Climate change, resulted from the rise in global temperature, drives many stressors which make it difficult to predict the outcome in a general way. However, impact of climate change is so far more visible in agriculture than other sectors. Rise in temperature causes oxidation of soil organic carbon and affect biogeochemical processes and mechanisms, which make soil health and productive potential of soils weaker. It also affects weather at local regional and global scale, and hydrological cycle as well, which result in drought, flood, cyclones etc. Simultaneously it impinges directly upon reproductive biology of crops by reducing pollen viability and making spikelets sterile, which result in crop yield reduction. In India, impact of climate change on agriculture is predicted to occur more in northern parts, where wheat production may suffer losses of 4-5 million tons for each degree rise in temperature. Rice, pearl millet, soybean are other crops in that line. Globally, it has been predicted to have a huge burden in future as the world needs to feed nine billion population by the turn of the 21st century. Several techniques like conservation agriculture, integrated farming, crop diversification and carbon sequestration through agroforestry advocated helping climate change mitigation and adaptation have been discussed in detail in this book. Therefore, this book serves as a repository of information on climate change, mitigation and adaptation in relation to agroforestry, which can be useful to planner, researchers and undergraduate and post graduate students pursuing studies in the field of agricultural and allied sciences.

To understand the catastrophic processes of forest fire danger, different deterministic, probabilistic, and empiric models must be used. Simulating various surface and crown forest fires using predictive information technology could lead to the improvement of existing systems and the examination of the ecological and economic effects of forest fires in other countries. Predicting, Monitoring, and Assessing Forest Fire Dangers and Risks provides innovative insights into forestry management and fire statistics. The content within this publication examines climate change, thermal radiation, and remote sensing. It is designed for fire investigators, forestry technicians, emergency managers, fire and rescue specialists, professionals, researchers, meteorologists, computer engineers, academicians, and students invested in topics centered around providing conjugate information on forest fire danger and risk.

Shivalik ranges cover an area of about 2.14 million ha in Himachal Pradesh, Uttarakhand, Jammu and Kashmir, Punjab and Haryana States of north-west India. Over exploitation of the resources in the region had lead to soil erosion resulting in the rise of riverbeds, siltation of tanks, reservoirs and other natural water bodies. Soil erosion greater than 80 t ha-1 yr-1 have been recorded from denuded hills at places. More than 70 per cent people of the region are dependent on agriculture, however, only 18 per cent of the cultivated area is irrigated. Agroforestry where tree and crops are integrated with each other had been recommended worldwide to check soil erosion and simultaneously achieve production goals. Adoption of scientifically proven agroforestry systems in Shivaliks can reverse the degradation and improve the economic status of the farmers of the region. Extensive research had been done till date on role of agroforestry in resource conservation and livelihood security in the region. The book is an attempt to compile the available knowledge on the subject. There are 20 s in the book covering various topics relating agroforestry systems with soil and water conservation, livelihood security, slope protection through mechanical and vegetative measures, fertility build up, mine spoil rehabilitation, bamboos, climate change and carbon sequestration.

The environmental and economic importance of monitoring forests and agricultural resources has allowed remote sensing to be increasingly in the development of products and services responding to user needs. This volume presents the main applications in remote sensing for agriculture and forestry, including the primary soil properties, the estimation of the vegetation's biophysical variables, methods for mapping land cover, the contribution of remote sensing for crop and water monitoring, and the estimation of the forest cover properties (cover dynamic, height, biomass). This book, part of a set of six volumes, has been produced by scientists who are internationally renowned in their fields. It is addressed to students (engineers, Masters, PhD), engineers and scientists, specialists in remote sensing applied to agriculture and forestry. Through this pedagogical work, the authors contribute to breaking down the barriers that hinder the use of radar imaging techniques.

Forest fires cause ecological, economic, and social damage to various states of the international community. The causes of forest fires are rather varied, but the main factor is human activity in settlements, industrial facilities, objects of transport infrastructure, and intensively developed territories (in other words, anthropogenic load). In turn, storm activity is also a basic reason for forest fires in remote territories. Therefore, scientists across the world have developed methods, approaches, and systems to predict forest fire danger, including the impact of human and storm activity on forested territories. An important and comprehensive point of research is on the complex deterministic-probabilistic approach, which combines mathematical models of forest fuel ignition by various sources of high temperature and probabilistic criteria of forest fire occurrence. Forest Fire Danger Prediction Using Deterministic-Probabilistic Approach provides a comprehensive approach of forest fire danger prediction using mathematical models of forest fuel with consideration to anthropogenic load, storm activity, and meteorological parameters. Specifically, it uses the deterministic-probabilistic approach to predict forest fire danger and improve forest protection from fires. The chapters will cover various tree types, mathematical models, and solutions for reducing the destructive consequences of forest fires on ecosystems. This book is ideal for professionals and researchers working in the field of forestry, forest fire danger researchers, executives, computer engineers, practitioners, government officials, policymakers, academicians, and students looking for a new system to predict forest fire danger.