Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables

ABSTRACT

Global, fast and accessible monitoring of biodiversity is one of the main pillars of the efforts undertaken in order to revert it loss. The Group on Earth Observations Biodiversity Observation Network (GEO-BON) provided an expert-based definition of the biological properties that should be monitored, the Essential Biodiversity Variables (EBVs). Initiatives to provide indicators for EBVs rely on global, freely available remote sensing (RS) products in combination with empirical models and field data, and are invaluable for decision making. In this study, we provide alternatives for the expansion and improvement of the EBV indicators, by suggesting current and future data from the European Space Agencýs COPERNICUS and explore the potential of RS-integrated Dynamic Global Vegetation Models (DGVMs) for the estimation of EBVs. Our review found that mainly due to the inclusion of the Sentinel constellation, Copernicus products have similar or superior potential for EBV indicator estimation in relation to their NASA counterparts. DGVMs simulate the ecosystem level EBVs (ecosystem function and structure), and when integrated with remote sensing data have great potential to not only offer improved estimation of current states but to provide projection of ecosystem impacts. We suggest that focus on producing EBV relevant outputs should be a priority within the research community, to support biodiversity preservation efforts.     

A meta-analysis of global crop water productivity of three leading world crops (wheat,corn, and rice) in the irrigated areas over three decades

ABSTRACT

The overarching goal of this study was to perform a comprehensive meta-analysis of irrigated agricultural Crop Water Productivity (CWP) of the world’s three leading crops: wheat, corn, and rice based on three decades of remote sensing and non-remote sensing-based studies. Overall, CWP data from 148 crop growing study sites (60 wheat, 43 corn, and 45 rice) spread across the world were gathered from published articles spanning 31 different countries. There was overwhelming evidence of a significant increase in CWP with an increase in latitude for predominately northern hemisphere datasets. For example, corn grown in latitude 40–50° had much higher mean CWP (2.45?kg/m³) compared to mean CWP of corn grown in other latitudes such as 30–40° (1.67?kg/m³) or 20–30° (0.94?kg/m³). The same trend existed for wheat and rice as well. For soils, none of the CWP values, for any of the three crops, were statistically different. However, mean CWP in higher latitudes for the same soil was significantly higher than the mean CWP for the same soil in lower latitudes. This applied for all three crops studied. For wheat, the global CWP categories were low (≤0.75?kg/m³), medium (>0.75 to <1.10?kg/m³), and high CWP (≥1.10?kg/m³). For corn the global CWP categories were low (≤1.25?kg/m³), medium (>1.25 to ≤1.75?kg/m³), and high (>1.75?kg/m³). For rice the global CWP categories were low (≤0.70?kg/m³), medium (>0.70 to ≤1.25?kg/m³), and high (>1.25?kg/m³). USA and China are the only two countries that have consistently high CWP for wheat, corn, and rice. Australia and India have medium CWP for wheat and rice. India’s corn, however, has low CWP. Egypt, Turkey, Netherlands, Mexico, and Israel have high CWP for wheat. Romania, Argentina, and Hungary have high CWP for corn, and Philippines has high CWP for rice. All other countries have either low or medium CWP for all three crops. Based on data in this study, the highest consumers of water for crop production also have the most potential for water savings. These countries are USA, India, and China for wheat; USA, China, and Brazil for corn; India, China, and Pakistan for rice. For example, even just a 10% increase in CWP of wheat grown in India can save 6974 billion liters of water. This is equivalent to creating 6974 lakes each of 100?m³ in volume that leads to many benefits such as acting as ‘water banks’ for lean season, recreation, and numerous ecological services. This study establishes the volume of water that can be saved for each crop in each country when there is an increase in CWP by 10%, 20%, and 30%.     

A Framework and Software Tool to Support Collaborative Landscape Analysis: Fitting Square Pegs into Square Holes

For landscape models to be applied successfully in management situations, models must address appropriate questions, include relevant processes and interactions, be perceived as credible and involve people affected by decisions. We propose a framework for collaborative model building that can address these issues, and has its roots in adaptive management, computer‐supported collaborative work and landscape ecology. Models built through this framework integrate a variety of information sources, address relevant questions, and are customized for the particular landscape and policy environment under study. Participants are involved in the process from the start, and because their input is incorporated, they feel ownership of the resulting models, increasing the chance of model acceptance and application. There are two requirements for success: a tool that supports rapid model prototyping and modification, that makes a clear link between a conceptual and implemented model, and that has the ability to implement a wide range of model types; and a core team with skills in communication, research and analysis, and knowledge of ecology and forestry in addition to modelling. SELES (Spatially Explicit Landscape Event Simulator) is a tool for building and running models of landscape dynamics. It combines discrete event simulation with a spatial database and a relatively simple modelling language to allow rapid development of landscape simulations, and provides a high‐level means of specifying complex model behaviours ranging from management actions to natural disturbance and succession. We have applied our framework in several forest modelling projects in British Columbia, Canada. We have found that this framework increases the interest by local experts and decision‐makers to participate actively in the model building process. The workshop process and resulting models have efficiently provided insight into the dynamics of large landscapes over long time frames. The use of SELES has facilitated this process by providing a flexible, transparent environment in which models can be rapidly implemented and refined. As a result, model findings may be more readily incorporated into decision‐support systems designed to assist resource managers in making informed decisions.     

Precise Real-Time Positioning in WADGPS Networks

In recent years the importance of real-time positioning and navigation with the Global Positioning System (GPS) has grown rapidly. Starting from the establishment of differential GPS (DGPS) reference stations for marine and land navigation, new users and applications have emerged that resulted in a high demand for the establishment of a high-density network of reference stations around the world. Many countries have established their own DGPS service, which is either governmentally or commercially owned. These services are referred to as Local Area DGPS Systems (LADGPS). However, the costs for the establishment and maintenance of a dense network of reference stations are very high. Therefore Wide Area DGPS Systems (WADGPS) are being developed to overcome the main drawbacks of LADGPS. In this case, only a few reference stations are used to cover a large area, such s a continent like Europe. To achieve high positioning accuracies, real-time modeling of the main error sources for long-range baselines is required as errors in the satellite orbit and ionospheric refraction do not cancel entirely in double differencing. In this article, a real-time correction model based on the Kalman filter for WADGPS and networked LADGPS services is discussed and results of field tests in a WADGPS network in Europe are presented. ? 2000 John Wiley & Sons, Inc.     

From GPS and GLONASS via EGNOS to Galileo – Positioning and Navigation in the Third Millennium

Positioning and navigation – as are presently possible with the American Global Positioning System (GPS) and the Russian GLONASS system – is briefly reviewed. Deficiencies, which have led to augmentations like the European Geostationary Navigation Overlay System (EGNOS), are outlined. Europe's decision to get involved in the definition and possible set-up of a Global Navigation Satellite System (GNSS) of the second generation (GNSS-2), called Galileo, is discussed in detail as well as the GPS modernization program that might take place during the sample phase. Finally, some brief thoughts on the benefit of GNSS-2 for geodesy and surveying are given. ? 2000 John Wiley & Sons, Inc.     

The success rate and precision of GPS ambiguities

 An application of a theorem on the optimality of integer least-squares (LS) is described. This theorem states that the integer LS estimator maximizes the ambiguity success rate within the class of admissible integer estimators. This theorem is used to show how the probability of correct integer estimation depends on changes in the second moment of the ambiguity `float' solution. The distribution of the `float' solution is considered to be a member of the broad family of elliptically contoured distributions. Eigenvalue-based bounds for the ambiguity success rate are obtained. Received: 11 January 1999 / Accepted: 2 November 1999     

Integer estimation in the presence of biases

 Carrier phase ambiguity resolution is the key to fast and high-precision GNSS (Global Navigation Satellite System) kinematic positioning. Critical in the application of ambiguity resolution is the quality of the computed integer ambiguities. Unsuccessful ambiguity resolution, when passed unnoticed, will too often lead to unacceptable errors in the positioning results. Very high success rates are therefore required for ambiguity resolution to be reliable. Biases which are unaccounted for will lower the success rate and thus increase the chance of unsuccessful ambiguity resolution. The performance of integer ambiguity estimation in the presence of such biases is studied. Particular attention is given to integer rounding, integer bootstrapping and integer least squares. Lower and upper bounds, as well as an exact and easy-to-compute formula for the bias-affected success rate, are presented. These results will enable the evaluation of the bias robustness of ambiguity resolution. Received: 28 September 2000 / Accepted: 29 March 2001