability and avalanche events. Keeping this in mind, the present study focuses on SCA variability and its relationship with various topographical features such as elevation, slope and aspect. The study has been carried out in the upper part of the Satluj River Basin on the basis of MODIS Terra (MOD10A2) data from 2001 to 2014. It has been noticed that the average annual SCA in this part of the Satluj River Basin varies from 44 to 56% with an average of about 48% of the total basin area of 16, 650 km². Further, snow accumulation and depletion curves have been suggested for assessing the SCA in the study area.     

Study of influence of terrain and climatic factors on groundwater-level fluctuation in a minor river basin using GIS

Terrain environment parameters play a vital role in controlling groundwater movement:its recharge and discharge me-chanisms.Many earlier studies have been conducted relating terrain parameters and groundwater condition using conventional me-thods and remote sensing techniques.This study,however,endeavors to spatially visualize the degree of fluctuation in the ground-water level of Ongur,a minor river basin in different terrain units under different seasons(monsoon and summer) for three histori-cal periods of time using Geographic Information System(GIS) raster analysis.     

Study of influence of terrain and climatic factors on groundwater-level fluctuation in a minor river basin using GIS

Terrain environment parameters play a vital role in controlling groundwater movement: its recharge and discharge mechanisms. Many earlier studies have been conducted relating terrain parameters and groundwater condition using conventional methods and remote sensing techniques. This study, however, endeavors to spatially visualize the degree of fluctuation in the groundwater level of Ongur, a minor river basin in different terrain units under different seasons (monsoon and summer) for three historical periods of time using Geographic Information System (GIS) raster analysis.     

Landslide Mapping and Assessment by Integrating Landsat-8, PALSAR-2 and GIS Techniques: A Case Study from Kelantan State,Peninsular Malaysia

Integration of satellite remote sensing data and GIS techniques is an applicable approach for landslide mapping and assessment in highly vegetated regions with a tropical climate. In recent years, there have been many severe flooding and landslide events with significant damage to livestock, agricultural crop, homes, and businesses in the Kelantan river basin, Peninsular Malaysia. In this investigation, Landsat-8 and phased array type L-band synthetic aperture radar-2 (PALSAR-2) datasets and analytical hierarchy process (AHP) approach were used to map landslide in Kelantan river basin, Peninsular Malaysia. Landslides were determined by tracking changes in vegetation pixel data using Landsat-8 images that acquired before and after flooding. The PALSAR-2 data were used for comprehensive analysis of major geological structures and detailed characterizations of lineaments in the state of Kelantan. AHP approach was used for landslide susceptibility mapping. Several factors such as slope, aspect, soil, lithology, normalized difference vegetation index, land cover, distance to drainage, precipitation, distance to fault, and distance to the road were extracted from remotely sensed data and fieldwork to apply AHP approach. The excessive rainfall during the flood episode is a paramount factor for numerous landslide occurrences at various magnitudes, therefore, rainfall analysis was carried out based on daily precipitation before and during flood episode in the Kelantan state. The main triggering factors for landslides are mainly due to the extreme precipitation rate during the flooding period, apart from the favorable environmental factors such as removal of vegetation within slope areas, and also landscape development near slopes. Two main outputs of this study were landslide inventory occurrences map during 2014 flooding episode and landslide susceptibility map for entire Kelantan state. Modeled/predicted landslides with a susceptible map generated prior and post-flood episode, confirmed that intense rainfall throughout Kelantan has contributed to produce numerous landslides with various sizes. It is concluded that precipitation is the most influential factor for landslide event. According to the landslide susceptibility map, 65% of the river basin of Kelantan is found to be under the category of low landslide susceptibility zone, while 35% class in a high-altitude segment of the south and south-western part of the Kelantan state located within high susceptibility zone. Further actions and caution need to be remarked by the local related authority of the Kelantan state in very high susceptibility zone to avoid further wealth and people loss in the future. Geo-hazard mitigation programs must be conducted in the landslide recurrence regions for reducing natural catastrophes leading to loss of financial investments and death in the Kelantan river basin. This investigation indicates that integration of Landsat-8 and PALSAR-2 remotely sensed data and GIS techniques is an applicable tool for Landslide mapping and assessment in tropical environments.     

Updated Inventory of Glacial Lakes in Teesta Basin Using Remote Sensing Data for Use in GLOF Risk Assessment

Detailed inventory of glacial lakes in a Glacial Lake Outburst Flood (GLOF) prone area is vital for disaster mitigation. Availability of cheaper high resolution satellite data from Indian remote sensing satellites enables us to create up-to-date inventory for use in prioritisation of glacial lakes for GLOF risk assessment. Earlier inventories show presence of more glacial lakes in Brahmaputra basin in Indian Himalaya. Teesta River is one of the tributary of Brahmaputra and previous studies have shown that the inventory of glacial lakes in Teesta basin varies from 143 to 320. In the present study, the inventory carried out using satellite data of years 2000, 2007 and 2014 show presence of 301 (25.789 km²), 302 (26.081 km²) and 644 (29.706 km²) glacial lakes in Teesta basin respectively. The steep increase in number of lakes in the latest inventory is primarily due to the finer spatial resolution of satellite data used. Analysis of water spread area of glacial lakes at different altitudes shows that most of the lakes in the higher altitudes are small in size. It is observed that more than 66% of lakes are in the altitude beyond 4500 m and of size less than 50,000 sqm (5 ha). Out of 301 glacial lakes inventoried during 2000, water spread area of 6 lakes have decreased in 2014 and 31 lakes have shown increase in area. Out of these 31 lakes, 17 lakes are classified as end moraine dammed lakes and among them, 14 are located in Upper Teesta sub-basin and in higher altitudes (beyond 5000 m). The prioritisation of these lakes for GLOF risk needs to be carried out with detailed field investigation.     

A method for monthly mapping of wet and dry snow using Sentinel-1 and MODIS: Application to a Himalayan river basin

Satellite Remote Sensing, with both optical and SAR instruments, can provide distributed observations of snow cover over extended and inaccessible areas. Both instruments are complementary, but there have been limited attempts at combining their measurements. We describe a novel approach to produce monthly maps of dry and wet snow areas through application of data fusion techniques to MODIS fractional snow cover and Sentinel-1 wet snow mask, facilitated by Google Earth Engine. The method is demonstrated in a 55,000 km² river basin in the Indian Himalayan region over a period of ∼2.5 years, although it can be applied to any areas of the world where Sentinel-1 data are routinely available. The typical underestimation of wet snow area by SAR is corrected using a digital elevation model to estimate the average melting altitude. We also present an empirical model to derive the fractional cover of wet snow from Sentinel-1. Finally, we demonstrate that Sentinel-1 effectively complements MODIS as it highlights a snowmelt phase which occurs with a decrease in snow depth but no/little decrease in snowpack area. Further developments are now needed to incorporate these high resolution observations of snow areas as inputs to hydrological models for better runoff analysis and improved management of water resources and flood risk.