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.     

Land cover dynamics monitoring with Landsat data in Kunming,China: a cost-effective sampling and modelling scheme using Google Earth imagery and random forests

Changes in forest composition impact ecological services, and are considered important factors driving global climate change. A hybrid sampling method along with a modelling approach to map current and past land cover in Kunming, China is reported. MODIS land cover (2001–2011) data-sets were used to detect pixels with no apparent change. Around 3000 ‘no change points’ were systematically selected and sampled using Google Earth’s high-resolution imagery. Thirty-five per cent of these points were verified and used for training and validation. We used Random forests to classify multi-temporal Landsat imagery. Results show that forest cover has had a net decrease of 14385?ha (1.3% of forest area), which was primary converted to shrublands (11%), urban and barren land (2.7%) and agriculture (2.5%). Our validation indicates an overall accuracy (Kappa) of 82%. Our methodology can be used to consistently map the dynamics of land cover change in similar areas with minimum costs.     

Contrasting Signals of Glacier Changes in Zanskar Valley,Jammu & Kashmir,India Using Remote Sensing and GIS

The study of advancement and recession of the glaciers in the Himalayas is essential due to their contrasting response towards climatic change. In the present study, Survey of India (SOI) topographical maps of 1962, IRS: LISS-III image of 2001 and LANDSAT-5: TM (Thematic Mapper) image of 2009 were used to analyze the glacier fluctuations in a part of Zanskar valley. The analysis carried out on 212 glaciers indicated decrease of 57 km² (8 %) of glacier area over many glacier which was partly compensated with area increase by 42 km² (6 %) in other glaciers, resulting an overall glacier area decrease by only 15 km² (2 %) from 1962–2001. Due to glacier fragmentation the number of glaciers increased from 212 in 1962 to 238 by 2001. Although majority of glaciers (88 %) exhibited retreat (up to 13 my^?1), minor advancement (<15 my^?1) also took place in few glaciers during this period. Advancement took place mainly in larger glaciers (2–5 km² and >5 km²) located over wider altitudinal range (700 m–1,000 m) whereas smaller glaciers (<2 km²) with narrow altitudinal range (100 m–500 m) exhibited retreat. The supraglacial debris analysis indicated that percentage of debris cover over glaciers ranges from 1.43 % to 18.15 %. Smaller glaciers (<2 km²) were debris free in comparison to the larger glaciers (>5 km²). During 2001–2009 majority of the glaciers were apparently stable in terms of their area and snout position indicating less impact of climate forcing in parts of Zanskar valley as compared to other parts of the Himalaya.     

Land degradation mapping in the upper catchment of river Tons

A study on land degradation in the upper catchment of river Tons, a tributary of Yamuna river, in Uttarkashi district of the Uttarakhand state, was carried out using on-screen visual interpretation of IRS LISS-III + PAN merged data. The study area, which is largely mountainous, includes Govind Wildlife Sanctuary and National Park. Vegetation cover, slope and erosion status were used as criteria for the delineation of four major land degradation categories viz., undegraded, moderately degraded, degraded and severely degraded. More than 50 per cent of the study area is reported to be covered with snow and grassland. The moderate to severely degraded area worked out to be 42.4 per cent of the total area. The 32.8 per cent of area was found to be moderately degraded, followed by degraded (6.63%) and severely degraded (2.88%) areas. The depletion of vegetation cover on mountainous terrain and subsequent cultivation without proper protection measures is the reason for severe soil erosion and land degradation. In view of the existing land degradation situation, the catchment requires immediate treatment on priority for the sustenance of agriculture and wild life. It is expected that these measures will reduce the silt load in the river Tons and eventually, in river Yamuna.     

Land Cover Classification Using ICESat/GLAS Full Waveform Data

In the present study, parameters derived from Ice, Cloud, and land Elevation Satellite/Geoscience Laser Altimeter System (GLAS) full waveform were used for land cover classification in western part of Doon valley, Uttarakhand, India. Three parameters, viz, height, front slope angle (afslope) and canopy return ratio (rCanopy) were extracted from the returned full waveform signals. k-means (KM), partitioning around medoids (PAM), and fuzzy c-means (FCM) with different cluster sizes were used for classifying the land cover types with the help of GLAS-derived parameters. Among the clustering methods, KM performed the best. The overall accuracy (89.41 %) of all methods were quite significant with cluster size three i.e. with three classes forest, mango orchard and other class including agriculture, barren/fallow land, settlement, dry river bed, etc. The accuracy of the PAM (60 %) and the FCM (68.4 %) decreased drastically at four clusters with the separation of agriculture from barren/fallow land. The accuracy of the PAM and the FCM further decreased with increase in the number of clusters whereas KM showed reliable results for all clusters. KM with five clusters was able to distinguish five different land covers, viz, forest, mango orchard, agriculture and barren/fallow land and other class including settlement, dry river bed, etc. with an overall classification accuracy of 72.93 %. The study presents a method for classifying land cover types using GLAS full waveform data.     

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。     

Land-Cover change analysis of garur Ganga watershed using GIS/Remote Sensing technique

Land-use change and Land-cover classes in Garur Ganga watershed of Bageshwar district in Uttranchal State during the periods 1963–1996 and 1986–1996 were analyzed through Survey of India Topographical Sheet and visual interpretation of LANDSAT 5 TM image bands 2, 3 and 4 using Geographical Information System (GIS). The detailed analysis have revealed that the area under agriculture and settlement increased from 34.98 to 42.34%. whereas the forest and barren land show a declining trend. Expansion of agriculture land and builtup areas have been found to be maximum in the 1200–1600 m elevation zone with 7–14° slope class. The loss of vegetation cover has been estimated to be 5.07% between 1963-1996 and 0.81% between 1986–1996.     

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.     

Assessing the carbon sequestration potential of subtropical pine forest in north-western Himalayas — A GIS approach

The present investigation was carried out to determine carbon sequestration potential of Solan Forest Division of Himachal Pradesh during 2006–2007. There are six land uses viz., Chir pine, Ban oak, Deodar, Other broadleaves, Culturable and Un-culturable, which are distributed in 538 compartments along altitudinal gradient from 900 to 2,100m. The study reveals that among various land uses, the Other broadleaved species will result in maximum expected carbon (19.88 Mt) which will be 28.81, 23.95, and 3.07 times higher than standing carbon in Ban oak, Deodar and Chir pine, respectively. The Solan Forest Division on the whole, has potential to sequester 17 times more carbon over standing carbon of 1.67 Mt, if forest species are extended to their corresponding altitudinal limits in the “land area available for planting” i.e., Uncultrable land area in the forest division however, to have an accurate estimate of the carbon sequestration potential of the area, other attributes that decides the establishment of plantation of different species such as slope, aspect, soil, climate, etc. need to be taken into consideration beside altitude.     

A Hybrid CNN + Random Forest Approach to Delineate Debris Covered Glaciers Using Deep Features

The main aim of this study is to propose a novel hybrid deep learning framework approach for accurate mapping of debris covered glaciers. The framework comprises of integration of several CNNs architecture, in which different combinations of Landsat 8 multispectral bands (including thermal band), topographic and texture parameters are passed as input for feature extraction. The output of an ensemble of these CNNs is hybrid with random forest model for classification. The major pillars of the framework include: (1) technique for implementing topographic and atmospheric corrections (preprocessing), (2) the proposed hybrid of ensemble of CNNs and random forest classifier, and (3) procedures to determine whether a pixel predicted as snow is a cloud edge/shadow (post-processing). The proposed approach was implemented on the multispectral Landsat 8 OLI (operational land imager)/TIRS (thermal infrared sensor) data and Shuttle Radar Topography Mission Digital Elevation Model for the part of the region situated in Alaknanda basin, Uttarakhand, Himalaya. The proposed framework was observed to outperform (accuracy 96.79%) the current state-of-art machine learning algorithms such as artificial neural network, support vector machine, and random forest. Accuracy assessment was performed by means of several statistics measures (precision, accuracy, recall, and specificity).     

Recession of samudra tapu glacier, chandra river basin, Himachal Pradesh

Himalayas possess one of the largest resources of snow, ice and glaciers that act as a huge freshwater reservoir. Monitoring the glaciers is important to assess the overall reservoir health of the Himalayas. Samudra Tapu is one of the largest glaciers in Chandra basin of district Lahaul and Spiti, Himachal Pradesh. Based on the field investigations and the remote sensing techniques. features such as accumulation area, ablation area snowline/equilibrium line, moraine-dammed lakes and permanent snowfields were mapped. The glacial terminus was identified using moraine-dammed lake, as lake is located at down streamside of the terminus. The total recession of glacier during the period of 38 years (1962–2000) is about 742 m with an average rate of 19.5 m/yr. In addition, glacial extent is reduced from 73 to 65 km² between 1962 and 2000. suggesting overall deglaciation of 11%. During field investigation. three stages of glaciation using terminal moraine were identified. These moraines were mapped by merging LISS-II1 and PAN data. At the peak of glaciation. the glacial terminus was extended 3.18 km downstream of terminus position in year 2000. Total area during peak of glaciation period has been observed to be 77.67 km², which is 12.67 km² higher than the present glacier extent.     

Estimation of Snowmelt Runoff in Beas Basin,India

Abstract

Estimation of snowmelt runoff is very important in the Western Himalayan rivers in India where it is required to plan for hydropower generation and the water management during the non‐monsoon season. An attempt has been made to estimate snowmelt runoff on a 10 day average basis in Beas Basin up to Pandoh Dam during May, 1998 and November, 1999 using a Snowmelt Runoff Model (SRM), which is a degree day method. The input parameters for the model are derived from existing maps, satellite data, metrological and hydrological data. The relief of the basin is divided into 12 elevation zones of 500 m each. The temperature was extrapolated to these elevation zones using temperature lapse rate calculated using the observed temperature at seven stations within the basin. Snow covered area in the basin was determined using Indian Remote Sensing Satellites IRS ‐ 1C / 1D Wide Field Sensor (WIFS). The runoff from the snow covered area and snow free area was separately calculated in each elevation zone. The model parameter degree‐day factor is taken from literature and runoff coefficients for snow and rain are derived using the observed data. The total discharge at the dam site is computed by a weighted sum of runoff components from all the elevation zones. There is a good agreement between the observed and computed runoff with a coefficient of determination of 0.854 and the difference in volume is + 4.6 %.     

Forest cover monitoring using remote sensing and GIS — A case study in Dhaulkhand range of Rajaji National Park,Uttar pradesh

Rajaji National Park in U.P. is a protected area where large number of nomad population live within the park area. Their dependence on the forest for cattle rearing and firewood has caused degradation of the forests. Proximity to settlements outside the park further adds to the problems. In the present study, forest cover and river, bed changes have been attempted by using temporal aerospace data of the year 1960 and 1993. Subsequently, PAMAP GIS package has been used for the change detection analysis. The study indicates that the land cover changes are mainly due to biotic factors. Some of the important changes in forest cover are: (i) transformation of mixed forest to scrub forest in 67 ha (ii) the sal mixed and mixed sal forest categories have replaced sal forest in 262 ha (iii) significant increase in forest plantation i.e. 2075 ha in the year 1960 to 3793 ha in 1993 (iv) eighteen times increase in Chirpine area, it increased from 13 ha in 1960 to 230 ha in 1993. The land cover changes in 6663 ha (45%) out of 14962 ha of the study area. The consequential changes in the river beds due to the change in the forest cover was also analyzed. During this period river beds with boulders have increased by 87 ha. These river bed changes include lengthening and broadening of river and change in river course.     

Use of landsat in mapping land-utilization of north maidan,Karnatka

North Maidan consist of seven districts of North Karnataka. It is named after its relatively low and subdued relief or landscape of monoto-nous plateau. Most of the area lies in the rain shadow of the Western Ghats. The land utilization map shows majority of the area during December and January months is under agriculture with fallow land as the second largest category Large areas of North Maidan are under grassland which look barren by the beginning of summer. A total of nine landuse categories were delineated wifh the help of Landsat data.     

A GIS-based method for defining snow zones: application to the western United States

This study maps the geographic extent of intermittent and seasonal snow cover in the western United States using thresholds of 2000–2010 average snow persistence derived from moderate resolution imaging spectroradiometer snow cover area data from 1 January to 3 July. Results show seasonal snow covers 13% of the region, and intermittent snow covers 25%. The lower elevation boundaries of intermittent and seasonal snow zones increase from north-west to south-east. Intermittent snow is primarily found where average winter land surface temperatures are above freezing, whereas seasonal snow is primarily where winter temperatures are below freezing. However, temperatures at the boundary between intermittent and seasonal snow exhibit high regional variability, with average winter seasonal snow zone temperatures above freezing in west coast mountain ranges. Snow cover extent at peak accumulation is most variable at the upper elevations of the intermittent snow zone, highlighting the sensitivity of this snow zone boundary to climate conditions.     

Distribution analysis of salt affected soils under canal and non-canal command area in a part of Etah district,U. P., using remote sensing technique

A World Bank-aided project on sodic land reclamation in Uttar Pradesh is being executed by U.P. Bhumi Sudhar Nigam, Lucknow, and Remote Sensing Applications Centre, U.P., Lucknow has the responsibility of sodic land mapping for the execution of land reclamation programme at the cadastral level. Sodic lands are mainly concentrated in the Gangetic alluvial plains but the problem of sodicity is particularly acute in the canal-irrigated areas. A study of the distribution pattern of sodic lands in canal and noncanal command areas in a reclamation site (covering 60 villages out of which sodic lands were mapped in 51 villages) of Etah district in Uttar Pradesh, indicates that 18.39 per cent area of the canal command villages was barren sodic which was 13.41 per cent of the total geographical area of the site (15417 ha), however, 11.69 per cent area was recorded to be barren sodic in the non-canal command villages which was only 3.16 per cent of the geographical area of the site. The results of soil chemical analysis indicate that barren sodic lands of canal command area are saline-sodic with higher concentration of soluble salts (pH₂ >8.5, EC₂ >4 dSm⁻¹), however, those of non-canal command area are sodic (pH₂ >8.5, EC₂ <4 dSm⁻¹). The post-monsoon ground level in the canal-irrigated areas was in the critical and semicritical zone (< 3.0 mbgl) whereas it was well below the semi-critical zone in the non-canal command area, which indicates that the high ground water level is a major factor to higher the area under sodicity.     

Mapping the Extent of Agroforestry Area in Different Altitudes of Tehri District,North Western Himalaya,India Through GIS and Remote Sensing Data

Assessment of area under agroforestry in Tehri district of North Western Himalaya, Uttarakhand, India has been done using GIS and remote sensing technology. The study district characterized by hilly terrain with varying elevations from 288 m to more than 2800 m and generally gentle slopes, valleys, flat land covers and agricultural terraces. High-resolution satellite imageries (spatial resolution 5.8 m) were used in this study for land uses and land covers classification. According to unsupervised classification, highest area was found under forest class (65.22%) followed by cropland (20.41%). Considerable area was also found under snow cover (9.45%) in the district. Area under agroforestry was estimated to be 5572.26 ha (1.53%) by this method, whereas it was estimated to be 7029.06 ha (1.93%) by supervised classification. Estimated cropland area comes out to be about 20.0%. An accuracy of 86.5% was found in this classification for agroforestry class. Highest area under agroforestry of 3707.36 ha was obtained in 1200–2000 m elevations followed by 2231.26 ha in 288–1200 m elevations. Negligible area was found on high elevation zones of more than 2800 m. The major agroforestry systems of dominated by Grewia oppositifolia (Bhimal), Celtis australis (Kharik) and Quercus leucotrichophora (Banj) were identified and mapped and remaining systems were grouped as others class. Estimated area under G. oppositifolia, C. australis and Q. leucotrichophora based systems come out to be 2330.82, 1456.80 and 1129.10 ha, respectively. These systems are multiple usufructs are food, fuelwood, fodder, fiber and small timber. It has been observed from the accuracy assessment that the estimates of area under agroforestry obtained under this study are reliable.     

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。     

Glacier inventory in Himachal Pradesh using satellite images

A total of 125 glaciers covering an area of 1896 sq. km. were mapped on 1:250,000 scale in Himachal Pradesh using satellite images. The areal extent obtained from satellite images was found to be comparable with that from field estimates for eight glaciers for which data are available. This suggests that remote sensing can provide glacial areal extent similar to ground-based methods. Depth of an individual glacier was inferred indirectly by using its relationship with areal extent and geomorphological characteristics, as suggested by Muller (1970). These characteristics were estimated by using satellite images. The analysis suggests that the water equivalent of the glaciers in Himachal Pradesh is about 165 cu km. It is seventeen times more than the storage capacity of the Govind Sagar. This estimate will get revised when other snow/ice features as permanent snow field, ice apron, hanging glaciers and rocky glaciers are mapped. Mapping on larger scale, say 1:50,000, will lead to a further revision as many smaller glaciers and other features will get mapped.     

基于摄影测量系统的岩体结构面精细识别表征及应用

岩体结构面的识别和特征参数的表征对于岩体特性及失稳机制研究具有重要的基础意义。本文基于无人机航测、GPS-RTK,以及地面近景摄影组成的摄影测量系统对甘肃北山不同尺度岩体结构面进行了系统性研究。利用不同视角摄影得到的地物照片建立了场区数字正射影像模型和露头三维重构数字表面模型,通过数字化的识别和统计方法实现了岩体结构面信息的有效解译和特征参数的表征。对典型露头和区域的研究结果表明,采用的摄影测量系统可从不同维度和尺度进行岩体结构面的精细化调查和识别。根据结构面特征参数的变异性,对场区大断裂F31断层的断裂影响带进行了评估,初步得到F31断层对上盘岩体完整性的影响范围约为150~200m,影响形式为负指数型。