Spatial Analysis Research Articles

Analysis of Urban Spatial Morphology in Harbin: A Study Based on Building Characteristics and Driving Factors

With the advancement of urbanization, the complexity and diversity of urban spatial forms have become increasingly prominent, profoundly and widely affecting aspects such as urban spatial layout and planning, as well as residents’ quality of life. This paper focuses on the buildings in Harbin City, comprehensively reflecting the spatial form of Harbin through multiple dimensions including building height, volume, and area. This research precisely quantifies three key indicators of urban buildings: building coverage, building expandability, and building staggeredness. Subsequently, these indicators are intertwined with the main driving factors of urban development (including economic development and resident population) to conduct a multidimensional spatial form analysis. The results indicate that the diversity of Harbin’s urban spatial form is the result of the interplay of multiple factors, including economic and demographic influences. These analytical outcomes not only reveal the evolution mechanism of Harbin’s current urban spatial form but also provide data support and theoretical basis for future urban planning and management.

Spatiotemporal Evolution and Driving Factors of Land Use Carbon Emissions in Jiangxi Province, China

Analyzing the spatiotemporal changes and influencing factors of carbon emissions generated by land use is of great importance for improving land use structure and promoting regional low-carbon economic development. This study, based on remote sensing and statistical yearbook data from 1995 to 2020, calculated the carbon emissions from land use in Jiangxi Province, China. Multiple spatial analysis methods and the logarithmic mean Divisia index were used to elucidate the spatiotemporal evolution and driving factors of carbon emissions, and the findings revealed the following: (1) The spatiotemporal changes in land use in Jiangxi Province during 1995–2020 were substantial as forest land accounted for 65% of the entire land area, while construction land increased by 98.1%. Cultivated land decreased the most, followed by forest land. (2) There was a fourfold rise in carbon emissions in Jiangxi Province, driven primarily by construction land, and northern areas produced higher carbon emissions compared with central and southern regions. Forest land was the main carbon sink. (3) Economic development (257.36%) and the impact of the proportion of construction land (211.31%) were the primary factors contributing to the increase in carbon emissions from land use, while other factors had inhibitory effects. This study transformed the macroscale low-carbon development strategy of cities into targeted local policies, and the research theories and methods adopted could provide scientific reference for other regions in urgent need of carbon reduction worldwide.

Spatiotemporal Analysis of Complex Emission Dynamics in Port Areas Using High-Density Air Sensor Network.

Cargo terminals, as pivotal hubs of mechanical activities, maritime shipping, and land transportation, are significant sources of air pollutants, exhibiting considerable spatiotemporal heterogeneity due to the complex and irregular nature of emissions. This study employed a high-density air sensor network with 17 sites across four functional zones in two Shanghai cargo terminals to monitor NO and NO2 concentrations with high spatiotemporal resolution post sensor data validation against regulatory monitoring stations. Notably, NO and NO2 concentrations within the terminal surged during the night, peaking at 06:00 h, likely due to local regulations on heavy-duty diesel trucks. Spatial analysis revealed the highest NO concentrations in the core operational areas and adjacent roads, with significantly lower levels in the outer ring, indicating strong emission sources and limited dispersion. Employing the lowest percentile method for baseline extraction from high-resolution data, this study identified local emissions as the primary source of NO, constituting over 80% of total emissions. Elevated background concentrations of NO2 suggested a gradual oxidation of NO into NO2, with local emissions contributing to 32-70% of the total NO2 concentration. These findings provide valuable insights into the NO and NO2 emission characteristics across different terminal areas, aiding decision-makers in developing targeted emission control policies.

Spatial Big Data and Analysis Strategies Supporting Geographic Information System for Transportation (GIS-T) in Conceptual Design, Modelling, and Decision-making: A Review

Abstract. Transportation is a key component in urban design for cities’ efficiency and residents’ life quality, and GIS has the capability of handling data management, model design, and scientific decision-making for transportation studies. This article reviews how spatial big data and analysis strategies help GIS-T studies from the phases of conceptual design, modelling, and decision-making. In this research, we firstly summarized categorizes of data objects and relevant information for real-world issues from transportation applications in the conceptual design phase. In the modelling phase, optimization strategies for transport planning and accessibility measures through network data were also summarized. Finally, we reviewed spatial analysis methods in supporting transport decision-making, and how spatial methods take advantage of geography features of transport variables in previous studies. Our research primarily focuses on geography research with transportation topics as applications, and this work can help transport experts to have a better understanding of GIS values for transportation modelling and planning.

Site Selection of Large Shopping Malls in Wanbailin District of Taiyuan City

The construction and site selection of shopping malls are directly related to their commercial operation effectiveness and market competitiveness. Some scholars have conducted extensive research in this field, particularly achieving notable results in terms of influencing factors, methodologies, and technological applications for site selection, yet there are still some deficiencies. Traditional site selection methods primarily rely on qualitative analysis and empirical judgment. However, with technological advancements, Geographic Information System technology has gradually been applied to shopping mall site selection. GIS technology enables the integration of multiple data sources, spatial analysis, and visualization, providing a scientific basis for site selection decisions. This article utilizes ArcGIS software to construct an application model for shopping mall site selection in Wanbailin District. Through spatial analysis, eligible areas are identified, achieving a scientific and visual approach to site selection. By considering the main factors affecting the location of large shopping malls in Wanbailin District and using ArcGIS as the basic platform, an application model is built to find the optimal location for building shopping malls. The results show that introducing GIS into mall location planning improves efficiency and accuracy while providing a reliable basis for scientific location.

Self-reported prevalence of tuberculosis: unveiling spatial representation in the districts of Tamil Nadu.

The objective of the current study was to estimate the self-reported individual-level crude prevalence and cluster-level adjusted prevalence of TB for the districts of Tamil Nadu and to understand the spatial distribution of TB cases through spatial autocorrelation and hotspot analysis. National Family Health Survey (NFHS) data, gathered during 2014-2015 (NFHS-4) and 2019-2021 (NFHS-5), were used in the current study to estimate district-wise, individual-level crude and cluster-level adjusted TB prevalence per 100 000 population in Tamil Nadu. This was illustrated with the help of spatial geographic representation for various districts of Tamil Nadu using SPSS and QGIS software. The spatial autocorrelation and hotspot analysis were performed using Geoda software. The overall self-reported individual-level crude prevalence of TB was 337 (95% CI 302 to 375) and 169 (95% CI 144 to 197) per 100 000 population, whereas the cluster-level adjusted prevalence of TB was 356 (95% CI 311 to 405) and 184 (95% CI 154 to 219) per 100 000 population in NFHS-4 and NFHS-5, respectively. This study highlights those geographical areas with high rates of TB prevalence. This information would be useful for the state and district programme managers to identify areas of high TB prevalence where interventions can be focused.

The Concept of Levels of Detail for 3D Niche Models in CityGML

Abstract. Buddhist niches in grottoes can be represented in three-dimensional (3D) for their detailed geometries on surfaces by using triangular meshes generated from point clouds. However, not all applications require 3D models with high geometric detail. The mesh models of niches have drawbacks such as large data volumes, lack of semantic information, and absence of spatial relationships between structural components and members within niches. Those limitations make mesh models suitable only for visualization and challenging to use directly in tasks like spatial analysis, simulation experiments, mechanical analysis, and disease investigation. To address this problem, this study defines four Levels of Detail (LoDs) for Buddhist niches, ranging from LoD0 to LoD3, drawing on the concept of LoDs for urban buildings in CityGML 3.0. As the LoD level increases, 3D models contain more detailed geometries, including spatial points, bounding boxes, niche structural components, and component members. Those 3D models at different LoDs can represent niches with varying degrees of abstraction, making them suitable for different applications and guiding the production of standardized 3D semantic models. To validate the feasibility of the LoDs definition for Buddha niches, this paper reconstructs 3D models of niches at different LoDs based on high-precision mesh models. Finally, a comparison is made between the original mesh model and models at different LoDs in terms of data size and potential application scenarios.

An Information Gradient Approach to Optimizing Traffic Sensor Placement in Statewide Networks

Traffic sensors are vital to the development and operation of Intelligent Transportation Systems, providing essential data for traffic monitoring, management, and transportation infrastructure planning. However, optimizing the placement of these sensors, particularly across large and complex statewide highway networks, remains a challenging task. In this research, we presented a novel search algorithm designed to address this challenge by leveraging information gradients from K-nearest neighbors within an embedding space. Our method enabled more informed and strategic sensor placement under budget and resource constraints, enhancing overall network coverage and data quality. Additionally, we incorporated spatial kriging analysis, harnessing spatial correlations of existing sensors to refine and reduce the search space. Our proposed approach was tested against the widely used Genetic Algorithm, demonstrating superior efficiency in terms of convergence time and producing more effective solutions with reduced information loss.

Changes in hydraulic and physico-water parameters of surface waters under the influence of anthropogenic activities in the Western Carpathians

To evaluate the quality of watercourses in the Western part of Carpathians from a hydro-chemical perspective, a systematic approach is required. This involves gradually excluding factors that contribute to the washing, mixing, and transportation of contaminants in the watercourse pathway. The model that considers spatial dependencies by autoregression was implemented in this study to determine the correlation between hydrodynamic and physico-chemical characteristics of waters at surface in different groups and forms of catchment use. The surface water at forested areas had the maximum average shear stress of 0.178 N∙m−2. The watercourse at sustained grassland had the maximum average Reynolds number (Re) of 23,654 and the minimum number of 0.426 at arable lands. Spatial autoregression analysis revealed space-time relations in various measurement points. When constructing the space-physical model, it is important to consider the influence of hydraulic characteristic parameters on the generation of physicochemical indicators in the flysch basin. Specifically, it may be beneficial to take into account the turbulent diffusion coefficient. The autoregression analysis demonstrated that for the ions P-PO43− and K+ in surface water on cropland and for total iron and the cation K+ ion grassland (p < 0.05), the turbulent diffusion coefficient proved to be of great importance. The study did not identify any physicochemical dependency for woodland surface waters. The findings can be utilised to create an erosion model that considers the contribution of material supply in a catchment area, specifically from weathered Carpathian flysch or surface runoff, to the alimentation of alluvial deposits.

Multidimensional analysis of matched primary and recurrent glioblastoma identifies contributors to tumor recurrence influencing time to relapse.

Glioblastoma (GBM) is a lethal brain tumor without effective treatment options. This study aimed to characterize longitudinal tumor changes in order to find potentially actionable targets to prevent GBM relapse. We extracted RNA and proteins from fresh frozen tumor samples from patient-matched IDHwt WHO grade 4 primary (pGBM) and recurrent (rGBM) tumors for transcriptomics and proteomics analysis. A tissue microarray containing paired tumor samples was processed for spatial transcriptomics analysis. Differentially expressed genes and proteins between pGBM and rGBM were involved in synapse development and myelination. By categorizing patients into short (STTR) and long (LTTR) time-to-lapse, we identified genes/proteins whose expression levels positively or negatively correlated with TTR. In rGBM, expressions of Fcγ receptors (FCGRs) and complement system genes were negatively correlated with TTR, whereas expression of genes involved in DNA methylation was positively correlated with TTR. Spatial transcriptomics of the tumor cells showed enrichment of oligodendrocytes in rGBM. Besides, we observed changes in the myeloid compartment such as a switch from quiescent to activated microglia and an enrichment in B and T cells in rGBM with STTR. Our results uncover a role for activated microglia/macrophages in GBM recurrence and suggest that interfering with these cells may hinder GBM relapse.

Effect of Aspect and Elevation on the Degree of Aggregation and the Functional Traits in Phlomis floccosa D. Don (Lamiacae) Populations

ABSTRACTPhlomis floccosa D. Don populations are distributed in different microhabitats within Al‐Akhdar mountainous landscape, in Libya. Five populations were selected for the study. Spatial relationships among individuals were investigated using the spatial point pattern analysis. Functional traits were recorded at the vegetative, flowering and fruiting stages. Seeds were collected at the dispersal stage to estimate the regeneration potential. Greater degree of aggregation was found at higher elevations on both northern and southern sides of the mountain but with different demography and traits. On the northern side, greater degree of aggregation was accompanied by absence of large adults and greater percentage of seedlings, and it was positively associated with the reproductive output, while negatively associated with the size and regeneration indices. On the southern side, greater degree of aggregation was accompanied by greater contribution of large adults and greater percentage of seedlings, and it was positively associated with the size and regeneration indices, while negatively associated with the reproductive output. On the other hand, the population in the wadi (valley) microhabitat showed coarse‐scale clumped pattern, higher values for most of the functional traits and higher contribution of seedlings but with lower facilitation offered by adults. The variations in the degree of aggregation and the functional traits trade‐offs in P. floccosa populations ensured successful survival and regeneration in the heterogeneous microhabitats. Meanwhile, stressed conditions greatly affect the survival and regeneration of the species suggesting the need for conservation measures to overcome the adverse effects of climate change.

Temporal trends, spatial and spatiotemporal clusters of cervical cancer mortality in Brazil from 2000 to 2021

Cervical cancer, despite being preventable through primary and secondary prevention strategies, remains one of the leading causes of morbidity and mortality among women in Brazil. This study aimed to analyze the temporal, spatial, and space-time patterns of cervical cancer mortality in Brazil. An ecological study was conducted using temporal, spatial, and space-time analysis techniques, using death certificates with cervical cancer as the underlying cause or associated condition among females in Brazil from 2000 to 2021. Death certificate and population data were provided by the Department of Health Informatics of the Unified Health System (DATASUS) and the Brazilian Institute of Geography and Statistics (IBGE), respectively. A total of 123,306 deaths associated with cervical cancer among women were registered during the study period. A rising trend in mortality was detected since 2014 onwards, after 14 years of decline. Particularly, an increase in mortality was observed among the younger age groups, and in the North and Northeast regions regardless of age. Heterogeneity in the spatial distribution of cervical cancer mortality was observed, with high mortality clusters around the country, but mostly concentrated in the North and Northeast regions. These findings suggest a need and an opportunity to develop efficient and effective health policies targeting those regions and groups of women at higher risk which in turn will allow for fast and significant reductions in cervical cancer mortality in Brazil.

Use of geoprocessing in the simulation of mining tailings dam rupture

The study of hypothetical dam rupture aims to understand the flow through the valley downstream of the volume released by a tailing dam rupture to seek preventive actions in the event of a real rupture. In this research, the open and free program for simulating dam ruptures, called HEC-RAS (Hydrologic Engineering Center-River Analysis System), software developed by the US Army Corps of Engineers Hydrologic Engineering Center is used for simulation dam ruptures. A hydrodynamic simulation of the rupture of dam B1, in Brumadinho, Minas Gerais, Brazil, was applied, is developed for this test area. Six simulation scenarios are defined, for the configuration of the hydrodynamic model of the valley downstream of the B1 dam, where all the input data identical besides the DTMs that are configured from a rescaling process of an original DTM obtained from a LiDAR (Light Detection and Ranging) survey, ranging the spatial resolution from 1 m to 25 m. Each of these DTMs is introduced into the simulation processes in HEC-RAS. A direct comparation with data obtained from the real rupture event is made to validate the results of these simulation scenarios. The flooded areas obtained in the model were assessed using the performance indicator F that considers the under and overestimated areas. The other results are subjected to a descriptive statistical analysis through the coefficient of variation (Cv) to verify the discrepancies between the values ​​for each scenario. Form the the results, it is concluded that the scenarios presented very similar performance, in terms of the rupture of the studied dam, with the velocity being the variable most sensitive to the spatial resolution change, without presenting a very discrepant response in relation to the other metrics analyzed.

Multi-Scenario Simulation of Land Use and Assessment of Carbon Stocks in Terrestrial Ecosystems Based on SD-PLUS-InVEST Coupled Modeling in Nanjing City

In the context of achieving the goal of carbon neutrality, exploring the changes in land demand and ecological carbon stocks under future scenarios at the urban level is important for optimizing regional ecosystem services and developing a land-use structure consistent with sustainable development strategies. We propose a framework of a coupled system dynamics (SD) model, patch generation land-use simulation (PLUS) model, and integrated valuation of ecosystem services and trade-offs (InVEST) model to dynamically simulate the spatial and temporal changes of land use and land-cover change (LUCC) and ecosystem carbon stocks under the NDS (natural development scenario), EPS (ecological protection scenario), RES (rapid expansion scenario), and HDS (high-quality development scenario) in Nanjing from 2020 to 2040. From 2005 to 2020, the expansion rate of construction land in Nanjing reached 50.76%, a large amount of ecological land shifted to construction land, and the ecological carbon stock declined dramatically. Compared with 2020, the ecosystem carbon stocks of the EPS and HDS increased by 2.4 × 106 t and 1.5 × 106 t, respectively, with a sizable ecological effect. It has been calculated that forest and cultivated land are the two largest carbon pools in Nanjing, and the conservation of both is decisive for the future carbon stock. It is necessary to focus on enhancing the carbon stock of forest ecosystems while designating differentiated carbon sink enhancement plans based on the characteristics of other land types. Fully realizing the carbon sink potential of each ecological functional area will help Nanjing achieve its carbon neutrality goal. The results of the study not only reveal the challenges of ecological conservation in Nanjing but also provide useful guidance for enhancing the carbon stock of urban terrestrial ecosystems and formulating land-use planning in line with sustainable development strategies.

Changes of blue and green water in arid inland dissipation area based on coupled surface water and groundwater model

Study regionThe Mainstream in the Tarim River Basin, Southern Xinjiang, China Study focusClimate change and human activities have significantly altered the water cycle, and water security evaluation and management are urgent. In arid and semi-arid areas, the assessment of blue and green water is particularly important. In this study, the MIKE SHE model is used to simulate the spatial and temporal changes of blue and green water resources in the mainstream of the Tarim River Basin (TRB) from 1990 to 2050 under land use and climate change conditions. The scarcity and vulnerability of blue-green water are introduced to evaluate the water security of the basin. The impacts of different land uses on blue-green water resources were also calculated according to the model zoning. New hydrological insights for the regionThe results indicate that from 1990 to 2050, blue water resources show a spatial pattern of gradual decrease from upstream to downstream. Compared to blue water, green water is dispersed more evenly over space. Future climatic scenarios will impact water security, as will changes in blue and green water security in terms of time and space. By comparing the influence of ecological water transport on the change of blue and green water before and after 2000, it was found that environmental water transport plays a certain role in improving the blue water scarcity in downstream of the TRB. The study is significant in maintaining regional water security and ecosystem stability.

A Practice of City-scale 3D Geographic Entity Representation and Application in China: The Smart Chongqing City Centre

Abstract. The Chinese photogrammetry industry is currently experiencing a significant revolution driven by digital intelligence technologies. Traditional city-scale 3D modelling, typically reconstructed from oblique photogrammetry or laser points, is facing increasing limitations in refined expression, real-time rendering, machine recognition, data sharing, and interoperability due to its large data volume and mesh structure. These limitations make it difficult to meet the substantial demands of spatial analysis, simulation, and prediction. The concept of geographic entities, which are machine-recognizable spatial data structures, is anticipated to provide a competitive solution for these challenges. This work employs 3D scene modelling and geographic knowledge graphs to construct geographic entities with semantic relationships at city-scale, addressing the limitations encountered in the application of traditional mesh/point-based 3D models. A case study in Chongqing city centre demonstrates the feasibility and effectiveness of the proposed approach and its potential applications in simulation, prediction, early warning, and feedback for urban planning and smart city management.

Spatiotemporal Analysis of Open Biomass Burning in Guangxi Province, China, from 2012 to 2023 Based on VIIRS

Open biomass burning has significant adverse effects on regional air quality, climate change, and human health. Extensive open biomass burning is detected in most regions of China, and capturing the characteristics of open biomass burning and understanding its influencing factors are important prerequisites for regulating open biomass burning. The characteristics of open biomass burning have been widely investigated at the national scale, with regional studies often focusing on northeast China, but few studies have examined regional discrepancies in spatiotemporal variations over a long timescale in Guangxi province. In this study, we used the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fire product (VNP14IMG), combined with land cover data and high-resolution remote sensing images, to extract open biomass burning (crop residue burning and forest fire) fire points in Guangxi province from 2012 to 2023. We explored the spatial density distribution and temporal variation of open biomass burning using spatial analysis methods and statistical methods, respectively. Furthermore, we analyzed the driving forces of open biomass burning in Guangxi province from natural (topography, climate, and plant schedule), policy, and social (crop production and cultural customs) perspectives. The results show that open biomass burning is concentrated in the central, eastern, and southern parts of the study area, where there are frequent agricultural activities and abundant forests. At the city level, the highest numbers of fire points were found in Baise, Yulin, Wuzhou, and Nanning. The open biomass burning fire points exhibited large annual variation, with high levels from 2013 to 2015 and a remarkable decrease from 2016 to 2020 under strict control measures; however, inconsistent enforcement led to a significant rebound in fire points from 2021 to 2023. Forest fires are the predominant type of open biomass burning in the region, with forest fires and crop residue burning accounting for 76.82% and 23.18% of the total, respectively. The peak period for crop residue burning occurs in the winter, influenced mainly by topography, planting schedules, crop production, and policies, while forest fires predominantly occur in the winter and spring, primarily influenced by topography, climate, and cultural customs. The results indicate that identifying the driving forces behind spatiotemporal variations is essential for the effective management of open biomass burning.

A geographic perspective of the association between physical activity and cardiovascular health: A need for community-level intervention

Cardiovascular diseases (CVDs) are a major cause of death globally, and minority communities are at higher risk of chronic health outcomes. A combination of lifestyle, including physical activity (PA), good nutrition, and reduced stress, can improve life expectancy. This study aimed to analyze the association between CVDs and PA among the adult population (N = 3,956) based on the World Health Organization (WHO) STEPwise Approach to Surveillance (STEPS) survey in Afghanistan. Descriptive statistics, logistic regression, and spatial analytical techniques were used to analyze the data. Based on the WHO STEPS data, the computed prevalence of CVDs, obesity, hypertension, diabetes, and high cholesterol were 7.41%, 45.57%, 34.06%, 9.51%, and 12.16%, respectively. Multivariate logistic analysis indicated that moderate work-related PA was associated with higher odds of CVDs and high cholesterol while inversely associated with obesity. Moderate leisure-related PA was positively associated with obesity. Vigorous leisure-related PA was associated with lower risks of CVDs, obesity, and high cholesterol but had a positive association with hypertension. Spatial analysis revealed a CVD hotspot in the southern region and the risk factors clustered in the northern region. These findings offer valuable insights for community and public health practitioners to design targeted interventions for reducing the burden of CVDs and risk factors in communities in developing countries.

Analysis of the spatial characteristics and driving forces of underground consumer service space in Chinese megacities based on multi-source data

Underground consumer service spaces (UCSS) offer new solutions for urban residents’ daily needs, but existing studies on their distribution and driving forces are often fragmented and overshadowed by research on other underground spaces, lacking targeted analysis. This study examines UCSS in the central urban areas of seven representative Chinese megacities. Using spatial analysis methods like kernel density estimation, multi-distance spatial clustering, and geographical detectors, the spatial characteristics and driving forces of UCSS are analyzed alongside aboveground consumer service spaces (ACSS). Results show that both ACSS and UCSS exhibit multi-centered, concentric spatial patterns, though UCSS demonstrates higher spatial aggregation. Unlike other underground public spaces (UPS), UCSS relies more on service industry agglomeration and market factors, while other UPS are more influenced by surrounding development intensity. UCSS follows the core principles of central place theory but deviates from the market-driven patterns typical of ACSS. Socioeconomic conditions and transportation infrastructure form the foundational basis for UCSS distribution, while service industry agglomeration, market dependence, and land development intensity exert more direct influence. The commercial atmosphere and existing underground space development play critical roles in UCSS distribution. Two key spatial scales for understanding UCSS distribution are the strong influence zones of shopping malls and metro stations, and high-density urban areas.

Historical expansion of tea plantations over 150years (1876-2023) in North Bengal, India.

The Camellia sinensis (L.) Kuntze agroforestry system has been a dominant driver of land transformation for over a century. However, most previous studies have not captured the dynamics of tea plantations since their inception. To address this research gap, this study investigates 150years (1876 to 2023) of tea area dynamics and two decades (2001-2022) of tree loss in the Bengal-Dooars region (Jalpaiguri and Alipurduar districts). Various data sources were employed, including Sentinel-2A imagery (10m), early twentieth century topographic maps at a 1:50,000 scale, and historical records from the British colonial period. Results revealed that the tea area expanded from 331 to 95,800ha (a 70% increase) during the study period. The 1-km grid-wise spatial analysis indicated that approximately 70% of the increase was attributed to the 60-90% and > 90% grid categories, signifying the expansion of large tea estates. Most tea gardens(TG) are sustained with trees, which can significantly contribute to carbon stock. Tree loss within and outside TG for 2001-2022 was analyzed using annual tree loss data at 30m from the Global Forest Watch (GFW) platform. Between 2001 and 2022, about 52.7% of tree loss was attributed to TG, although tea covers only 15.3% of the geographic area of the study region. Our findings highlight the historical expansion of tea plantations and their impact on natural land cover. We suggest that future studies address the mean age of TG along with tree fractions for improved carbon estimates.