Land Cover Changes And Their Relationship With Land Surface Temperature Using Remote Sensing Technique Penerbit Usm

Nowadays, land cover changes are a major issue of global environmental change. Investigation on this subject has now been done by using remote sensing application. Research has been done in the Penang Island, which is one of the affected areas due to industrial and residential areas growth. Thus, this monograph is published to demonstrate an effective application through remote sensing technique to explore the environmental change and its impact on local environment that is caused by abrupt change in land use. It provides appropriate and comprehensive information for researchers involved in the study of environmental management, urban planning, land surface characteristics, and related support fields. This monograph highlights the relationship between land surface temperature and normalized difference vegetation index as the major results. The remote sensing technique used in this study was found to be efficient. It reduced the time for the analysis of land cover changes and was found to be a useful tool. Universiti Sains Malaysia, Penerbit Universiti Sains Malaysia

This monograph is the outcome of 15 years experience of working with satellite images with the funding from IRPA RM7, ESCAP NASDA, Science Fund and several short term grants. It introduces a new methodology and algorithms for water and air quality monitoring by using conventional digital camera as a sensor to provide multi-spectral remote sensing data. The image is either captured by a digital camera mounted in an unman aircraft vehicle (UAV) or directly captured from a light air-craft. New algorithms were developed to correlate the pollutant concentration with the digital images. The algorithms can also generate a map of the pollutant concentration of the studied area. Pollutant information is very important for survey information, tourism information, development assessment, coastal preservation and area development planning. This new methodology allows images to be captured below the cloud level. Thus, with this method and the algorithms, cloud cover problem of satellite and airborne images can be overcome. They also overcome the problems of time, money, and resources wasted in collecting in-situ data for algorithm calibration of cloud cover satellite images. Furthermore, they provide real-time, high accuracy information. Universiti Sains Malaysia, Penerbit Universiti Sains Malaysia

Although remote sensing is recognized as a powerful tool, less attention has been given in the past to the use of thermal, and especially thermal infrared (TIR) remote sensing. TIR data is useful for understanding the fluxes and redistribution of materials as a key aspect of land surface processes and land-atmosphere inter-relationships. This book

The rapid urban expansion and associated land cover conversions in the last two decades call for an urgent need for developing advanced analytical and quantitative methods to manage the adverse impacts on urban ecology and climate. The lower landscape connectivity, higher land cover fragmentation and increase in higher surface temperatures in urban areas are largely a consequence of surface energy balance alteration triggered by the replacement of natural land covers like green spaces, wetlands with built areas, and impervious surfaces. These spatial-temporal variability changes have detrimental and significant impacts on the local and regional urban climate challenges that require both new Geospatial Analytic approaches and new sources of data and information. Emerging Geospatial technologies (Big Data, Cloud Computing, Google Earth Engines, Advanced Machine Learning Algorithms and Deep learning) offer great opportunities to acquire ubiquitous spatial data, continuous observations, and monitoring of the earth’s surface, detect the spatiotemporal patterns of changes in the landscape and urban climate and make predictions and scenarios for future urban ecology and surface temperature trends.

This book focuses on validation and reconstruction work on the land surface temperature (LST) products retrieved by thermal infrared remote sensing. The LST is a key parameter in the energy-water balance process and has been widely used in research on the global climate change, water cycle, vegetation growing, and drought detection. Remote sensing retrieving LST is the most important source for regional and even global application. However, there are several factors that limited their widespread use: (1) the thermal infrared remote sensing is easily influenced by clouds; therefore, there are lots of pixel with invalid LST; (2) LST products have not been sufficiently validated in global scale. This book arms to overcome above defects and guide the readers to estimate the LST of cloudy pixel and implement the general validation on the remote sensing LST. Furthermore, it helps to understand the scale mismatch between different observation and land surface heterogeneity. The book covers ground-based observation, validation and reconstruction theories, scale mismatch analysis, heterogeneity and representativeness evaluation for observations, and application cases. It is an essential reference to the quantitative retrieval of thermal infrared remote sensing technologies.

This book provides a step-by-step guide on how to use various publicly available remotely sensed time series data sources for environmental monitoring and assessment. Readers will learn how to extract valuable information on global changes from a 20-year collection of ready-to-use remotely sensed data through the free open statistical software R and its geographic data analysis and modeling tools. The case studies are from the Mediterranean region—a designated hot spot regarding climate change effects. Each chapter is dedicated to specific remote sensing products chosen for their spatial resolution. The methods used are adapted from large-scale to smaller-scale problems for different land cover areas. Features Includes real-world applications of environmental remotely sensed data Analyzes the advantages and restrictions of each data source Focuses on a wide spectrum of applications, such as hydrology, vegetation changes, land surface temperature, fire detection, and impacts Includes R computer codes with explanatory comments and all applications use only freely available remotely sensed data Presents a step-by-step processing through open source GIS and statistical analysis software Advanced Environmental Monitoring with Remote Sensing Time Series Data and R describes and provides details on recent advances concerning publicly available remotely sensed time series data in environmental monitoring and assessment. This book is a must-have practical guide for environmental researchers, professionals, and students.

Written by world renowned scientists, this book provides an excellent overview of a wide array of methods and techniques for the processing and analysis of multitemporal remotely sensed images. These methods and techniques include change detection, multitemporal data fusion, coarse-resolution time series processing, and interferometric SAR multitemporal processing, among others. A broad range of multitemporal datasets are used in their methodology demonstrations and application examples, including multispectral, hyperspectral, SAR and passive microwave data. This book features a variety of application examples covering both land and aquatic environments. Land applications include urban, agriculture, habitat disturbance, vegetation dynamics, soil moisture, land surface albedo, land surface temperature, glacier and disaster recovery. Aquatic applications include monitoring water quality, water surface areas and water fluctuation in wetland areas, spatial distribution patterns and temporal fluctuation trends of global land surface water, as well as evaluation of water quality in several coastal and marine environments. This book will help scientists, practitioners, students gain a greater understanding of how multitemporal remote sensing could be effectively used to monitor our changing planet at local, regional, and global scales.