Abstract Soil organic carbon (SOC) is a crucial component in soil quality, health, and ecosystem function. Knowledge about its distribution is paramount for sustainable agriculture, food security, soil stabilityand carbon sequestration monitoring, especially in areas like northern Nigeria, where the soils are highly heterogeneous. This study applied machine learning algorithms of random forest, extreme gradient boosting, and categorical boosting to predict and map the spatial distribution of SOC in northern Nigeria at 30 m resolution. We used 181 soil samples collected from the 0–20 cm top layer across agricultural lands; 12 environmental covariates were selected from 22 covariates to fit the models using ten-fold cross-validation. Quantile random forest was used to estimate the associated SOC uncertainties. The result revealed that Random Forest achieved higher prediction accuracy (R2 = 0.43, RMSE = 0.45%, MAE = 0.33%), outperforming XGBoost (R2 = 0.39, RMSE = 0.54%, MAE = 0.37%) and CatBoost (R2 = 0.37, RMSE = 0.49%, MAE = 0.38%). Random forest further indicates that Landsat 9 Band 5 (NIR) is the most critical predictor variable, followed by annual precipitation, elevation, and mean temperature; the predicted SOC map shows a significant variation of SOC, with higher concentration in the southern area and lower in the northern part. The uncertainty estimation shows a broader range of uncertainties in the highly elevated areas. The study suggests that further observations and denser sampling should be carried out, especially in highly elevated areas, to capture more spatial variability.

While the effects of urbanization are widely studied, the effects of soil sealing, particularly in the case of Hungary, have only received limited attention in recent years. Our study aimed at understanding the underutilized capacity of urban soils at the national level. We have applied a 20 m resolution, spatially explicit daily water balance-based methodology to calculate the potential water dynamics for the top 75 cm of the soils currently covered by urban fabric in Hungary, for the time period of 1971–2024. We aimed to utilize primarily publicly available data and open-source software to support further use and development. Our results indicated that these (currently sealed) soil surfaces could allow between 0.14 and 0.29 km3 of water to infiltrate into the soil, equaling about 7% of the estimated annual water withdrawal in Hungary. The on-site evaporation from these surfaces would produce about 400 PJ of total cooling service annually, corresponding to an average of 145 MJ/m2. Our findings highlighted the water storage potential of soils in Hungary, particularly in urban areas, supporting the future application of nature-based solutions and blue-green infrastructure.

Reliable and harmonised soil information remains critically limited across Africa, constraining soil monitoring, climate-resilient agriculture, and evidence-based land management. Existing soil resources are often fragmented, spatially uneven, outdated, or derived from legacy observations, limiting their usefulness for contemporary continental-scale assessment. The Soils4Africa project implemented a coordinated field campaign across 33 African countries between 2022 and 2025 to establish a harmonised soil monitoring framework for agricultural lands. Using a hierarchical probabilistic sampling design, 24,951 soil samples were collected from 14,311 locations, supported by standardised field protocols, digital data capture, QR-based sample traceability, and centralised quality control. This paper presents the conceptual, operational, and data-management framework underpinning the survey and reports baseline field observations on farming systems, land management, vegetation structure, and soil physical constraints. The framework achieved more than 70% of planned sampling coverage despite major logistical, environmental, and security-related constraints. Baseline observations show that African agricultural landscapes remain dominated by smallholder systems, low external input use, limited soil and water conservation, and widespread dependence on rainfed production. Field indicators also reveal sparse woody vegetation cover and common physical constraints, including compaction, coarse fragments, shallow effective rooting depth, and subsoil barriers. Unlike earlier continental resources based largely on legacy profiles or site-based surveillance, Soils4Africa provides a contemporary, harmonised, spatially structured field-survey framework designed to support future laboratory-based soil assessment, digital soil mapping, land suitability analysis, and long-term soil monitoring. The study therefore provides a scalable model for coordinated soil monitoring across diverse African agroecosystems and establishes an operational baseline for subsequent analytical studies.

ABSTRACT In this commentary, we argue that the soil profile represents an indispensable window into the soil system. The soil profile is a vertical section of the soil body that represents a pattern in the landscape. The description and interpretation of the layers and horizons from the surface to the parent material or bedrock is the language of soil scientists to record and communicate the story of the soil. The story tells the evolution (genesis) of the soil and explains the resulting physical, chemical, and biological properties. The exposed profile can therefore help in determining the soil's potential to provide ecosystem services as well as its suitability for different land‐use applications. Efforts to classify soils globally across different climates and land management by soil profiling have contributed extensively to soil mapping and have enabled stakeholders to make informed decisions for sustainable land management. Despite its utility and significance, the soil profile has almost become a “lost language” within soil science. Pedology, as a subject within which soil profiling was once vehemently instructed and practiced, has notably declined in the past decade. The number of fully trained pedologists has dwindled, and investment in training the next generation in the art of profiling has declined. The trained pedologist may represent something of an endangered profession, yet soil profiling has allowed and continues to allow vital discoveries to be made about the soil system. This commentary traces the progress and trends on the study of soils over the century, considering their genesis, functions, and degradation captured by a profile. We chart the transformative contributions of remote and proximal sensing to advance soil science in the past decades, and how these findings have been used to ensure more sustainable and resilient land management practices. Furthermore, in chronicling the evolution of soil profiling, we aim to set out an inspiring roadmap for the next generation of pedologists to motivate them to “pick up the shovel” and engage with profiling without fear. Profile characterization is not only science but also literacy. Now that soil degradation has become a priority concern, careful observation and description of the profile are more important than ever, not only for diagnostic purposes but also as a historical record of the current, unique state of the soil.

According to climate projections, the Pannonian region is expected to experience an increasing frequency of drought events. This trend affects not only agricultural areas but also natural grasslands. The Festuca wagneri species, selected for this study, is a dominant and well-adapted grass in dry natural habitats. A total of 54 Festuca wagneri individuals were examined across three soil types: sand, loam, and clay. In each soil type, 18 plants were assessed for drought tolerance. Water was applied at three dosage levels: 200, 300, and 400 mL. The experiment was conducted between 4 April and 18 July 2024, during which the total weight of the pots and the amount of drained water were measured regularly. All data processing and statistical analyses were performed in R version 4.3.2. A three-way factorial ANOVA was used to evaluate main and interaction effects. Model residuals were tested for normality (Shapiro–Wilk test) and homoscedasticity using diagnostic plots. The results showed that Festuca wagneri individuals tolerated even the lowest soil moisture levels induced by low water-holding capacity of the soil and low water input. This indicates that the species can be effectively used in grassland management and restoration under future climate change scenarios. The main differences were observed among soil types, highlighting the crucial importance of soil structure when establishing this species. Loam soils, already near optimal, respond best to moderate.

Accurate forest biomass estimation is essential for quantifying carbon stocks, guiding sustainable forest management, and informing climate change mitigation strategies. Kenya’s forests are diverse, ranging from Afromontane and mangrove ecosystems to dryland woodlands and plantations, each presenting unique challenges for biomass measurement. This review synthesizes literature on field-based, remote sensing, and machine learning approaches applied in Kenya, highlighting their effectiveness, limitations, and integration potential. A systematic search across multiple databases identified peer-reviewed studies published in the last decade, screened against defined inclusion and exclusion criteria. The main findings are (1) Field-based techniques (e.g., allometric equations, quadrat sampling) provide reliable and site-specific estimates but are labor-intensive and limited in scalability. (2) Remote sensing methods (LiDAR, UAVs, multispectral and radar imagery) enable large-scale and repeat assessments, though they require extensive calibration and investment. (3) Machine learning and hybrid approaches enhance prediction accuracy by integrating multi-source data, but their success depends on data availability and methodological harmonization. This review identifies opportunities for integrating field and remote sensing data with machine learning to strengthen biomass monitoring. Establishing a national biomass inventory, supported by robust policy frameworks, is critical to align Kenya’s forest management with global climate and biodiversity goals.

Although numerous studies have reported an increased yield upon adoption to improved agricultural practices (IAPs), yet smallholder farmers face limited access to this information. The objective of this study was to assess smallholder farmers' awareness and adoption of IAPs. A total of 206 active and registered households were surveyed by mixed sampling in the Mbeya region. The data was collected from smallholder farmers using the ODK collect tool through a well-structured questionnaire. The probit model and One-way ANOVA test were performed to identify predictor variables. Results pointed out that farming period, top dressing, flood exposure, fallowing time, soil information on IAPs, and knowledge about soil type showed a significant difference (p < 0.05) on the farmers’ adoption of IAPs. Moreover, 81

A hidromorf talajokban a jelentős mennyiségű víztöbblet egyedi morfológiai bélyegeket eredményezhet, amelyek talajosztályozási szempontból fontos szerepet töltenek be. A vaskiválások és a velük összefüggésbe hozható diagnosztikus jellemzők mind a hazai, mind a nemzetközi diagnosztikus szemléletű osztályozási rendszerekben nagy jelentőséggel bírnak. A hazai talajtani szakirodalom számos olyan vaskiválást említ, amelyek szerepelnek a genetikus osztályozási rendszerünk útmutatóiban, ugyanakkor a diagnosztikus szemléletű hazai talajosztályozási rendszerben történő értelmezésük fejlesztésre szorul. Ennek egyik oka az, hogy egyes, világviszonylatban elterjedtnek számító hidromorf vaskiválási formák részletes dokumentációja még nem történt meg hazánkban – sok esetben a képződési körülmény hiánya okán –, másrészt archív talajtani adatbázisainkban a hidromorf vaskiválási bélyegek dokumentálása gyakran hiányos és/vagy pontatlan. A kutatás során áttekintettük a hazai hidromorf talajokra jellemző elkülönült vaskiválási formákat. Két talajszelvény leírásával és értelmezésével rávilágítottunk egyes szegregált, cementált vaskiválási formák osztályozási sajátosságaira. A talaj vasdinamikájával összefüggésbe hozható diagnosztikai kategóriák jelentős részénél fontos vasformák mennyiségét, illetve azok egymáshoz való arányát (a főként vas(III)-oxidok, -hidroxidok, -oxi-hidroxidok (Fe dith )) és (a gyengén kristályosodott vas-oxidok, vas-hidroxidok, vas-oxi-hidroxidok (Fe ox )) módszere alapján vizsgáltuk. A kutatás során feltárt cementált vaskiválások a talajszelvények leírásának és értelmezésének, valamint a begyűjtött talajminták laboratóriumi vizsgálatának tükrében mind morfológiájában, mind a releváns vasformák mennyisége és egymáshoz való aránya alapján gyepvasércként azonosíthatók. Mindezek alapján javaslatot fogalmaztunk meg a Gyepvasérces szint diagnosztikai szint, illetve a Gyepvasérces változati tulajdonság bevezetésére a hazai, diagnosztikus alapon megújult talajosztályozási rendszerbe.

Understanding how elevation gradients and soil depths influence soil organic carbon stocks (SOCS) and total nitrogen stocks (TNS) is essential for sustainable forest management (SFM) and climate change mitigation. This study investigated the effects of elevation and soil depth on SOCS and TNS in the Mount Kenya East Forest (MKEF). A stratified systematic sampling approach was applied, involving collection of 38 soil samples from two depths (0–20 cm and 20–40 cm) across three elevation zones: Lower Forest (1700–2000 m), Middle Forest (2000–2350 m), and Upper Forest (2350–2650 m). Samples were analysed for bulk density (BD), pH, texture, soil organic carbon (SOC), and total nitrogen (TN), using standard laboratory methods. In topsoil (0–20 cm), SOCS ranged from 109.28 ± 23.41 to 151.27 ± 17.61 Mg C ha−1, while TNS varied from 8.89 ± 1.77 to 12.00 ± 2.46 Mg N ha−1. In subsoil (20–40 cm), SOCS ranged from 72.03 ± 19.90 to 132.23 ± 11.80 Mg C ha−1, with TNS varying between 5.71 ± 1.63 and 10.50 ± 1.90 Mg N ha−1. SOCS and TNS increased significantly with elevation (p < 0.05), exhibiting the following trend: Lower Forest < Middle Forest < Upper Forest. Topsoil consistently stored significantly higher SOCS than subsoil (p < 0.05), emphasizing the critical role of surface soils in carbon sequestration. Regression analysis revealed a significant positive relationship between SOCS and TNS (R2 = 0.84, p < 0.001). Both SOCS and TNS were positively correlated with elevation, SOC, TN, and total annual precipitation (TAP), but negatively correlated with BD and mean annual temperature (MAT). These findings provide baseline data for monitoring SOCS and TNS in the MKEF, offering insights into sustainable forest management strategies to improve soil health and enhance climate change mitigation efforts.

The Namibian Soil Profile Database contains 4960 entries, all samples with geographic coordinates. Each soil property presents a different number of observations, which decreases with depth. To perform the Digital Soil Map of Soil Organic Carbon (SOC) up to 30 cm, 1298 sample points were used. The covariates used in the model were composed from land cover, geology, terrain characteristics extracted from the digital elevation model and remote sensing data. Most of the covariates carry 30 m of spatial resolution. The Random Forest model implemented in Google Earth Engine (GEE) was applied with an external validation split of 80/20 %. As the second validation layer, samples from the Namibian tier of the Soils4Africa project were applied. The use of GEE facilitated the generation of a SOC distribution map for Namibia at a spatial resolution of 30 × 30 m. The highest amounts of SOC are stored in the central region of Namibia, with SOC values ranging from 0.1 to 1.9 %. The map is suitable for national and regional decision-making, offering a baseline for determining SOC stocks, monitoring changes in SOC, assessing the effects of bush encroachment/thickening and bush control, and for agriculture implications. Mapping of soil properties in other depths are scheduled for the near future.

Industrial agriculture since the middle of the 20th century has provided bountiful food, but it has also altered and degraded soil physical, chemical, and biological properties on a continental scale. To combat this situation, sustainable agricultural practices are advocated, as well as retiring or "rewilding" some soils from agriculture and letting them revert to natural conditions for preserving biodiversity. Many scientific disciplines (biological, pedological, agricultural) are playing roles in sustainability. Soil classification can also play a role since its function is to group soil properties into soil types and create maps that show soil patterns across the landscape. In addition, classification is based largely on the genesis of diagnostic properties. Each diagnostic property has an evolutionary history resulting from factors -* pedogenic processes -* soil properties. Understanding a soil's genesis not only enables us to understand what soils are today, and which ecosystem and soil health functions they perform, it also enables us to know what they were in the past based on chronosequences and soil memory, and what they will likely become in the future. If, for example, a residual soil shallow to limestone bedrock (e.g., Leptosols, or Lithic Hapludalfs) is plowed, remains uncovered by vegetation, and is allowed to erode to bedrock, it is neither sustainable nor regenerative. If, on the other hand, a soil with a mollic horizon (e.g., Chernozem or Mollisol) that formed in deep loess with no restrictive layers is allowed to erode causing it to lose carbon, moisture storage capacity, and favorable structure, it can regain its sustainability and become regenerative through proper management, such as cover crops and conservation tillage. Similar examples can be found for soils worldwide that illustrate the role classification can contribute to soil sustainability and regenerative capacity at the landscape scale.

Understanding the influence of land use and elevation gradient on soil organic carbon stocks (SOCS) is essential for effective land management, sustainable agricultural practices, and mitigation of climate change impacts. This research aimed to explore how land use types and elevation gradients influence SOCS on the eastern slopes of Mount Kenya. Using a stratified systematic sampling approach, 68 soil samples were collected from 0–20 and 20–40 cm depths, representing forestland and farmland, across six elevation gradients ranging from 1000 to 2650 m above sea level (a.s.l.). Soil samples were analysed for bulk density (BD), pH, texture, soil organic carbon concentration (SOC), and total nitrogen concentration (TN) using standard methods. The results showed that SOCS were significantly higher (p<0.001) in the forest compared to the farms. The forestland SOCS ranged from 87.40 to 168.75 Mg ha−1 at the 0–20 cm and 38.31 to 148.58 Mg ha−1 at the 20–40 cm depths. On the other hand, farmland SOCS at the 0–20 cm and 20–40 cm depths were in the range of 21.86 to 50.38 Mg ha−1 and 17.27 to 49.84 Mg ha−1, respectively. The SOCS generally exhibited a declining trend with increasing soil depth in both land use types. Elevation-wise, the mean SOCS in the aggregated 0–40 cm depth ranged from 29.21 ± 5.6 Mg ha−1 in the lower farmland (1000–1200 m a.s.l) to 141.75 ± 17.4 Mg ha−1 in the upper forestland (2350–2650 m a.s.l). There was an increasing trend in the SOCS with an increase in elevation (r² = 0.78). A significant positive correlation was observed among the studied soil parameters between SOCS, SOC and TN. In contrast, a negative correlation existed between SOCS, BD, and soil temperature for both land use types. The outcomes of this investigation provide foundational data for monitoring SOCS in the Mount Kenya ecosystem. It serves as a basis for future assessments and sustainable management strategies to promote soil health and enhance climate change mitigation measures.

Salinization and sodification are serious and worldwide growing threats to healthy soil functions. Although plants developed a plethora of traits to cope with high salinity, soil bacteria are also essential players of the adaptation process. However, there is still lack of knowledge on how other biotic and abiotic factors, such as land use or different soil properties, affect the bacterial community structure of these soils. Therefore, besides soil chemical and physical investigations, bacterial communities of differently managed salt-affected soils were analysed through 16S rRNA gene Illumina amplicon sequencing and compared. Results have shown that land use and soil texture were the main drivers in shaping the bacterial community structure of the Hungarian salt-affected soils. It was observed that at undisturbed pasture and meadow sites, soil texture and the ratio of vegetation cover were the determinative factors shaping the bacterial community structures, mainly at the level of phylum Acidobacteriota. Sandy soil texture promoted the high abundance of members of the class Blastocatellia, while at the slightly disturbed meadow soil showing high clay content was dominated by members of the class Acidobacteriia. The OTUs belonging to the class Ktedonobacteria, which were reported mostly in geothermal sediments, reached a relatively high abundance in the meadow soil.

Soil exchangeable acidity (EA) is an indicator of aluminium toxicity potential in acidic soils. Predicting the distribution and dynamics of EA is needed for the identification and management of acidic soils. In this study, we used datasets of 355 pedons from across Ghana and the Cubist rule-based algorithm to generate pedotransfer functions (PTFs) of EA. Eight soil properties (pH, organic carbon, calcium, sodium, magnesium, total exchangeable bases, cation exchange capacity [CEC] to clay ratio and soil depth) were used to predict EA. We first used the whole dataset to construct generic PTFs and then stratified the dataset based on World Reference Base-Reference Soil Groups (WRB-RSGs) to generate soil-specific PTFs. Goodness-of-fit statistics comprising the root mean squared error (RMSE), Lin's concordance correlation coefficient (rho(c)) and coefficient of determination (R-2) were used to evaluate the prediction accuracy and reliability of the developed PTF models on both calibration and validation datasets. The Fluvisols EA-PTF exhibited lower performance metrics in the validation (RMSE = 0.17 cmol(c) kg(-1), rho(c) = 0.19, R-2 = 0.24), whereas the EA-PTFs for all other WRB-RSGs and whole dataset had above-average performance metrics in the validation (0.05 <= RMSE <= 0.97 cmol(c) kg(-1); 0.34 <= rho(c) <= 0.94; 0.52 <= R-2 <= 0.96). Soil pH sufficed for predicting EA in soils with pH above 5.0, but in soils with a pH < 5.0, the levels of exchangeable bases (e.g., Na+, K+, Mg2+, Ca2+), CEC to clay ratio (CCR) and soil depth improved the prediction of EA. The developed EA-PTFs are useful for estimating the missing values of EA in soil databases.

The central highlands of Kenya play a vital role in supporting agricultural activities and sustaining the livelihoods of smallholder farmers. Despite its crucial role, the region faces substantial environmental challenges like soil erosion and land degradation, necessitating the adoption of sustainable land management practices. The aim of this study was to investigate the determinants of the adoption of Soil and Water Conservation Practices (SWCPs) among smallholder farmers in central Kenya. Primary data was collected from three administrative wards of Tharaka Nithi County (TNC) using 150 semi-structured household (HH) questionnaires, Key Informant Interviews (KII), and field observations. STATA and Microsoft Office Excel software were used to analyse the HH survey data, using descriptive statistics, inferential statistics, and the binary logistic regression model. Qualitative data from the KII was analysed through synthesized text summaries. The results show that 65.33 % of the respondents adopted SWCPs on their farms, while 34.67 % did not at the time of our study. The study findings further revealed that farm size (β ​= ​0.641; p ​< ​0.05), and Agro-ecological zone (AEZ) (β ​= ​1.341; p ​< ​0.05) positively influenced the adoption of SWCPs. On the other hand, distance from homestead to farm (β ​= ​−0.003; p ​< ​0.05), and age (β ​= ​−0.039; p ​≤ ​0.05) negatively influenced the adoption of SWCPs by the farmers. Challenges in SWCPs implementation included inadequate capital (76.53 %), high labor costs (62.24 %), lack of technical knowledge (34.69 %), lack of infrastructure (17.35 %), and insecure land tenure (1.02 %). These study findings hold the potential to guide the TNC government in formulating tailored strategies that can foster the adoption and sustainable implementation of SWCPs among smallholder farmers. If properly implemented, the strategies will bolster agricultural productivity, mitigate soil erosion, and enhance the region's overall environmental and economic well-being.

Napjainkban soha nem látott igény mutatkozik megfelelő mennyiségű és minőségű talajadatra és információra. Spektroszkópiai technológiák a hagyományos laboratóriumi módszerekkel együttesen, párhuzamosan alkalmazva lehetőséget kínálnak a talajfelvételezés idő- és költséghatékonyabbá, valamint környezetkímélőbbé tételére. Jelen munkában lokális, regionális és globális léptékű talajspektrális könyvtárak bemutatása mellett az első országos szintű, az Agrártechnológiai Nemzeti Laboratórium projekt keretében kidolgozásra kerülő, Magyarország talajtani változatosságát reprezentáló spektrális adatbázis létrehozásának koncepcióját mutatjuk be. A spektrális könyvtárak olyan speciális talajadatbázisoknak tekinthetőek, melyek tartalmazzák egy adott terület talajait reprezentáló talajminták hagyományos laboratóriumi módszerrel meghatározott paramétereit, valamint spektroszkópiai módszerrel rögzített spektrumait. A spektrális könyvtárakban tárolt adatok alapján elvégzett, spektroszkópiai kalibrációkra alapozott talajparaméter becslési eljárások lehetőséget kínálnak az adatbázisban szereplő talajminták fizikai-kémiai-ásványtani tulajdonságaihoz hasonló minták paramétereinek spektrális alapú megbízható megbecsléséhez. A hazai spektrális könyvtár alappillérét a Talajvédelmi Információs és Monitoring (TIM) rendszer mintavételezés kezdeti évében (1992-ben) gyűjtött, talajok genetikai szintjeiből vett talajmintákról felvett spektrumokra építjük. A spektrális adatbázist a középső-infravörös (middle-infrared, MIR), valamint a látható- és közeli infravörös (visible and near-infrared, VIS-NIR) tartományban, a Global Soil Laboratory Network (GLOSOLAN) iránymutatásai alapján rögzített spektrális adatokra építjük. A folyamatosan bővülő spektrális könyvtár, és az erre az adatbázisra épülő talajtulajdonság-becslő eljárás lehetőséget fog kínálni számos fizikai és kémiai paraméterének megbízható meghatározására, ezzel (számottevő többletköltség nélkül) nyújt lehetőséget a jelenlegi laboratóriumi kapacitás növelésére.

Land use system has a great impact on soil properties. The effect of land use on soil chemical, microbiologicalproperties and soil moisture of salt-affected soils was investigated in India. Soil samples were collected from Solonetz soilsunder different land uses such as arable land (SnA), bare land (SnB) and pasture land (SnP). Results of the study showed thatthe chemical and microbiological properties of all three sites were statistically different from each other. The principalcomponents (PC1 and PC2) retained for the analysis accounted for 86.26% of the total variance. The values of microbiologicalproperties were the highest in SnA, intermediate in SnP and the lowest in case of SnB. Discriminant analysis of microbiologicalproperties showed that 93.64% of variation and can be determined by MBC. The primary objective of our study was toascertain how farmers' perceptions and decisions regarding land use systems, which are based on their experiences ratherthan laboratory results, align with soil physical, chemical and microbiological properties, and how they contribute to preservingsoil quality. Overall, it was concluded that arable land (SnA) had more favorable chemical properties and it has beenmicrobiologically more active in investigated salt affected (Solonetz) soils. Moreover, soil conservation and ameliorationpractices are suggested in bare land and pasture land to prevent further degradation and to improve the soil quality of theinvestigated salt affected areas. Also, it is important to educate and transfer knowledge to the farmers about the consequencesof soil degradation and advocate good soil management practices (gypsum application, nutrient management, crop cover,tillage etc.)

A vizes élőhelyek a vízi és a szárazföldi ökoszisztémák között elhelyezkedő, igen változatos, és általában nehezen lehatárolható területek. Kiemelt jelentőségük annak köszönhető, hogy bár csak a globális szárazföldi területek mintegy 6–7%-át borítják, kulcsfontosságú szerepet játszanak az éghajlat szabályozásában, a vizes ökoszisztémák biodiverzitásának és hidrológiai viszonyainak fenntartásában, valamint számos további ökológiai és társadalmi funkciót is szolgáltatnak, beleértve az árvízvédelmi, víztisztítási, szén-dioxid-tárolási, élőhelytámogatási és kulturális, rekreációs előnyöket. A vizes élőhelyek azonban mind természetes, mind antropogén hatások következtében térben és időben is dinamikusan változnak, ezért védelmük és megfigyelésük napjainkra igen fontos kutatási területté nőtte ki magát. A műholdas távérzékelés nagyobb területek egyidejű megfigyelését teszi lehetővé, azonban érzékeny a felhőzetre és a légköri hatásokra, bizonytalanságot okozva ezzel az eredményekben. A hagyományos monitoring technológiák mellett a pilóta nélküli légi járművek térnyerése egyre kifejezettebb, köszönhetően rugalmasságának, hatékonyságának és alacsony költségének, miközben nagy térbeli és időbeli felbontású, szisztematikus adatszolgáltatásra képes. Tanulmányunk a pilóta nélküli légi járművek alkalmazási lehetőségeibe nyújt betekintést a vizes élőhelyek felmérésében, valamint áttekinti és összehasonlítja az egyéb távérzékelés technológiák alkalmazhatóságát ezen területek megfigyelésében. Célja, hogy elősegítse a dróntechnológia további terjedését és széles körű alkalmazását a vizes élőhelyek monitorozásában.