Spatio-temporal comparison of different approaches to derive land use and land cover change emissions by models

2021 ◽  
Author(s):  
Wolfgang Obermeier ◽  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Large Scale ◽  
Agricultural Land ◽  
Land Cover Changes ◽  
Legacy Effects ◽  
Equatorial Africa ◽  
The Usa ◽  
Spatio Temporal ◽  
Global Carbon

<p>The quantification of the net carbon flux from land use and land cover changes (f<sub>LULCC</sub>) is essential to understand the global carbon cycle, and consequently, to support climate change mitigation. However, large-scale f<sub>LULCC</sub> is not directly measurable, and can only be inferred by models, such as semi-empirical bookkeeping models, and process-based dynamic global vegetation models (DGVMs). By definition, f<sub>LULCC</sub> estimates between these two model types are not directly comparable. For example, transient DGVM-based f<sub>LULCC</sub> of the annual global carbon budget includes the so-called Loss of Additional Sink Capacity (LASC). The latter accounts for environmental impacts on the land carbon storage capacities of managed land compared to potential vegetation which is not included in bookkeeping models. Additionally, estimates of transient DGVM-based f<sub>LULCC</sub> differ from bookkeeping model estimates, since they depend on arbitrarily chosen simulation time periods and the timing of land use and land cover changes within the historic period (which includes different accumulation periods for legacy effects). However, DGVMs enable a f<sub>LULCC</sub> approximation independent of the timing of land use and land cover changes and their legacy effects by simulations run under constant pre-industrial or present-day environmental forcings.</p><p>In this study, we analyze these different DGVM-derived f<sub>LULCC</sub> definitions, under transiently changing environmental conditions and fixed pre-industrial and fixed present-day conditions, within 18 regions for twelve DGVMs and quantify their differences as well as climate- and CO<sub>2</sub>-induced components. The multi model mean under transient conditions reveals a global f<sub>LULCC</sub> of 2.0±0.6 PgC yr<sup>-1</sup> for 2009-2018, with ~40% stemming from the LASC (0.8±0.3 PgC yr<sup>-1</sup>). Within the industrial period (1850 onward), cumulative f<sub>LULCC</sub> reached 189±56 PgC with 40±15 PgC from the LASC.</p><p>Regional hotspots of high LASC values exist in the USA, China, Brazil, Equatorial Africa and Southeast Asia, which we mainly relate to deforestation for cropland. Distinct negative LASC estimates were observed in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land). Negative LASC estimates indicate that fLULCC estimates in these regions are lower in transient DGVM simulations compared to bookkeeping-approaches. By unraveling the spatio-temporal variability of the different DGVM-derived f<sub>LULCC</sub> estimates, our study calls for a harmonized attribution of model-derived f<sub>LULCC</sub>. We propose an approach that bridges bookkeeping and DGVM approaches for f<sub>LULCC</sub> estimation by adopting a mean DGVM-ensemble LASC for a defined reference period.</p>

scholarly journals Modelled land use and land cover change emissions – A spatio-temporal comparison of different approaches

2021 ◽  
Author(s):  
Wolfgang A. Obermeier ◽  
Julia E. M. S. Nabel ◽  
Tammas Loughran ◽  
Kerstin Hartung ◽  
Ana Bastos ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Environmental Conditions ◽  
Agricultural Land ◽  
Environmental Changes ◽  
Land Cover Changes ◽  
Legacy Effects ◽  
Spatio Temporal ◽  
The Impact ◽  
Global Carbon

Abstract. Quantifying the net carbon flux from land use and land cover changes (fLULCC) is critical for understanding the global carbon cycle, and hence, to support climate change mitigation. However, large-scale fLULCC is not directly measurable, but has to be inferred from models instead, such as semi-empirical bookkeeping models, and process-based dynamic global vegetation models (DGVMs). By definition, fLULCC estimates are not directly comparable between these two different model types. As an example, DGVM-based fLULCC in the annual global carbon budgets is estimated under transient environmental forcing and includes the so-called Loss of Additional Sink Capacity (LASC). The LASC accounts for the impact of environmental changes on land carbon storage potential of managed land compared to potential vegetation which is not represented in bookkeeping models. In addition, fLULCC from transient DGVM simulations differs depending on the arbitrary chosen simulation time period and the historical timing of land use and land cover changes (including different accumulation periods for legacy effects). An approximation of fLULCC by DGVMs that is independent of the timing of land use and land cover changes and their legacy effects requires simulations assuming constant pre-industrial or present-day environmental forcings. Here, we analyze three DGVM-derived fLULCC estimations for twelve models within 18 regions and quantify their differences as well as climate- and CO2-induced components. The three estimations stem from the commonly performed simulation with transiently changing environmental conditions and two simulations that keep environmental conditions fixed, at pre-industrial and present-day conditions. Averaged across the models, we find a global fLULCC (under transient conditions) of 2.0 ± 0.6 PgC yr-1 for 2009–2018, of which ∼40 % are attributable to the LASC (0.8 ± 0.3 PgC yr-1). From 1850 onward, fLULCC accumulated to 189 ± 56 PgC with 40 ± 15 PgC from the LASC. Regional hotspots of high cumulative and annual LASC values are found in the USA, China, Brazil, Equatorial Africa and Southeast Asia, mainly due to deforestation for cropland. Distinct negative LASC estimates, in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land), indicate that fLULCC estimates in these regions are lower in transient DGVM- compared to bookkeeping-approaches. By unraveling spatio-temporal variability in three alternative DGVM-derived fLULCC estimates, our results call for a harmonized attribution of model-derived fLULCC. We propose an approach that bridges bookkeeping and DGVM approaches for fLULCC estimation by adopting a mean DGVM-ensemble LASC for a defined reference period.

scholarly journals Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches

2021 ◽  
Vol 12 (2) ◽  
pp. 635-670
Author(s):  
Wolfgang A. Obermeier ◽  
Julia E. M. S. Nabel ◽  
Tammas Loughran ◽  
Kerstin Hartung ◽  
Ana Bastos ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Environmental Conditions ◽  
Agricultural Land ◽  
Environmental Changes ◽  
Land Cover Changes ◽  
Environmental Forcing ◽  
The Impact ◽  
Global Carbon

Abstract. Quantifying the net carbon flux from land use and land cover changes (fLULCC) is critical for understanding the global carbon cycle and, hence, to support climate change mitigation. However, large-scale fLULCC is not directly measurable and has to be inferred from models instead, such as semi-empirical bookkeeping models and process-based dynamic global vegetation models (DGVMs). By definition, fLULCC estimates are not directly comparable between these two different model types. As an important example, DGVM-based fLULCC in the annual global carbon budgets is estimated under transient environmental forcing and includes the so-called loss of additional sink capacity (LASC). The LASC results from the impact of environmental changes on land carbon storage potential of managed land compared to potential vegetation and accumulates over time, which is not captured in bookkeeping models. The fLULCC from transient DGVM simulations, thus, strongly depends on the timing of land use and land cover changes mainly because LASC accumulation is cut off at the end of the simulated period. To estimate the LASC, the fLULCC from pre-industrial DGVM simulations, which is independent of changing environmental conditions, can be used. Additionally, DGVMs using constant present-day environmental forcing enable an approximation of bookkeeping estimates. Here, we analyse these three DGVM-derived fLULCC estimations (under transient, pre-industrial, and present-day forcing) for 12 models within 18 regions and quantify their differences as well as climate- and CO2-induced components and compare them to bookkeeping estimates. Averaged across the models, we find a global fLULCC (under transient conditions) of 2.0±0.6 PgC yr−1 for 2009–2018, of which ∼40 % are attributable to the LASC (0.8±0.3 PgC yr−1). From 1850 onward, the fLULCC accumulated to 189±56 PgC with 40±15 PgC from the LASC. Around 1960, the accumulating nature of the LASC causes global transient fLULCC estimates to exceed estimates under present-day conditions, despite generally increased carbon stocks in the latter. Regional hotspots of high cumulative and annual LASC values are found in the USA, China, Brazil, equatorial Africa, and Southeast Asia, mainly due to deforestation for cropland. Distinct negative LASC estimates in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land), indicate that fLULCC estimates in these regions are lower in transient DGVM compared to bookkeeping approaches. Our study unravels the strong dependence of fLULCC estimates on the time a certain land use and land cover change event happened to occur and on the chosen time period for the forcing of environmental conditions in the underlying simulations. We argue for an approach that provides an accounting of the fLULCC that is more robust against these choices, for example by estimating a mean DGVM ensemble fLULCC and LASC for a defined reference period and homogeneous environmental changes (CO2 only).

Spatio-temporal analysis of land cover changes in the evergreen and semi-evergreen rainforests: A case study in Chittagong Hill Tracts, Bangladesh

2020 ◽  
Vol 2 (2) ◽  
pp. 87-99
Author(s):  
M. Mamnun ◽  
S. Hossen
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Temporal Analysis ◽  
Present Condition ◽  
Land Cover Changes ◽  
Landsat 8 ◽  
Chittagong Hill Tracts ◽  
Barren Land ◽  
Spatio Temporal

The main purpose of this study is to describe the spatio-temporal analysis of land use and land cover status and to identify land cover changes, especially of deforestation and degradation in evergreen, semi-evergreen rainforests of Chittagong Hill Tracts from 1988-2018 by using Landsat 8 OLI-TIRS and Landsat 5 TM satellite imagery. The ArcGIS v10.5 and ERDAS Imagine v15 software were used to process satellite imageries and assess quantitative data for land-use change assessment of this study area. The study revealed that the area of forest land and water body decreased by 17.92% and 5.43% respectively from 1988-2018. On the other hand, the area of agricultural land, barren land and settlement increased by 45.66%, 312.08% and 240.01% respectively. If the present condition remains constant, the projection of future land-use/ land cover changes for the next 15 years will predict that more than 7.37% dense forest (2253.83 ha) land will be decreased and 19.60% agricultural will be converted to other land uses. This study suggests that proper policy should be adopted urgently to conserve residual forest coverage and restore it to regain its past appearance.

scholarly journals Assessment of Spatio-Temporal Changes of Land Use and Land Cover over South-Western African Basins and Their Relations with Variations of Discharges

Hydrology ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 56 ◽  
Author(s):  
Salomon Obahoundje ◽  
Arona Diedhiou ◽  
Eric Antwi Ofosu ◽  
Sandrine Anquetin ◽  
Baptiste François ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Water Bodies ◽  
Annual Precipitation ◽  
Land Cover Changes ◽  
Climate Services ◽  
Discharge Data ◽  
Spatio Temporal ◽  
Annual Discharge

West African basins play a vital role in the socio-economic development of the region. They are mostly trans-boundary and sources of different land use practices. This work attempts to assess the spatio-temporal land use and land cover changes over three South Western African basins (Volta, Mono and Sassandra basins) and their influence on discharge. The land use and land cover maps of each basin were developed for 1988, 2002 and 2016. The results show that all the studied basins present an increase in water bodies, built-up, agricultural land and a decline in vegetative areas. These increases in water bodies and land use are as a result of an increase in small reservoirs, of dugouts and of dam constructions. However, the decline in some vegetative clusters could be attributed to the demographic and socio-economic growth as expressed by the expansion of agriculture and urbanization. The basic statistical analysis of precipitation and discharge data reveals that the mean annual discharge varies much more than the total annual precipitation at the three basins. For instance, in the entire Volta basin, the annual precipitation coefficient of variation (CV) is 10% while the annual discharge CV of Nawuni, Saboba and Bui are 43.6%, 36.51% and 47.43%, respectively. In Mono basin, the annual precipitation CV is 11.5% while the Nangbeto and Athieme annual discharge CV are 37.15% and 46.60%, respectively. The annual precipitation CV in Sassandra basin is 7.64% while the annual discharge CV of Soubre and Dakpadou are 29.41% and 37%, respectively. The discharge varies at least three times much more than the precipitation in the studied basins. The same conclusion was found for all months except the driest months (December and January). We showed that this great variation in discharge is mainly due to land use and land cover changes. Beside the hydrological modification of the land use and land cover changes, the climate of the region as well as the water quality and availability and the hydropower generation may be impacted by these changes in land surfaces conditions. Therefore, these impacts should be further assessed to implement appropriate climate services and measures for a sustainable land use and water management.

scholarly journals Assessing land use and land cover changes and Effects of Large-scale Agricultural Farm Expansion in Southwester Ethiopia by using remote sensing/GIS tools.

2020 ◽  
Author(s):  
Getaneh Haile Shoddo
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Large Scale ◽  
Agricultural Land ◽  
Driving Forces ◽  
Land Cover Changes ◽  
Gis Tools ◽  
Market Factors ◽  
Agricultural Land Expansion

Abstract Development initiatives like the recent increase in large-scale investment agriculture have made a significant impact on the forest. In the name of development, the land is often given to investors often in long-term leases and at bargain prices. Research on deforestation has been mostly restricted to poverty and population growth as the driving forces for tropical deforestation; however, explanations emphasizing market factors such as increases in large-scale investment agriculture as a cause of deforestation have only been carried out in a small number of areas. The aim of this study is to explore the effects of agricultural land expansion in changing land use and land use cover changes using remote sensing/GIS tools in Sheka zone southwester Ethiopia from 1995 to 2015. The results showed that expansion of investment agriculture has a clear impact on both the local people and the forest ecosystem. The conversion of forestland to investment agriculture has caused varied and extensive environmental degradation to the Sheka forest. The Land Use and Land Cover changes in the Sheka zone are discussed based on underlying socioeconomic factors.

Unmixing the regional climate response to recent historical land cover changes in Europe

2020 ◽  
Author(s):  
Bo Huang ◽  
Xiangping Hu ◽  
Geir-Arne Fuglstad ◽  
Xu Zhou ◽  
Wenwu Zhao ◽  
...  
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Agricultural Land ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Energy Budget ◽  
Land Cover Changes ◽  
Climate Response ◽  
Statistical Regression ◽  
Cooling Effects

<p>Land cover changes (LCCs) influence the regional climate because they alter biophysical mechanisms like evapotranspiration, albedo, and surface roughness. Previous research mainly assessed the regional climate implications of individual land cover transitions, such as the effects of historical forest clearance or idealized large-scale scenarios of deforestation/afforestation, but the combined effects from the mix of recent historical land cover changes in Europe have not been explored. In this study, we use a combination of high resolution land cover data with a regional climate model (the Weather Research and Forecasting model, WRF, v3.9.1) to quantify the effects on surface temperature of land cover changes between 1992 and 2015. Unlike many previous studies that had to use one unrealistic large-scale simulation for each LCC to single out its climate effects, our analysis simultaneously considers the effects of the mix of historical land cover changes in Europe and introduces a new method to disentangle the individual contributions. This approach, based on a ridge statistical regression, does not require an explicit consideration of the different components of the surface energy budget, and directly shows the temperature changes from each land transition.</p><p>            From 1992 to 2015, around 70 Mha of land transitions occurred in Europe. Approximately 25 Mha of agricultural land was left abandoned, which was only partially compensated by cropland expansion (about 20 Mha). Declines in agricultural land mostly occurred in favor of forests (15 Mha) and urban settlements (8 Mha). Relative to 1992, we find that the land covers of 2015 are associated with an average temperature cooling of -0.12±0.20 °C, with seasonal and spatial variations. At a continental level, the mean cooling is mainly driven by agriculture abandonment (cropland-to-forest transitions). Idealized simulations where cropland transitions to other land classes are excluded result in a mean warming of +0.10±0.19 °C, especially during summer. Conversions to urban land always resulted in warming effects, whereas the local temperature response to forest gains and losses shows opposite signs from the western and central part of the domain (where forests have cooling effects) to the eastern part (where forests are associated to warming). Gradients in soil moisture and local climate conditions are the main drivers of these differences. Our findings are a first attempt to quantify the regional climate response to historical LCC in Europe, and our method allows to unmix the temperature signal of a grid cell to the underlying LCCs (i.e., temperature impact per land transition). Further developing biophysical implications from LCCs for their ultimate consideration in land use planning can improve synergies for climate change adaptation and mitigation.</p><p> </p>

scholarly journals Land use and land cover changes in the Lower Neretva Region from 1990 to 2020

2021 ◽  
Vol 83 (2) ◽  
pp. 7-31
Author(s):  
Josip Šetka ◽  
◽  
Petra Radeljak Kaufmann ◽  
Luka Valožić ◽  
◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Confusion Matrix ◽  
Hybrid Approach ◽  
Land Cover Changes ◽  
Landsat 8 ◽  
Economic Changes ◽  
Sparse Vegetation ◽  
Landsat 7

Changes in land use and land cover are the result of complex interactions between humans and their environment. This study examines land use and land cover changes in the Lower Neretva Region between 1990 and 2020. Political and economic changes in the early 1990s resulted in changes in the landscape, both directly and indirectly. Multispectral image processing was used to create thematic maps of land use and land cover for 1990, 2005, and 2020. Satellite images from Landsat 5, Landsat 7 and Landsat 8 were the main source of data. Land use and land cover structure was assessed using a hybrid approach, combining unsupervised and manual (visual) classification methods. An assessment of classification accuracy was carried out using a confusion matrix and kappa coefficient. According to the results of the study, the percentage of built-up areas increased by almost 33%. Agricultural land and forests and grasslands also increased, while the proportion of swamps and sparse vegetation areas decreased.

scholarly journals Land Use and Land Cover Change Detection and Prediction in the Kathmandu District of Nepal Using Remote Sensing and GIS

2020 ◽  
Vol 12 (9) ◽  
pp. 3925 ◽  
Author(s):  
Sonam Wangyel Wang ◽  
Belay Manjur Gebru ◽  
Munkhnasan Lamchin ◽  
Rijan Bhakta Kayastha ◽  
Woo-Kyun Lee
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Water Bodies ◽  
Geographical Information ◽  
Land Cover Changes ◽  
Rapid Urbanization ◽  
Urbanized Areas

Understanding land use and land cover changes has become a necessity in managing and monitoring natural resources and development especially urban planning. Remote sensing and geographical information systems are proven tools for assessing land use and land cover changes that help planners to advance sustainability. Our study used remote sensing and geographical information system to detect and predict land use and land cover changes in one of the world’s most vulnerable and rapidly growing city of Kathmandu in Nepal. We found that over a period of 20 years (from 1990 to 2010), the Kathmandu district has lost 9.28% of its forests, 9.80% of its agricultural land and 77% of its water bodies. Significant amounts of these losses have been absorbed by the expanding urbanized areas, which has gained 52.47% of land. Predictions of land use and land cover change trends for 2030 show worsening trends with forest, agriculture and water bodies to decrease by an additional 14.43%, 16.67% and 25.83%, respectively. The highest gain in 2030 is predicted for urbanized areas at 18.55%. Rapid urbanization—coupled with lack of proper planning and high rural-urban migration—is the key driver of these changes. These changes are associated with loss of ecosystem services which will negatively impact human wellbeing in the city. We recommend city planners to mainstream ecosystem-based adaptation and mitigation into urban plans supported by strong policy and funds.

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