Mapping of apple orchards using remote sensing techniques in cold desert of Himachal Pradesh,India

The present study was conducted to map Apple orchards in dry alpine Spiti region of Indian Himalaya using LISS III satellite image. The barren terrain with sparse woody vegetation helped in classification of apple orchards with 91.3 % accuracy. The orchards were found in 154.6 ha of the study area and are anticipated to expand owing to its economic importance.     

Land suitability analysis for cereal production in Himachal Pradesh (India) using Geographical Information System

Land suitability analysis is prerequisite for sustainable agriculture and it plays a pivotal role in the niche based agricultural planning in mountain regions. In this paper different parameters viz. climatic (precipitation and temperature), topographic (elevation), soil type and land cover/land use have been used in order to perform land suitability evaluation for cereals food-grain crops in Himachal Pradesh using Geographic Information System (GIS). The suitability analysis was performed by digital processing of geo-referenced data (elevation, climate, soil and landcover) and calculating potential production areas by combining different types of geographical data through decision rules framed for each crop in ArcView spatial analyst. Suitable areas have been delineated for cereal crops in the form of land suitability maps. In comparison to the actual area under cereal crops, the possibility of further expansion under each cereal crop was determined. These discriminated areas appear suitable for growing these crops and can be harnessed efficiently for achieving long term sustainability and food security.     

Reconstruction of the moraine dammed lake,based on field evidence and paleo-history,Samudra Tapu Glacier,Chandra Basin,Himachal Pradesh

Peri-glacial studies of the Samudra Tapu glacier reveal three stages of well preserved moraines which are also marked by fluvial overprinting. The signatures of fluvial outwashes over the otherwise morainal deposits have been utilized in estimating the extent of palaeo-lake in the valley of Samudra Tapu glacier of the Chandra basin. Distance and thickness of snout of the glacier and its morainal deposits is estimated by the Laser Range Finder. With the change in the position of the snout there is a change in the extent and orientation of the lake. Recent expedition to the glacier confirms this process to be continuing. The study is important in reconstructing formation of the lake with respect to snout position of the glacier. Based on ground truth, fast melting of the snout is confirmed from year 2004 onwards, with the development of fresh end/terminal moraine. The study reveals that the snout region of the Samudra Tapu glacier is thinning and retreating at an alarming rate and is enlarging the lake extent. The development of fresh terminal moraine has the potential to impound the fast melting glacial waters which in turn can pose serious threat to the downstream regions of the Chandra valley.     

Geology in parts of Sainj Valley,Kulu district,Himachal Pradesh

The paper highlights the findings of photogeological studies, with selective field checks, carried out in Sainj Valley. For the first time, a photogeological map of the area has been prepared using large scale aerial photographs Structurally the area forms‘Window in a Window’ structure as the oldest rocks of Kulu formation are thrusted over the younger rocks of Larji Group (Larji and Banjar formations) and further Banjars are thrusted over Larjis. Thus, Larjis being stratigraphically youngest, occupy the lowest tectonic position. The Kulu formation mainly consists of Central Crystalline, schists and gneisses. Banjar is composed of quartzite, metabasics, slate and phyllite. Larji predominantly consists of dolomite and quartzite with slate and phyllite. The photogeological studies have helped to bring out the lineament pattern, landslide zones, major structural trends and main geological formations. The lineaments mainly trend in NNE-SSW, NW-SE, NE-SW and NNW-SSE directions. A key for photo-characters of different litho units and terrain elements of the area is established.     

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.     

Remote sensing of horticultural plantations in Kumarsain tehsil in Shimla district, Himachal Pradesh

The favourable agroclimatic conditions for orchards especially apples have increased the acreages in Himachal Pradesh (HP) which has significantly contributed in the growth of state economy. Realizing the importance of horticulture in HP and its changing scenario of the land use/land cover, a study was conducted to identify and map apple and almond plantations in the Kumarsain tehsil of Shimla district using Remote Sensing (RS) techniques. IRS-IB LISS-II False Colour Composite (FCC) diapositives of October 27, March 30 and April 20, 1992 were visually analysed for mapping apple and almond plantations. The results indicate that IRS LISS-II data of April 20 on 1∶50,000 scale was found very useful for identification and mapping of apple and almond plantations in this region. Accuracy of interpretation was also tested on sample basis assuming a binomial distribution for the probability of success/failure of sample points. The overall interpretation accuracy assessed based on 40 sample points was found to be 87 per cent at 90 per cent confidence limits.     

Glacier changes using satellite data and effect of climate in Tirungkhad basin located in western Himalaya

Glaciers are widely recognized as key indicators of climate change, and melt water obtained from them is an important source of fresh water and for hydropower generation. Regular monitoring of a large number of Himalayan glaciers is important for improving our knowledge of glacier response to climate change. In the present study, Survey of India topographical maps (1966) and Landsat datasets as ETM+ (2000, 2006) and TM (2011) have been used to study glacier fluctuations in Tirungkhad basin. A deglaciation of 26.1% (29.1?km²) in terms of area from 1966 to 2011 was observed. Lower altitude small glaciers (area?<?1?km²) lost more ice (34%), while glaciers with an area <10?km² lost less (20%). The percentage of change in glacier length was 26% (31.9?km) from 1966 to 2011. The south-facing glaciers showed high percentages of loss. From 2000 to 2011, debris cover has increased by 1.34%. The analysis of the trend in meteorological data collected from Kalpa and Purbani stations was carried out by Mann Kendall non-parametric method. During the last two decades, the mean annual temperature (T_max and T_min) has increased significantly, accompanied with a fall in snow water equivalent (SWE) and rainfall. The increasing trend in temperature and decreasing trend in SWE were significant at 95% confidence level. This observation shows that the warming of the climate is probably one of the major reasons for the glacier change in the basin.     

Mapping forest windthrows using high spatial resolution multispectral satellite images

Wind disturbances represent the main source of damage in European forests, affecting them directly (windthrows) or indirectly due to secondary damages (insect outbreaks and forest fires). The assessment of windthrows damages is very important to establish adequate management plans and remote sensing can be very useful for this purpose. Many types of optical remote sensing data are available with different spectral, spatial and temporal resolutions, and many options are possible for data acquisition, i.e. immediately after the event or after a certain time. The objective of this study is to compare the windthrows mapping capabilities of two multispectral satellite constellations (i.e. Sentinel-2 and PlanetScope) characterized by very different spectral, spatial and temporal resolutions, and to evaluate the impact of the acquisition conditions on the mapping results. The analysed area, with an extent of 732 km², is located in the Trentino-South Tyrol region (Italy) which was affected by the Vaia storm on the 27th-30th of October 2018, causing serious forest damages. The change vector analysis technique was used to detect the windthrows. For each data source, two pairs of images were considered: 1) pre- and post- event images acquired as close as possible to the event; 2) pre- and post- event images acquired at optimal conditions, i.e. at similar phenological state and similar illumination conditions. The results obtained with the two satellite constellations are very similar despite their different resolutions. Data acquired in optimal conditions allowed having the best detection rate (accuracy above 80 %), while data acquired just after the event showed many limitations. Improved spatial resolution (PlanetScope data) allows for a better delineation of the borders of the windthrow areas and of the detection of smaller windthrow patches.     

Hydromorphogeological mapping of Panwari area,Hamirpur district,Uttar Pradesh using satellite data

The area around Panwari town, Hamirpur district, Uttar Pradesh, faces acute water scarcity and chronically drought prone. The groundwater resources in the area have not been fully exploited. The present study was undertaken to evaluate the groundwater prospective zones. Landsat TM and IRS-1A LISS-II data have been used to differentiate different hydromorphogeological units and to delineate the major trends of lineaments. The digitally enhanced False Colour Composite, Principal Component Analysis and Edge Detections were useful for better correlation. The digital enhancement was helpful with identification of faint lineaments. In addition, the boundaries of various lands forms were better discriminable on the digitally enhanced products. The deeply and moderately weathered buried pediplains are the most potential zones for groundwater targeting. Occurrence of lineaments in such zones is also a favourable indicator. A number of promising groundwater well sites have been located in the pediplains.     

Road detection from high-resolution satellite images using artificial neural networks

This article treats the possibility of using artificial neural networks for road detection from high-resolution satellite images on a part of RGB Ikonos and Quick-Bird images from Kish Island and Bushehr Harbor, respectively. Attempts are also made to verify the impacts of different input parameters on network's ability to find out optimum input vector for the problem. A variety of network structures with different iteration times are used to determine the best network structure and termination condition in training stage.It was found that when the input parameters are made up of spectral information and distances of pixels to road mean vector in a 3 × 3 window, the network's ability in both road and background detection can be improved in comparison with simple networks that simply use spectral information of a single pixel in their input vector.     

Change detection study of islands in Hooghly estuary using multidate satellite images

River estuarine environment constitutes a highly dynamic fluvio-morphological setting where processes of accretion and deposition are active. Hooghly estuary, being one of the largest of estuaries in the east coast of India, needs constant monitoring. Multidate satellite images of IRS-1A L1SS-I and Landsat MSS for 1975–1991 period are studied to detect long term morphological changes in this estuary. The study reveals that the estuarine islands like Sagar, Ghorarmara and Suparbhanga are eroding whereas Lohachara islands has completely eroded off Nayachara island near Haldia due to its shape and size bifurcates the river into two channels. The island as revealed from Satellite images is in accretional phase where the total surface area has increased. The study, therefore, indicates that constant monitoring of spatial and temporal changes in this type of environment would help to understand physical processes.     

Damage assessment after 2001 Gujarat earthquake using Landsat-7 satellite images

In this paper, we present a method of earthquake damage detection by comparing the optical images with panchromatic bands for the Gujarat, India earthquake, which occurred on January 26, 2001. The data used in this study are optical remote sensing images taken by Landsat-7 satellite on January 8 and February 29, 2001, before and after the earthquake. We have investigated the pre and post-earthquake satellite images calculating the differences in the reflection intensity (digital number) of the two images. The estimated affected area has been subtracted on a pixel unit based on the obtained frequency distributions of the differences in the optical sensor values, which show significant changes in the reflectance due to the earthquake disaster. We have investigated the accuracy of our analysis result using a classification method for the training areas with aerial photographs taken after the earthquake. The two damage detection methods show a very similar result.     

TerraSAR-X卫星影像中大比例尺测图应用研究

为了研究TerraSAR-X卫星的中大比例尺测图可行性,文章利用成都都江堰市3m、1m分辨率的TerraSAR-X影像、控制点及可见光卫星影像,对TerraSAR-X影像在多云多雨地区的中、大比例尺测图展开了研究和分析。实验表明利用TerraSAR-X影像能够符合中大比例尺基础地图测图或修测的精度要求,可用于困难地区1∶50 000~1∶10 000比例尺的基础测图生产和更新。     

Cyclone track forecasting based on satellite images using artificial neural networks

Many places around the world are exposed to tropical cyclones and associated storm surges. In spite of massive efforts, a great number of people die each year as a result of cyclone events. To mitigate this damage, improved forecasting techniques must be developed. The technique presented here uses artificial neural networks to interpret NOAA-AVHRR satellite images. A multi-layer neural network, resembling the human visual system, was trained to forecast the movement of cyclones based on satellite images. The trained network produced correct directional forecast for 98% of test images, thus showing a good generalization capability. The results indicate that multi-layer neural networks could be further developed into an effective tool for cyclone track forecasting using various types of remote sensing data. Future work includes extension of the present network to handle a wide range of cyclones and to take into account supplementary information, such as wind speeds, water temperature, humidity, and air pressure.     

Groundwater prospects in a developing satellite township of Andhra Pradesh, India, using remote sensing techniques

Geomorphologic map prepared, using the remote sensing techniques and conventional methods, has been used to assess groundwater prospects in a developing satellite township of Visakhapatnam Metropolitan Complex. Andhra Pradesh, India. The geomorphic units delineated are denudational, fluvial and coastal. The study indicates that the fluvial and rolling plains are promising zones for groundwater occurrence. The denudational landforms are not considered as groundwater potential zones, whereas the groundwater occurring in the coastal plain is not suitable for any use, because of its brackish nature.     

Landsat imagery analysis and field studies in the Kullu and Chauhar valleys,Himachal Pradesh,India

The rough terrain between the Gogar Dhar (Mandi-Brot rise) and the Kullu-Larji valley is geologically unexplored. This paper brings out for the first time the geology and regional tectonic set-up of the area on the basis of LANDSAT imagery interpretation and field checks. Image analysis of about 3700 sq. km area and field observations along selected sections of the area reveal that the area mainly comprises mica-chlorite schists, quartzites and phyllites i.e. low to medium grade Chail metamorophics with acid and basic intrusions within them. Structually the rocks are arranged in the form of a NNW-SSE trending faulted synclinorium, the axis of which passes through Daggi Dhar. The western flank of the synclinorium is more strongly folded. Granitoids and basics show concordent relations with the country rocks. Two belts of granitoids are found occupying the cores of the folds on both the limbs of the synclinorium. Along the Uhl river (in the Chauhar valley) and the Kullu valley passes the Chail thrust separating the Chail metamorphics from the rocks of the outer carbonate belt and the traps of the Mandi unit, and the inner carbonate belt of the Larji window zone respectively. The area is dissected into blocks by cross cutting, deep-seated major faults of three generations. The fold and fault systems have prominent control over the geomorphology including the drainage patterns and landforms of the area. The present area is a typical case of inverted relief, anticlinal valleys and synclinal hills being the main geomorphic features developed due to structural control. The change in the course of the Beas River between Mandi and Pandoh is a typical case of structural control on the present drainage system.     

A community-based urban forest inventory using online mapping services and consumer-grade digital images

Community involvement in gathering and submitting spatially referenced data via web mapping applications has recently been gaining momentum. Urban forest inventory data analyzed by programs such as the i-Tree ECO inventory method is a good candidate for such an approach. In this research, we tested the feasibility of using spatially referenced data gathered and submitted by non-professional individuals through a web application to augment urban forest inventory data. We examined the use of close range photogrammetry solutions of images taken by consumer-grade cameras to extract quantitative metric information such as crown diameter, tree heights and trunk diameters. Several tests were performed to evaluate the accuracy of the photogrammetric solutions and to examine their use in addition to existing aerial image data to supplement or partially substitute for standard i-Tree ECO field measurements.     

Glacier surface velocity estimation using repeat TerraSAR-X images: Wavelet- vs. correlation-based image matching

For the observation and monitoring of glacier surface velocity (GSV), remote sensing is an increasingly suitable tool thanks to the high temporal and spatial resolution of the data. Radar sensors have the specific advantage over optical sensors of being nearly weather and time-independent.Two image pairs separated by 11 days, acquired with the high-resolution spotlight (HS) and stripmap (SM) modes of the German sensor TerraSAR-X, were used to estimate GSV over Switzerland’s Aletsch Glacier. The SM mode covers larger ground swaths, making it more suitable for glacier-wide observations, while the HS images cover less area but offer the highest-possible spatial resolution, approximately 1 × 1 m on the ground. The images were acquired during the summer to maximise feature visibility by minimal snow cover.GSV estimation was performed using two methods, the comparison of which was a major goal of this study: traditional cross-correlation optimisation and a dense image matching algorithm based on complex wavelet decomposition. Each method was found to have unique advantages and disadvantages, but it was concluded that for GSV monitoring, cross-correlation is probably preferable to the wavelet-based approach. While it generates fewer estimates per unit area, this is not necessarily a critical requirement for all glaciological applications, and the method requires less initial “tuning” (calibration) than the wavelet algorithm, making it a slightly better tool in operational contexts. Also, the use of the highest-resolution spotlight datasets is recommended over stripmap mode images when large-area coverage is less critical. The comparative lack of visible features at the resolution of the stripmap images made reliable GSV estimation difficult, with the exception of several small areas dominated by large crevasses.     

Fractal compression of satellite images

Fractal geometry provides a means for describing and analysing the complexity of various features present in digital images. In this paper, characteristics of Fractal based compression of satellite data have been tested for Indian Remote Sensing (IRS) images (of different bands and resolution). The fidelity and efficiency of the algorithm and its relationship with spatial complexity of images is also evaluated. Results obtained from fractal compression have been compared with popularly used compression methods such as JPEG 2000, WinRar. The effect of bands and pixel resolution on the compression rate has also been examined. The results from this study show that the fractal based compression method provides higher compression rate while maintaining the information content of RS images to a great extent than that of JPEG. This paper also asserts that information loss due to fractal compression is minimal. It may be concluded that fractal technique has many potential advantages for compression of satellite images.     

Multiscale techniques for the detection of precipitation using thermal IR satellite images

It is thought that satellite thermal infrared (IR) images can aid to the detection of precipitation, an interesting possibility due to the existence of geostationary satellites with thermal IR sensors which would enable a good spatial and temporal tracking of rain and storms. In this letter, we explore the application of multiscale/multifractal techniques in the design of new methods for the assessment and tracking of pluviometry. We first identify the main streamlines by a singularity analysis of the wavelet projections of the IR record. From the streamlines, we derive a proxy scalar image that represents the result of pure horizontal advection. From the comparison of original and proxy we localize the places at which horizontal advection fails, which we identify with convection places. We illustrate our methodology with thermal IR images from Metosat acquired during heavy tropical rainfall, and compare the results with some data from the Tropical Rainfall Measuring Mission satellite.