Area Monitoring Research Articles

Multidrug Resistance Tuberculosis in the Context of Co-Infection in Ethiopia: A Systematic Review and Meta-Analysis

The rise of multidrug-resistant tuberculosis (MDR-TB) remains a critical public health challenge, particularly in developing countries like Ethiopia. This systematic review and meta-analysis aimed to estimate the pooled prevalence of MDR-TB with co-infections and assess its effects among different co-infections in Ethiopia. The systematic review and meta-analysis were conducted from August to October 2024. The study adhered to PRISMA guidelines and utilized various academic databases including PubMed, Web of Science and Science Direct to identify relevant articles. To check for publication bias and small study effects, a funnel plot and Egger’s test were employed. The statistical analysis was performed with R software version 4.4.1. From an original pool of 6,461 papers, 15 studies published between 2014 and 2024 were considered after applying certain inclusion and exclusion criteria. The analysis revealed an overall pooled prevalence of MDR-TB in the context of co-infections at 20% (95% CI: 14.0–26.0). Notably, the prevalence was higher among individuals with HIV co-infection at 23.2% (95% CI: 18.3–28.0), while it was lower in those with diabetes co-infection at 10% (95% CI: 3.0-17.3). The study found significant heterogeneity among the reported prevalence rates (I² = 94.93%, p < 0.001). These findings highlight the complex interplay between MDR-TB and other co-infections, posing significant challenges for clinical management and public health in Ethiopia. To enhance health outcomes and curb the spread of MDR-TB, government and public health authorities must implement targeted interventions, including monitoring and treatment programs in high-prevalence areas.

The Role of Remote Sensing and GIS in Sustainable Development and National Resilience

Purpose: This study explores the critical role of Remote Sensing (RS) and Geographic Information Systems (GIS) in supporting Sustainable Development Goals (SDGs) and strengthening national resilience. It aims to highlight the originality and significance of RS and GIS as strategic tools for spatial data collection, analysis, and visualization. Study Design/Methodology/Approach: This research employs a qualitative methodology based on a literature review and case studies. The study evaluates the application of RS and GIS in various sectors, including disaster mitigation, environmental preservation, and resource optimization. Findings: The findings indicate that RS and GIS significantly contribute to SDGs by facilitating actions on climate change, biodiversity conservation, equitable resource distribution, and poverty alleviation. Additionally, RS and GIS strengthen national resilience through economic optimization, ecological disaster mitigation, conflict resolution, and strategic area monitoring. Originality/Value: This study underscores the integrative role of RS and GIS in aligning SDGs and national resilience objectives, offering practical implications for decision-making across multiple sectors. The results provide a foundation for policymakers and practitioners to leverage RS and GIS for holistic and sustainable development.

Assessing survey design changes of long-term fishery-independent groundfish trawl surveys in the Gulf of Mexico

Long-term fishery-independent surveys provide a wealth of information on fisheries stocks that inform stock assessments. One of the strengths of these surveys is that the design and methods are consistent through time. However, maintaining an unchanged time series can pose several potential issues as management needs change resulting in the need to alter either the survey design or its spatial extent. In the United States Gulf of Mexico, bottom trawl surveys targeting groundfish and shrimp (hereafter, groundfish surveys) have been conducted since the 1950s, with standardized surveys beginning in 1972. The resulting data can provide a great deal of information on commercially and recreationally important species. However, many of the alterations to the survey design have been buried in gray literature or otherwise poorly noted. The history of these surveys is discussed, along with the rationale behind these changes and the impacts they had on stock assessments in the region. Starting in 1981, the Southeast Area Monitoring and Assessment Program began groundfish surveys, continuing the time series. Over time, the survey’s spatial extent and design have been altered to meet changing management needs. Delta-lognormal models are used to draw inferences concerning the effects of the survey design change on the relative abundance and their associated coefficients of variation for several commercially and recreationally important species. The expansion of the surveys across the Gulf of Mexico is examined in relation to stock assessments. Overall, the design changes and spatial expansion have been beneficial from a stock assessment standpoint, resulting in an increase in the number of indices used for single-species stock assessments and the utility of survey data in support of ecosystem modeling efforts. Finally, a discussion around the lesson learned (i.e., the critical need for overlap of survey designs), emphasizing the potential impacts of these changes on the overall time series concerning stock assessments, is presented.

Urban green spaces as regulators of thermal comfort for different age groups in the context of heat waves

ABSTRACT This study aims to bolster the resilience of cities in the face of heat wave disasters by considering climate regulation and residents’ thermal sensation. We chose a humid-hot climatic region for the experiment and used blend of objective climatic measurements and subjective questionnaires to analyze the thermal environment characteristics of different spatial forms of green spaces and the thermal sensation of people from different socio-demographic groups. The results demonstrate that (1) waterfront vegetation (semi-enclosed spaces) and mixed vegetation area (semi-open spaces) are the most effective in regulating urban microclimate effects and improving subjective thermal experience, (2) the subjective thermal sensation ranges reported by individuals consistently exceed the corresponding grading criteria under high heat pressure defined by the Wet Bulb Globe Temperature (WBGT), and (3) both elders (>65 years old) and children (<14 years old) exhibit weaker thermal sensitivity and a gentler response to temperature changes than people in other age groups. These results imply that green spaces with different structures and compositions have different effects on people’s thermal perception and people from different age groups respond heat waves differently. Consequently, it is necessary to implement real-time temperature monitoring in areas where these individuals gather, and to strengthen the early warning systems and guidance for their outdoor activities. These findings provide a reference for optimizing urban spatial forms and developing integrated ‘Heat-Health Action Plan’ in humid-hot regions around the world.

Fusion of numerical meteorological data to mitigate residual tropospheric error in GNSS RTK for large bridge monitoring in mountainous areas

Fusion of numerical meteorological data to mitigate residual tropospheric error in GNSS RTK for large bridge monitoring in mountainous areas

Vibration-based gear wear area monitoring for quantitative assessment of wear severity under variable speed conditions

Vibration-based gear wear area monitoring for quantitative assessment of wear severity under variable speed conditions

Integration of Primary Health Care Services at Puskesmas in East Pekalongan Sub-district with a Formative Evaluation Approach

Primary care integration (ILP) is a pillar of health transformation to strengthen primary health care by bringing health services closer to the village level, targeting the entire life cycle, and strengthening local area monitoring (PWS). The purpose of the study was to analyze the implementation of Primary Care Integration (ILP) at Puskesmas in East Pekalongan District. The research method used qualitative analysis with a case study approach. Data collection was carried out at the Puskesmas in the East Pekalongan sub-district of Pekalongan City. Data collection with in-depth interviews involving 20 informants and data processing using thematic analysis with CIPP variables. This study found that in the context aspect, the goal has not been achieved optimally to bring health services closer and expand due to the lack of cadres, influential factors are family support and officer involvement and infrastructure, targeting the entire life cycle. In the input aspect, human resources are not sufficient, especially medical personnel and cadres for many targets, funding is insufficient for activities, infrastructure for tools is sufficient but the place of implementation is still not large enough and health test kits are still lacking. In the process aspect, planning has gone well, organizing is well structured, it's just that the number of cadres and health workers is still lacking to serve all life cycles, for Pekalsanaan it is still running as much as possible and for evaluation it still refers to the old mechanism and for evaluations carried out regularly every month. In the product aspect, the results of activities can increase the level of visits and the community becomes more enthusiastic in participating in the ILP posyandu.

Monitoring benthic plumes, sediment redeposition and seafloor imprints caused by deep-sea polymetallic nodule mining

A deep-sea (4500 m) trial of a pre-prototype polymetallic nodule collector with independent scientific monitoring revealed that a gravity current formed behind the collector channeled through steeper seafloor sections and traveled 500 m downslope. The prevailing bottom currents dominated sediment dispersion up to the end of the monitoring area at 4.5 km distance. The maximum suspended particle concentration recorded 50 m from mining lanes was up to four orders of magnitude higher than ambient values but decreased rapidly with increasing time, distance, and altitude. Most of the plume remained close to the seafloor, with the highest concentrations at 1 m monitoring altitude and reaching background concentrations at 50 m. Rapid particle flocculation was followed by fast and substantial sediment redeposition. A mm-scale photogrammetric seafloor reconstruction allowed quantitative estimates of the thickness of redeposited sediment next to mining lanes of ≈ 3 cm and a minimum erosional depth of 5 cm.

Struktur Komunitas Teripang (Holothuroidea) di Pantai Elak-Elak Sekotong Lombok Barat

Sea cucumbers are marine animals of the holothuroidea class (phylum Echinoderms), which are natural decomposers and play an important role in maintaining aquatic ecosystems. Sea cucumbers can clean up the remnants of organic matter on the seafloor, so that they can maintain the balance of nutrients in an ecosystem. This study aims to determine the species composition and structure of sea cucumber communities, including: abundance, diversity index, uniformity index, and dominance index, as well as to determine the influence of environmental parameters on the abundance of sea cucumber species. Sea cucumber data collection was carried out using the transect belt method, with a transect length of 100 m and a width of 1 meter to the left and 1 meter to the right, respectively, so that a total monitoring area of 200 m2 was obtained. At station 1, the width of the beach is less than 100 meters, so the area of the observation area is adjusted to these conditions. 6 species of sea cucumbers were found, namely: Synapta maculata, Opheodesoma grisea, Chirota smirnovi, Holothuria leucospilota, Actinopyga alboniger, Holothuria scabra. The total abundance value of sea cucumbers found in the waters of Elak-Elak Beach ranges from 164-172 ind/ha. S. maculata is the species with the largest abundance value, ranging from 500-883 ind/ha, while the species with the smallest abundance value are A. alboniger and H. scabra, at 17 ind/ha. Environmental parameters affect the abundance of sea cucumbers, where more sea cucumbers are found in habitats with muddy sand substrates and seagrass vegetation.

Identification and suppression of low-frequency oscillations using PMU measurements based power system model in smart grid

Low-frequency oscillations (LFO) are inherent to large interconnected power systems. Timely detection and mitigation of these oscillations is essential to maintain reliable power system operation. This paper presents a methodology to identify and mitigate low-frequency oscillations ( forced and inter-area) using a wide area monitoring system (WAMS) based power system model utilizing phasor measurement units (PMUs). These models accurately identify the behavior and location of generators contributing to low-frequency oscillations in real-time and hence can efficiently improve the performance of WADC to mitigate them. The proportional resonant power system stabilizer (PR-PSS) is utilized to suppress these LFOs, as determined from the Wide Area Power System Model. The damping structure based on PR-PSS with measurements from WAMS effectively suppresses both forced and inter-area oscillation modes.

Spatial Evaluation of Salurnis marginella Occurrence According to Climate Change Using Multiple Species Distribution Models

Salurnis marginella causes agricultural and forest damage in various Asian environments. However, considering the environmental adaptability of pests and the active international trade, it may invade other regions in the future. As the damage to local communities caused by pests becomes difficult to control after invasion, it is essential to establish measures to minimize losses through pre-emptive monitoring and identification of high-risk areas, which can be achieved through model-based predictions. The aim of this study was to evaluate the potential distribution of S. marginella by developing multiple species distribution modeling (SDM) algorithms. Specifically, we developed the CLIMEX model and three machine learning-based models (MaxEnt, random forest, and multi-layer perceptron), integrated them to conservatively assess pest occurrence under current and future climates, and overlaid the host distribution with climatically suitable areas of S. marginella to identify high-risk areas vulnerable to the spread and invasion of the pest. The developed model, demonstrating a true skill statistic &gt;0.8, predicted the potential continuous distribution of the species across the southeastern United States, South America, and Central Africa. This distribution currently covers approximately 9.53% of the global land area; however, the model predicted this distribution would decrease to 6.85%. Possible areas of spread were identified in Asia and the southwestern United States, considering the host distribution. This study provides data for the proactive monitoring of pests by identifying areas where S. marginella can spread.

Concentration of traffic air pollutants and influencing metrological factors in Hawassa City roadways, Ethiopia

IntroductionThe traffic air pollution caused by transportation is a growing global problem that contributes to millions of deaths each year. Despite its importance, information on pollutant concentration is limited in many developing cities, especially in Ethiopia. This study aimed to determine the concentration levels and spatial and temporal variations of traffic air pollutants in Hawassa and to investigate the influence of metrological parameters on the concentration of traffic air pollutants.MethodsA real-time monitoring system of Aero-Qual Series 300/500 was used to monitor pollutants, and 24 monitoring sites were included on both heavy and low-traffic volume roads. The study monitored morning and afternoon times over 24 days to comprehensively characterize the temporal variations.ResultsThe results showed that the mean PM2.5 concentration on heavy- and low-traffic volume roads was 161.6 ± 26.1 μg/m3 and 95 ± 14.2 μg/m3, respectively, whereas the PM10 concentration was 178.7 ± 20.3 μg/ m3 and 102.3 ± 17.6 μg/m3, respectively. Similarly, the mean NO2 concentrations on roads with heavy and low traffic volumes were 86.4 ± 14.4 μg/m3 and 61.7 ± 14.2 μg/m3, respectively. Significantly higher, concentrations were recorded on traffic light roads, followed by main asphalt roads, for both types of traffic air pollutants. The ratio of PM2.5/PM10 was higher (0.924), in which the pollution sources attributed to anthropogenic sources. Kendall’s tau-b correlation analysis suggested that Meteorological parameters (temperature and relative humidity) were positively correlated with traffic air pollutants. Likewise, stepwise multiple linear regression analysis confirms that the concentrations of traffic air pollutants had a positive relationship with metrological parameters.ImplicationsThe findings of this study therefore showed the need for regular air quality monitoring of the urban areas to copping out the adverse public health impacts. And, it highlighted an urgent need for long-term monitoring of traffic air pollution and the development of emission control programs that can be readily implemented to decrease the emissions from anthropogenic sources. Also, it brings a sense of collaboration among stakeholders to tackle the effects of air pollution by providing an inclusive and sustainable development agenda for Hawassa.

Investigating the Impact of Spatiotemporal Variations in Water Surface Optical Properties on Satellite-Derived Bathymetry Estimates in the Eastern Mediterranean

Bathymetric data are crucial for benthic monitoring in coastal areas but are traditionally obtained through costly and geographically limited acoustic methods. This study uses satellite-derived bathymetry (SDB) in the Eastern Mediterranean, focusing on the Cretan Sea in Greece. It explores how variations in water surface optical properties affect SDB models over four years (2019–2022), using Sentinel-2 satellite data. The research covers two areas with contrasting features: the Chania Gulf and the open waters around Chrissi Island. Three methodologies were tested: the band-ratio method, the linear-logarithmic method, and an inherent optical properties linear model. Significant spatiotemporal variations in the SDB models were found, due to seasonal changes in water surface properties, such as temperature and suspended organic materials. Linear optical properties-based methods performed best, achieving a mean RMSE close to 1 m, slightly outperforming the ratio-based method. The logarithmic method was less effective, with RMSE values ranging from 1.3 to 1.5 m. A preliminary Kalman filter (KF) analysis increased RMSE to the decimeter level. This study demonstrates the impact of water surface optical properties on SDB models. It highlights the value of SDB for cost-effective, high-resolution coastal mapping in complex coastlines like those in Greece.

Managing soil to support soil biodiversity in protected areas agroecosystems: a comparison between arable lands, olive groves, and vineyards in the Conero Park (Italy).

Sustainable soil management is essential to conserve soil biodiversity and its provision of vital ecosystem services. The EU Biodiversity Strategy for 2030 highlights the key role of organic farming and land protection in halting biodiversity loss, including edaphic biodiversity. To assess the effectiveness of the proposed measures, a 1-year study was conducted in spring 2022 to determine the soil quality of three organically managed agroecosystems and four sites for each: arable lands, olive groves, and vineyards in the Conero Park, using the arthropod-based Biological Soil Quality Index (QBS-ar) and also considering soil chemical-physical characteristics. Soil microarthropods are sensitive indicators of the impact of agricultural practices on soil quality. Given the diversity of the agronomic practices applied in these agroecosystems, the study aimed to compare the soil quality and identify the system with the least impact on soil biodiversity conservation, with the goal of laying the basis for identifying soil quality benchmarks within each system to be used in monitoring activities in land protected areas. Results showed that organic farming combined with land protection had a positive impact on soil quality. The overall soil quality was excellent, with the highest levels found in arable lands. This is consistent with the intermediate disturbance hypothesis (IDH), which states that slightly disturbed habitats (i.e., arable land with minimum tillage) tend to have higher organism diversity than stable ones. The composition of microarthropod communities in arable land differed from those in stable arboreal crops. Olive groves showed a higher abundance and diversity of microarthropods compared to vineyards, which showed lower values. Promoting the use of QBS-ar, identifying benchmarks for prevalent agroecosystems, and ensuring continuous monitoring of protected areas are thus crucial issues.

An Updated Environmental Resistance Model for Predicting the Spread of Invasive Species

ABSTRACTAimPredictive models on invasive species spread can assist in identifying large‐scale invasion risk. Environmental resistance (ER) models, which predict spread based on ecological similarity to already‐invaded communities, offer one approach. However, gaps remain in understanding how different ER measurements perform across different taxa and how they can be integrated with future global change. Here, we aim to discern the primary drivers of invasion spread by comparing different ER models and then use the best models to forecast future invasion dynamics.LocationEastern US.Taxa1873 invasive plants and animals.MethodsWe developed different ER measurements, including biotic similarities among native plants in their species and phylogenetic assemblages, and functional traits, and abiotic similarities in climate, soil, and human disturbances. We obtained the best ER model for each invasive species to evaluate their potential invasion extents; and we further predicted their future range shifts under climate change.ResultsNative plant similarities provided the best proxy measure of ER for both invasive plants and animals. Invasion hotspots were identified in urban and coastal areas, and the predicted potential invasion ranges under current conditions extended from these hotspots to the neighboring areas. The invasion range for most invasives was predicted to increase under future climate change, with Arthropoda and Tracheophyta generally expanding the most among all taxa. The invasives that are predicted to expand their range in the future have already occupied larger areas than the invasives whose ranges are predicted to contract.Main ConclusionsThese results highlight the importance of maintaining diverse native communities in invasion control and raise the concern of increased invasion risk in the future. Our findings call for more efforts on invasion monitoring in areas near large cities, and increased capacity for early detection and rapid response to prevent the current invasives spreading more widely.

Passive acoustic monitoring for assessing forest bird distribution and identifying conservationally important areas in a subtropical forest landscape

AbstractPassive acoustic monitoring (PAM) has recently been developed and used for long‐term and/or large spatial scale surveys. PAM is expected to be one of the most efficient methods for assessing species distribution and examining the factors affect it, helping identify important areas for biodiversity conservation and inform the management plan. In this study, we tested the feasibility of the PAM for monitoring bird species and revealed some critical points to consider in improving or developing more widely applicable PAM. We conducted PAM in the subtropical forest landscape of Amami‐Oshima Island, Japan, which harbors rich biodiversity (over 100 species), including endangered and/or endemic plants and animals. Nine endemic forest bird species were detected across recording locations. The effects of environmental factors on the four bird species were analyzed, excluding the five species that were commonly detected and did not require occupancy modeling. Different environmental factors influenced the occupancy probability of the four species examined according to their habitat preferences, which is consistent with previous studies. Our results suggest that the combination of PAM and occupancy model enables us to identify the bird's spatial occupancy pattern, associated environmental factors, and the important areas that should be protected for conservation. PAM is a relatively low‐cost and non‐invasive method that can be applied in various monitoring of biodiversity conservation areas.

Monthly drought monitoring of the surface water area of Sawa Lake, Iraq during 2016-2022 using remote sensing data

Drought is a common phenomenon in Iraq's environment, and the country has experienced severe drought events exacerbated by the threat of climate change (low rainfall and high temperatures) over the past two decades. Iraq is located in a semi-arid region whose water resources have been restricted and mostly shared with its neighbours. To investigate the effect of drought on the surface water area of Sawa lake, we analysed 52 Sentinel-2 images from May 2016 to July 2022 using an open-source SNAP toolbox to map the boundary of the surface-water body of the lake. The results indicate that the surface water area of Sawa lake has de-creased significantly over the last six years with the most extreme decline beginning in May 2021, when the area of the lake lost about 51% of its initial size (May 2016). By March 2022, the lake had disappeared and about 96% of the water's surface area had been lost. To better understand the potential causes of droughts, further analysis has been conducted on the effects of precipitation and human activities (vegetation cover and Al-Samawah saltpan for salt production) on the lake. Investigations revealed that the rapid expansion of agricultural areas around the lake by 254% and the increase in salt production from the Al-Samawah saltpan by about 121% are among the direct causes of the drought. In addition, the results of the statistical test anal-ysis between the estimated surface water area of Sawa lake and human activities were significant at a 95% level of confidence. The findings of this study can assist decision-makers to understand the interaction be-tween human activities and the lake's environment to design a strategic plan for lake recovery and a sustain-able water resource management system in southern Iraq.

A review of techniques for measurement of forces and neutral temperatures in railway track

Track failures in the form of thermally induced buckling events or rail breakages on continuously welded rails (CWRs) have long posed challenges for the rail industry. These issues arise because CWRs cannot freely expand or contract as rail temperatures fluctuate during operation, resulting in compressive or tensile stresses. As temperature variations increase, these stresses can lead to rail buckling under compression or separation under tension. Buckling, in particular, poses a serious threat, as it is often associated with derailments, carrying substantial social (rail safety, public perception) and economic (track downtime, damage to freight, rolling stock, and infrastructure) consequences. For this reason, understanding the thermal stress state or neutral rail temperature (NRT) of installed track is critical for rail network owners and operators. This knowledge enables more precise planning of maintenance, targeted rail replacement, and monitoring of high-risk areas. Consequently, there is growing demand for in-situ, non-destructive methods to measure NRT. This paper reviews existing methods for measuring NRT, encompassing approaches developed from the 1960s to the present. Each method is critically evaluated, with the findings summarized in a table that outlines their operational principles, limitations, reported accuracy, and current technology readiness level.

An Evaluation of Eco-Environmental Quality Based on the Fused Remote Sensing Ecological Index (FRSEI) in the Jinjie Coal Mine Area, Northwest China

This study focused on the Jinjie mining area by addressing the severe resource and environmental issues arising from excessive coal mining in Shenmu County, Northwest China. Multi-source remote sensing data from GF-1 and Landsat 8 OLI were utilized in this study. Specifically, the fused remote sensing ecological index (FRSEI) was constructed to conduct a detailed evaluation and analysis of the eco-environmental quality in the mining area from 2013 to 2023. The results indicated that the overall eco-environmental quality of the Jinjie mining area exhibited a trend of initial improvement, followed by degradation, and then improvement again over the decade. The eco-environmental quality of the mine pits and their surrounding areas was significantly lower than the overall level, confirming the destructive impact of coal mining on the eco-environment. Meanwhile, as the study area, Shenmu County is actively utilizing coal mining subsidence areas to develop the photovoltaic power generation industry, aiming to achieve green and low-carbon transformation. Although the construction of photovoltaic power plants initially led to the degradation of the condition of vegetation and the FRSEI, both gradually improved after the plants were operational. Furthermore, by comparing the FRSEI with the remote sensing ecological index (RSEI) calculated solely using Landsat 8 OLI data, we found a high degree of similarity between the two, thereby validating the stability and accuracy of the FRSEI. This study not only provides high-precision data support for eco-environmental monitoring in mining areas but also highlights the potential of multi-source remote sensing data fusion technology in improving monitoring accuracy, further providing a scientific basis for formulating sustainable development strategies specifically for the eco-environment in mining areas.

Comprehensive Monitoring of Construction Spoil Disposal Areas in High-Speed Railways Utilizing Integrated 3S Techniques

High-speed railways are critical infrastructure in many countries, but their construction generates substantial spoil, particularly in mountainous regions dominated by tunnels and slopes, necessitating the establishment and monitoring of spoil disposal areas. Inadequate monitoring of spoil disposal areas can lead to significant environmental issues, including soil erosion and geological hazards such as landslides and debris flows, while also hindering the recycling and reuse of construction spoil, thereby impeding the achievement of circular economy and sustainable development goals for high-speed railways. Although the potential of geographic information systems, remote sensing, and global positioning systems in waste monitoring is increasingly recognized, there remains a critical research gap in their application to spoil disposal areas monitoring within high-speed railway projects. This study proposes an innovative framework integrating geographic information systems, remote sensing, and global positioning systems for monitoring spoil disposal areas during high-speed railway construction across three key scenarios: identification of disturbance boundaries (scenario 1), extraction of soil and water conservation measures (scenario 2), and estimation of spoil volume changes (scenario 3). In scenario 1, disturbance boundaries were identified using Gaofen-1 satellite data through processes such as imagery fusion, unsupervised classification, and spatial analysis. In scenario 2, unmanned aerial vehicle data were employed to extract soil and water conservation measures via visual interpretation and overlay analysis. In scenario 3, Sentinel-1 data were used to analyze elevation changes through the differential interferometric synthetic aperture radar method, followed by the estimation of spoil volume changes. The effectiveness of this integrated framework was validated through a case study. The results demonstrate that the framework can accurately delineate disturbance boundaries, efficiently extract soil and water conservation measures, and estimate dynamic changes in spoil volume with an acceptable error margin (15.5%). These findings highlight the framework’s capability to enhance monitoring accuracy and efficiency. By integrating multi-source data, this framework provides robust support for sustainable resource management, reduces the environmental impact, and advances circular economy practices. This study contributes to the efficient utilization of construction spoil and the sustainable development of high-speed railway projects.