Uncertainties in classification system conversion and an analysis of inconsistencies in global land cover products

In this study, using the common classification systems of IGBP-17, IGBP-9, IPCC-5 and TC (vegetation, wetlands and others only), we studied spatial and areal inconsistencies in the three most recent multi-resource land cover products in a complex mountain-oasis-desert system and quantitatively discussed the uncertainties in classification system conversion. This is the first study to compare these products based on terrain and to quantitatively study the uncertainties in classification system conversion. The inconsistencies and uncertainties decreased from high to low levels of aggregation (IGBP-17 to TC) and from mountain to desert areas, indicating that the inconsistencies are not only influenced by the level of thematic detail and landscape complexity but also related to the conversion uncertainties. The overall areal inconsistency in the comparison of the FROM-GLC and GlobCover 2009 datasets is the smallest among the three pairs, but the smallest overall spatial inconsistency was observed between the FROM-GLC and MODISLC. The GlobCover 2009 had the largest conversion uncertainties due to mosaic land cover definition, with values up to 23.9%, 9.68% and 0.11% in mountainous, oasis and desert areas, respectively. The FROM-GLC had the smallest inconsistency, with values less than 4.58%, 1.89% and 1.2% in corresponding areas. Because the FROM-GLC dataset uses a hierarchical classification scheme with explicit attribution from the second level to the first, this system is suggested for producers of map land cover products in the future

Assessing inconsistency in global land cover products and a synthesis of studies on land use and land cover dynamics during 2001-2017 in the southeastern region of Bangladesh

The high-quality Land Use and Land Cover data is important for monitoring and analyzing environmental changes in the background of global warming. This study accessed the spatial and areal inconsistencies in the four most recent multi-resources land cover products in a complex manner using the common classification systems of IGBP-17, IGBP-9, IPCC-5 and TC (vegetation, wetlands and others only). Based on inconsistencies and multi temporal land cover datasets, a synthesis of study was triggered out on land use and land cover dynamics during 2001-2017 in the southeastern region of Bangladesh. The overall areal and spatial inconsistencies decreased from high to low levels of aggregation (IGBP-17 to TC), indicating that the inconsistencies are not only influenced by the level of thematic detail and landscape complexity but also related to the conversion uncertainties. Overall areal inconsistency in the comparison of the FROM-GLC and GlobeLand30 datasets was the smallest among the six pairs, while, the pair of MODISLC and LULC was observed the highest inconsistencies. Based on overall lower inconsistencies classification system (IGBP-9), the synthetic land use cover changes at the study area were assessed. During the period of study, the areal distribution of forest cover, built-up areas and water were found increased in annually by 0.4%, 1.32%, and 0.3% respectively, while the croplands and wetlands were respectively decreased by 0.5% and 0.3%. The dynamic changes of croplands, forest, and artificial surface were identified the prime cyclic land cover change. This research is helpful in providing training areas for the producer of land cover products

Challenges in using land use and land cover data for global change studies

Land use and land cover data play a central role in climate change assessments. These data originate from different sources and inventory techniques. Each source of land use/cover data has its own domain of applicability and quality standards. Often data are selected without explicitly considering the suitability of the data for the specific application, the bias originating from data inventory and aggregation, and the effects of the uncertainty in the data on the results of the assessment. Uncertainties due to data selection and handling can be in the same order of magnitude as uncertainties related to the representation of the processes under investigation. While acknowledging the differences in data sources and the causes of inconsistencies, several methods have been developed to optimally extract information from the data and document the uncertainties. These methods include data integration, improved validation techniques and harmonization of classification systems. Based on the data needs of global change studies and the data availability, recommendations are formulated aimed at optimal use of current data and focused efforts for additional data collection. These include: improved documentation using classification systems for land use/cover data; careful selection of data given the specific application and the use of appropriate scaling and aggregation methods. In addition, the data availability may be improved by the combination of different data sources to optimize information content while collection of additional data must focus on validation of available data sets and improved coverage of regions and land cover types with a high level of uncertainty. Specific attention in data collection should be given to the representation of land management (systems) and mosaic landscape

Land-use Change and Forestry in Austria: A Scientific Assessment of Austria's Carbon Balance in Light of Article 3 of the Kyoto Protocol

Article 3 of the Kyoto Protocol states that Parties included in Annex I shall use net changes in greenhouse gas emissions from sources and removals by sinks resulting from direct human-induced land-use change and forestry (LUCF) activities since 1990 to meet their their emission reduction commitments. However, even with clear guidelines on how to calculate LUCF emissions and removals, considerable problems remain. Our paper addresses a number of relevant issues by summarizing the knowledge gained from assessing and quantifying sources and sinks of carbon compounds relevant to Austria on the basis of an interated operational model framework, the "Austrian Carbon Balance Model" (ACBM). The ACBM covers Austria's biosphere and technosphere and at present permits project researchers to run a Reference Scenario for 1990-2050. We attempt to generalize our experience and also to compare our model results regarding Austria's net atmospheric carbon contribution on the basis of uncertainties underlying these results. This permits us (1) to identify several high-priority research issues that will enable Austria to cope adequately with its commitments under the Kyoto Protocol; and (2) to draw general conclusions that may provide support to the Conference of the Parties as it decides upon modalities, rules and guidelines in accounting for LUCF emissions and removals

Harmonizing and combining existing land cover/land use datasets for cropland area monitoring at the African continental scale

Mapping cropland areas is of great interest in diverse fields, from crop monitoring to climate change and food security. Recognizing the value of a reliable and harmonized crop mask that entirely covers the African continent, the objectives of this study were to (i) consolidate the best existing land cover/land use datasets, (ii) adapt the Land Cover Classification System (LCCS) for harmonization, (iii) assess the final product, and (iv) compare the final product with two existing datasets. Ten datasets were compared and combined through an expert-based approach to create the derived map of cropland areas at 250m covering the whole of Africa. The resulting cropland mask was compared with two recent cropland extent maps at 1km: one derived from MODIS and one derived from five existing products. The accuracy of the three products was assessed against a validation sample of 3591 pixels of 1km regularly distributed over Africa and interpreted using high resolution images, which were collected using the Geo-Wiki tool. The comparison of the resulting crop mask with existing products shows that it has a greater agreement with the expert validation dataset, in particular for places where the cropland represents more than 30% of the area of the validation pixel.JRC.H.4-Monitoring Agricultural Resource

The challenges of using satellite data sets to assess historical land use change and associated greenhouse gas emissions: a case study of three Indonesian provinces

Advances in satellite remote sensing and the wealth of earth observation (EO) data now available have improved efforts toward determining and quantifying historical land use and land cover (LULC) change. Satellite imagery can overcome the absence of accurate records of historical land use; however, the variability observed in the case study regions demonstrates a number of current challenges. Differences in spatial coverage, resolution and land cover classification can lead to challenges in analyzing historical data sets to estimate LULC change and associated GHG emissions. This paper demonstrates the calculation of LULC change from three existing, open-source data sets to show how this can lead to significant variation in estimates of GHG emissions related to differences in land classification methodologies, EO input data and period of investigation. This article focuses on selected regions of Indonesia, where quantifying land use change is important for GHG assessments of agricultural commodities and for evidencing progress against corporate and government deforestation commitments. Given the significance of GHG emissions arising from LULC change and the increasing need for emissions monitoring, this research highlights a need for consensus building to develop consistency in historical and future LULC change estimates. This paper concludes with a set of recommendations for improvements to ensure consistent LULC mapping

Review of land flow accounting methods and recommendations for further development

Robust land footprint indicators can potentially extend the consumption-based resource use indicator of the German sustainability strategy, which focuses on abiotic resources including fossil fuels, metals, and construction and industrial minerals and decidedly excludes biotic resources. Various approaches exist for quantifying the land embodied in international trade flows and consumption, i.e. the land footprint. These can be classified into a) environmental-economic accounting approaches, applying input-output analysis and tracking supply chains in monetary values, b) physical accounting approaches, using an accounting framework based on data for production, trade and utilization of agricultural and forestry commodities and tracking supply chains in physical units, and c) hybrid accounting, combining elements from both environmental-economic and physical accounting. The results of recent studies vary widely, indicating a lack of robustness and thus hampering their application in policy making. This report provides an in-depth review of the current state of the art in measuring land footprints. We identify differences in available accounting methods and indicate their shortcomings, which are mainly attributable to the product and supply chain coverage and detail, and biases introduced by the use of monetary flows as a proxy for actual physical flows. We offer options and give clear recommendations for the further development of actual and virtual global biomass and land flow accounting methods, particularly highlighting the advantages of hybrid accounting approaches as a framework for the robust and transparent assessment of land footprints associated with global biomass flows

Review of land flow accounting methods and recommendations for further development

Robust land footprint indicators can potentially extend the consumption-based resource use indicator of the German sustainability strategy, which focuses on abiotic resources including fossil fuels, metals, and construction and industrial minerals and decidedly excludes biotic resources. Various approaches exist for quantifying the land embodied in international trade flows and consumption, i.e. the land footprint. These can be classified into a) environmental-economic accounting approaches, applying input-output analysis and tracking supply chains in monetary values, b) physical accounting approaches, using an accounting framework based on data for production, trade and utilization of agricultural and forestry commodities and tracking supply chains in physical units, and c) hybrid accounting, combining elements from both environmental-economic and physical accounting. The results of recent studies vary widely, indicating a lack of robustness and thus hampering their application in policy making. This report provides an in-depth review of the current state of the art in measuring land footprints. We identify differences in available accounting methods and indicate their shortcomings, which are mainly attributable to the product and supply chain coverage and detail, and biases introduced by the use of monetary flows as a proxy for actual physical flows. We offer options and give clear recommendations for the further development of actual and virtual global biomass and land flow accounting methods, particularly highlighting the advantages of hybrid accounting approaches as a framework for the robust and transparent assessment of land footprints associated with global biomass flows

The Austrian Carbon Database (ACDb) Study - Overview [Revised 28 October 2003]

This is the final overview report of the Austrian Carbon Database (ACDb) Study, which pursues three main objectives: (1) to support the Austrian Carbon Balance Model (ACBM) II; (2) to internationalize the Austrian carbon analysis and to place Austrias carbon accounting within an international science and policy context focusing on the UN Framework Convention on Climate Change (FCCC); and (3) to provide good practice guidance in consideration of Full Carbon Accounting (FCA) rather than Partial Carbon Accounting (PCA). The Study is divided into two phases, a deductive and an inductive research phase. The deductive research phase builds upon the theoretical insights gained during the ACDb Study and addresses Objective 2 (Internationalization). The inductive research phase builds upon the generalized experiences from working with uncertainties in building the ACDb and addresses Objectives 1 (ACBM II Support) and 3 (Good Practice Guidance). The ACDb is a carbon consistent database for Austria that acknowledges FCA. It focuses on publicly available, including measured, data around 1990 and attributes special importance to the direct and transparent understanding of both first (mean values) and second statistical moments (uncertainties). The ACDb does not replace existing, officially agreed and widely accepted, Austrian databases but provides a thematically less detailed, however, carbon consistent standard that allows to quantify the uncertainties underlying these databases when using them in a wider (Austrian-integrated) context than traditionally done. The focus of the Study is on conclusions that are generally valid and are not only specific for Austria. Based on our deductive and inductive research, we conclude that the Kyoto Protocol and the way national emissions are inventoried urgently need fundamental as well as methodological improvements, more than ever before

Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments

This is the author accepted manuscript. The final version is available from European Geosciences Union (EGU) via the DOI in this record.Land-use and land-cover change (LULCC) represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in terrestrial biosphere models (TBMs). The published results of these models are used in major assessments of processes and impacts of global environmental change, such as the reports of the Intergovernmental Panel on Climate Change (IPCC). Fully coupled models of climate, land use and biogeochemical cycles to explore land use-climate interactions across spatial scales are currently not available. Instead, information on land use is provided as exogenous data from the land-use change modules of integrated assessment models (IAMs) to TBMs. In this article, we discuss, based on literature review and illustrative analysis of empirical and modeled LULCC data, three major challenges of this current LULCC representation and their implications for land use-climate interaction studies: (I) provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II) accounting for sub-grid processes and bidirectional changes (gross changes) across spatial scales, and (III) the allocation strategy of independent land-use data at the grid cell level in TBMs. We discuss the factors that hamper the development of improved land-use representation, which sufficiently accounts for uncertainties in the land-use modeling process. We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs. Moreover, we suggest concentrating on the development of integrated modeling frameworks that may provide further understanding of possible land-climate-society feedbacks.The research in this paper has been supported by the European Research Council under the European Union’s Seventh Framework Programme project LUC4C (Grant No. 603542), ERC grant GLOLAND (No. 311819) and BiodivERsA project TALE (No. 832.14.006) funded by the Dutch National Science Foundation (NWO). This research contributes to the Global Land Project (www.globallandproject.org). This is paper number 26 of the Birmingham Institute of Forest Research