scholarly journals Current challenges of implementing land-use and land-cover change in climate assessments

2016 ◽  
Author(s):  
Reinhard Prestele ◽  
Almut Arneth ◽  
Alberte Bondeau ◽  
Nathalie de Noblet-Ducoudré ◽  
Thomas A. M. Pugh ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Spatial Scales ◽  
Global Environmental Change ◽  
Implementation Strategies ◽  
Land Use Modeling ◽  
Global Environmental

Abstract. 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 Dynamic Global Vegetation Models (DGVMs) and Earth System Models (ESMs), whose published results 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). In the absence of coupled models of climate, land use and biogeochemical cycles to explore land use – climate interactions across spatial scales, information on LULCC is currently provided as exogenous data from the land-use change modules of Integrated Assessment Models (IAMs) to ESMs and DGVMs, while data from dedicated land-use change models (LUCMs) are rarely considered. In this article, we discuss major uncertainties and existing shortcomings of current implementation strategies originating in both LULCC data-provider and LULCC data-user communities. We identify, based on literature review and the analysis of empirical and modeled LULCC data, three major challenges related to LULCC representation, which are currently not or insufficiently accounted for: (1) provision of consistent, harmonized LULCC time series spanning from historical reconstructions to future projections while accounting for uncertainties due to different land-use modeling approaches, (2) accounting for sub-grid processes and bi-directional changes (gross changes) across spatial scales and (3) the allocation strategy of LULCC at the grid cell level in ESMs and DGVMs. Based on these three challenges, we discuss the reasons that hamper the development of implementation strategies that sufficiently account for uncertainties in the land-use modeling process and conclude that both providers and users of LULCC data products often miss appropriate knowledge of the requirements and constraints of one another’s models, thus leading to large discrepancies between the representation of LULCC data and processes in both communities. We propose to focus future research on 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.

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

2017 ◽  
Vol 8 (2) ◽  
pp. 369-386 ◽  
Author(s):  
Reinhard Prestele ◽  
Almut Arneth ◽  
Alberte Bondeau ◽  
Nathalie de Noblet-Ducoudré ◽  
Thomas A. M. Pugh ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Land Cover Change ◽  
Spatial Scales ◽  
Global Environmental Change ◽  
Land Use Modeling ◽  
Global Environmental ◽  
Anthropogenic Land Use

Abstract. 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 SYPR Integrative Assessment Model: Complexity in Development

2004 ◽  
Author(s):  
Steven Manson
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Environmental Change ◽  
Land Cover Change ◽  
Integrated Assessment ◽  
Global Environmental Change ◽  
Global Scale ◽  
Assessment Model ◽  
Integrated Assessment Modeling ◽  
Global Environmental

Be it global environmental change or environment and development, landuse and land-cover change is central to the dynamics and consequences in question in the southern Yucatán peninsular region. Designing policies to address these impacts is hampered by the difficulty of projecting land use and land cover, not only because the dynamics are complex but also because consequences are strongly place-based. This chapter describes an integrated assessment modeling framework that builds on the research detailed in earlier chapters in order to project land-use and land-cover change in a geographically explicit way. Integrated assessment is a term that describes holistic treatments of complex problems to assess both science and policy endeavors in global environmental change (Rotmans and Dowlatabadi 1998). The most common form of integrated assessment is computer modeling that combines socioeconomic and biogeophysical factors to predict global climate. Advanced in part by the successes of these global-scale models, integrated assessment has expanded to structure knowledge and set research priorities for a large range of coupled human–environment problems. Increasing recognition is given to the need for integrated assessment models to address regionalscale problems that are masked by global-scale assessments (Walker 1994). Such models must address two issues to project successfully land-use and land-cover change at the regional scale. First, change occurs incrementally in spatially distinct patterns that have different implications for global change (Lambin 1994). Second, a model must account for the complexity of, and relationships among, socio-economic and environmental factors (B. L. Turner et al. 1995). The SYPR integrated assessment model, therefore, has a fine temporal and spatial grain and it places land-use and landcover change at the intersection of land-manager decision-making, the environment, and socio-economic institutions. What follows is a description of an ongoing integrated assessment modeling endeavor of the SYPR project (henceforth, SYPR IA model). The depth and breadth of the SYPR project poses a challenge to the integrated assessment modeling effort since some unifying framework must reconcile a broad array of issues, theories, and data. The global change research community offers a general conception of how environmental change results from infrastructure development, population pressure, market opportunities, resource institutions, and environmental or resource policies (Stern, Young, and Drukman 1992).

scholarly journals Land Cover Change Assessment of Vaal Harts Irrigation Scheme using Multi-temporal Satellite Sata

2013 ◽  
Vol 39 (4) ◽  
pp. 59-70 ◽  
Author(s):  
Fredrick Ao Otieno ◽  
Olumuyiwa I Ojo ◽  
George M. Ochieng
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Program ◽  
Land Use Land Cover ◽  
Irrigation Scheme ◽  
Multi Temporal

Abstract Land cover change (LCC) is important to assess the land use/land cover changes with respect to the development activities like irrigation. The region selected for the study is Vaal Harts Irrigation Scheme (VHS) occupying an area of approximately 36, 325 hectares of irrigated land. The study was carried out using Land sat data of 1991, 2001, 2005 covering the area to assess the changes in land use/land cover for which supervised classification technique has been applied. The Normalized Difference Vegetation Index (NDVI) index was also done to assess vegetative change conditions during the period of investigation. By using the remote sensing images and with the support of GIS the spatial pattern of land use change of Vaal Harts Irrigation Scheme for 15 years was extracted and interpreted for the changes of scheme. Results showed that the spatial difference of land use change was obvious. The analysis reveals that 37.86% of additional land area has been brought under fallow land and thus less irrigation area (18.21%). There is an urgent need for management program to control the loss of irrigation land and therefore reclaim the damaged land in order to make the scheme more viable.

scholarly journals Time Series Land Cover Mapping and Change Detection Analysis Using Geographic Information System and Remote Sensing, Northern Ethiopia

2018 ◽  
Vol 11 ◽  
pp. 117862211775160 ◽  
Author(s):  
Gebiaw T Ayele ◽  
Aschalew K Tebeje ◽  
Solomon S Demissie ◽  
Mulugeta A Belete ◽  
Mengistu A Jemberrie ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Population Growth ◽  
Change Detection ◽  
Land Cover Change ◽  
Training Data ◽  
Steady Increase ◽  
Northern Ethiopia ◽  
Detection Techniques

Land use planners require up-to-date and spatially accurate time series land resources information and changing pattern for future management. As a result, assessing the status of land cover change due to population growth and arable expansion, land degradation and poor resource management, partial implementation of policy strategies, and poorly planned infrastructural development is essential. Thus, the objective of the study was to quantify the spatiotemporal dynamics of land use land cover change between 1995 and 2014 using 5 multi-temporal cloud-free Landsat Thematic Mapper images. The maximum likelihood (ML)-supervised classification technique was applied to create signature classes for significant land cover categories using means and variances of the training data to estimate the probability that a pixel is a member of a class. The final Bayesian ML classification resulted in 12 major land cover units, and the spatiotemporal change was quantified using post-classification and statistical change detection techniques. For a period of 20 years, there was a continuously increasing demand for arable areas, which can be represented by an exponential growth model. Excepting the year 2009, the built-up area has shown a steady increase due to population growth and its need for infrastructure development. There was nearly a constant trend for water bodies with a change in slope significantly less than +0.01%. The 2014 land cover change statistics revealed that the area was mainly covered by cultivated, wood, bush, shrub, grass, and forest land mapping units accounting nearly 63%, 12%, 8%, 6%, 4%, and 2% of the total, respectively. Land cover change with agro-climatic zones, soil types, and slope classes was common in most part of the area and the conversion of grazing land into plantation trees and closure area development were major changes in the past 20 years.

scholarly journals An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)

2015 ◽  
Vol 8 (4) ◽  
pp. 3359-3402 ◽  
Author(s):  
S. Moulds ◽  
W. Buytaert ◽  
A. Mijic
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Global Environmental Change ◽  
Model Development ◽  
Spatially Explicit ◽  
Change Models ◽  
R Programming Language ◽  
Global Environmental ◽  
R Programming ◽  
Scientific Results

Abstract. Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment.

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