scholarly journals Gross and net land cover changes based on plant functional types derived from the annual ESA CCI land cover maps

Author(s):  
Wei Li ◽  
Natasha MacBean ◽  
Philippe Ciais ◽  
Pierre Defourny ◽  
Céline Lamarche ◽  
...  

Abstract. Land-use and land-cover change (LULCC) impacts local energy and water balance and contributes at global scale to a net carbon emission to the atmosphere. The newly released annual ESA CCI land cover maps provide continuous land cover changes at 300 m resolution from 1992 to 2015, and can be used in land surface models (LSMs) to simulate LULCC effects on carbon stocks and on surface energy budgets. Here we investigate the absolute areas, gross and net changes of different plant functional types (PFTs) derived from ESA CCI products. The results are compared with other datasets. Global areas of forest, cropland and grassland PFTs from ESA are 30.4, 19.3 and 35.7 million km2 in 2000. The global forest area is lower than that from LUH2v2h (Hurtt et al., 2011), Hansen et al. (2013) and Houghton and Nassikas (2017) while cropland area is higher than LUH2v2h (Hurtt et al., 2011), in which cropland area is from HYDE3.2 (Klein Goldewijk et al., 2016). Gross forest loss and gain during 1992–2015 are 1.5 and 0.9 million km2 respectively, resulting in a net forest loss of 0.6 million km2, mainly occurring in South and Central America. The magnitudes of gross changes of forest, cropland and grassland PFTs in ESA CCI are smaller than those in other datasets. The magnitude of global net cropland gain for the whole period is consistent with HYDE3.2 (Klein Goldewijk et al., 2016), but most of the increases happened before 2004 in ESA while after 2007 in HYDE3.2. Brazil, Bolivia and Indonesia are the countries with the largest net forest loss from 1992 to 2015, and the decreased areas are generally consistent with those from Hansen et al. (2013) based on Landsat 30 m resolution images. Despite discrepancies compared to other datasets, and uncertainties in converting into PFTs, the new ESA CCI products provide the first detailed long time-series of land-cover change and can be implemented in LSMs to characterize recent carbon dynamics, and in climate models to simulate land-cover change feedbacks on climate. The annual ESA CCI land cover products can be downloaded from http://maps.elie.ucl.ac.be/CCI/viewer/download.php (Land Cover Maps – v2.0.7; see details in Section 2.5).

2018 ◽  
Vol 10 (1) ◽  
pp. 219-234 ◽  
Author(s):  
Wei Li ◽  
Natasha MacBean ◽  
Philippe Ciais ◽  
Pierre Defourny ◽  
Céline Lamarche ◽  
...  

Abstract. Land-use and land-cover change (LULCC) impacts local energy and water balance and contributes on global scale to a net carbon emission to the atmosphere. The newly released annual ESA CCI (climate change initiative) land cover maps provide continuous land cover changes at 300 m resolution from 1992 to 2015, and can be used in land surface models (LSMs) to simulate LULCC effects on carbon stocks and on surface energy budgets. Here we investigate the absolute areas and gross and net changes in different plant functional types (PFTs) derived from ESA CCI products. The results are compared with other datasets. Global areas of forest, cropland and grassland PFTs from ESA are 30.4, 19.3 and 35.7 million km2 in the year 2000. The global forest area is lower than that from LUH2v2h (Hurtt et al., 2011), Hansen et al. (2013) or Houghton and Nassikas (2017) while cropland area is higher than LUH2v2h (Hurtt et al., 2011), in which cropland area is from HYDE 3.2 (Klein Goldewijk et al., 2016). Gross forest loss and gain during 1992–2015 are 1.5 and 0.9 million km2 respectively, resulting in a net forest loss of 0.6 million km2, mainly occurring in South and Central America. The magnitudes of gross changes in forest, cropland and grassland PFTs in the ESA CCI are smaller than those in other datasets. The magnitude of global net cropland gain for the whole period is consistent with HYDE 3.2 (Klein Goldewijk et al., 2016), but most of the increases happened before 2004 in ESA and after 2007 in HYDE 3.2. Brazil, Bolivia and Indonesia are the countries with the largest net forest loss from 1992 to 2015, and the decreased areas are generally consistent with those from Hansen et al. (2013) based on Landsat 30 m resolution images. Despite discrepancies compared to other datasets, and uncertainties in converting into PFTs, the new ESA CCI products provide the first detailed long-term time series of land-cover change and can be implemented in LSMs to characterize recent carbon dynamics, and in climate models to simulate land-cover change feedbacks on climate. The annual ESA CCI land cover products can be downloaded from http://maps.elie.ucl.ac.be/CCI/viewer/download.php (Land Cover Maps – v2.0.7; see details in Sect. 5). The PFT map translation protocol and an example in 2000 can be downloaded from https://doi.org/10.5281/zenodo.834229. The annual ESA CCI PFT maps from 1992 to 2015 at 0.5∘×0.5∘ resolution can also be downloaded from https://doi.org/10.5281/zenodo.1048163.


2020 ◽  
Author(s):  
Shaoqiang Ni ◽  
Hui Lu

<p>By changing matter and energy exchange, biogeochemical process and geophysical process, land use and land cover changes have crucial effects on the earth system modelling. Previous studies have focused on reconstructing the land use and land cover change to be a continuous changing process over time considering human and natural factors. The real land cover change processes have rarely been taken into consideration in the simulation of earth system. Using Gong global land cover mapping products (1985-2015) and the Lawrence land cover dataset (default) in CESM, this study have quantitatively compared the differences in plant function types (PFT) between two products. The results show the land cover changes in default dataset are slowly changing processes with little variation from year to year. In contrast, the Gong global mapping products express a noticeable drastic change tendency between adjacent years. Driving the model with different land cover datasets, our results indicates that globally land evapotranspiration (ET) is dramatically impacted by the land cover changes, especially in areas with distinct tree changes. Also the land cover change can cause a certain proportion variation in soil water (-50%-65%) and runoff (-60%-60%, even >90% in some special grid points) in a global scale. This study estimates the substantial effect land use and land cover changes can have on the land surface hydrological process in earth system modelling.</p>


2021 ◽  
Vol 6 (3) ◽  
pp. 301
Author(s):  
Fahrudin Hanafi ◽  
Dinda Putri Rahmadewi ◽  
Fajar Setiawan

Land cover changes based on cellular automata for surface temperature in Semarang Regency has increased significantly due to the continuous rise in its population. Therefore, this study aims to identify, analyze and predict multitemporal land cover changes and surface temperature distribution in 2028. Data on the land cover map were obtained from Landsat 7 and 8 based on supervised classification, while Land Surface Temperature (LST) was calculated from its thermal bands. The collected data were analyzed for accuracy through observation, while Cellular Automata - Markov Chain was used to predict the associated changes in 2028. The result showed that there are 4 land cover maps with 5-year intervals from 2003 to 2018 at an accuracy of more than 85%. Furthermore, the existing land covers were dominated by forest with decreasing trend, while the built-up area continuously increased. The existing Land surface temperature range from 20.6°C to 36.6°C, at an average of 28.2°C and a yearly increase of 0.07°C. The temperature changes are positively correlated with the occurrence of land conversion. Land cover predictions for 2028 show similar forest dominance, with a 23,4% built-up area at a surface temperature of 28.9°C. Keywords: Land cover change; Cellular Automata-Markov Chain; Land Surface Temperature Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember     This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License


2003 ◽  
Vol 16 (9) ◽  
pp. 1261-1282 ◽  
Author(s):  
Valéry Masson ◽  
Jean-Louis Champeaux ◽  
Fabrice Chauvin ◽  
Christelle Meriguet ◽  
Roselyne Lacaze

Abstract Ecoclimap, a new complete surface parameter global dataset at a 1-km resolution, is presented. It is intended to be used to initialize the soil–vegetation–atmosphere transfer schemes (SVATs) in meteorological and climate models (at all horizontal scales). The database supports the “tile” approach, which is utilized by an increasing number of SVATs. Two hundred and fifteen ecosystems representing areas of homogeneous vegetation are derived by combining existing land cover maps and climate maps, in addition to using Advanced Very High Resolution Radiometer (AVHRR) satellite data. Then, all surface parameters are derived for each of these ecosystems using lookup tables with the annual cycle of the leaf area index (LAI) being constrained by the AVHRR information. The resulting LAI is validated against a large amount of in situ ground observations, and it is also compared to LAI derived from the International Satellite Land Surface Climatology Project (ISLSCP-2) database and the Polarization and Directionality of the Earth's Reflectance (POLDER) satellite. The comparison shows that this new LAI both reproduces values coherent at large scales with other datasets, and includes the high spatial variations owing to the input land cover data at a 1-km resolution. In terms of climate modeling studies, the use of this new database is shown to improve the surface climatology of the ARPEGE climate model.


2020 ◽  
Vol 18 ◽  
pp. 100314 ◽  
Author(s):  
Abdulla - Al Kafy ◽  
Md. Shahinoor Rahman ◽  
Abdullah-Al- Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Muhaiminul Islam

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