Gully Erosion Research Articles

The Implications of Geotechnical Properties of Soil in the Development of Gully Erosion in Ukpor, Southeastern Nigeria

Gully erosion is a devastating form of soil degradation threatening environmental sustainability, socio-economic development, and human well-being worldwide. The Southeastern region of Nigeria, particularly Ukpor, is prone to gully erosion, which has resulted in the loss of infrastructure, agricultural land, and human settlements. While various factors contribute to gully erosion, the soil’s geotechnical properties remain an important aspect that has been given limited attention. This study investigates the implications of geotechnical properties of soils in the development of gully erosion in Ukpor. A comprehensive approach was adopted, combining drone-aided geologic field mapping, laboratory tests and spatial analysis. Soil samples were collected from different locations at 0.5 – 1m depth, and laboratory tests (Particle Size Distribution (PSD) and Atterberg Limits) were conducted to determine the soil’s geotechnical properties. The results reveal that the study area is underlain by the Ogwashi-Asaba formation. From the Particle Size Distribution and Atterberg Limit tests, the soils in the area were classified into 3; Group A (coarse-grained clayey sands), Group B (coarse-grained poorly graded to clayey sands) and Group C (poorly-graded coarse-grained sands). The Plasticity Index (PI) of Group A ranges from 13.4 – 18.2 while the Liquid Limit (LL) ranges from 27.8 to 34.9. The PI of Group B ranges from 15.49 to 17.35 while the LL ranges from 30.7 to 35.7, From the results, Group C soils were most affected by gullying. Given the above, the underlying soil strata of Ukpor metropolis could be classified as low plasticity soil, thus, highly susceptible to erosion. The results show a significant correlation between soil geotechnical properties and gully erosion susceptibility. The results have pivotal implications for soil conservation, sustainable land management, and infrastructure development in Ukpor and similar regions. The study recommends soil stabilization techniques and vegetation management strategies to mitigate gully erosion.

Vulnerability to Risk of Gully Erosion on Transportation routes and Landed Properties in Benin City Nigeria

The Edo State Ministry of Environment registered 25 gully erosion sites in Benin City. The impacts of some of them have been very detrimental to lives, destroying roads and properties worth billions of Naira. Despite the treat to lives, properties, and accessibility, many are still living around the gullies. The study examined the perceptions of the population at risk and their preparedness to relocate. Questionnaire, GPS, Field measurement, and Google Earth Image were used as data sources to accomplish the objective of the paper. The result indicates that there is a high level of perception among the population at risk. Residents’ perceived vulnerability to gully hazards is directly related to their proximity to the hazard point, while the level of residents’ preparedness to vacate the gully environment is directly related to perceived vulnerability and financial capability. The study result was depicted in map form. Though managing the gully erosion hazard is beyond the capability of the residents within the neighbourhoods, government intervention has been very poor. The study recommended the relocation of populations at risk, while advance drainage designs and construction be executed in order to put an end to the gully.

Assessing the Socio-Economic Impacts of Gully Erosion on Farming Activities in Northern Adamawa State, Nigeria

Gully erosion is a significant environmental challenge in Northern Adamawa State, Nigeria, with profound socio-economic impacts on farming activities. This study assesses the extent and effects of gully erosion on the local farming communities. Using a combination of field observations, transect walks, and questionnaire surveys, data were collected from 400 farmers, with a 72.5% response rate. The study reveals that 94.2% of the respondents are aware of gully erosion in their areas, and 76.7% recognize its threat to their farmlands and residences. The results indicate that 33.3% of farmers have lost farmland, 20% have experienced soil quality degradation, and 12.5% have faced increased crop transportation costs due to gully erosion. The findings underscore the urgent need for intervention to mitigate the adverse effects of gully erosion on agricultural productivity and community livelihoods.

Arid erosion mapping: comparing LiDAR and structure from motion

Rapid development and uptake in uncrewed aerial vehicles (UAVs) for environmental monitoring, specifically using three-dimensional data from LiDAR and structure from motion (SfM), has enabled improved condition assessment, including fine-scale erosion monitoring. Comparing the precision of LiDAR and SfM for measuring erosion is essential in enabling appropriate method selection. Additionally, knowledge regarding optimal flight heights allows for consideration of the trade-off among survey areas, flight times and precision. We assessed UAV-based LiDAR and SfM for providing high-precision digital surface models (DSM) of substantial gully erosion on a conservation reserve in the southern Australian arid rangelands. The gullies exist in low-slope chenopod shrublands with calcareous soils, and are of significant management concern, with erosion occurring rapidly over short periods following irregular and intense rainfall events. Root mean squared error (RMSE) values for SfM-derived DSMs with resolutions of 2, 4 and 6 cm were lower than comparable LiDAR datasets (SfM = 0.72–1.39 cm; LiDAR = 2.08–3.15 cm). Additionally, 2 cm SfM-derived datasets exhibit notably lower RMSE values than 4 and 6 cm datasets (2 cm = 0.72 cm; 4–6 cm = 2.08–3.15 cm). Change detection over the 1-year study period highlighted erosion in locations of management concern. We propose that, although both methods are of value, SfM is preferred over LiDAR because of its simplicity, reduced cost, and the additional monitoring capabilities of visible-colour imagery, with no notable sacrifice in precision. Visible-colour survey areas and times can be optimised by increasing flight height without dramatic losses in precision. The use of either method will be of great benefit for the monitoring of arid gully erosion and assessing the effectiveness of management interventions, allowing adaptive management and leading to improved condition of arid rangelands into the future.

Assessing Water Erosion Vulnerability in the Lower Ziz Watershed: Integrating PAP/RAC methodology with Remote Sensing and GIS

Degradation presents a significant challenge, particularly exacerbated by current climate change. Our study focuses on the Lower Ziz watershed, located in southeastern Morocco, which is characterized by a semi-desert climate and is at high risk of land degradation due to water and wind erosion. Natural factors such as precipitation intensity and frequency, slope inclinations, low vegetation cover density, and soil characteristics, combined with anthropogenic activities, contribute to increasing the erosion risk within this watershed. The use of unsustainable agricultural practices has also contributed to this growing vulnerability. To investigate this phenomenon, we adopted the PAP/CAR method, a qualitative approach for mapping and assessing vulnerability to water erosion in the watershed. This method integrates essential physical data such as topography, lithology, soil types, and vegetation cover, facilitating a comprehensive analysis of erosion risk. Through the use of remote sensing tools and geographic information systems (GIS), we have generated detailed thematic maps, streamlined the mapping process, and improved data management. The findings of this research provide valuable insights for sustainable land and natural resource management in the Lower Ziz watershed and can aid in the formulation of prevention and mitigation strategies for water erosion in similar contexts globally. Our predictive mapping approach indicates that 37.34% of the watershed exhibits low to very low susceptibility to water erosion, while 55.96% experiences moderate erosion, with the remaining 6.7% being highly erodible. Additionally, our descriptive analysis highlights the prevalence of gully and surface gullying erosion, encompassing 49.32% of the area, as well as deep gully erosion, affecting 41.89%.”

Integrated Geophysical Investigation of Gully Erosion in Ukpor Metropolis, Southeastern Nigeria Using Vertical Electrical Sounding and Electrical Resistivity Tomography Methods

This research investigates the geophysical aspects of gully erosion in Ukpor Metropolis using Vertical Electrical Sounding (VES) and Electrical Resistivity Tomography (ERT) methods. We identified distinct subsurface lithological layers by interpreting resistivity curves and geoelectric sections across multiple sites, including clayey sands, dry sands, water-saturated sands, kaolinite clays, and shales. The resistivity data reveal a complex stratigraphy with varying aquifer depths and thicknesses, such as 39.5 meters and 97.3 meters. The study found that high resistivity values near the surface, indicative of porous and air-filled structures, significantly contribute to the area’s susceptibility to erosion. Soils with resistivity over 50 Ωm have an 87% probability of being highly erodible, which correlates with the gully-prone zones identified. The ERT results depict unstable heterogeneous zones, particularly those with sand lithology, prone to gully formation and potential landslides. Conversely, areas with consolidated kaolinite sand exhibit higher resistivity and lower susceptibility to erosion due to compaction and cement deposition in the sand’s pore spaces. The findings of this study underscore the critical role of subsurface lithology and resistivity characteristics in gully erosion processes. The study highlights the need for targeted erosion control measures and sustainable land management practices to mitigate the impact of gully formation in Ukpor Metropolis.

Risks of Gully Erosion in Valley (Wadi) Mazrwan Basin in Erbil Governorate Within Kurdistan Region of Iraq

Risks of Gully Erosion in Valley (Wadi) Mazrwan Basin in Erbil Governorate Within Kurdistan Region of Iraq

A Label Correction Learning Framework for Gully Erosion Extraction Using High-Resolution Remote Sensing Images and Noisy Labels

A Label Correction Learning Framework for Gully Erosion Extraction Using High-Resolution Remote Sensing Images and Noisy Labels

Evaluation of the Gully Erosion Risks in the Mamran Basin within Sulaymaniyah Governorate using GIS & RS

Evaluation of the Gully Erosion Risks in the Mamran Basin within Sulaymaniyah Governorate using GIS & RS

Multi-Scale Feature Extraction Model for Remote Sensing Identification of Erosion Gullies in Northeast China's Black Soil Region： A Case Study of Hailun City

Multi-Scale Feature Extraction Model for Remote Sensing Identification of Erosion Gullies in Northeast China's Black Soil Region： A Case Study of Hailun City

Performance Assessment of Machine Learning Techniques for Gully Erosion Mapping in South-East Nigeria

Soil erosion is a serious environmental hazard affecting southeast Nigeria. The rate of erosion has continued to increase with devastating impact and has led to land degradation (gullies). To assess the socio-economic and environmental implications of gully erosion and to develop management plans to deal with them, quantitative and qualitative data on soil erosion rates at regional scales are needed. Hence, this study aimed at investigating the spatial and temporal variations of gully erosion impacted areas of South East Nigeria using machine learning techniques to develop a suitable approach for accurately modelling gully erosion impact in South East, Nigeria. Its objectives are to: acquire, process, and perform object-based gully mapping analysis with Kompsat-3 imagery of South East Nigeria, Nigeria using three machine learning algorithms (Linear discriminant analysis, Support Vector Machine, and Artificial Neural Network); compare the performance of the three selected machine learning algorithms using statistical techniques and determine the best suited for gully mapping within the study area; determine the pattern and trend of Gully Erosion in South East, Nigeria between 2010 and 2020, using the best-suited machine learning algorithm; and predict the future gully development pattern for the next 10 years. The methodology involved the acquisition and use of KOMPSAT-3 imagery, identification of gully erosion impacted areas, and topographic maps. Image preprocessing, development of classification scheme, object-based image analysis, trend analysis, and pattern of gully development and expansion. Accuracy assessment and gully development prediction to 2030 as data analysis. The results showed consistent identification of eight class features, including waterbody, dense vegetation, agricultural land, bare ground, built-up area, sand, savannah, and gully erosion. The performance evaluation of the three techniques revealed promising outcomes. LDA achieved an accuracy of 0.759, while SVM demonstrated a higher accuracy of 0.853 and balanced sensitivity and specificity. ANN showed good performance with an accuracy of 0.790. Based on its superior accuracy and balanced performance, SVM was selected for mapping the spatial trend of gully erosion in the study area.

Testing the Reliability of Maximum Entropy Method for Mapping Gully Erosion Susceptibility in a Stream Catchment of Calabria Region (South Italy)

Gully erosion poses severe problems for land degradation in several areas worldwide. This study aims to evaluate the accuracy and robustness of the maximum entropy (MaxEnt) method for assessing gully erosion susceptibility. We selected the catchment of the Mesima stream as the test site, which is situated in the southwest sector of the Calabria region (South Italy). An inventory map of gully erosion was realised and 12 predisposing factors, such as lithology, soil texture, soil bulk density, land use, drainage network, slope gradient, aspect, length–slope (LS), plan curvature, stream power index (SPI), topographic position index (TPI), and topographic wetness index (TWI), were selected to implement the dataset in the MaxEnt method. The accuracy and uncertainty of the method were tested by 10-fold cross-validation based on accuracy, kappa coefficient, and receiver operating characteristic curve (ROC) and related area under curve (AUC). The dataset was randomly divided into 10 equal-sized groups (folds). Nine folds (90% of the selected dataset) were used to train the model. Instead, the remaining fold (10% of the dataset) was used for testing the model. This process was repeated 10 times (equal to the number of the folds) and each fold was used only once as the validation data. The average of 10 repeated processes was performed to generate the susceptibility map. In addition, this procedure allowed the reliability of the susceptibility map to be assessed, in terms of variables, importance and role of predisposing factors selected, prediction ability, and accuracy in the assessed probabilities for each pixel of the map. In addition to exploiting the 10-fold cross-validation, the mean value and standard deviation for the probability estimates of each pixel were computed and reported in the susceptibility and uncertainty map. The results showed that the MaxEnt method has high values of accuracy (>0.90), of the kappa coefficient (>0.80), and AUC (>0.92). Furthermore, the achieved findings showed that the capacity of the method used for mapping gully erosion susceptibility is quite robust when the training and testing sets are changed through the 10-fold cross-validation technique.

A strategy for modelling sediment distribution along slope lengths of an ephemeral gully through the simulated scouring experiments

Accurately describing the soil erosion process is crucial for improving the accuracy of existing simulation models of ephemeral gully erosion. However, a laboratory experimental strategy for simulating sediment distribution along slope lengths of an ephemeral gully is lacking. This limitation greatly hinders the development of simulation models for ephemeral gully erosion. In this study, we constructed six soil flumes with 12 m in length, 0.1 m in width, and 0.5 m in depth, which were filled with cultivated loess soils. Four flow rates (5.33, 10.67, 21.33, and 42.67 × 10−3 m3 s−1 m−1), four slope gradients (5°, 10°, 15°, and 20°), and six gully lengths (2, 4, 6, 8, 10 and 12 m) were adopted to perform a series of laboratory scouring experiments. The measured sediment concentrations at the outlet ranged from 23.39 kg m−3 to 534.60 kg m−3. The trend of exponential increase in sediment concentrations along slope lengths of an ephemeral gully was similar to that observed in a rill. According to the fitting equation, the maximum sediment concentrations (Ae) ranged from 358.05 kg m−3 to 910.88 kg m−3. The attenuation coefficients (Be) indicated the rate of increase in sediment load with slope length, which ranged from 0.042 m−1 to 0.185 m−1. By combining the measured sediment loads along the slope length (8 m) with the sediment transport capacity, the sediment distribution along slope lengths of an ephemeral gully could be accurately quantified. Moreover, the results confirmed that a flume with a short slope length (4/6 m) could effectively determine the sediment distribution along slope lengths at gentle slope of 5° and 10°. However, a minimum length of 8 m was advisable at steep slope of 15° and 20°. In summary, our experimental strategy provides an efficient method for determining the sediment distribution along slope lengths of an ephemeral gully.

Response of gully morphology and density to the spatial and rainy-season monthly variation of rainfall at the regional scale of the Chinese Loess Plateau

Gully erosion normally causes land degradation, especially on the Chinese Loess Plateau (CLP). However, research on gully spatial variations at larger regional scales, particularly considering the influence of rainfall, remains limited. The effects of monthly rainfall variations during the rainy season (June-September) on gully morphology and density have also been less explored. To narrow these gaps, we conducted a study in five representative catchments along a rainfall gradient in the CLP.Using high-resolution satellite imagery, we visually interpreted 2511 gullies and computed multiple gully morphological and density parameters, including length, area, volume, number density, length density and area density, etc. Long-term (1961–2014) monthly rainfall data and other environmental factors were analyzed to understand their impact on gully morphology and density.Results revealed that gully length, width and depth were crucial parameters representing gully morphology, exhibiting obvious variation across catchments. Generally, gully dimensions increased with higher rainfall, while densities decreased. Gully number density (GND) had a more significant impact on regional gully erosion degree than gully scales (length and area).Gully length and depth were primarily influenced by upslope runoff, while width mainly by runoff and potentially freezing and thawing. Rainfall in July and June-September, respectively, and especially the upslope catchment maximum slope were critical factors influencing gully head retreating and bottom incising, while June rainfall played a key role in sidewall collapsing. These result from the interplay of gully development sub-processes, monthly rainfall characteristics, and concurrent vegetation conditions. NDVI and July-September rainfall primarily determined GND at this scale, with the protective effect of rainfall-contributed vegetation outweighing rainfall’s promotion on gully occurrence.Our study highlights the importance of tailored gully erosion control measures that consider monthly rainfall variations and the significance of vegetation restoration in controlling new gully formation in the CLP and similar regions with comparable climatic and underlying-surface features.

Giving gully detection a HAND – Testing the scalability and transferability of a semi-automated object-orientated approach to map permanent gullies

Gully erosion can incur on- and off-site impacts with severe environmental and socio-economic consequences. Semi-automated mapping provides a means to map gullies systematically and without bias, providing information on their location and extent. If used temporally, semi-automated mapping can be used to quantify soil loss and identify soil loss source areas. The information can be used to identify mitigation strategies and test the efficacy thereof. We develop, describe, and test a novel semi-automated mapping workflow, gHAND, based on the distinct topographic landform features of a gully to enhance transferability to different climatic regions. Firstly, topographic heights of a Digital Elevation Model are normalised with reference to the gully channel thalweg to extract gully floor elements, and secondly, slope are calculated along the direction of flow to determine gully wall elements. As the gHAND workflow eliminates the need to define kernel thresholds that are sensitive towards gully size, it is more scalable than kernel-based methods. The workflow is rigorously tested at different gully geomorphic scales, in contrasting geo-environments, and compared to benchmark methods explicitly developed for region-specific gullies. Performance is similar to benchmark methods (variance between 1.4 % and 14.8 %). Regarding scalability, gHAND produced under- and over-estimation errors below 30.6 % and 16.1 % for gullies with planimetric areas varying between 1421.6 m2 and 355403.7 m2, without editing the workflow. Although the gHAND workflow has limitations, most markedly the requirement of manually digitising gully headcuts, it shows potential to be further developed to reliably map gullies of small- to large-scales in different geo-environments.

Geo-environmental factors controlling gully distribution at the local scale in a Mediterranean environment

The study was conducted with a view to identifying the primary factors controlling the formation and evolution of gullies in Central Portugal. A total of 38 permanent gullies were identified in an 11 km2 area. Their mean length, maximum width, and mean width were 105 m, 6.8 m, and 3.8 m, respectively, based on orthophotograph analysis. The gullies are located in an area of highly weathered granites which led to the formation of deeply weathered mantles. To understand gully distribution, 11 geo-environmental controlling factors were selected. Group Analysis (GA) identified two groups of gullies. These are differentiated not only by morphological aspects but also by geo-environmental elements. One group (Gg1) is characterised by being larger in size, and these tend to be located on hillslopes with a higher slope. The second group (Gg2) contains the smaller gullies that are located on the lower slopes of hillsides. Principal component analysis (PCA) identifies as controlling factors the slope, topographic ruggedness index (TRI), and vegetation gain (VG), after the October 2017 wildfire. Although this wildfire affected all the study area, the creation of higher burn severity mosaics positively enhanced the drainage and accelerated the gully erosion of Gg1, as well as the location of the nearest roads and paths, which emerge as a primary factor in the initiation and enlargement of this group of gullies. This study helps to better identify the current gully erosion conditions, and this can provide an important reference for risk assessment and control of gully erosion. Given the size of the gullies and the likelihood that recurring forest fires will affect the study area, some vital gully erosion control practices should be implemented urgently.

Assessment of the Effect of Bench Terracing in El Ogla and El Hadada Watersheds in Tunisia in the Context of Gully Erosion

The study of the erosive manifestation in El Ogla and El Hadada watersheds showed a strong and accelerated erosive dynamic. The aggression of the rains, the unstable nature of the Lower Eocene clays and the pressure of humans on the marginal lands seem to be at the origin of the instability of the slopes. Thus, the preservation of lands requires a colossal effort from the part of the State as well as the peasants. Unfortunately, the majority of developments have been implemented on an ad hoc basis and are far from being implemented comprehensively. In El Ogla and El Hadada watersheds, bench terracing is the most spectacular form of State intervention. It is considered by technicians as the unique solution for all forms of erosion. However, the appearance of forms of failure in various sectors cannot neglect the good functioning of some of them in the stability of the slopes and the reduction of the water slide. The objective of this applied research is to evaluate the behaviour of these benches as an interactive system with the other components of the natural environment based on photointerpretation, field monitoring and the results of the diagnosis of the balance sheet displacement of sediments obtained from the application of the isotopic method of Cesium 137. This assessment of bench terracing is largely based on the Bugeat formula, which seems to be the most appropriate method for determining the suitable dimensions of both height and terrace spacing.

Gully erosion susceptibility maps and influence factor analysis in the Lhasa River Basin on the Tibetan Plateau, based on machine learning algorithms

The environment of the Tibetan Plateau is under stress due to the warming climate and increased human activity, which also increases the risk of soil erosion. Gully erosion is one of the main environmental problems in the Tibetan Plateau. Taking Lhasa River Basin as a representative, investigating the spatial variation and influencing factors in this area will help to understand the current status and mechanism of gully erosion. However, gully erosion factor analysis has not been carried out at the regional scale. Therefore, three machine learning algorithms, including Random Forest (RF), Support Vector Machine, and Logistic Regression, were used to analyze 2224 samples and 18 influencing factors and detect the gully erosion susceptibility in the Lhasa River Basin. Seventy percent of the samples were used to train the model and rank the influencing factors by importance, and 30% were used to assess the prediction ability of the model. Approximately 15%–20% of the study area has a high or very high gully erosion susceptibility. The slopes of the lower Lhasa River and the Nyenchen Tanglha valleys were identified as areas with a high gully erosion susceptibility. The RF model exhibits the best performance, with area under the curve (AUC) values of 0.969 and 0.894 for the training and testing datasets, respectively. The main factors affecting the occurrence of gully erosion were determined to be the elevation, normalized difference vegetation index, relief, human footprint, mean annual temperature, and distance to the residential area. Elevation has the greatest effect on gully erosion, which can be explained as elevation indirectly controls gully erosion by affecting human activities and rainfall. The findings of this study provide insights into the effects of human activities, climate and permafrost on soil erosion and can serve as a basis for regional land use planning and gully erosion prevention and control in the Tibetan Plateau.

Soil erosion triggered by the archeological excavation and conservation of trenches. The case of “Cerro de las Trincheras” in Bailén (Jaén, Spain)

Gully erosion is a landform developed due to accelerated soil erosion rates. Gullies can be identified by human impacts on geomorphological processes, as well as hydrological and erosional systems. In Spain, the trenches or "trincheras" from the Spanish Civil War (1936-1939) are considered of archaeological interest for several reasons. At Cerro de las Trincheras in Bailén (Jaén, Spain), a trench was built during the Spanish Civil War. In 2020, an archaeological excavation took place to restore the ruins, triggering the development of gullies and rills and a decrease in vegetation quality. We present a first approximation of the variations in vegetation cover and the decrease in quality (using NDVI, the normalized difference vegetation index) due to the trench acting as a gully (1956, 2005-2020) and the increase in rills and gullies after the excavation. We strongly advocate for future archaeological excavations to include a protocol (soil mapping, vegetation survey, and hydrological connectivity index) to reduce soil degradation and prevent damage to vegetation and associated ecosystems, thereby curbing the increase in soil erosion rates.

The first inventory of gullies in the Upper Taquari River Basin (Brazil) and its agreement with land use classes

Gully erosion represents the most severe soil loss, with far-reaching consequences beyond the immediate site. Assessing the stability of gullies is particularly challenging in tropical regions with sandy soils and limited accurate data. Nonetheless, initiating gully inventories is a crucial first step in guiding public policies and conservation projects. In this study, we focus on the Upper Taquari River Basin (UTRB) situated on the fringes of the Brazilian Pantanal, where extensive erosion occurs in the upper regions and flooding occurs in the plains. We present the first qualitative and quantitative analysis of gullies in this region. Considering the historical context of the UTRB, it has long suffered from land mismanagement, particularly in livestock activities. Our objective was to evaluate the correspondence between gullies and land use classes in the MapBiomas Project, Brazil's most reliable non-governmental land use map, and the Rural Environmental Registry (CAR), the official information shared between landowners and public authorities. Thirteen remote-sensed indicators encompassing vegetation, water, soil, and terrain indices were assessed for 2022. Gullies were digitized through visual interpretation of a high-resolution Maxar Vivid Basic 2017 image. The classification was performed using the Random Forest (RF) algorithm, wherein pixels were classified into three classes: active, intermediate, and stable, based on the degree of vegetation cover and bare soil. The agreement of the gullies with the features of MapBiomas and CAR was also examined. The results revealed an overall accuracy of 96% and a Kappa index of 93% for the pixel classification. In the study area, 2960 gullies were digitized, with 60% classified as active features and only 2% as stable. Furthermore, the MapBiomas algorithm misclassified many pixels with active gullies as pasture. Conversely, the CAR data failed to identify gullies as areas demanding restoration. To address these issues, we recommend revising both land use maps to accurately represent the presence of erosions and improve decision-making that favors efficient conservation efforts of the region. As a further result of our actions, the method described here may prove valuable in formulating restoration plans for other tropical savanna regions.