scholarly journals Partitioning global change: Assessing the relative importance of changes in climate and land cover for changes in avian distribution

2019 ◽  
Vol 9 (4) ◽  
pp. 1985-2003 ◽  
Author(s):  
Matthew J. Clement ◽  
James D. Nichols ◽  
Jaime A. Collazo ◽  
Adam J. Terando ◽  
James E. Hines ◽  
...  
Keyword(s):  
Global Change ◽  
Land Cover ◽  
Relative Importance ◽  
Avian Distribution

scholarly journals Global change in microcosms: Environmental and societal predictors of land cover change on the Atlantic Ocean Islands

Anthropocene ◽  
2020 ◽  
Vol 30 ◽  
pp. 100242 ◽  
Author(s):  
Sietze J. Norder ◽  
Ricardo F. de Lima ◽  
Lea de Nascimento ◽  
Jun Y. Lim ◽  
José María Fernández-Palacios ◽  
...  
Keyword(s):  
Global Change ◽  
Land Cover ◽  
Atlantic Ocean ◽  
Land Cover Change ◽  
Ocean Islands

scholarly journals Modelling landslide hazard under global change: the case of a Pyrenean valley

2020 ◽  
Author(s):  
Séverine Bernardie ◽  
Rosalie Vandromme ◽  
Yannick Thiery ◽  
Thomas Houet ◽  
Marine Grémont ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Global Change ◽  
Land Cover ◽  
Slope Stability ◽  
Landslide Hazard ◽  
Forest Growth ◽  
Global Changes ◽  
Rcp 8.5 ◽  
Socioeconomic Scenarios

Abstract. Several studies have shown that global changes have important impacts in mountainous areas, since they affect natural hazards induced by hydro-meteorological events such as landslides. To estimate the capacity of mountainous valleys to cope with landslide hazard under global change (climate change as well as climate- and human-induced land use change), it is necessary to evaluate the evolution of the different components that define this type of hazard: topography, geology and geotechnics, hydrogeology and land cover. The present study evaluates, through an innovative methodology, the influence of both vegetation cover and climate change on landslide hazard in a Pyrenean valley from the present to 2100. Once the invariant features of the studied area, such as geology and topography, were set, we first focused on assessing future land use changes through the construction of four prospective socioeconomic scenarios and their projection to 2040 and 2100. These inputs were then used to spatially model land use and land cover (LUCC) information to produce multi-temporal LUCC maps. Then, climate change inputs were used to extract the water saturation of the uppermost layers, according to two greenhouse gas emissions scenarios. The impacts of land use and climate change based on these scenarios were then used to modulate the hydro-mechanical model to compute the factor of safety (FoS) and the hazard levels over the considered area. The results demonstrate the influence of land use on slope stability through the presence and type of forest. The resulting changes are significant despite being small and dependent on future land use linked to the socioeconomic scenarios. In particular, a reduction in human activity results in an increase in slope stability; in contrast, an increase in anthropic activity leads to an opposite evolution in the region, with some reduction in slope stability. Climate change may also have a significant impact in some areas because of the increase in the soil water content; the results indicate a reduction in the FoS in a large part of the study area, depending on the landslide typology considered. Therefore, even if future forest growth leads to slope stabilization, the evolution of the groundwater conditions will lead to destabilization. These changes are not uniform over the area and are particularly significant under the most extreme climate scenario, RCP 8.5. Compared to the current period, the size of the area that is prone to deep landslides is higher in the future than the area prone to small landslides (both rotational and translational). On the other hand, the increase rate of areas prone to landslides is higher for the small landslide typology than for the deep landslide typology. Interestingly, the evolution of extreme events is related to the frequency of the highest water filling ratio. The results indicate that the occurrences of landslide hazards in the near future (2021–2050 period, scenario RCP 8.5) and far future (2071–2100 period, scenario RCP 8.5) are expected to increase by factors of 1.5 and 4, respectively.

scholarly journals ASSESSMENTS OF SENTINEL-2 VEGETATION RED-EDGE SPECTRAL BANDS FOR IMPROVING LAND COVER CLASSIFICATION

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 871-874 ◽  
Author(s):  
S. Qiu ◽  
B. He ◽  
C. Yin ◽  
Z. Liao
Keyword(s):  
Land Cover ◽  
Land Cover Classification ◽  
Relative Importance ◽  
East Texas ◽  
Spectral Bands ◽  
Red Edge ◽  
Sentinel 2A ◽  
Land Cover Maps ◽  
Confusion Matrices ◽  
Sentinel 2

The Multi Spectral Instrument (MSI) onboard Sentinel-2 can record the information in Vegetation Red-Edge (VRE) spectral domains. In this study, the performance of the VRE bands on improving land cover classification was evaluated based on a Sentinel-2A MSI image in East Texas, USA. Two classification scenarios were designed by excluding and including the VRE bands. A Random Forest (RF) classifier was used to generate land cover maps and evaluate the contributions of different spectral bands. The combination of VRE bands increased the overall classification accuracy by 1.40 %, which was statistically significant. Both confusion matrices and land cover maps indicated that the most beneficial increase was from vegetation-related land cover types, especially agriculture. Comparison of the relative importance of each band showed that the most beneficial VRE bands were Band 5 and Band 6. These results demonstrated the value of VRE bands for land cover classification.

scholarly journals GLOBAL LAND-USE AND LAND-COVER DATA FOR ECOLOGISTS: HISTORICAL, CURRENT AND FUTURE SCENARIOS

2021 ◽  
Author(s):  
Mariana Moncassim Vale ◽  
Taina Carreira da Rocha ◽  
Matheus de Souza Lima Ribeiro
Keyword(s):  
Land Use ◽  
Global Change ◽  
Land Cover ◽  
Ecological Niche Modeling ◽  
Climatic Conditions ◽  
Land Use Land Cover ◽  
Distribution Models ◽  
Change Analysis ◽  
Land Cover Data ◽  
Global Change Scenarios

Land-use land-cover (LULC) data are important predictors of species occurrence and biodiversity threat. Although there are LULC datasets available for ecologists under current conditions, there is a lack of such data under historical and future climatic conditions. This hinders, for example, projecting niche and distribution models under global change scenarios at different times. The Land Use Harmonization Project (LUH2) is a global terrestrial dataset at 0.25° spatial resolution that provides LULC data from 850 to 2300 for 12 LULC state classes. The dataset, however, is compressed in a file format (NetCDF) that is incompatible with most ecological analysis and intractable for most ecologists. Here we selected and transformed the LUH2 data in order to make it more useful for ecological studies. We provide LULC for every year from 850 to 2100, with data from 2015 on provided under two Shared Socioeconomic Pathways (SSP2 and SSP5). We provide two types of file for each year: separate files with continuous values for each of the 12 LULC state classes, and a single categorical file with all state classes combined. To create the categorical layer, we assigned the state with the highest value in a given pixel among the 12 continuous data. The final dataset provides LULC data for 1251 years that will be of interest for macroecology, ecological niche modeling, global change analysis, and other applications in ecology and conservation. We also provide a description of LUH2 prediction of future LULC change through time.

scholarly journals Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models

2016 ◽  
Vol 9 (9) ◽  
pp. 3055-3069 ◽  
Author(s):  
Yannick Le Page ◽  
Tris O. West ◽  
Robert Link ◽  
Pralit Patel
Keyword(s):  
Land Use ◽  
Global Change ◽  
Land Cover ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Critical Parameters ◽  
Reference Scenario ◽  
Change Assessment ◽  
Global Change Assessment Model ◽  
Wide Range

Abstract. The Global Change Assessment Model (GCAM) is a global integrated assessment model used to project future societal and environmental scenarios, based on economic modeling and on a detailed representation of food and energy production systems. The terrestrial module in GCAM represents agricultural activities and ecosystems dynamics at the subregional scale, and must be downscaled to be used for impact assessments in gridded models (e.g., climate models). In this study, we present the downscaling algorithm of the GCAM model, which generates gridded time series of global land use and land cover (LULC) from any GCAM scenario. The downscaling is based on a number of user-defined rules and drivers, including transition priorities (e.g., crop expansion preferentially into grasslands rather than forests) and spatial constraints (e.g., nutrient availability). The default parameterization is evaluated using historical LULC change data, and a sensitivity experiment provides insights on the most critical parameters and how their influence changes regionally and in time. Finally, a reference scenario and a climate mitigation scenario are downscaled to illustrate the gridded land use outcomes of different policies on agricultural expansion and forest management. Several features of the downscaling can be modified by providing new input data or changing the parameterization, without any edits to the code. Those features include spatial resolution as well as the number and type of land classes being downscaled, thereby providing flexibility to adapt GCAM LULC scenarios to the requirements of a wide range of models and applications. The downscaling system is version controlled and freely available.

scholarly journals Global land-use and land-cover data for ecologists: Historical, current, and future scenarios

2021 ◽  
Vol 16 (1) ◽  
pp. 28-38
Author(s):  
Tainá Rocha ◽  
Mariana M Vale ◽  
Matheus S. Lima-Ribeiro
Keyword(s):  
Land Use ◽  
Global Change ◽  
Land Cover ◽  
Ecological Niche Modeling ◽  
Climatic Conditions ◽  
Land Use Land Cover ◽  
Distribution Models ◽  
Change Analysis ◽  
Land Cover Data ◽  
Global Change Scenarios

Land-use land-cover (LULC) data are important predictors of species occurrence and biodiversity threat. Although there are LULC datasets available for ecologists under current conditions, there is a lack of such data under historical and future climatic conditions. This hinders, for example, projecting niche and distribution models under global change scenarios at different times. The Land Use Harmonization Project (LUH2) is a global terrestrial dataset at 0.25o spatial resolution that provides LULC data from 850 to 2300 for 12 LULC state classes. The dataset, however, is compressed in a file format (NetCDF) that is incompatible with most ecological analysis and intractable for most ecologists. Here we selected and transformed the LUH2 data in order to make it more useful for ecological studies. We provide LULC for every year from 850 to 2100, with data from 2015 on provided under two Shared Socioeconomic Pathways (SSP2 and SSP5). We provide two types of file for each year: separate files with continuous values for each of the 12 LULC state classes, and a single categorical file with all state classes combined. To create the categorical layer, we assigned the state with the highest value in a given pixel among the 12 continuous data. The final dataset provides LULC data for 1251 years that will be of interest for macroecology, ecological niche modeling, global change analysis, and other applications in ecology and conservation. We also provide a description of LUH2 prediction of future LULC change through time.

scholarly journals Quantifying the relative importance of land cover change from climate and land use in the representative concentration pathways

2015 ◽  
Vol 29 (6) ◽  
pp. 842-853 ◽  
Author(s):  
T. Davies-Barnard ◽  
P. J. Valdes ◽  
J. S. Singarayer ◽  
A. J. Wiltshire ◽  
C. D. Jones
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Relative Importance ◽  
Representative Concentration Pathways

scholarly journals Disentangling the relative importance of climate, size and competition on tree growth in Iberian forests: implications for forest management under global change

2011 ◽  
Vol 17 (7) ◽  
pp. 2400-2414 ◽  
Author(s):  
LORENA GÓMEZ-APARICIO ◽  
RAÚL GARCÍA-VALDÉS ◽  
PALOMA RUÍZ-BENITO ◽  
MIGUEL A. ZAVALA
Keyword(s):  
Forest Management ◽  
Global Change ◽  
Tree Growth ◽  
Relative Importance

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

2011 ◽  
Vol 17 (2) ◽  
pp. 974-989 ◽  
Author(s):  
PETER H. VERBURG ◽  
KATHLEEN NEUMANN ◽  
LINDA NOL
Keyword(s):  
Land Use ◽  
Global Change ◽  
Land Cover ◽  
Land Cover Data
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