Local Scale Research Articles

Diel dissolved organic matter patterns reflect spatiotemporally varying sources and transformations along an intermittent stream

AbstractStream dissolved organic matter (DOM) is a globally important carbon flux and a locally important control on stream ecosystems, and therefore understanding controls on stream DOM fluxes and dynamics is crucial at both local and global scales. However, attributing process controls is challenging because both hydrological and biological controls on DOM are integrated and may vary over time and throughout stream networks. Our objective was to assess the patterns and corresponding controls of diel DOM cycles through a seasonal flow recession by using reach‐scale in situ sensors in a non‐perennial stream network. We identified five characteristic diel variations in DOM with differing phase and amplitude. During snowmelt flows, diel variations in DOM were consistent among sites and reflected diel flowpath shifts and photodegradation. Evapotranspiration‐driven diel stage oscillations emerged at two upstream sites, shaping diel DOM patterns indirectly, by creating conditions for instream DOM processing. At a spring‐fed site, minimal diel variation was observed throughout the summer whereas at an intermittent reach, daily drying and rewetting created biogeochemical hot moments. This research demonstrates that controls on DOM vary over time and space, even in close proximity, generating asynchronous fDOM patterns during low flows, illuminating shifts in biogeochemical processes and flowpaths.

Diverse and larger tree islands promote native tree diversity in oil palm landscapes.

In monoculture-dominated landscapes, recovering biodiversity is a priority, but effective restoration strategies have yet to be identified. In this study, we experimentally tested passive and active restoration strategies to recover taxonomic, phylogenetic, and functional diversity of woody plants within 52 tree islands established in an oil palm landscape. Large tree islands and higher initial planted diversity catalyzed diversity recovery, particularly functional diversity at the landscape level. At the local scale, results demonstrated that greater initial planting diversity begets greater diversity of native recruits, overcoming limitations of natural recruitment in highly modified landscapes. Establishing large and diverse tree islands is crucial for safeguarding rare, endemic, and forest-associated species in oil palm landscapes.

Statistical-dynamical analog ensemble system for real time quantitative precipitation forecasts (QPFs) at local scale in the north-west Himalaya (NWH), India

Statistical-dynamical analog ensemble system for real time quantitative precipitation forecasts (QPFs) at local scale in the north-west Himalaya (NWH), India

Green Infrastructure Mapping in Almeria Province (Spain) Using Geographical Information Systems and Multi-Criteria Evaluation

Green infrastructure (GI) is increasingly prioritised in landscape policy and planning due to its potential to benefit ecosystems and enhance wildlife conservation. However, due to the uneven distribution of protected areas (PAs) and the fragmentation of habitats more generally, multi-level policy strategies are needed to create an integrated GI network bridging national, regional and local scales. In the province of Almeria, southeastern Spain, protected areas are mainly threatened by two land use/land cover changes. On the one hand, there is the advance of intensive greenhouse agriculture, which, between 1984 and 2007, increased in surface area by more than 58%. On the other hand, there is the growth of artificial surfaces, including urban areas (+64%), construction sites (+194%) and road infrastructures (+135%). To address this challenge, we present a proposal for green infrastructure deployment in the province of Almeria. We combine Geographic Information Systems (GISs) and multi-criteria evaluation (MCE) techniques to identify and evaluate suitability for key elements to be included in GI in two key ways. First, we identify the most suitable areas to form part of the GI in order to address vulnerability to degradation and fragmentation. Second, we propose 15 ecological corridors connecting the 35 protected areas of the province that act as core areas. The proposed GI network would extend along the western coast of the province and occupy the valleys of the main rivers. The river Almanzora plays a leading role. Due to its remoteness from the coast and its climatic conditions, it has not attracted intensive greenhouse agriculture and urban development, the main drivers of the transformation and fragmentation of traditional land uses. Around 50% of the area occupied by the proposed corridors would be located in places of medium and high suitability for the movement of species between core areas.

Assessing climate change threats and urbanization impacts on surface runoff in Gdańsk (Poland): insights from remote sensing, machine learning and hydrological modeling

AbstractThis study investigates the impacts of Land Use/Land Cover (LULC) changes and climate change on surface runoff in Gdańsk, Poland, which is crucial for local LULC planning and urban flood risk management. The analysis employs two primary methodologies: remote sensing and hydrological modeling. Remote sensing was conducted using Google Earth Engine and Land Change Modeler in IDRISI Terrset software to analyze historical (1985–2022) and future (2050–2100) LULC. Hydrological modeling was performed using the Natural Resources Conservation Service curve number method to assess the overall impact of LULC changes on Gdańsk’s hydrology at the local scale. The Orunia basin, a critical area due to intensive LULC development, was selected for detailed hydrological analysis using the Hydrologic Modeling System (HEC-HMS). The analysis encompassed three scenarios: LULC changes, climate change, and combined LULC and climate change effects. The LULC analysis revealed a marked increase in urban area, a shift in forest and vegetation cover, and a reduction in agricultural land. HEC-HMS simulations showed an increase in the runoff coefficient across selected decades, which was attributed to the combined effect of LULC and climate change. The projected increases under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios for 2050 and 2100 are projected to surpass those observed during the baseline period. The findings highlight that the synergistic effects of LULC and climate change have a more significant impact on Gdańsk’s hydrology at both local and basin scales than their separate effects. These insights into LULC shifts and urban hydrological responses hold implications for sustainable urban planning and effective flood risk management in Gdańsk and similar urban settings.

Global Versus Local? A Study on the Synergistic Relationship of Ecosystem Service Trade-Offs from Multiple Perspectives Based on Ecological Restoration Zoning of National Land Space—A Case Study of Liaoning Province

Clarifying the trade-offs and synergies of ecosystem services in Liaoning’s ecological restoration zones is crucial for strengthening the positioning of ecological restoration zones and optimizing ecosystem services. This study is based on “Liaoning Provincial Land Spatial Planning (2021–2035)” and divides the area into ecological restoration zones. We utilized the InVEST model, ArcGIS Pro, and Geoda in this study to quantify five ecosystem services (Soil Conservation, Carbon Storage, Habitat Quality, Water Yield, and Food Production) and constructed an evaluation framework to assess the trade-offs and synergies of ecosystem services at both global and local levels. The conclusions are as follows: (1) The global relationships among ecosystem services in different ecological restoration zones are ranked as: strong trade-offs (35.51%) > weak trade-offs (33.17%) > low synergies (29.09%) > high synergies (2.24%); (2) The area exhibiting synergistic relationships between pairs of local ecosystem services in ecological restoration zones is larger than the area exhibiting trade-offs; (3) The strongest synergy is observed between water yield and soil conservation, while the most significant trade-off occurs between food production and soil conservation. These relationships exhibit similar spatial characteristics in the WSFR, SWCR, and WCR zones; (4) The proportion of areas showing trade-offs and synergies differs between global and local scales.

A Pore-Scale Simulation of the Effect of Heterogeneity on Underground Hydrogen Storage

Using underground hydrogen storage technology has been recognized as an effective way to store hydrogen on a large scale, yet the physical mechanisms of hydrogen flow in porous media remain complex and challenging. Studying the heterogeneity of pore structures is crucial to enhance the efficiency of hydrogen storage. In order to better understand the pore-scale behavior of hydrogen in underground heterogeneous porous structures, this paper investigates the effects of wettability, pore–throat ratio, and pore structure heterogeneity on the behavior of the two-phase H2–brine flow using pore-scale simulations. The results show that the complex interactions between wettability, heterogeneity, and pore geometry play a crucial role in controlling the repulsion pattern. The flow of H2 is more obstructed in the region of the low pore–throat ratio, and the obstructive effect is more obvious when adjacent to the region of the high pore–throat ratio than that when adjacent to the region of the medium pore–throat ratio. In high-pore–throat ratio structures, the interfacial velocity changes abruptly as it passes through a wide pore and adjacent narrower throat. Interfacial velocities at the local pore scale may increase by several orders of magnitude, leading to non-negligible viscous flow effects. It is observed that an increase in the pore–throat ratio from 6.35 (low pore–throat ratio) to 12.12 (medium pore–throat ratio) promotes H2 flow, while an increase from 12.12 (medium pore–throat ratio) to 23.67 (high pore–throat ratio) negatively affects H2 flow. Insights are provided for understanding the role of the heterogeneity of pore structures in H2–brine two-phase flow during underground hydrogen storage.

Influence of fuel data assumptions on wildfire exposure assessment of the built environment

Background Land cover information is routinely used to represent fuel conditions in wildfire hazard, risk and exposure assessments. Readily available land cover data options that vary in resolution, extent, cost and purpose of collection have become increasingly accessible in recent years. Aim This study investigates the sensitivity of community-scale wildfire exposure assessments to different land cover information products used to identify hazardous fuel. Methods Ten versions of a community wildfire exposure assessment were conducted for each of five case study locations in Alberta, Canada, by varying the input land cover data. Proportional and spatial distribution of hazardous fuels and classified exposure are compared across datasets and communities. Key results We found proportional and spatial variation of exposure values between datasets within each community, but the nature of this variation differed between communities. Land cover classification definitions and scale were important factors that led to inconsistencies in assessment results. Conclusions Readily available land cover information products may not be suitable for exposure assessments at a localised scale without consideration of unique context and local knowledge of the assessment area. Implications Results may inform fuel data selection considerations for improved results in various wildfire applications at localised scales.

DRONES4BLUECARBONSEAGRASS: A Capacity-Building Program for Mapping Seagrasses using Unmanned Aerial System (UAS) Technology in the Philippines

Abstract. Coastal blue carbon ecosystems, such as mangrove forests and seagrass meadows, are important for various environmental functions, serving as habitats, food sources, and carbon sinks. Despite their importance, seagrass ecosystems are experiencing global decline due to numerous stressors, including anthropogenic activities. To address this, effective monitoring and management strategies are crucial. Traditional in situ surveys for seagrass monitoring are labor-intensive and time-consuming. Alternatively, remote sensing technologies, particularly satellite imagery, offer a more efficient means of mapping seagrass distribution over large areas. However, accurately assessing seagrass cover at a local scale remains challenging with satellite data alone. Recently, unmanned aerial system (UAS) technology has emerged as a promising approach for seagrass mapping. With its fine resolution and flexibility for image acquisition, UAS can provide more precise estimates of seagrass cover, complementing satellite data. This integration enhances accuracy assessments and expands data availability for training and validation purposes. Under the BlueCARES Project, a drone training program was developed to equip stakeholders with the skills needed for cost-effective UAS-based seagrass mapping. The drone training program encompasses lectures on UAS basics, flight planning, and image processing. Beyond training, collected data are used to create seagrass maps and assess seagrass density. This initiative not only advances seagrass conservation but also fosters collaboration between government agencies, academia, and local communities to achieve sustainable management of blue carbon ecosystems.

3-D intrinsic attenuation tomography using ambient seismic noise applied to La Palma Island (Canary Islands)

The potential of the island of La Palma (Canary Islands) to host geothermal resources is very high, mainly due to its high volcanic activity. The primary goal of this study is to get a tridimensional image of the seismic intrinsic attenuation using ambient seismic noise and to identify anomalies that may be linked to active geothermal reservoirs on La Palma island. For this purpose, we developed a new Ambient Noise Attenuation Tomography (ANAT) technique, which uses seismic ambient noise for imaging intrinsic attenuation in 3-D at a local scale down to 5 km depth. Our research identifies two areas with high attenuation in the island’s southern region. One area could be associated with hydrothermal alteration zones beneath the Cumbre Vieja volcanic complex. Another high-attenuation zone was observed in the island’s southern part, which could be associated with extensively fractured rocks that might facilitate the circulation of heated fluids. Furthermore, we discuss the geothermal relevance of such anomalies, making a comparison with previous resistivity, S-wave velocity and density models. This study confirms that intrinsic attenuation retrieved from the coda of Rayleigh waves is more sensitive to the presence of fluids than velocity. Fluids being a key component of active geothermal reservoirs, it is reasonable to expect intrinsic attenuation anomalies in these systems. Therefore, we conclude that ANAT can be useful for geothermal exploration.

Downscaling MODIS evapotranspiration into finer resolution using machine learning approach on a small scale, Ribb watershed, Ethiopia.

By monitoring evapotranspiration (ET), the exchange of water and energy between the soil, plants, and the atmosphere can be controlled. Routine estimations of ET on a daily, monthly, and seasonal basis can give relevant information on small-scale agricultural practices, such as the Ribb watershed in Ethiopia. However, MODIS sensors have recently given high temporal resolution ET products across large areas, but their low spatial resolution limits its application on a local scale. The primary goal of the study was to downscale the MODIS ET (1km) product to a finer spatial resolution at the watershed level. The model's 12 predictor variables (NDVI, EVI, LAI, FVC, SAVI, NDMI, NDWI, Albedo, emissivity, LST, and DEM: slope and elevation) were produced using the random forest (RF) algorithm using Sentinel-2 (S-2) 20m and Landsat-8 (L-8) 30m. The RF regression model was used to assess the relationship between predicted variables and downscaled MODIS ET. The FAO-PM ET model, developed from meteorological stations, was validated by and RMSE for three seasons (rainy, post-rainy, and dry) in 2022. The results were in good agreement with MODIS ET, with an RMSE of 0.22 for S-2 and 0.28 for L-8. In the FAO-PM ET model, the downscaled result showed greater spatial details and better agreement with gage station readings ( and ). Thus, considering the effectiveness and simplicity of machine learning techniques, our study demonstrated the potential for ET downscaling. Furthermore, the study suggests integrating spatiotemporal time series data to reach higher resolution.

Unraveling global species richness patterns of the Lysmatidae family: a multi-scale and multi-hypothesis ecological approach

While diversity gradients are well-explored in macroecology, factors shaping species richness at broad scales remain debated. We investigated the species richness of the decapod family Lysmatidae across 4 spatial scales: realm, province, ecoregion, and local (2° × 2° grid cells). We tested 4 ecological hypotheses: physiological stress (PSH), resource availability (RAH), habitat heterogeneity (HHH), and anthropogenic impact (AIH). Occurrence data (52 Lysmatidae species) and environmental variables (salinity, temperature, primary productivity, bathymetry, coral richness, anthropogenic impact index) were obtained from online databases and literature. Fifteen regression models, incorporating spatial filters, were tested to assess the hypotheses. The highest Lysmatidae species richness occurred in the Tropical Atlantic and Central Indo-Pacific realms. Richness varied with scale, with the highest values in the transition between the tropical and subtropical zones. Bathymetry was associated with Lysmatidae richness across all scales, especially at local and ecoregional scales, while coral richness was related to province and realm scales. HHH explained Lysmatidae richness patterns at the realm scale. Variables related to PSH and AIH were associated with richness at the ecoregion and province scales. Our study emphasized the importance of scale in biodiversity research, influencing richness patterns in Lysmatidae, and pointed to bathymetry, coral richness, and temperature range as the main drivers of richness. As this study showed a relationship between Lysmatidae richness, coral richness, and temperature at 3 spatial scales, this family may be susceptible to the effects of climate change, such as tropicalization of subtropical zones and defaunation of tropical ecosystems, including coral reefs.

Sustainable Groundwater Management through Collaborative Local Scale Monitoring

Sustainable Groundwater Management through Collaborative Local Scale Monitoring

Social-ecological system trajectories of peri-urban watersheds based on a spatial analysis of vulnerability components: A case study in Mexico City, 1999-2039.

Urban periphery watersheds play a crucial role in providing diverse ecosystem services, especially hydrological services (HES), for society at different temporal and spatial scales; moreover, local populations directly influence ecosystem functionality through their decisions and actions. The interactions between social and ecological factors create social-ecological systems (SESs), whose trajectories continuously change in response to internal factors such as land use cover change (LUCC) and external factors such as climate change (CC). This situation influences the vulnerability of SESs in terms of exposure, sensitivity and adaptation capacity. In this study, the social-ecological vulnerability (SEV) of the periphery of Mexico City was investigated based on the Collaborative Protocol for Ecosystem Services Assessment and Social-ecological Vulnerability Mapping (ECOSER) and a quantitative method approach. For this purpose, spatial analysis was performed using the ecological and social spatial data for LUCC tendencies calculated for 1999-2019 and projected for short-term CC scenarios and using LUCC calculated for 2039 in trend-based (TREND) and restrictive (REST) scenarios. The results reveal that increases in the SEV in 2039 will be related to important decreases in the HES; furthermore, the REST scenario suggests decreases in the SEV due to decreases in the HES, assuming that environmental public policy instruments will be preserved in this region. The present work aims to contribute to decision-making for HES preservation at local and regional scales and to help develop adaptation strategies under LUCC and CC scenarios.

Empirical Evaluation and Simulation of the Impact of Global Navigation Satellite System Solutions on Uncrewed Aircraft System–Structure from Motion for Shoreline Mapping and Charting

Uncrewed aircraft systems (UASs) and structure-from-motion/multi-view stereo (SfM/MVS) photogrammetry are efficient methods for mapping terrain at local geographic scales. Traditionally, indirect georeferencing using ground control points (GCPs) is used to georeference the UAS image locations before further processing in SfM software. However, this is a tedious practice and unsuitable for surveying remote or inaccessible areas. Direct georeferencing is a plausible alternative that requires no GCPs. It relies on global navigation satellite system (GNSS) technology to georeference the UAS image locations. This research combined field experiments and simulation to investigate GNSS-based post-processed kinematic (PPK) as a means to eliminate or reduce reliance on GCPs for shoreline mapping and charting. The study also conducted a brief comparison of real-time network (RTN) and precise point positioning (PPP) performances for the same purpose. Ancillary experiments evaluated the effects of PPK base station distance and GNSS sample rate on the accuracy of derived 3D point clouds and digital elevation models (DEMs). Vertical root mean square errors (RMSEz), scaled to the 95% confidence interval using an assumption of normally-distributed errors, were desired to be within 0.5 m to satisfy National Oceanic and Atmospheric Administration (NOAA) requirements for nautical charting. Simulations used a Monte Carlo approach and empirical tests to examine the influence of GNSS performance on the quality of derived 3D point clouds. RTN and PPK results consistently yielded RMSEz values within 10 cm, thus satisfying NOAA requirements for nautical charting. PPP did not meet the accuracy requirements but showed promising results that prompt further investigation. PPK experiments using higher GNSS sample rates did not always provide the best accuracies. GNSS performance and model accuracies were enhanced when using base stations located within 30 km of the survey site. Results without using GCPs observed a direct relationship between point cloud accuracy and GNSS performance, with R2 values reaching up to 0.97.

Exploring the Contribution Roles from Municipal Cities in the Rise in Household CO2 Emissions in China: From a Local Scale Analysis in the Global Context

A major source of carbon dioxide emissions (CO2) arises from the household sector. Recent studies have reported increasing household CO2 emissions (HCO2) in many countries. Cities represent a key administrative level in China and can be managed to mitigate HCO2 if spatial and temporal variations in HCO2 are understood at fine scales. Here, we applied panel data analysis to map HCO2 at a pixel scale of 1 km in China using remotely sensed time series nighttime light data, grid population density data, and provincial energy consumption statistics from 2000 to 2020. Spatial and temporal variations in HCO2 were observed with four growth modes, including high growth (HG), low growth (LG), negative growth (NG), and high negative growth (HNG), for different periods, i.e., 2000–2010, 2010–2020, and 2000–2020. We proposed a local scale analysis of HCO2 growth patterns within a global context to assess the contribution roles of 372 municipal cities to the changes in the national total HCO2 (T-HCO2). The results indicated that T-HCO2 has tripled in the last two decades, but the roles of the contribution to the increase varied among cities. The local scale analysis revealed that more cities contributed to the rise in T-HCO2 through HG and LG than those that suppressed it through NG and HNG. The majority of the cities displayed contributions to the rise in T-HCO2 through two or more of the growth modes, confirming a significant variation in HCO2 across locations, even within a city. This study provides a new approach to understanding the roles cities play in the long-term dynamics of T-HCO2. We recommend increased efforts to encourage HCO2 mitigation in cities that have contributed to the rise in T-HCO2 to help neutralize carbon emissions at the national level.

People or predators? Comparing habitat‐dependent effects of hunting and large carnivores on the abundance of North America's top mesocarnivore

Variation in animal abundance is shaped by scale‐dependent habitat, competition, and anthropogenic influences. Coyotes Canis latrans have dramatically increased in abundance while expanding their range over the past 100 years. Management goals typically seek to lower coyote populations to reduce their threats to humans, pets, livestock and sensitive prey. Despite their outsized ecological and social roles in the Americas, the factors affecting coyote abundance across their range remain unclear. We fit Royle–Nichols abundance models at two spatial scales in a Bayesian hierarchical framework to three years of data from 4587 camera trap sites arranged in 254 arrays across the contiguous USA to assess how habitat, large carnivores, anthropogenic development and hunting regulations affect coyote abundance. Coyote abundance was highest in southwestern USA and lowest in the northeast. Abundance responded to some factors as expected, including positive (soft mast, agriculture, grass/shrub habitat, urban–natural edge) and negative (latitude and forest cover) relationships. Colonization date had a negative relationship, suggesting coyote populations have not reached carrying capacity in recently colonized regions. Several relationships were scale‐dependent, including urban development, which was negative at local (100‐m) scales but positive at larger (5‐km) scales. Large carnivore effects were habitat‐dependent, with sometimes opposing relationships manifesting across variation in forest cover and urban development. Coyote abundance was higher where human hunting was permitted, and this relationship was strongest at local scales. These results, including a national map of coyote abundance, update ecological understanding of coyotes and can inform coyote management at local and landscape scales. These findings expand results from local studies suggesting that directly hunting coyotes does not decrease their abundance and may actually increase it. Ongoing large carnivore recoveries globally will likely affect subordinate carnivore abundance, but not in universally negative ways, and our work demonstrates how such effects can be habitat and scale dependent.

Landscape Character and Management Zones in Polder Landscapes: A Case Study of the Dongting Lake Area

Polder landscapes, as a representative of lowland agriculture landscapes, possess diverse natural and cultural values. However, polder landscapes are facing multiple challenges arising from economic and climate changes, including increasing flood threats and the fragmentation of landscape patterns. These issues have severely threatened the safety and regional characteristics of the polder landscape. Therefore, this study aims to preserve the regional characteristics of polder landscapes while promoting the sustainable development of lowland environments, and the objective is to provide a foundation and baseline for the management and planning of polder landscapes. In this study, the Dongting Lake Area (DLA) was selected as a representative case of polder landscapes. To identify the landscape character and delineate the landscape management zones, this study employed the Landscape Character Assessment (LCA) method in conjunction with a polder typology method at two scales. As a result, the polder landscape types were identified and visualized at two different scales. At the Lake Scale, a comprehensive identification method for polder unit types and polder landscape regions was established, achieving a stepwise transition from polder areas to polder clusters and ultimately to individual polder units. At the Local Scale, an integrative analysis of landscape character diversity (LCD) and land construction suitability (LCS) was employed to establish five landscape management zones for polder landscapes, thereby realizing a balance between the conservation of polder landscape diversity with the sustainable development of wetland environments. This study contributes a set of cross-scale ideas and methods for identifying landscape characters and delineating management zones in polder landscapes, which could be expanded to other lowland agricultural landscapes.

Correlation Analysis of Vertical Ground Movement and Climate Using Sentinel-1 InSAR

Seasonal vertical ground movement (SVGM), which refers to the periodic vertical displacement of the Earth’s surface, has significant implications for infrastructure stability, agricultural productivity, and environmental sustainability. Understanding how SVGM correlates with climatic conditions—such as temperatures and drought—is essential in managing risks posed by land subsidence or uplift, particularly in regions prone to extreme weather events and climate variability. The correlation of periodic SVGM with climatic data from Earth observation was investigated in this work. The European Ground Motion Service (EGMS) vertical ground movement measurements, provided from 2018 to 2022, were compared with temperature and precipitation data from MODIS and CHIRP datasets, respectively. Measurement points (MP) from the EGMS over Italy provided a value for ground vertical movement approximately every 6 days. The precipitation and temperature datasets were processed to provide drought code (DC) maps calculated ad hoc for this study at a 1 km spatial resolution and daily temporal resolution. Seasonal patterns were analyzed to assess correlations with Spearman’s rank correlation coefficient (ρ) between this measure and the DCs from the Copernicus Emergency Management Service (DCCEMS), from MODIS + CHIRP (DC1km) and from the temperature. The results over the considered area (Italy) showed that 0.46% of all MPs (32,826 MPs out of 7,193,676 MPs) had a ρ greater than 0.7; 12,142 of these had a positive correlation, and 20,684 had a negative correlation. DC1km was the climatic factor that provided the highest number of correlated MPs, roughly giving +59% more correlated MPs than DCCEMS and +300% than the temperature data. If a ρ greater than 0.8 was considered, the number of MPs dropped by a factor of 10: from 12,142 to 1275 for positive correlations and from 20,684 to 2594 for negative correlations between the DC1km values and SVGM measurements. Correlations that lagged in time resulted in most of the correlated MPs being within a window of ±6 days (a single satellite overpass time). Because the DC and temperature are strongly co-linear, further analysis to assess which was superior in explaining the seasonality of the MPs was carried out, resulting in DC1km significantly explaining more variance in the SVGM than the temperature for the inversely correlated points rather than the directly correlated points. The spatial distribution of the correlated MPs showed that they were unevenly distributed in clusters across the Italian territory. This work will lead to further investigation both at a local scale and at a pan-European scale. An interactive WebGIS application that is open to the public is available for data consultation. This article is a revised and expanded version of a paper entitled “Detection and correlation analysis of seasonal vertical ground movement measured from SAR and drought condition” which was accepted and presented at the ISPRS Mid-Term Symposium, Belem, Brasil, 8–12 November 2024. Data are shared in a public repository for the replication of the method.

Robust Multimodal Image Matching Based on Radiation Invariant Phase Correlation

Abstract. Due to the influence of nonlinear radiation distortion and geometric deformation, achieving multimodal image matching remains a challenging task. To address these issues, this paper proposes a method called radiation invariant phase correlation (RIPC) to simultaneously estimate the rotation, scale, and displacement changes of multimodal image pairs. Firstly, based on the local structure characteristics of the image itself, we harness the nonlinear invariance of kernel canonical correlation analysis to devise the multimodal local self-correlation (MLSC) descriptor. This descriptor is resilient to nonlinear radiative differences, as well as local rotation and scale variations. Subsequently, we incorporate the log-polar coordinate transformation to capture the overall rotation and scale changes in the image, enabling independent representation of these factors on the Cartesian coordinate system. Finally, drawing upon the continuity of displacement estimation, as well as rotation and scale estimation, we construct a five-dimensional descriptor tailored for phase correlation. Extensive experiments conducted on five open-source datasets demonstrate that our proposed method surpasses state-of-the-art (SOTA) techniques in matching performance. Furthermore, our RIPC method achieves matching accuracy within 2-pixel threshold, which underscores its effectiveness in multimodal remote sensing image matching.