Remote sensing (satellite image data)



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Remote sensing (satellite image data)



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Digital image processing has been a critical study area in satellite remote sensing applications. The rising interest in space and earth’s surface exploration has resulted in the launching of various satellites into space used to collect the different information essential in geographical research. The satellites are designed with significantly advanced technology, which lengthens the durability periods of these satellites in space, enabling them to capture and collect enormous amounts of data (Alshehhi and Marpu, p.245). These data sets are then transferred to the remote sensing stations for analysis, interpretation and presentation. The application of digital software such as the ERDAS and RADAR for image processing tools and the interpretation tools such as ENVI (64 bit) and ENVI classic (64 bit) offer better experiences in visualization and retrieval of information remotely from the sensed images and data. In remote sensing, the physical characteristics of a specific geometric area are detected and monitored, through either its reflection or radiation emissions from a distance by the satellite which is connected to the special cameras that are used to collect the sensed image remotely hence, assisting the researchers in feeling things about the earth. Thus, remote sensing is a technique used to obtain information about the earth with the help of electromagnetic energy without direct contact with it. The process of acquiring information in remote sensing can be affected by the variations in the distribution of acoustic waves, distribution of electromagnetic energy and other forces such as gravity and magnetic field (Alshehhi and Marpu, p.246). These variations determine the characteristics of the image captured.


The objectives of this research on remote sensing techniques are as stated below:

  • To make the description of the utility and applications of remote sensing.
  • To analyze a satellite image product.
  • To explain the usefulness of the satellite product in addressing specific environmental and socio-economic issues.
  • To use the knowledge, learn on remote sensing to identify, locate and download the satellite image yourself.
  • To apply the satellite image processing software such as ERDAS imagine and Radar; and image interpreting software such as ENVI (64 bit) and ENVI classic (64 bit) to get information from the images.

Scope of the study

In this practical, the remote sensing instrument used was the active remote sensing instrument.

Active remote sensing

The active remote sensing emits their electromagnetic radiations, which are used in lighting the objects or the scenes they observe. Images capture is done by transferring energy pulses from the sensor to the object, which is reflected the sensor as radiations from the object. Examples of active remote sensing software are: ERDAS IMAGINE and RADAR (Radio detection and ranging) tools which are used in image processing and analysis, and the ENVI (64 bit) and ENVI classic (64 bit) are used in image interpretation. Some of the active remote sensings are:

  1. Radio detection and ranging (RADAR)

The radar emits electromagnetic radiation, which uses transmitters that operate simultaneously as microwave and radio wave frequencies. The radiations are directed to the object, and both the time of emission and the reflected radiations from the object are measured at a distance by a receiver. The electromagnetic waves travel at the same speed as light. Hence, the object’s distance is determined by measuring travel time and reflecting.

  1. ERDAS IMAGINE (world-class remote sensing software)

The ERDAS IMAGINE software is used in detecting and identifying raw geospatial image data, collect the data on the image; process data; and analyzes it. It is used in delivering accurate and precise useful information which are used in photogrammetry presentations for remote sensing applications. ERDAS IMAGINE facilitates the actual value; it combines remote sensing with photogrammetry by providing the basic vector analysis, LiDAR analysis, and RADAR processes as single-output (product).

Remote sensing 

The remote sensing technique is mostly used in detecting, recording and analyzing the electromagnetic waves transmitted, which include visible light, infrared, microwaves and radio waves radiation as opposed to direct contact technique for data collection. Example of remotely sensed images are the satellite imagery and the aerial images.

Literature review

Remote sensing technique is used to obtain information about the earth and water bodies with the aid of electromagnetic energy without direct contact with them.  The images’ characteristics are determined by the intensity of the reflection of the electromagnetic radiation’s emissions from the earth’s images. Each object will possess a unique feature after emission or reflection. In another case, the term remote sensing comprises of all the techniques that obtain images or other form of electromagnetic record of the surface of the earth at a distance and the image is well processed, analyzed and the interpreted information is made useful for application (Ding, Zhang, Deng, Jia and Kuijper, p.208). Thus, we can say that remote sensing is a wide area sensing that is meant to detect and record the electromagnetic radiation from the targeted region which is in line with the sensor. The radiation can originate from the solar then reflected by the target or the reflection of the transmitted energy from the target to the sensor for detection and recording.

Satellite imagery, is captured by the sensors and not cameras in which the scenes are recorded (Demattê, Fongaro, Rizzo and Safanelli, p.161). Remote sensing acts like the electronic scanning where the radiations are used beyond the reach of the normal visual range of the film and camera. Here, the thermal, Radar, microwaves, ultraviolet, infrared, multispectral and advanced techniques like; ERDAS IMAGINE and ENVI (64 bits) are used to process and interpret the remotely sensed image with the aim of application. 

The application of world-class remote sensing software such as ERDAS IMAGINE and RADAR; and ENVI (64 bit) and ENVI classic (64 bit) tools have been of great boost in the rapid advancement of satellite technology, which has brought about the study in remote sensing. Due to the increased desire for exploration and research, satellites have been made with special cameras that use remote sensing image software. The ERDAS IMAGINE and RADAR image tools are used to create comprehensive image processing, and analysis then sent to ENVI (64 bit) or ENVI classic (64 bit) for interpretation (Demattê, Fongaro, Rizzo and Safanelli, p.162). The information obtained after analysis is applied in surveying, mapping, and monitoring various factors around the globe.

The remote sensing data comes from the emission or the reflection, which originates from the objects about the earth in the form of electromagnetic radiations. Forces such as magnetic field and gravity are essential in remote sensing. Thus, the Remote sensing technique is used to obtain information about the earth with the help of electromagnetic energy without direct contact with it.  The images’ characteristics are determined by the intensity of the reflection of the electromagnetic radiation’s emissions from the earth’s images (Li, Xia,  Du, Lin and Samat, p.5653). Each object possesses a unique feature after emission or reflection. Hence, the technology of remote sensing is used in identifying and understanding an object by emission and reflection


The satellite remote sensing

The satellite remote sensing is assembled with sensors facing the region about the earth. The sensor monitors the earth as the satellite moves about orbit. The satellite remote sensing of the earth is done in the area beyond the earth’s atmosphere, where the earth’s surface separates monitoring of the sensor by the layers of the atmosphere. This facilitates the analysis of the various effects of the atmospheric condition on electromagnetic radiations that travel from the earth. The satellite sensors pass the atmosphere, which caters to essential data. The atmosphere affects the wavelength of the radiations by making them scatter or absorbed, which leads to the loss of more data when the quality of the images gets lowered. 

The atmospheric transmission windows are essential in remote sensing since they are permissible regions where the wavelengths in the electromagnetic spectrum penetrate the atmosphere. These transmission windows exist in microwave regions near the ultraviolet, the whole visible region, and the infrared wavelength bands. Thus, the remote sensing system is designed to carry its operations in single or multiple transmission windows.

Microwave remote sensing 

The microwave remote sensing satellites produce their own electromagnetic radiations, which are used in illuminating the objects or the scenes they observe. The image capturing is done by transferring energy pulses from the sensor to the feature, which is eventually received back as reflected radiations from the object. The images can be captured simultaneously in microwave remote sensing, either day or night. The images from the earth are captured by measuring the microwave energy scattered back by sea or the surfaces of the sensors.

Optical remote sensing

The optical remote sensing is equipped with optical sensors used to detect the solar radiation reflected from the region about the earth. The images captured are similar to those taken from space. In optical remote sensing, the wavelength varies from visible and near-infrared to short wave infrared.

Infrared remote sensing 

Infrared remote sensing measures the thermal radiation of the infrared’s emissions from the earth. It is essential in the determination of the landmass and water mass temperatures.

Imaging and processing

  1. Imaging

The images in the remote sensing are captured through the satellite sensors, which emit electromagnetic waves in the form of visible light, infrared, microwaves, and radio waves that remotely sense, identify, and understand an object by emission. The waves are reflected sensors, and images are produced depending on how the scuttering of the wave happens.

  1. Image processing

After acquiring the remotely sensed image, the image is taken for pre-processing before proceeding to more analysis; the pre-processing aims to remove noise (denoising) that could have corrupted the image. Other image development methods such as sharpness, contrast, and brightness enhancement are done.

Image analysis

After the enhancement process, the remotely sensed image was taken to the image analysis software applied in remote sensing. The ERDAS IMAGINE tool is used to understand raw geospatial image data, collect the data, process it, and analyze it. This image processing tool is accurate, precise, and time-saving in transforming the image data into useful information in photogrammetry presentations for remote sensing applications. ERDAS IMAGINE facilitates the actual value; by combining remote sensing with photogrammetry to provide the critical vector analysis, LiDAR analysis, and RADAR processes as one product.

Data Interpretation, filtering and classification

  1. Image data interpretation

The ENVI (16 bit) and the ENVI classic (64 bit) tools are used to interpret the data analyzed by the ERDAS IMAGINE and the RADAR tool. The software application has both local and global contrast details.  The ENVI has the discrete cosine transform and regularized histogram equalization, which is the empirical used to improve the quality of the images and interpretations. They are used to produce remote sensing images with high contrast and with much reliable information for the application.

  1. Filtering

The number of features within the image, like the values of brightness and contrast; the size and shape; dimensions of regions; the terrain and texture of the surfaces, are extracted from the image based on the characteristics of the features before they are classified depending on such features.

  1. Classification

The classification on the remotely sensed image is done based on features available in various regions such as; Classification according to regional features will be the area; shape; size; terrain; texture; temperature; soil moisture and the classification according to the image features will be the brightness, contrast, and the image resolution (intensity) values.

Components of image analysis

The image analysis comprises of many steps such as; obtaining of data from remotely sensed image, pre-processing of image, developing image enhancement techniques, testing of enhancement techniques, image segmentation and feature extraction, classification and regional description, and application.


Remote sensing under the Landsat images interpretation has got many areas of application such as environmental monitoring, cartography, forestry, land use planning, civil engineering, land resources analysis, geography, botany, water resource analysis, geology and agriculture. In geology Landsat imaging is crucial in; the land mapping, geological structure identifications and in exploration of the resources.  The images from the mineral-rich areas are analyzed to give the characteristics of the mineral’s depositions. This is used as evidence to show if there are new minerals in such regions. The satellite imagery provides for large scale survey of the geology area over a short time as compared to using the physical approach. The images captured by satellite are well enhanced and processed to give quality geological searches that are used to identify new minerals deposits.