Remote Sensing . GIS . Maps : May 2023

LIST OF TOPICS / INDEX

REMOTE SENSING, GIS and GPS

Fundamentals of Remote Sensing

About Satellite Images

Applications

Satellite Sensors

Miscellaneous

Digital Image Processing

Digital Image Processing: An Introduction

Geographic Information System (GIS)

Understanding GIS

Drones for GIS / Remote Sensing

Global Positioning System (GPS)

Please feel free to suggest topics of your interest in comment box.

Books on Remote Sensing & GIS

There are many books available on remote sensing and GIS. Here is brief introduction of some of these books which are useful for learning and understanding basics of remote sensing and GIS.

Title: Remote Sensing and Image Interpretation

by T.M. Lillesand and R.W. Kiefer John Wiley & Sons, Inc., New York

A must have. One of the best books on Remote Sensing highly recommended for beginners. It is like 'Bible' of Remote Sensing. Good reference material for experts also. All the aspects of remote sensing and image interpretation are discussed in details with all fundamental concepts.

Title: Remote Sensing of the Environment: An Earth Resource Perspective

by John R Jensen Pearson Education, Inc.

This book contains thirteen chapters. Basic principals of remote sensing for environment are discussed in depth. There are separate chapters for visual image interpretation, aerial photography and photogrammetry.

Title: Introduction to Remote Sensing

by James B. Cambell Taylor & Francis

Another good book on remote sensing fundamentals and basics.

Title: Introductory Digital Image Processing: A Remote Sensing Perspective

by John R Jensen Prentice Hall, New Jersey

Another good work from John R. Jensen. This book is a must for learning image processing of digital satellite images.

Title: Principles of Geographical Information System for Land Resource Assessment

by P.A. Burrough Oxford University Press

This is a fundamental book for understanding basic concepts of GIS.

Title: Geographical Information System

Volume I: Principal and Technical Issues

Volume II: Management Issues and Applications

Edited by P.A. Longley, M.F. Goodchild, D.J. Manguire, D.W. Rhino John Wiley & Sons

These two volumes contain chapters on principles, management and applications of GIS. A number of experts contributed in these to discuss and unfold various aspects of GIS and its applications in detail.

Title: The GIS Book

by George B Korte Onword Press, Thomson Learning, Inc.

What this book offers to you is written on its cover page itself- “How to implement, manage and assess the value of Geographical Information System".

Please see INDEX for complete list of topics.

Drones: An Overview and Benefits

OVERVIEW

Drones are Unmanned Aerial Vehicles (UAV) which are remotely controlled without any pilot on board. They are operated through a combination of technologies like computer vision, artificial intelligence and object avoidance. Like other remote sensing technologies, earlier drones were also used by military only. The emergence of drones for public use changed the way remotely sensed data are collected. It has enabled capturing of otherwise very expensive high-resolution data at low cost.

Drone mapping is the process of using drones to capture aerial images of an area and creating 2D or 3D maps and models.

The drones which are used for mapping purposes are equipped with GPS enabled sensors to record location and height. These can be calibrated with DGPS to achieve high locational accuracy. There can me multiple payloads on UAV depending upon application, e. g. thermal sensors for infrastructure inspections.

BENEFITS OF DRONE MAPPING

Cost-effective

Drone mapping is often more cost-effective than traditional mapping methods. Drones are relatively inexpensive to operate compared to manned aircraft or satellite imagery. They require fewer resources, have lower operational costs, and can cover large areas quickly, reducing the need for manual surveying or inspection.

Time-efficient

Drones can significantly reduce the time required for data collection and mapping. They can quickly capture high-resolution aerial imagery over large areas, saving time compared to ground-based surveying or traditional mapping methods. This increased efficiency allows for faster decision-making and project implementation.

Safety

Using drones for mapping eliminates or reduces the need for human personnel to access hazardous or inaccessible areas. Drones can be deployed to survey dangerous terrains, inspect tall structures or assess disaster-stricken areas without risking human lives. This enhances safety and mitigates potential risks associated with on-site inspections.

High Resolution Data

Drones equipped with advanced cameras and sensors can capture high-resolution imagery, enabling detailed mapping and analysis. This level of detail provides accurate measurements, precise identification of features and the ability to create detailed 2D or 3D maps, models, or point clouds.

Flexibility and Accessibility

Drones offer flexibility in terms of flight paths, altitude, and viewpoints. They can navigate through tight spaces, fly at various altitudes, and capture imagery from different angles. This flexibility allows for a comprehensive view of the area of interest and ensures accessibility to hard-to-reach or restricted areas.

Real-time Data and Monitoring

Drone mapping provide real-time data, allowing for instant analysis and decision-making. It enables live monitoring of construction sites, disaster areas or ongoing projects, providing up-to-date information for timely interventions or adjustments.

Environmental Impact

Compared to traditional mapping methods involving ground vehicles or manned aircraft, drones have a smaller carbon footprint. They consume less energy and produce fewer emissions, contributing to reduced environmental impact during data collection.

Enhanced Data Analysis

Drone mapping data can be processed using specialized software to generate accurate and detailed maps, models, or point clouds. This data can be integrated with Geographic Information System (GIS) or other analytical tools to extract valuable insights, identify patterns and make informed decisions.

Scalability

Drone mapping is scalable, meaning it can be used for small-scale projects or scaled up for larger areas. Drones can efficiently cover vast territories, making them suitable for applications such as large-scale infrastructure projects, agricultural monitoring or environmental assessments.

Vector Data Vs. Raster Data

Vector Data

Represented by point, line and polygon.
Relatively small file size (small data volume)
Excellent representation of networks.
A large no. of attributes can be attached, hence more information intensive and a number of thematic maps can be prepared from a single layer.
Features are more detailed & accurate.
Creating, cleaning and updating data is more time and labour consuming.
Topology-based analysis & operations are easier to perform (like network analysis etc.).
Can not represent continuous values like land use, elevation etc. very well.
Assigning projection and transformations are less time taking and consumes less memory of the computer system.
Topology makes data structure complex.

Raster Data

Points, line & polygons everything in the form of Pixels.
File size is larger than vector data.
Networks are not so well represented.
Only one pixel value represents each grid cell.
Generalization of features (like boundaries) hence accuracy may decrease.
Simulations and modeling is easier (spatial analysis, terrain modeling etc.).
Maintaining is easier.
Excellent for representing data containing continuous values (like land use, elevation etc.)
Coordinate-system transformations take more time and consume a lot of memory.
Grid cells or pixel makes simpler data structure.

Click here for many other useful topics

Visual Image Interpretation: ‘Visually Reading’ a Satellite Image

Satellite images are like books. To read and interpret these, we need to learn the language in which these are written. The more we practice the more conversant we become in interpreting images. Experience is the key for digging more and more information. Visual image interpretation comes with time and with understanding of elements which help to ‘decode’ the language of images. These elements of visual image interpretation are as follows:

Shape

Size

Tone

Texture

Pattern

Shadow

Location

Association

Shape

Shape of ground objects and features is one of the most important elements to identify them. For example- Road and rail both appear like lines but road has sharp curves while railway track has smooth curves. Natural water bodies are with irregular shape while most of the man-made water bodies have definite shape (rectangular, circular etc.). Same is true for natural drainage and man-made canal.

Size

Sizes are important in identifying many objects, e.g. on the basis of size we can differentiate between trees and bushes. Length, width, height (i.e. dimensions) and area provide clue for many objects. We can interpret in terms of absolute and relative sizes. When we talk about absolute size of a feature we go for exact dimensions while in relative size we look in terms of smaller or bigger. In high resolution satellite image one can easily assume size of a building by comparing it with size of a car parked next to it.

Tone

It refers to reflectance of features which we see in the form of tone of colours in a satellite image. As we discussed earlier different objects appear different in an image depending upon their spectral signatures. Hence this element gives firm evidence in identification of many features. On the basis of tone we can differentiate between plant species, age of plants, shallow & deep water bodies, dry & wet soil, crop types etc.

Texture

Texture of ground feature refers to how tones vary in the image. In other terms, how frequently tone varies. Textures are often said to be coarse and fine/smooth e.g. young plants generally have smooth texture while mature ones appear coarse-textured. Crops have smoother texture than vegetation.

Scale or resolution of satellite image should be considered while interpretation is being done on the basis of texture because low resolution images will show most of the features smooth-textured and after certain scale we can not differentiate between objects only on it.

Pattern

Arrangement of objects also helps in image interpretation. Most of the man-made features show definite pattern hence these can easily be differentiated from natural objects. For example, plantations have definite arrangement of trees with well defined pattern while natural vegetation will not have uniform pattern.

Shadow

Shadows are both good and bad for image interpretation. These are good for studying relief and identifying hilly regions. Tall objects (like clock tower, overhead water tanks etc.) which are sometimes difficult to locate, can easily identified with the help of their shadows.

Shadows are bad because these mask most of the features coming in their zone. These particularly create problems in hilly terrain where hill shadows hide information about vegetation and many other features.

Location/site

Site of presence of an object helps in avoiding misinterpreting it as other same looking object. For example- tones of two vegetation species may appear similar in an image but their geographical location can help to identify them correctly.

Association

While interpreting an image we should always consider how a particular feature is associated with its surroundings. For example- one can identify a village by- its small number of settlements, connecting roads, agriculture land in its adjoining area and often a water body.

Whether we are experts or novice- in image interpretation we should always consider a number of elements before concluding about features. Only considering one element may lead to erroneous identification of objects.