This article provides an overview of some of the recent research in agriculture involving remote sensing and GIS. Attention focuses on application of remote sensing and GIS specially in agriculture including geography, land surveying, most Earth Science disciplines, parent child relationship, unique identification, attributes, technical parameters, 2D/3D view and any other requirement customized. These advances have been made over recent years and foundations for future research established and can be efficiently used in Agriculture for better results.
Innovations in the agri-food sector are needed to create a sustainable food supply. Sustainable food supply requires unexpectedly that densely populated regions remain food producers. A Dutch innovation program has aimed at showing the way forward through creating a number of practice and scientific projects. Generic lessons from the scientific projects in this program are likely to be of interest to agricultural innovation in other densely populated regions in the world.
There is an ongoing debate on what constitutes sustainable intensification of agriculture (SIA). In this paper, we propose that a paradigm for sustainable intensification can be defined and translated into an operational framework for agricultural development. We argue that this paradigm must now be defined—at all scales—in the context of rapidly rising global environmental changes in the Anthropocene, while focusing on eradicating poverty and hunger and contributing to human wellbeing.
The increasing demand for agricultural commodities is a major cause of tropical deforestation. However, pressure is increasing for greater sustainability of commodity value chains. This includes the demand to establish new crop plantations and pasture areas on already deforested land so that new forest clearing for agriculture is minimized. Where tree crops are planted as part of agroforestry systems on deforested land, this amounts to a form of re-agro-forestation which can generate environmental benefits in addition to crop production.
The objective of this chapter is to describe the processes and experiences of forming country project teams, partnership models and approaches to reach farmers in Zimbabwe, Zambia and Malawi. This will improve understanding of methods of setting up sustainable partnerships that exist beyond donor-funded projects
Regional agroecological systems are examples of complex adaptive systems, where sustainability is promoted by social networks that facilitate information sharing, cooperation, and connectivity among specialized components of the system. Much of the existing literature on social capital fails to recognize how networks support multiple social processes.
This chapter presents an analytic framework to identify agricultural innovations that are sustainable and suitable for the poorest and most vulnerable parts of the population. The framework contains a set of tools to collect and evaluate information on appropriate innovations based on relevant criteria. It considers the dimensions of environmental resilience, economic viability, and social sustainability, as well as technical sustainability considering important properties of the innovation itself.
This book is an informative volume written by international experts in the fieldPresents recent advances in sustainable agriculture research and development focuses on environmentally sustainable and profitable food production systems. This volume is a ready reference on sustainable agriculture and reinforce the understanding for its utilization to develop environmentally sustainable and profitable food production systems.
Although many agronomic researchers currently focus on designing and developing decision support systems, they rarely discuss the methodological implications of such work. In this paper, with the examples of two decision support systems, we propose methodological elements for conducting the participatory design of such tools. The authors proposition aims at building dialogue between designers and users but also between humans, tools and work situations.
In this paper, a novel method to collect symptoms of the disease, as observed by the farmers, using a mobile phone application has been presented. A cumulative composite risk index (CCRI) obtained from more than one existing disease forecast models is validated from the actual late blight queries received from the farmers. The main contribution of the paper is a protocol that combines the symptoms based diagnostic approach along with the plant disease forecasting models resulting in detection of Potato late blight with higher accuracy.