Online Spatial Data Analysis and Algorithm Development for Geo-scientific Applications Using Remote Sensing Data

2017 ◽  
Vol 87 (4) ◽  
pp. 701-712 ◽  
Author(s):  
Harish C. Karnatak ◽  
Hariom Singh ◽  
R. D. Garg
Keyword(s):  
Remote Sensing ◽  
Data Analysis ◽  
Spatial Data ◽  
Remote Sensing Data ◽  
Spatial Data Analysis ◽  
Scientific Applications ◽  
Algorithm Development ◽  
Sensing Data

An Introduction to Spatial Data Analysis

2020 ◽  
Author(s):  
Martin Wegmann ◽  
Jakob Schwalb-Willmann ◽  
Stefan Dech
Keyword(s):  
Remote Sensing ◽  
Data Analysis ◽  
Open Source ◽  
Spatial Data ◽  
Remote Sensing Data ◽  
Spatial Data Analysis ◽  
Data Sets ◽  
Data Handling ◽  
Book Covers

This is a book about how ecologists can integrate remote sensing and GIS in their research. It will allow readers to get started with the application of remote sensing and to understand its potential and limitations. Using practical examples, the book covers all necessary steps from planning field campaigns to deriving ecologically relevant information through remote sensing and modelling of species distributions. An Introduction to Spatial Data Analysis introduces spatial data handling using the open source software Quantum GIS (QGIS). In addition, readers will be guided through their first steps in the R programming language. The authors explain the fundamentals of spatial data handling and analysis, empowering the reader to turn data acquired in the field into actual spatial data. Readers will learn to process and analyse spatial data of different types and interpret the data and results. After finishing this book, readers will be able to address questions such as “What is the distance to the border of the protected area?”, “Which points are located close to a road?”, “Which fraction of land cover types exist in my study area?” using different software and techniques. This book is for novice spatial data users and does not assume any prior knowledge of spatial data itself or practical experience working with such data sets. Readers will likely include student and professional ecologists, geographers and any environmental scientists or practitioners who need to collect, visualize and analyse spatial data. The software used is the widely applied open source scientific programs QGIS and R. All scripts and data sets used in the book will be provided online at book.ecosens.org. This book covers specific methods including: what to consider before collecting in situ data how to work with spatial data collected in situ the difference between raster and vector data how to acquire further vector and raster data how to create relevant environmental information how to combine and analyse in situ and remote sensing data how to create useful maps for field work and presentations how to use QGIS and R for spatial analysis how to develop analysis scripts

scholarly journals A Review of Kernel Methods in Remote Sensing Data Analysis

2011 ◽  
pp. 171-206 ◽  
Author(s):  
Luis Gómez-Chova ◽  
Jordi Muñoz-Marí ◽  
Valero Laparra ◽  
Jesús Malo-López ◽  
Gustavo Camps-Valls
Keyword(s):  
Remote Sensing ◽  
Data Analysis ◽  
Kernel Methods ◽  
Remote Sensing Data ◽  
Sensing Data

Uncertainty Handling in Remote Sensing Data Analysis for Defence

1995 ◽  
Vol 45 (4) ◽  
pp. 303-306
Author(s):  
D. P. Mandal ◽  
C. A. Murthy ◽  
S. K. Pal
Keyword(s):  
Remote Sensing ◽  
Data Analysis ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Uncertainty Handling

scholarly journals Hyperspectral Remote Sensing Data Analysis and Future Challenges

2013 ◽  
Vol 1 (2) ◽  
pp. 6-36 ◽  
Author(s):  
Jose M. Bioucas-Dias ◽  
Antonio Plaza ◽  
Gustavo Camps-Valls ◽  
Paul Scheunders ◽  
Nasser Nasrabadi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Analysis ◽  
Remote Sensing Data ◽  
Hyperspectral Remote Sensing ◽  
Sensing Data ◽  
Future Challenges
Sign in / Sign up

Export Citation Format

Share Document