Sustainable Development Practices Using Geoinformatics. Группа авторов

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      Preface

      The sustainable development refers to the qualitative and quantitative stability in the use of natural resources. It involves equilibrium between anthropogenic activities as influenced by social activities, acquired knowledge, applied technology, and food production. Sustainability attempts to address the issues such as resource degradation, deforestation, ecosystem loss, and environmental deterioration from global to local scale. The sustainable use and management of essential natural resources cannot be done without considering the direct and indirect impacts of human. It is required to apply an interdisciplinary approach in order to ensure long-term conservation of natural resources and its sustainable use at ecological and socioeconomic perspectives.

      Geoinformatics, including Remote Sensing (RS), Geographical Information System (GIS), and Global Positioning System (GPS), has tremendous potential to effectively monitor the natural resources and addressing the concerns related to sustainable development and planning of society. RS is a quick and cost-effective technique to measure the location and spectral properties of earth surface features in comparison to traditional ground-based surveying. It provides reliable geospatial information for comprehensive sustainable development plans, policy making, and decision. GIS is a computer-based system used to digitize remotely sensed data matched with various ground-truth data, which are geo-coded using a GPS. It is able to manipulate, analyze, and display spatial database. Applications of Geoinformatics include land use change and planning, agriculture and soil, water resource management, forest resource mapping and management, glacier mapping and monitoring, climate change, disaster management, and many more.

Sustainable applications of Geoinformatics have become more essential in understanding various characteristics of Earth surfaces with the launch of Landsat mission in the 1970s. Many studies of direct relevance to the sustainable development and management have been reported. However, few studies have been reported using the harmonized approach of core science and research basics, as there are larger concerns of capacity building to use Geoinformatics in sustainable development practices and management. This could be overcome by taking the advantages of Geoinformatics into consideration to the scientific and research communities. The book entitled “Sustainable Development Practices Using Geoinformatics” contains chapters written by well-known researchers, academicians, and experts. The potential readers of this book are scientists, environmentalists, ecologists, policy makers, administrators, university students, urban planners, land managers, and professionals working in the field of sustainable development and management of natural resources.

      In Chapter 1, multi-temporal Landsat images are used to investigate the change in variability of surface temperature in the Barasat municipal area, West Bengal, India. A correlation analysis is performed between Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST) to show the urban growth and its pattern and trend in relation to surface temperature variation. This study is very useful for investigating the changes in environmental condition due to human activity in an urban area.

      In Chapter 2, attempts are made to estimate the geo-environmental hazards and risks in South Karanpura Coalfield region using information on land use/land cover (LU/LC), aerosol optical thickness (AOT), precipitable water vapor (PWV), and temperature conditions integrated with socio-economic vulnerability using Geoinformatics approach. Most of the risk-prone zones are found to present in the vicinity of industry and mining areas with higher population density. This study provides a basis to allocate resources for risk mitigation, improve community preparedness, and prepare cost-effective emergency planning.

      In Chapter 3, a co-polarized radar system is investigated for the estimation of soil moisture along specular direction. The data are collected by indigenously designed ground-based scatterometer system for 20°–60° incidence angles at steps of 10° in the specular direction for HH- and VV-polarizations at L-band. In this study, a hybrid machine learning algorithm combined with fuzzy inference system and artificial neural network called neuro-fuzzy inference system were evaluated for the estimation of soil moisture. The performance index Root Mean Squared Error (RMSE) was used to evaluate the estimation efficiency of the algorithm. This study is very useful for accurate and timely soil moisture estimation for agricultural practices.

In Chapter 4, a study is conducted for detailed morphometric analysis of Tapi basin using Geographic Information System (GIS) technique. Different morphometric parameters analyzed, viz., stream order, stream length, bifurcation ratio, drainage density, relief ratio, drainage density, stream frequency, texture ratio, form factor, circulatory ratio, elongation ratio, etc., are calculated. The stream order of the basin is mainly controlled by lithological and physiographic conditions of the area. The present study will be helpful for sustainable water resource management and agricultural applications.

      In Chapter 5, the demand for fossil fuels is increasing speedily with the rapid population growth and development. It is a leading factor of greenhouse gases emission, global warming, and climate change. There are some satellites are available to monitor the concentration of these gases in the atmosphere. This chapter described the importance and capacity of GOSAT satellite to observe and monitor the global distribution of carbon dioxide (CO₂). The kriging method is applied to analyze the global distribution of CO₂ during 2009 to 2020 for the months of December, January, February, and March.

      In Chapter 6, a study is СКАЧАТЬ