Knowledge generation using satellite earth observations to support sustainable development goals (SDG): A use case on Land degradation

Land degradation is a critical issue globally requiring immediate actions for protecting biodiversity and associated services provided by ecosystems that are supporting human quality of life. The latest Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services Landmark Assessment Report highlighted that human activities are considerably degrading land and threating the well-being of approximately 3.2 billion people.In order to reduce and ideally reverse this prevailing situation, national capacities should be strengthened to enable effective assessments and mapping of their degraded lands as recommended by the United Nations Sustainable Development Goals (SDGs). The indicator 15.3.1 (“proportion of land that is degraded over total land area”) requires regular data production by countries to inform and assess it through space and time. Earth Observations (EO) can play an important role both for generating the indicator in countries where it is missing, as well complementing or enhancing national official data sources.In response to this issue, this paper presents an innovative, scalable and flexible approach to monitor land degradation at various scales (e.g., national, regional, global) using various components of the Global Earth Observation System of Systems (GEOSS) platform to leverage EO resources for informing SDG 15.3.1. The proposed approach follows the Data-Information-Knowledge pattern using the Trends.Earth model (http://trends.earth) and various data sources to generate the indicator. It also implements additional components for model execution and orchestration, knowledge management, and visualization.The proposed approach has been successfully applied at global, regional and national scales and advances the vision of (1) establishing data analytics platforms that can potentially support countries to discover, access and use the necessary datasets to assess land degradation; and (2) developing new capacities to effectively and efficiently use EO-based resources.     

GIS辅助下的基于知识的遥感影像分类方法研究——以土地覆盖/土地利用类型为例

提高计算机遥感影像的分类精度，是遥感应用中研究的主要问题之一。作者以规则的形式表示遥感影像解译知识，使用ＴＭ影像数据和ＤＥＭ、坡度、土地利用图等地理辅助数据，从遥感影像处理／地理数据／专家知识一体化的角度出发，使用基于知识的方法进行了研究，改善了分类精度。实例研究证明了方法的正确性。     

扎龙湿地沼泽的提取模型研究

利用扎龙湿地TM图像,通过分析各类地物的光谱特征、谱间结构特征以及采样剖面线,发现了扎龙湿地沼泽的光谱特征,并由此建立了一个基于知识发现的沼泽提取模型。提取结果表明,建立的沼泽提取模型能够实现自动提取扎龙湿地的芦苇沼泽,其精度可以达到98%。     

基于SPOT-5影像的河网结构知识挖掘研究

为从SPOT-5图像上提取苏州河网,设计了一种按层次进行的河网结构类型识别方法。首先,针对苏州河网总体结构特征,选择出典型判别因子；然后,用其中某一个或几个判别因子进行判别,按照统计特征分成可能的几个类别,再在结果类别中利用其它因子进行下一步判别。这样,以二分法的方式逐层深入地进行分类,最后达到河网结构类别识别的目的。     

Towards a knowledge base to support global change policy goals

ABSTRACT

In 2015, it was adopted the 2030 Agenda for Sustainable Development to end poverty, protect the planet and ensure that all people enjoy peace and prosperity. The year after, 17 Sustainable Development Goals (SDGs) officially came into force. In 2015, GEO (Group on Earth Observation) declared to support the implementation of SDGs. The GEO Global Earth Observation System of Systems (GEOSS) required a change of paradigm, moving from a data-centric approach to a more knowledge-driven one. To this end, the GEO System-of-Systems (SoS) framework may refer to the well-known Data-Information-Knowledge-Wisdom (DIKW) paradigm. In the context of an Earth Observation (EO) SoS, a set of main elements are recognized as connecting links for generating knowledge from EO and non-EO data – e.g. social and economic datasets. These elements are: Essential Variables (EVs), Indicators and Indexes, Goals and Targets. Their generation and use requires the development of a SoS KB whose management process has evolved the GEOSS Software Ecosystem into a GEOSS Social Ecosystem. This includes: collect, formalize, publish, access, use, and update knowledge. ConnectinGEO project analysed the knowledge necessary to recognize, formalize, access, and use EVs. The analysis recognized GEOSS gaps providing recommendations on supporting global decision-making within and across different domains.     

<Emphasis Type="Italic">Steak up to the horns</Emphasis>!

Recent conversations concerning organic food systems have focused on the conventionalization hypothesis, which posits that the organic food sector has become increasingly bifurcated between “historical” players in the organic movement on one side, and on the other by distributors and industrial operators recently arrived in the sector, who practice a more conventionalized form of organic agriculture which is now on the ascendancy. The most prominent explanations for the growth and dominance of a conventionalized organic food system have been economic, based in the logics of input costs, especially land rent. We use the cases of the Belgian Blue commodity system and the Belgian organic beef commodity system to argue that conventionalization is also cognitive. To understand the role of cognition in the ascendance of the conventional organic food sector, we utilize concept of “référentiel”—or system of cognitive references—as developed by Muller and Jobert. We believe that comparing organic and conventional practices as two systems of cognitive references makes a deeper understanding of conventionalization possible in two ways: first because it makes it clear that the two systems coexist on a cognitive level, understood in a broad sense as tightly knit sets of knowledges, beliefs, standards, and images. Secondly, the concept of référentiel enables one to understand how the conventional system can become irreversible (lock-in effect) and thus incompatible with the development of the organic system.

Science-based coastal management in Fiji: Two case studies from the NGO sector

The effectiveness of coastal management in developing countries is widely perceived to be inhibited by a lack of scientific data on the coastal zone. To try to fill this need for information, donors and big international non-governmental organizations are increasingly initiating large-scale, science-driven conservation programs, with the goal of creating and using management relevant transdisciplinary datasets. In Oceania, these programs are entering a context where local ecological knowledge is already informing existing community-based approaches to coastal management. This paper examines two large-scale programs in Fiji, the Marine Management Area Science initiative and the Vatu-i-Ra and Cakau Levu Reefs Seascape Project, and offers insight relevant to the planning and implementation of similar programs where local management systems are already in place. Research methods used to examine the programs included document analysis, direct observation, and semi-structured interviews with key stakeholders over multiple field visits to Fiji in 2009 and 2010. Results suggest that as donors, non-governmental organizations, and partners move forward in implementing these programs, there must be active steps taken to bridge boundaries between disciplines and among knowledge systems, evaluate the added value of science for all stakeholder groups, and build opportunities for datasets to be used after donor funding ends.     

Why people matter in ocean governance: Incorporating human dimensions into large-scale marine protected areas

Large-scale marine protected areas (LSMPAs) are rapidly increasing. Due to their sheer size, complex socio-political realities, and distinct local cultural perspectives and economic needs, implementing and managing LSMPAs successfully creates a number of human dimensions challenges. It is timely and important to explore the human dimensions of LSMPAs. This paper draws on the results of a global “Think Tank on the Human Dimensions of Large Scale Marine Protected Areas” involving 125 people from 17 countries, including representatives from government agencies, non-governmental organizations, academia, professionals, industry, cultural/indigenous leaders and LSMPA site managers. The overarching goal of this effort was to be proactive in understanding the issues and developing best management practices and a research agenda that address the human dimensions of LSMPAs. Identified best management practices for the human dimensions of LSMPAs included: integration of culture and traditions, effective public and stakeholder engagement, maintenance of livelihoods and wellbeing, promotion of economic sustainability, conflict management and resolution, transparency and matching institutions, legitimate and appropriate governance, and social justice and empowerment. A shared human dimensions research agenda was developed that included priority topics under the themes of scoping human dimensions, governance, politics, social and economic outcomes, and culture and tradition. The authors discuss future directions in researching and incorporating human dimensions into LSMPAs design and management, reflect on this global effort to co-produce knowledge and re-orient practice on the human dimensions of LSMPAs, and invite others to join a nascent community of practice on the human dimensions of large-scale marine conservation.     

The emergence of a hybrid mode of knowledge production in the Generation Challenge Programme Rice Research Network (GCP-RRN) in India: Exploring the concept of Commons-Based Peer Production (CBPP)

The Generation Challenge Programme (GCP) was an international agrarian knowledge-production programme created in 2003 by the CGIAR. GCP aims at developing drought tolerant varieties by reconciling upstream biotechnology based advanced research with the downstream development at the farmer's field. The objective of this paper is to apply the theory of Commons Based Peer Production (CBPP) to analyse the knowledge production process of GCP, especially the case of drought tolerant rice research network in Indian context (GCP-RRN). CBPP represents the theorisation of a mode of production that can be distinguished from market (private) and state (public) knowledge-production systems that was developed by observing the phenomena of Free and Open Source Software (FOSS). The organisational attributes of the CBPP mode applied in computer software production include the modulation of work, small-size granularity of components, and mechanisms that integrate these modules into an end product. Socio-economically, this form of production is based on cooperation, collaboration and collective action rather than property, contract and managerial hierarchies. This paper argues that GCP-RRN knowledge production is basically a hybridised one in which there are certain inclinations towards CBPP within certain larger context, and there are other attributes too that do not fall within CBPP theorisation. Further, this paper elaborates on the implications of this hybridised model for agrarian knowledge production discourse and institutions.     

知识经济时代对财会人员的素质要求

当今时代正处在由工业经济向知识经济过渡的新时期。我国改革开放和社会主义现代化建设事业蓬勃发展 ,社会主义市场经济体制逐步完善 ,加入WTO已成定局。为适应新形势的要求 ,财会人员面临新的挑战 ,肩负艰巨的任务 ,要求具备更高的素质