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Book ; Online: Monitoring Forest Carbon Sequestration with Remote Sensing

Du, Huaqiang / Fan, Wenyi / Li, Mingshi / Fan, Weiliang / Mao, Fangjie

2023

Keywords	Research & information: general ; Mathematics & science ; Probability & statistics ; forest height ; synthetic aperture radar (SAR) ; interferometry ; random volume over ground (RVoG) model ; three-stage inversion method ; bamboo forest ; BEPS model ; gross primary productivity ; net primary productivity ; spatiotemporal evolution ; climate change ; backscatter coefficients ; polarization decomposition ; collinearity ; ridge regression ; RF ; PCA ; aboveground carbon density ; LiDAR ; stratified estimation ; machine learning algorithm ; Northeast China ; canopy closure ; the GOST model ; fisheye camera photos ; transects ; LAI ; forest height inversion ; three-stage algorithm ; coherence optimization ; complex coherence amplitude inversion ; SRTM ; random forest ; stochastic gradient boosting ; random forest Kriging ; wavelet analysis ; carbon storage ; land use/cover change ; scenario simulation ; PLUS model ; InVEST model ; remote sensing inversion ; dynamic change ; driving factors ; Shaoguan City ; above-ground biomass (AGB) ; airborne LiDAR ; airborne hyperspectral ; wavelet transform ; feature fusion ; Landsat time-series ; VCT model ; classifying forest types ; forest aboveground biomass ; forest aboveground biomass (AGB) ; scale effect ; random forest (RF) ; scale correction ; phenology ; dynamic threshold method ; northeast China ; TIMESAT ; forest carbon stocks ; simulation ; LUCC ; multi-source data ; feature selection ; aboveground biomass ; habitat dataset ; Landsat 8-OLI images ; pine forest ; model comparison ; 3D green volume ; UAV-Lidar ; urban forest ; random forest model ; remote sensing ; MODIS ; FY-3C VIRR ; Yunnan Province ; mangrove forests ; Hainan Island ; deep learning ; influential mechanism ; Bayesian hierarchical modelling ; geostatistics ; Eucalyptus grandis ; Eucalyptus camaldulensis ; Pinus patula ; spatial random effects ; spatially varying coefficient ; rubber plantation ; time series ; shapelet ; Landsat ; Pinus densata ; terrain niche index ; dynamic model ; canopy volume ; diameter at breast height (DBH) ; aboveground biomass (AGB) ; stem volume (V) ; near-infrared reflectance of vegetation ; carbon budget ; L-band PolInSAR ; RVoG model ; forest density ; terrain slope ; coherence ; extinction coefficient ; signal penetration ; 3-PG model ; eucalyptus ; forest age ; forest structure ; sensitivity ; clumping index ; estimation ; impact analysis ; field measurement ; Sentinel-2 images ; artificial neural network ; random forests ; quantile regression neural network ; Pinus densata forests
Language	English
Size	1 electronic resource (652 pages)
Publisher	MDPI - Multidisciplinary Digital Publishing Institute
Publishing place	Basel
Document type	Book ; Online
Note	English
HBZ-ID	HT030377968
ISBN	9783036572093 ; 3036572090
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: Spatiotemporal patterns of net primary productivity of subtropical forests in China and its response to drought.

Yin, Shiyan / Du, Huaqiang / Mao, Fangjie / Li, Xuejian / Zhou, Guomo / Xu, Cenhen / Sun, Jiaqian

The Science of the total environment

2023 Volume 913, Page(s) 169439

Abstract: Net primary productivity (NPP) is an important indicator used to evaluate the carbon sequestration capacity of forest ecosystems. Subtropical forest ecosystems play an indispensable role in maintaining the global carbon balance, while frequently ... ...

Abstract	Net primary productivity (NPP) is an important indicator used to evaluate the carbon sequestration capacity of forest ecosystems. Subtropical forest ecosystems play an indispensable role in maintaining the global carbon balance, while frequently occurring drought events in recent years have seriously damaged their productivity. However, the spatiotemporal patterns of NPP, as well as its response to drought, remain uncertain. In this study, the multiscale drought characteristics in subtropical China during 1981-2015 were analyzed based on the standardized precipitation evapotranspiration index. Then, simulated and analyzed the spatiotemporal NPP of subtropical forests by the boreal ecosystem productivity simulator model. Finally, the response of NPP to drought was analyzed based on multiple statistical indices. The results show that most regions in subtropical China experienced mild and moderate drought during 1981-2015. In particular, the extent of drought severity has shown a noticeable increasing trend after 2000. The forest NPP ranged from 622.64 to 1323.82 gC·m
MeSH term(s)	Ecosystem ; Droughts ; China ; Forests ; Uncertainty ; Climate Change
Language	English
Publishing date	2023-12-20
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2023.169439
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Full phenology cycle carbon flux dynamics and driving mechanism of Moso bamboo forest.

Xu, Cenheng / Mao, Fangjie / Du, Huaqiang / Li, Xuejian / Sun, Jiaqian / Ye, Fengfeng / Zheng, Zhaodong / Teng, Xianfeng / Yang, Ningxin

Frontiers in plant science

2024 Volume 15, Page(s) 1359265

Abstract: Introduction: Moso bamboo forests, widely distributed in subtropical regions, are increasingly valued for their strong carbon sequestration capacity. However, the carbon flux variations and the driving mechanisms of Moso bamboo forest ecosystems of each ...

Abstract	Introduction: Moso bamboo forests, widely distributed in subtropical regions, are increasingly valued for their strong carbon sequestration capacity. However, the carbon flux variations and the driving mechanisms of Moso bamboo forest ecosystems of each phenology period have not been adequately explained. Methods: Hence, this study utilizes comprehensive observational data from a Moso bamboo forest eddy covariance observation for the full phenological cycle (2011-2015), fitting a light response equation to elucidate the evolving dynamics of carbon fluxes and photosynthetic characteristics throughout the entire phenological cycle, and employing correlation and path analysis to reveal the response mechanisms of carbon fluxes to both biotic and abiotic factors. Results: The results showed that, First, the net ecosystem exchange (NEE) of Moso bamboo forest exhibits significant variations across six phenological periods, with LS Discussion: The results provide a scientific basis for carbon sink assessment of Moso bamboo forests and provide a reference for developing Moso bamboo forest management strategies.
Language	English
Publishing date	2024-02-26
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2613694-6
ISSN	1664-462X
ISSN	1664-462X
DOI	10.3389/fpls.2024.1359265
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Spatiotemporal Evolution of the Carbon Fluxes from Bamboo Forests and their Response to Climate Change Based on a BEPS Model in China

Kang, Fangfang / Li, Xuejian / Du, Huaqiang / Mao, Fangjie / Zhou, Guomo / Xu, Yanxin / Huang, Zihao / Ji, Jiayi / Wang, Jingyi

Remote Sensing. 2022 Jan. 13, v. 14, no. 2

2022

Abstract: Carbon flux is the main basis for judging the carbon source/sink of forest ecosystems. Bamboo forests have gained much attention because of their high carbon sequestration capacity. In this study, we used a boreal ecosystem productivity simulator (BEPS) ... ...

Abstract	Carbon flux is the main basis for judging the carbon source/sink of forest ecosystems. Bamboo forests have gained much attention because of their high carbon sequestration capacity. In this study, we used a boreal ecosystem productivity simulator (BEPS) model to simulate the gross primary productivity (GPP) and net primary productivity (NPP) of bamboo forests in China during 2001–2018, and then explored the spatiotemporal evolution of the carbon fluxes and their response to climatic factors. The results showed that: (1) The simulated and observed GPP values exhibited a good correlation with the determination coefficient (R²), root mean square error (RMSE), and absolute bias (aBIAS) of 0.58, 1.43 g C m⁻² day⁻¹, and 1.21 g C m⁻² day⁻¹, respectively. (2) During 2001–2018, GPP and NPP showed fluctuating increasing trends with growth rates of 5.20 g C m⁻² yr⁻¹ and 3.88 g C m⁻² yr⁻¹, respectively. The spatial distribution characteristics of GPP and NPP were stronger in the south and east than in the north and west. Additionally, the trend slope results showed that GPP and NPP mainly increased, and approximately 30% of the area showed a significant increasing trend. (3) Our study showed that more than half of the area exhibited the fact that the influence of the average annual precipitation had positive effects on GPP and NPP, while the average annual minimum and maximum temperatures had negative effects on GPP and NPP. On a monthly scale, our study also demonstrated that the influence of precipitation on GPP and NPP was higher than that of the influence of temperature on them.
Keywords	atmospheric precipitation ; bamboos ; carbon ; carbon sequestration ; climate change ; forests ; gross primary productivity ; net primary productivity ; simulation models ; temperature ; China
Language	English
Dates of publication	2022-0113
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2513863-7
ISSN	2072-4292
ISSN	2072-4292
DOI	10.3390/rs14020366
Database	NAL-Catalogue (AGRICOLA)

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Article: Simulated net ecosystem productivity of subtropical forests and its response to climate change in Zhejiang Province, China

Mao, Fangjie / Du, Huaqiang / Zhou, Guomo / Zheng, Junlong / Li, Xuejian / Xu, Yanxin / Huang, Zihao / Yin, Shiyan

Science of the total environment. 2022 Sept. 10, v. 838

2022

Abstract: Net ecosystem productivity (NEP) is an important index that indicates the carbon sequestration capacity of forest ecosystems. However, the effect of climate change on the spatiotemporal variability in NEP is still unclear. Using the Integrated ... ...

Abstract	Net ecosystem productivity (NEP) is an important index that indicates the carbon sequestration capacity of forest ecosystems. However, the effect of climate change on the spatiotemporal variability in NEP is still unclear. Using the Integrated Terrestrial Ecosystem Carbon-budget (InTEC) model, this study takes the typical subtropical forests in the Zhejiang Province, China as an example, simulated the spatiotemporal patterns of forest NEP from 1979 to 2079 based on historically observed climate data (1979–2015) and data from three representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5) provided by the Coupled Model Intercomparison Project 5 (CMIP5). We analyzed the responses of NEP at different forest age classes to the variation in meteorological factors. The NEP of Zhejiang's forests decreased from 1979 to 1985 and then increased from 1985 to 2015, with an annual increase rate of 9.66 g C·m⁻²·yr⁻¹ and a cumulative NEP of 364.99 Tg·C. Forest NEP decreased from 2016 to 2079; however, the cumulative NEP continued to increase. The simulated cumulative NEP under the RCP2.6, RCP4.5, and RCP8.5 scenarios was 750 Tg·C, 866 Tg·C, and 958 Tg·C, respectively, at the end of 2079. Partial correlation analysis between forest NEP at different age stages and meteorological factors showed that temperature is the key climatic factor that affects the carbon sequestration capacity of juvenile forests (1979–1999), while precipitation is the key climatic factor that affects middle-aged forests (2000–2015) and mature forests (2016–2079). Adopting appropriate management strategies for forests, such as selective cutting of different ages, is critical for the subtropical forests to adapt to climate change and maintain their high carbon sink capacity.
Keywords	carbon sequestration ; carbon sinks ; climate change ; climatic factors ; juveniles ; meteorological data ; models ; net ecosystem production ; temperature ; China
Language	English
Dates of publication	2022-0910
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2022.155993
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Land use and cover in subtropical East Asia and Southeast Asia from 1700 to 2018

Mao, Fangjie / Li, Xuejian / Zhou, Guomo / Huang, Zihao / Xu, Yanxing / Chen, Qi / Yan, Mengjie / Sun, Jiaqian / Xu, Cenheng / Du, Huaqiang

Global and Planetary Change. 2023 May 29, p.104157-

2023 , Page(s) 104157–

Abstract: Land-use/cover change (LUCC) has severely disturbed the terrestrial carbon balance in subtropical East Asia and Southeast Asia (SEASA). High-precision, long-term historical land cover (LC) data, and LC spatiotemporal patterns and transitions, exhibit ... ...

Abstract	Land-use/cover change (LUCC) has severely disturbed the terrestrial carbon balance in subtropical East Asia and Southeast Asia (SEASA). High-precision, long-term historical land cover (LC) data, and LC spatiotemporal patterns and transitions, exhibit high levels of uncertainty. This study constructed base and potential map containing 18 LC categories by integrating multisource high-resolution remote sensing datasets in 2014; then collected official reports, FAOSTAT, and long-term historical datasets, and used the correction coefficient method to obtain the area time series of forest, cropland, and urban at the provincial scale from 1700 to 2018; Finally, the fraction map of 18 LCs in SEASA at 1 km resolution during 1700–2018 was reconstructed based on a pixel level area calibration method, and the spatiotemporal patterns and transitions of LUCC were analyzed. Over the past 300 years, SEASA forest area decreased by 145.22 million ha, most rapidly from 1950 to 1980 (sevenfold that of the preceding 250 years). The loss of tropical forest, mainly in Indonesia, Myanmar, and Thailand, accounting for >80% of this decline. Subtropical forest areas increased significantly in China. Cropland and urban areas increased greatly, by 86.55 and 7.97 million ha, respectively, with the largest increases in China, Thailand, Myanmar, Japan, and Indonesia. Other natural land types closely related to human activity declined more, becoming cropland and urban areas, with greater variability. Conversion of forest to other LC types accounted for >70% of the total LC transition from 1700 to 2018. The main sources of cropland were forest (mainly in Thailand, central Myanmar, and southern Vietnam) and other nonforest natural land. Urban growth was mainly via encroachment on forest and other natural land. This study elucidates the spatiotemporal evolution of LUCC in SEASA from 1700 to 2018, and provides historical spatiotemporal data for large-scale bamboo forests, along with high-precision LUCC data for studying terrestrial ecosystem responses to climate change in the SEASA.
Keywords	Japan ; bamboos ; carbon ; climate change ; cropland ; data collection ; humans ; image analysis ; land cover ; land use ; terrestrial ecosystems ; time series analysis ; tropical forests ; uncertainty ; urbanization ; China ; Indonesia ; Myanmar ; Thailand ; Vietnam ; LUCC ; Subtropical East Asia ; Southeast Asia ; Reconstruction
Language	English
Dates of publication	2023-0529
Publishing place	Elsevier B.V.
Document type	Article ; Online
Note	Pre-press version
ZDB-ID	2016967-X
ISSN	0921-8181
ISSN	0921-8181
DOI	10.1016/j.gloplacha.2023.104157
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Simulated net ecosystem productivity of subtropical forests and its response to climate change in Zhejiang Province, China.

Mao, Fangjie / Du, Huaqiang / Zhou, Guomo / Zheng, Junlong / Li, Xuejian / Xu, Yanxin / Huang, Zihao / Yin, Shiyan

The Science of the total environment

2022 Volume 838, Issue Pt 1, Page(s) 155993

Abstract	Net ecosystem productivity (NEP) is an important index that indicates the carbon sequestration capacity of forest ecosystems. However, the effect of climate change on the spatiotemporal variability in NEP is still unclear. Using the Integrated Terrestrial Ecosystem Carbon-budget (InTEC) model, this study takes the typical subtropical forests in the Zhejiang Province, China as an example, simulated the spatiotemporal patterns of forest NEP from 1979 to 2079 based on historically observed climate data (1979-2015) and data from three representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5) provided by the Coupled Model Intercomparison Project 5 (CMIP5). We analyzed the responses of NEP at different forest age classes to the variation in meteorological factors. The NEP of Zhejiang's forests decreased from 1979 to 1985 and then increased from 1985 to 2015, with an annual increase rate of 9.66 g C·m
MeSH term(s)	Carbon/analysis ; Carbon Sequestration ; China ; Climate Change ; Ecosystem ; Forests
Chemical Substances	Carbon (7440-44-0)
Language	English
Publishing date	2022-05-15
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2022.155993
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

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Article: Spatiotemporal dynamics of bamboo forest net primary productivity with climate variations in Southeast China

Mao, Fangjie / Du, Huaqiang / Li, Xuejian / Ge, Hongli / Cui, Lu / Zhou, Guomo

Ecological indicators. 2020 Sept., v. 116

2020

Abstract: Net primary productivity (NPP) is an important indicator of forest biomass accumulation as well as carbon sink capacity. Bamboo forests have gained much attention because of their high carbon sequestration potential. However, the estimations of bamboo ... ...

Abstract	Net primary productivity (NPP) is an important indicator of forest biomass accumulation as well as carbon sink capacity. Bamboo forests have gained much attention because of their high carbon sequestration potential. However, the estimations of bamboo forest NPP based on field investigations and statistical analyses in previous studies have varied and do not accurately reflect the spatiotemporal dynamics at the regional level, leading to missing information on the long-term spatiotemporal variations and the formative mechanisms of bamboo forest NPP. We used a process-based ecosystem model to estimate the spatiotemporal dynamics of bamboo forest NPP based on continuous forest resources inventory datasets for Zhejiang Province, China, from 2001 to 2015. Estimates of NPP increased from 250.75 g C m⁻² year⁻¹ in 2001 to 409.09 g C m⁻² year⁻¹ in 2015 and accounted for approximately 9.39% of the total NPP of forests in Zhejiang Province. A total of 67.51% of the bamboo forested area showed increasing NPP trends, and most increases occurred in the northwest, southwest, and eastern hilly regions of Zhejiang Province. The spatiotemporal patterns of bamboo forest NPP were sensitive to climatic factors and significantly correlated with precipitation. However, human activities, such as management measures, management levels, and policies, also had effects on the NPP of bamboo forests. This improved understanding of the spatiotemporal dynamics of bamboo forest NPP could provide a reference for the sustainable management of bamboo forests, and we will explore the response of the bamboo forest NPP to future climate changes in later studies.
Keywords	bamboos ; biomass production ; carbon sequestration ; carbon sinks ; data collection ; ecological models ; forests ; humans ; inventories ; net primary productivity ; China
Language	English
Dates of publication	2020-09
Publishing place	Elsevier Ltd
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	2036774-0
ISSN	1872-7034 ; 1470-160X
ISSN (online)	1872-7034
ISSN	1470-160X
DOI	10.1016/j.ecolind.2020.106505
Database	NAL-Catalogue (AGRICOLA)

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Article: Spatiotemporal Evolution of Fractional Vegetation Cover and Its Response to Climate Change Based on MODIS Data in the Subtropical Region of China

Liu, Hua / Li, Xuejian / Mao, Fangjie / Zhang, Meng / Zhu, Di’en / He, Shaobai / Huang, Zihao / Du, Huaqiang

Remote Sensing. 2021 Feb. 28, v. 13, no. 5

2021

Abstract: The subtropical vegetation plays an important role in maintaining the structure and function of global ecosystems, and its contribution to the global carbon balance are receiving increasing attention. The fractional vegetation cover (FVC) as an important ...

Abstract	The subtropical vegetation plays an important role in maintaining the structure and function of global ecosystems, and its contribution to the global carbon balance are receiving increasing attention. The fractional vegetation cover (FVC) as an important indicator for monitoring environment change, is widely used to analyze the spatiotemporal pattern of regional and even global vegetation. China is an important distribution area of subtropical vegetation. Therefore, we first used the dimidiate pixel model to extract the subtropical FVC of China during 2001–2018 based on MODIS land surface reflectance data, and then used the linear regression analysis and the variation coefficient to explore its spatiotemporal variations characteristics. Finally, the partial correlation analysis and the partial derivative model were used to analyze the influences and contributions of climate factors on FVC, respectively. The results showed that (1) the subtropical FVC had obvious spatiotemporal heterogeneity; the FVC high-coverage and medium-coverage zones were concentratedly and their combined area accounted for more than 70% of the total study area. (2) The interannual variation in the average subtropical FVC from 2001 to 2018 showed a significant growth trend. (3) In 76.28% of the study area, the regional FVC showed an increasing trend, and the remaining regional FVC showed a decreasing trend. However, the overall fluctuations in the FVC (increasing or decreasing) in the region were relatively stable. (4) The influences of climate factors to the FVC exhibited obvious spatial differences. More than half of all pixels exhibited the influence of the average annual minimum temperature and the annual precipitation had positive on FVC, while the average annual maximum temperature had negative on FVC. (5) The contributions of climate changes to FVC had obvious heterogeneity, and the average annual minimum temperature was the main contribution factor affecting the dynamic variations of FVC.
Keywords	atmospheric precipitation ; carbon ; climate change ; fractional vegetation cover ; models ; reflectance ; regression analysis ; subtropics ; temperature ; China
Language	English
Dates of publication	2021-0228
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	2513863-7
ISSN	2072-4292
ISSN	2072-4292
DOI	10.3390/rs13050913
Database	NAL-Catalogue (AGRICOLA)

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Article: Remote Sensing Estimation of Bamboo Forest Aboveground Biomass Based on Geographically Weighted Regression

Wang, Jingyi / Du, Huaqiang / Li, Xuejian / Mao, Fangjie / Zhang, Meng / Liu, Enbin / Ji, Jiayi / Kang, Fangfang

Remote Sensing. 2021 July 28, v. 13, no. 15

2021

Abstract: Bamboo forests are widespread in subtropical areas and are well known for their rapid growth and great carbon sequestration ability. To recognize the potential roles and functions of bamboo forests in regional ecosystems, forest aboveground biomass (AGB)— ...

Abstract	Bamboo forests are widespread in subtropical areas and are well known for their rapid growth and great carbon sequestration ability. To recognize the potential roles and functions of bamboo forests in regional ecosystems, forest aboveground biomass (AGB)—which is closely related to forest productivity, the forest carbon cycle, and, in particular, carbon sinks in forest ecosystems—is calculated and applied as an indicator. Among the existing studies considering AGB estimation, linear or nonlinear regression models are the most frequently used; however, these methods do not take the influence of spatial heterogeneity into consideration. A geographically weighted regression (GWR) model, as a spatial local model, can solve this problem to a certain extent. Based on Landsat 8 OLI images, we use the Random Forest (RF) method to screen six variables, including TM457, TM543, B7, NDWI, NDVI, and W7B6VAR. Then, we build the GWR model to estimate the bamboo forest AGB, and the results are compared with those of the cokriging (COK) and orthogonal least squares (OLS) models. The results show the following: (1) The GWR model had high precision and strong prediction ability. The prediction accuracy (R²) of the GWR model was 0.74, 9%, and 16% higher than the COK and OLS models, respectively, while the error (RMSE) was 7% and 12% lower than the errors of the COK and OLS models, respectively. (2) The bamboo forest AGB estimated by the GWR model in Zhejiang Province had a relatively dense spatial distribution in the northwestern, southwestern, and northeastern areas. This is in line with the actual bamboo forest AGB distribution in Zhejiang Province, indicating the potential practical value of our study. (3) The optimal bandwidth of the GWR model was 156 m. By calculating the variable parameters at different positions in the bandwidth, close attention is given to the local variation law in the estimation of the results in order to reduce the model error.
Keywords	Landsat ; aboveground biomass ; bamboos ; carbon ; carbon sequestration ; forests ; models ; prediction ; spatial variation ; China
Language	English
Dates of publication	2021-0728
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2513863-7
ISSN	2072-4292
ISSN	2072-4292
DOI	10.3390/rs13152962
Database	NAL-Catalogue (AGRICOLA)

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