Tag Archive: Remote sensing services

How remote sensing integrates into Geographic Information System


In a nutshell, GIS or Geographic Information System is a computing system that is used to collect, store, manage, analyse and study and display different sets of geographical data for a wide range of applications. There are a wide range of applications that help the users of the data thus collected to carry out a variety of tasks such as spatial query and analyses, spatial data editing and creating accurate hard copy of maps.

The major component of GIS is remote sensing which makes the entire collection of data possible. Remote sensing is the process or the act of collection various sets of information about the surface of the earth without ever making any physical contacts with the same.

Remote sensing heavily relies on sensing and capturing reflected energy trails off the earth. This energy beams are then analyzed to understand the presence of various geographical areas and locations.
It largely relies on the reaction that happens between the radiation that comes in and the object of interest whose reflected data is getting collected by analysing the emitted radiations.

Following are the components that primarily work in the remote sensing process.

  • The source of the energy
  • The atmosphere and the radiation
  • The interaction of the radiation with the target and collection of the energy reflected
  • Transmission of the energy sensed and processing of the same at the lab
  • Interpretation of the energy, analyses and the application of the same

It is remote sensing and various techniques used to collect geographical information that lays the ground work for any Geographic Information System to begin its work. Only if the process of remote sensing works properly can a GIS can deliver the results intended of the same. However, with the advent of better remote sensing and data analytical and interpretation tools, the quality of the results offered by Geographic Information System will only go higher.

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Is GIS a Reliable Option for Processing Insurance Claims?


Losing health, property and above all, life, is a serious affair and filing insurance claims further has turned out to be tiresome and time-consuming process. As time plays a key role, in getting the claims verified and money disbursed, every brand tries to retain and grow its customer base, by providing a swift and proficient service, but every time what delays the process is the mutual eye on profit, which sometimes need to be underwritten, and thus is vital for every insurance provider to make sure the claims processing is effective and efficient. With the technology improvements playing disruptor in every industry, it is high time for the insurance companies to automate the claims processing and GIS (Geographical Information Systems) can be one of the most reliable options, which leverages the visualization, data management and analysis to the core, empowering the claim adjusters to serve better.

The riskiest of the claims is property related damages and this needs to be handled with precise data as it has the capacity to turn a insurance company bankrupt. Visually and manually probing large datasets is not only time consuming but is exasperating and cannot be accurate. Change detection via 2D & 3D imagery and DSM (Digital Surface Model) datasets has not only been popular but is one of those GIS services on which the insurance companies rely upon these days. The 2D change detection process constitutes analysis of textural, spectral and linear feature changes in orthoimage data sets mapped at different intervals, helping the user to locate the areas of change with utmost precision and accuracy. On the other hand, the 3D change detection relies on DSM which helps in identifying the areas of changes especially in the vertical plane and is highly applicable in
the field of agricultural properties.

Geo-enabling the insurance business data is crucial and is the need of the hour as it relies on intuitive mapping and various analytical tools helps the user to access the hazardous location on a global base, associate the loss severity with topography and access historic data counting customer information and risk. The remote sensing technique, which relies on sensors placed on satellites helps in capturing geographical images, enables manipulation, visualization and analysis, and is extensively being applied in the banking and insurance sectors. Damage detection, both to the property or the crop can be accessed instantly and precautions can be made possible at the earliest hours. With the help of the images sent by the satellite, the insurance companies can keep their customers posted about the changes in the property and also about the crops, when it becomes
applicable in the field of agriculture. The customers on the other hand can take intuitive measures based on the alerts and can avoid a mutually chancy stance.

Faster and accurate processing of the insurance claims using GIS technology results in satisfied customers and protects insurance companies from false claims resulting in a win-win situation for all parties concerned. SBL has been working with insurance companies and their associated companies in processing geographical data to assess and verify claims against property and crop damage for more than 5 years now. Our USP is fast turnaround and accurate mapping and analysis which results in huge savings and transparent operations for the insurance companies.

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APPLICATIONS OF SATELLITE IMAGERY

Remote sensing data provides much essential and critical information for monitoring many applications such as image fusion, change detection and land cover classification. Remote sensing is an important technique to obtain information of earth resources and environment.
What popularized the satellite imagery are the open-access applications like Google Earth, BING Maps etc. From being simply able to find “where is my house” these applications have helped GIS community in project planning, monitoring disasters and natural calamities, guiding and helping civil defense people etc.

Remotely sensed satellite images comprise of spectral, spatial and temporal resolution. Spectral statistics is the substance of remotely sensed image classification. The main aspect which influences the accuracy of ground object is the Spatial resolution. Temporal Resolution will help in generation of land cover maps for environmental planning, land use change detection and transportation planning. Data assimilation and analysis of urban areas using medium resolution remote sensing imagery is mainly concentrated on documentation of built up areas or for judgement between residential, commercial and industrial zones.

There are 100’s of applications of Satellite imagery. From the days of Landsat’s and SPOT’s satellite imagery and when nations used to use information derived from the satellite imagery for spying on each other under the guise of scientific experiments, industry has grown in leap and bounds and today every sphere of life, government decision making, civil defense operations, police, you name the sphere of life, every one of which is influenced by Satellite Imagery in particular and Geographic Information Systems (GIS) in general.

SBL has pioneered in the field of Satellite Imagery processing and has got in-house expertise to handle any kind of sensor and product demands. Our projects have helped clients world over to help in having a better say in sustainability management and environmental assessment and management. An attempt is made and listed below to explain the uses of Satellite Imagery, even though the space given is not enough to cover all aspects of it.

1.Optimizing solar panel energy output with irradiance values.

Sustainable living has lot of interest in solar energy and it interest is growing rapidly across the world. Finding out location for placement of solar panels and If you were to choose a single position anywhere on Earth to install a solar panel, then we have to use Global Horizontal Irradiance (GHI) map. GHI measures the rate of total incoming solar energy at the Earth’s surface in watts per square kilometer. Epochs of satellite data (derived from GOES and Meteosat) has created this data with a standard error of only 5%.
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2.Generating Earth’s surface elevation with the Shuttle Radar Topography Mission

The SRTM digital elevation data, produced by NASA originally, is a major breakthrough in digital mapping of the world, and provides a major advance in the accessibility of high quality elevation data for large portions of the tropics and other areas of the developing world. The Shuttle Radar Topography Mission (SRTM) obtained elevation data on a near-global scale to generate the most complete high-resolution digital topographic database of Earth. SRTM consisted of a specially modified radar system that flew onboard the Space Shuttle Endeavour during an 11-day mission in February of 2000. SRTM is an international project spearheaded by the National Geospatial-Intelligence Agency (NGA), NASA, the Italian Space Agency (ASI) and the German Aerospace Center (DLR).

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3.Extracting mineral deposits with remote sensing based spectral analysis

During the pre feasibility and feasibility stages of the mineral exploration it is very essential to know the mineral potentiality of the area under consideration. In such scenario satellite remote sensing based lithological mapping, geological structural mapping, geomorphological mapping etc and its integration in a GIS platform will enable geo scientist to map the mineral potential zones. This will be further enhanced with the help of spectral analysis of satellite image bands to identify and map hydro thermal alteration zones which a indicators of mineral availability. This will enable exploration geologist to confine his geo physical, geo chemical and test drilling activities to high potential zones.

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4.Giving that a basemap for graphical reference and assisting planners and engineers

The amount of details that an Orthoimagery produced using high resolution satellite imagery is of immense value and provides an extreme amount of detail of the focus and surrounding areas. Maps are designed to communicate highly structured message about the world. As maps are location-based, aerial imagery supports people to orient themselves.

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5.Disaster Mitigation planning and recovery.

The result of a natural calamity can be calamitous and at times difficult to assess. But a disaster risk assessment is essential for rescue workers. This has to be prepared and executed quickly and with accuracy. Object-based image classification using change detection (pre- and post-event) is a quick way to get damage assessments. Other similar applications using satellite imagery in disaster assessments include measuring shadows from buildings and digital surface models.

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2D Feature mapping from High Resolution Satellite images

Remote sensing is a vital system to acquire information of earth resources and environment. Remotely sensed images comprise of spectral, spatial and temporal resolution. The introduction of High-resolution satellite imagery is projected to reduce cost for medium and small scale topographic mapping. Since high-resolution satellite imagery has a much close-fitting field angle, the projection of images is nearly calculated by parallel rather than central systems. Using high resolution we can extract valuable information that will serve as a reference to bigger data needs and planning.

The feature extraction stage is intended to obtain a solid, non-redundant and evocative demonstration of observations. It is accomplished by removing repetitive and irrelevant material from the data.

satimageinterpretation

satimageinterpretation


SBL has perfected its capabilities in 2D feature mapping in the form of base mapping, land use land cover mapping and other types of thematic mapping. This kind of remote sensing services requires the knowledge of pre-processing on the satellite images. These pre-processing steps includes geo-referencing for geometric corrections and image enhancement for radiometric corrections. Digitally enhanced and geo-referenced images can be (re)projected to real world co-ordinate systems to put it in use for 2D feature extraction.
map digitisation

map digitisation

GIS data represents real world entities and features such as roads, land use, elevation, trees, waterways, etc. In GIS all features are grouped under the classes of point, line or polygons. Points are the smallest entity in GIS. Land marks, spot heights and point features such as locations of wells, ATM’s etc. can be represented in the form of points. Lines constitute a series of points called vertices and nodes with a start point and an end node point. Transportation network, drainage network, telecommunication lines, power transmission lines, sewerage network and other utility and transport networks can be represented in the form of lines. Polygons are closed features in which a line has start point and end point the same and which will encompass an area within it. Parks, water bodies, residential areas and forests can be represented in the form of polygons.

For 2D feature extraction services SBL will follow a classification schema derived after the requirement and need study established with the end-client. For example, for a forest department forest land parcels along with hydrographic and transportation network will be captured. For a mining firm during their replacement and rehabilitation process residential buildings, plantations, and orchards may be the main concentration. The thematic mapping using 2D features will be established as per the project and need requirements and is designed with a long term vision of serving the future changes and developments.

GIS mapping for 2D features extraction can be possible through aerial photographs as well. The features can be extracted using image interpretation keys such as tone texture, size, shape, association ext. SBL’s experienced image interpreters will deduce the images to useful thematic categories based on the classification schema. The final stage of the GIS based mapping services is the cartographic layout preparation. Each and every mapped 2D features will be given with a suitable standard symbology and layout can be prepared based on standard cartographic norms. The above notes explains in general the 2D mapping approach adapted by SBL.

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Photogrammetry and Remote sensing

SBL is in the fore front of using the latest of mapping technologies such as Photogrammetry and Remote sensing to cater to the GIS services demands in the world-wide industry. As a leading GIS Services provider SBL has executed several complex Aerial Photogrammetry projects towards the fulfilment of Photogrammetry mapping demands.

The following is a brief introduction to Photogrammetry and Remote Sensing for those who are new with the technology.

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Photogrammetry

Photogrammetry, as its name implies, is a 3-dimensional coordinate measuring technique that uses photographs as the fundamental medium for metrology (or measurement). The fundamental principle used by Photogrammetry is triangulation or more specifically called Aerial Triangulation. By taking photographs from at least two different locations, so-called “lines of sight” can be developed from each camera to points on the object. These lines of sight (sometimes called rays owing to their optical nature) are mathematically intersected to produce the 3-dimensional coordinates of the points of interest.
The expression Photogrammetry was first used by the Prussian architect Albrecht Meydenbauer in 1867 who fashioned some of the earliest topographic maps and elevation drawings. Photogrammetry services in topographic mapping is well established but in recent years the technique has been widely applied in the fields of architecture, industry, engineering, forensic, underwater, medicine, geology and many others for the production of precise 3D data.
Branches of photogrammetry

There are two broad based branches in Photogrammetry

  • Metric Photogrammetry : Deals with the precise measurements and computations on photographs regarding the size, shape, and position of photographic features and/or obtaining other information such as relative locations (coordinates) of features, areas, volumes, These photographs are taken using a metric camera and  is mostly used in the engineering fields e.g. surveying etc
  • Interpretive Photogrammetry: Deals with recognition and identification of the photographic features on a photograph such as shape, size, shadow, pattern etc to add value and intelligence to information seen on the photograph (annotation).,

Remote Sensing

Remote Sensing is a closely aligned technology to Photogrammetry in that it also collects information from imagery. The term is derived from the fact that information about objects and features is collected without coming into contact with them. Where remote sensing differs from Photogrammetry is in the type of information collected, which tends to be based on differences in color, so land use and land cover is one of the primary output of remote sensing processing. Remote sensing was originally conceptualized to exploit the large number of color bands in satellite imagery to create 2D data primarily for GIS. Nowadays remote sensing tools are used with all types of imagery to assist in 2D data collection and derivation, such as slope. Software tools today tend to hold a much wider range of image technologies such as image mosaicing, 3D visualisation, GIS, radar as well as softcopy Photogrammetry.

Key concepts:

  • Spatial resolution.
  • Radiometric resolution. 
  • Spectral resolution. 
  • Temporal resolution
    • Spatial resolution describes the ability of a sensor to identify the smallest size detail of a pattern on an image. In other words, the distance between distinguishable patterns or objects in an image that can be separated from each other and is often expressed in meters.
    • Spectral resolution is the sensitivity of a sensor to respond to a specific frequency range (mostly for satellite and airborne sensors). The frequency ranges covered often include not only visible light but also non-visible light and electromagnetic radiation. Objects on the ground can be identified by the different wavelengths reflected (interpreted as different colours) but the sensor used must be able to detect these wavelengths in order to see these features.
    • Radiometric resolution is often called contrast. It describes the ability of the sensor to measure the signal strength (acoustic reflectance) or brightness of objects. The more sensitive a sensor is to the reflectance of an object as compared to its surroundings, the smaller an object that can be detected and identified.
    • Temporal resolution depends on several factors–how long it takes for a satellite to return to (approximately) the same location in space, the swath of the sensor (related to its ‘footprint’), and whether or not the sensor can be directed off-nadir. This is more formally known as the ‘revisit period’
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