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 ◽  
...  

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).

2021 ◽  
Author(s):  
Wolfgang A. Obermeier ◽  
Julia E. M. S. Nabel ◽  
Tammas Loughran ◽  
Kerstin Hartung ◽  
Ana Bastos ◽  
...  

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.


2020 ◽  
Vol 12 (9) ◽  
pp. 3925 ◽  
Author(s):  
Sonam Wangyel Wang ◽  
Belay Manjur Gebru ◽  
Munkhnasan Lamchin ◽  
Rijan Bhakta Kayastha ◽  
Woo-Kyun Lee

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.


2020 ◽  
Vol 4 (1) ◽  
pp. 699-707
Author(s):  
Nadya Faizah ◽  
Muhammad Rusdi ◽  
Sugianto Sugianto

Abstrak. Perubahan tutupan lahan mengakibatkan beberapa penggunaan lahan menjadi berubah, terutama pada lahan pertanian yang berubah menjadi non-pertanian. Perubahan penggunaan lahan saat ini sudah sering terjadi di beberapa daerah terutama pada lahan pertanian yang berubah menjadi lahan non-pertanian. Pasca Tsunami daerah yang terkena bencana dilakukan rehabilitasi dan rekontruksi, semua aktivitas tersebut berdampak kepada perubahan tutupan lahan. Perubahan tutupan lahan diperoleh dari overlay dengan kaedah union mulai dari tahun 2004 hingga tahun 2018. Hasil analisis menunjukkan bahwa perubahan tutupan lahan selama kurun waktu 14 tahun pasca Tsunami terbesar terjadi pada pemukiman, yaitu mengalami peningkatan sebesar 550,14 ha (76,96%). sedangkan Perubahan tutupan lahan terkecil yaitu semak belukar sebesar 66,41 ha (5,06%).Land Cover Changes after 14 years of the Tsunami Case Study at Kecamatan BaitussalamAbstract. Changes in land cover have caused some land use to change, especially on agricultural land that has turned into non-agricultural land. Post-tsunami areas affected by rehabilitation and reconstruction, all of these activities have an impact on land cover change. Changes in land cover were obtained from overlays with the unification method from 2004 to 2018. The results of the analysis showed that changes in land cover for 14 years after the Tsunami occurred mostly in settlements, which increased by 550.14 ha (76.96%). while the smallest land cover change is shrubs covering an area of 66.41 ha (5.06%).


2021 ◽  
Author(s):  
Wolfgang Obermeier ◽  

<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>


2020 ◽  
Vol 12 (2) ◽  
Author(s):  
Karagama Kolo Geidam ◽  
◽  
Nor Aizam Adnan ◽  
Baba Alhaji Umar ◽  
◽  
...  

Change detection is useful in many applications related to land use and land cover change (LULCC), such as shifting cultivation and landscape changes. Land degradation and desertification. Remote sensing technology has been used for the detection of the changes in land use land cover in Damaturu town Nigeria. The main objectives of this research is to derive the land use/cover change map of Damaturu town from 1986 to 2017 and to quantify land use/ land cover change in the study area. Methodology employed while carry the research includes three satellites images for the year 1986, 1998 and 2017 were downloaded from USGS websites and used for detecting the land cover changes. Ground truth points were collected using google images and used for verification of image classifications. The accuracy of images classification was checked using ground truth point which showed the overall accuracy of 84.6% and a kappa coefficient of 0.89 which indicated that the method of classification was accurate. In the process of the research work, an increased was recorded in the built-up area which rose from 7.2% to 22.0%, open space increased from 10.8 to 22.8%, vegetation from 4.0% to 9.7%, water bodies from 0.0% to 0.1% while agricultural land decreased from 78% to 45.4% due to increase in interest of building as a result of the expansion of the town. The study arrived at the conclusion that there has been a significant land use change due to increase in population and development interest in built up areas which resulted in increased of amount of agricultural land being converted to build up areas over the period of 31 years.


Author(s):  
Monalisa Kuanar ◽  
Swetalina Nath

Due to increasing demand for basic human needs and welfare of ever growing population there is seen remarkable changes in land use land cover of particular areas. Land use land cover has become a important component in current strategies for managing natural resource and managing environmental changes in present days. The objectives of this research were to analyse the land use land cover change for two periods 2005-06 and 2011-12 and comparing the changes, to study the impact of  LULC change on runoff and to estimate the runoff of a watershed area i.e. Gangua Jhumka watershed. Accurate estimation of runoff is an important work for proper watershed management. Direct runoff of a catchment is depended on soil type, and cover and rainfall. Among all the methods available for estimation of runoff SCS-CN method is the most popular. The curve number depends on soil and land use characteristics. This study was carried out in Gangua Jhumka watershed located Khurdha District of Odisha using remote sensing and GIS. The total area of watershed 685.711 sq. km. Soil map, Land use map, elevation maps are generated from GIS Environment. In this research work as the study area is a fast developing city and the population growth is remarkable so most of the agricultural land and forest lands are converted to built up lands. Land sat satellite image was used to obtain land cover information. The thematic maps like soil map, elevation map, and land cover map were created in Arc GIS 10.3. Curve numbers are assigned for different land cover and soil types. In present study the runoff calculated are 1307.6 mm and 1434.8 mm for the year 2005-06 and 2011-12 respectively. Due to increase urbanization runoff has decreased in the study area.


2021 ◽  
Author(s):  
Mohamad Wawan Sujarwo ◽  
◽  
Indarto Indarto ◽  
Marga Mandala ◽  
◽  
...  

Assessing the impact of land use and land cover change (LULCC) on hydrology is essential for water resource management. The Brantas watershed contributes about 30% of the water supply of the East Java region. The present rapid pace of land occupation for agriculture and settlements is expected to continue to alter flow processes within the watershed. This study aims to simulate LULCC and its impact on the hydrological processes of the watershed. The long-term impact of LULCC is evaluated using the Soil & Water Assessment Tool (SWAT). The analysis model is calibrated using monthly data series from 1996 to 2005 and then validated using data series from 2006 to 2015. Two editions of maps (2001 and 2015) are then used to calculate the LULCC that took place across this time period. The impacts of LULCC on hydrological processes at the sub-basin level are also evaluated. The results show that the variability of rainfall patterns from 2001 to 2015 strongly affected flow variability. The LULCC from agricultural land to other uses (irrigated rice fields, settlements and forests/plantations) is most evident in three sub-basins (sub-basins 2, 9 and 17). However, each sub-basin may respond differently with respect to the LULCC taking place. The increase in area occupied by each class of land use and cover use (LULC) is not always linear to the observed flow, and widely differing LULC classes may display similar flow responses while classes with similar characteristics may have differing impacts on flows within a sub-basin. In other words, the hydrological processes taking place are too complex to be simplified at the sub-basin level.


2021 ◽  
Author(s):  
Peter Hoffmann ◽  
Vanessa Reinhart ◽  
Diana Rechid ◽  
Nathalie de Noblet-Ducoudré ◽  
Edouard L. Davin ◽  
...  

Abstract. Anthropogenic land-use and land cover change (LULCC) is a major driver of environmental changes. The biophysical impacts of these changes on the regional climate in Europe are currently extensively investigated within the WCRP CORDEX Flagship Pilot Study (FPS) LUCAS – "Land Use and Climate Across Scales" using an ensemble of different Regional Climate Models (RCMs) coupled with diverse Land Surface Models (LSMs). In order to investigate the impact of realistic LULCC on past and future climates, high-resolution datasets with observed LULCC and projected future LULCC scenarios are required as input for the RCM-LSM simulations. To account for these needs, we generated the LUCAS LUC Version 1.0 at 0.1° resolution for Europe Hoffmann et al. (2021b,c). The plant functional type distribution for the year 2015 (i.e. LANDMATE PFT dataset) is derived from the European Space Agency Climate Change Initiative Land Cover (ESA-CCI LC) dataset. Details about the conversion method based on a cross-walking procedure and the evaluation of the LANDMATE PFT dataset are given in the companion paper by Reinhart et al. (submitted). Subsequently, we applied the land-use change information from the Land-Use Harmonization 2 (LUH2) dataset, provided at 0.25° resolution as input for CMIP6 experiments, to derive realistic LULC distribution at high spatial resolution and at annual timesteps from 1950 to 2100. In order to convert land use and land management change information from LUH2 into changes in the PFT distribution, we developed a Land Use Translator (LUT) specific to the needs of RCMs. The annual PFT maps for Europe for the period 1950 to 2015 are derived from the historical LUH2 dataset by applying the LUT backward from 2015 to 1950. Historical changes in the forest type changes are considered using an additional European forest species dataset. The historical changes in the PFT distribution of LUCAS LUC follow closely the land use changes given by LUH2 but differ in some regions compared to remotely-sensed PFT time series. From 2016 onward, annual PFT maps for future land use change scenarios based on LUH2 are derived for different Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) combinations used in the framework of the Coupled Modelling Intercomparison Project Phase 6 (CMIP6). The resulting LULCC maps can be applied as land use forcing to the next generation of RCM simulations for downscaling of CMIP6 results. The newly developed LUT is transferable to other CORDEX regions world-wide.


Sign in / Sign up

Export Citation Format

Share Document