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1. Land Use and Land Cover Mapping in the Era of Big Data

   https://doi.org/10.3390/land11101692  

   Zhang, Chuanrong; Li, Xinba (October 2022, Land)

   We are currently living in the era of big data. The volume of collected or archived geospatial data for land use and land cover (LULC) mapping including remotely sensed satellite imagery and auxiliary geospatial datasets is increasing. Innovative machine learning, deep learning algorithms, and cutting-edge cloud computing have also recently been developed. While new opportunities are provided by these geospatial big data and advanced computer technologies for LULC mapping, challenges also emerge for LULC mapping from using these geospatial big data. This article summarizes the review studies and research progress in remote sensing, machine learning, deep learning, and geospatial big data for LULC mapping since 2015. We identified the opportunities, challenges, and future directions of using geospatial big data for LULC mapping. More research needs to be performed for improved LULC mapping at large scales. 

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2. The land-use land-cover change–emerging infectious disease nexus reconsidered

   https://doi.org/10.1093/biosci/biaf045  

   Koren, Ore; Chaves, Luis Fernando (April 2025, BioScience)

   Abstract Deforestation due to land-use and land-cover (LULC) change has been linked to increased emerging zoonotic disease risk despite limited local level data on such outbreaks. This Forum reevaluates this risk inference using newly released data on zoonotic disease outbreaks, accounting for Structural One Health features, including socioeconomic development and armed conflict covariates. Event and time series data on disease and forest coverage anomalies at the 0.5-degree level for every month between January 2003 and December 2018 are used to estimate the relationship between LULC and zoonosis using Poisson generalized additive and generalized linear models. Once adjusted for Structural One Health features, outbreak risk is 7%–200% higher in areas that experienced forest cover reversion. These results highlight the importance of accounting for Structural One Health factors when analyzing complex socioecological phenomena such as the LULC–infectious disease nexus. 

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3. The ancestral chromatin landscape of land plants

   https://doi.org/10.1111/nph.19311  

   Hisanaga, Tetsuya; Wu, Shuangyang; Schafran, Peter; Axelsson, Elin; Akimcheva, Svetlana; Dolan, Liam; Li, Fay‐Wei; Berger, Frédéric (October 2023, New Phytologist)

   Summary Recent studies have shown that correlations between chromatin modifications and transcription vary among eukaryotes. This is the case for marked differences between the chromatin of the mossPhyscomitrium patensand the liverwortMarchantia polymorpha. Mosses and liverworts diverged from hornworts, altogether forming the lineage of bryophytes that shared a common ancestor with land plants. We aimed to describe chromatin in hornworts to establish synapomorphies across bryophytes and approach a definition of the ancestral chromatin organization of land plants.We used genomic methods to define the 3D organization of chromatin and map the chromatin landscape of the model hornwortAnthoceros agrestis.We report that nearly half of the hornwort transposons were associated with facultative heterochromatin and euchromatin and formed the center of topologically associated domains delimited by protein coding genes. Transposons were scattered across autosomes, which contrasted with the dense compartments of constitutive heterochromatin surrounding the centromeres in flowering plants.Most of the features observed in hornworts are also present in liverworts or in mosses but are distinct from flowering plants. Hence, the ancestral genome of bryophytes was likely a patchwork of units of euchromatin interspersed within facultative and constitutive heterochromatin. We propose this genome organization was ancestral to land plants. 

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4. Analysis of Land Use and Land Cover Changes through the Lens of SDGs in Semarang, Indonesia

   https://doi.org/10.3390/su14137592  

   Kelly-Fair, Mira; Gopal, Sucharita; Koch, Magaly; Pancasakti Kusumaningrum, Hermin; Helmi, Muhammad; Khairunnisa, Dinda; Kaufman, Les (July 2022, Sustainability)

   Land Use and Land Cover Changes (LULCC) are occurring rapidly around the globe, particularly in developing island nations. We use the lens of the United Nations’ Sustainable Development Goals (SDG) to determine potential policies to address LULCC due to increasing population, suburbia, and rubber plantations in Semarang, Indonesia between 2006 and 2015. Using remote sensing, overlay analysis, optimized hot spot analysis, expert validation, and Continuous Change Detection and Classification, we found that there was a spread of urban landscapes towards the southern and western portions of Semarang that had previously been occupied by forests, plantations, agriculture, and aquaculture. We also witnessed a transition in farming from agriculture to rubber plantations, a cash crop. The implications of this study show that these geospatial analyses and big data can be used to characterize the SDGs, the complex interplay of these goals, and potentially alleviate some of the conflicts between disparate SDGs. We recommend certain policies that can assist in preserving the terrestrial ecosystem of Semarang (SDG 15) while creating a sustainable city (SDG 11, SDG 9) and providing sufficient work for individuals (SDG 1) in a growing economy (SDG 8) while simultaneously maintaining a sufficient food supply (SDG 2). 

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5. Inside the flux footprint: The role of organized land cover heterogeneity on the dynamics of observed land-atmosphere exchange fluxes

   https://doi.org/10.3389/frwa.2023.1033973  

   Hernandez Rodriguez, Leila C.; Goodwell, Allison E.; Kumar, Praveen (March 2023, Frontiers in Water)

   Eddy covariance measurements quantify the magnitude and temporal variability of land-atmosphere exchanges of water, heat, and carbon dioxide (CO 2 ) among others. However, they also carry information regarding the influence of spatial heterogeneity within the flux footprint, the temporally dynamic source/sink area that contributes to the measured fluxes. A 25 m tall eddy covariance flux tower in Central Illinois, USA, a region where drastic seasonal land cover changes from intensive agriculture of maize and soybean occur, provides a unique setting to explore how the organized heterogeneity of row crop agriculture contributes to observations of land-atmosphere exchange. We characterize the effects of this heterogeneity on latent heat ( LE ), sensible heat ( H ), and CO 2 fluxes ( F c ) using a combined flux footprint and eco-hydrological modeling approach. We estimate the relative contribution of each crop type resulting from the structured spatial organization of the land cover to the observed fluxes from April 2016 to April 2019. We present the concept of a fetch rose, which represents the frequency of the location and length of the prevalent upwind distance contributing to the observations. The combined action of hydroclimatological drivers and land cover heterogeneity within the dynamic flux footprint explain interannual flux variations. We find that smaller flux footprints associated with unstable conditions are more likely to be dominated by a single crop type, but both crops typically influence any given flux measurement. Meanwhile, our ecohydrological modeling suggests that land cover heterogeneity leads to a greater than 10% difference in flux magnitudes for most time windows relative to an assumption of equally distributed crop types. This study shows how the observed flux magnitudes and variability depend on the organized land cover heterogeneity and is extensible to other intensively managed or otherwise heterogeneous landscapes. 

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