Terrain Digital Elevation Model Research Articles

Historical residues of iron ore mining in environs of the Holy Cross Mountains (the Góry Świętokrzyskie) are recognizable on the Digital Terrain Elevation Model (DEM) derived from the LIDAR data

Historical residues of iron ore mining in environs of the Holy Cross Mountains (the Góry Świętokrzyskie) are recognizable on the Digital Terrain Elevation Model (DEM) derived from the LIDAR data

Paths of soil erosion controlled by typical soil and water conservation practices based on the SIMWE model: A case study of the Tongshuang watershed.

Due to the basic topographical characteristics of the gentle and long slope lengths in the Mollisol region of Northeast China, severe soil erosion is easily aggravated by the concentration of surface flow. The spatial distribution of water depth and hydrological connectivity index were introduced to evaluate the effects of typical soil and water conservation practices on the overland flow path and hydrological connectivity based on the GIS and SIMWE (SIMulated Water Erosion) model. We analyzed the effects of different soil and water conservation practices on the hydrological connectivity, water flow path, and spatial distribution of soil erosion and sediment yield by quantifying the variations of soil infiltration rate and surface manning roughness, as well as by constructing an artificial terrain digital elevation model (DEM). The results showed that: 1) terraces could effectively affect the hydrological connectivity of the slope and regulate flow path, with significant differences between the responses of hydrological connectivity and flow path under different forms of terraced fields and ridges. The characteristics of spatial distribution of soil erosion and sediment yield varied with changes in water flow path, which would eventually lead to the intensification of local erosion; 2) practices of vegetated buffer strips and contour tillage presented limited effectiveness on runoff path controlling, though they played a significant role in sediment retention; and 3) conservation tillage could reduce the hydrological connectivity and improve the retention capacity of runoff by increasing surface roughness. This study quantified the effects of different soil and water conservation practices on the hydrological connectivity, flow path, and spatial distribution of soil erosion and sediment yield, and could provide a theoretical reference for scientific layout of soil and water conservation practices in black soil region.

An Improved D8‐LTD for the Extraction of Total Contributing Area (TCA) by Adopting the Strategies of Path Independency and Local Dispersion

AbstractD8‐LTD is a path‐based flow direction algorithm for estimating total contributing area (TCA). However, the precision of D8‐LTD TCA is seriously challenged by the incorporation of flow paths and basic hypothesis of allowing only one receiving pixel. To solve above problems, this work proposes an improved D8‐LTD by adopting the strategies of path independency and local dispersion (i.e., LTD‐PI‐LD). Two indicators are adopted to quantify size and extent precisions of estimated TCAs relative to theoretical TCA. Then, LTD‐PI‐LD is compared with several typical single‐flow‐direction (SFD) algorithms (i.e., D8, D8‐LTD, LTD‐PI) and multiple‐flow‐direction (MFD) algorithms (i.e., MFD‐Quinn, D∞) on synthetic surfaces. Results indicate that (1) TCA maps of D8 and D8‐LTD contain too many singular high‐TCA tubes and source pixels, which are caused by the incorporation of flow paths and converging characteristics of SFD algorithms. (2) In MFD algorithms, the problem of artificial dispersion triggers the mechanisms of cross compensation and mutual amplification, leading to high size precision but low extent precision in estimated TCAs. (3) Strategy of path independency prevents the occurrence of high‐TCA tubes and effectively reduces the number of source pixels. (4) Both size and extent precisions of D8‐LTD TCAs are largely improved by introducing the strategies of path independency and local dispersion. Of all algorithms, LTD‐PI‐LD obtains the highest/second‐highest size precision and the highest extent precision in estimated TCAs. As a whole, LTD‐PI‐LD shows advantages of high precision in estimated TCAs, low computation cost, high efficiency and robustness to DEM (Digital elevation model) resolution and terrain type.

Integrated Geospatial Analysis and Hydrological Modeling for Peak Flow and Volume Simulation in Rwanda

The ability to adequately and continually assess the hydrological catchment response to extreme rainfall events in a timely manner is a prerequisite component in flood-forecasting and mitigation initiatives. Owing to the scarcity of data, this particular subject has captured less attention in Rwanda. However, semi-distributed hydrological models have become standard tools used to investigate hydrological processes in data-scarce regions. Thus, this study aimed to develop a hydrological modeling system for the Nyabarongo River catchment in Rwanda, and assess its hydrological response to rainfall events through discharged flow and volume simulation. Initially, the terrain Digital Elevation Model (DEM) was pre-processed using a geospatial tool (HEC-GeoHMS) for catchment delineation and the generation of input physiographic parameters was applied for hydrological modeling system (HEC-HMS) setup. The model was then calibrated and validated at the outlet using sixteen events extracted from daily hydro-meteorological data (rainfall and flow) for the rainy seasons of the country. More than in other events, the 15th, 9th, 13th and 5th events showed high peak flows with simulated values of 177.7 m3s−1, 171.7 m3s−1, 169.9 m3s−1, and 166.9 m3s−1, respectively. The flow fluctuations exhibited a notable relation to rainfall variations following long and short rainy seasons. Comparing the observed and simulated hydrographs, the findings also unveiled the ability of the model to simulate the discharged flow and volume of the Nyabarongo catchment very well. The evaluated model’s performance exposed a high mean Nash Sutcliffe Efficiency (NSE) of 81.4% and 84.6%, with correlation coefficients (R2) of 88.4% and 89.8% in calibration and validation, respectively. The relative errors for the peak flow (5.5% and 7.7%) and volume (3.8% and 4.6%) were within the acceptable range for calibration and validation, respectively. Generally, HEC-HMS findings provided a satisfactory computing proficiency and necessitated fewer data inputs for hydrological simulation under changing rainfall patterns in the Nyabarongo River catchment. This study provides an understanding and deepening of the knowledge of river flow mechanisms, which can assist in establishing systems for river monitoring and early flood warning in Rwanda.

Methodology for determining the physical parameters of ground plane by the results of the optical and radar data fusion

The methodology of multispectral optical and dual-polarized radar satellite data fusion for soils physical parameters estimation is developed. In particular, the methodology comprises relative permittivity estimation based on the Integral Equation Model (IEM) by using high resolution Sentinel-1 GRDH radar data. The calibration of ε was provided based on the compensation of soil acidity and temperature destabilizing effects. High-resolution multispectral images PlanetScope were used for vegetation indices and thermal emissivity estimation. Both, low-resolution MODIS and medium resolution Landsat-7/8 ETM+/TIRS thermal infrared images were processed in order to estimate ground plane thermodynamic temperature. An investigated approach for the radar signal depolarization compensation is based on local signal deviations and surface roughness estimation. The relief heterogeneity is restored based on the medium-resolution digital terrain elevation model ALOS AWD3D. Aiming to evaluate the accuracy of a soil moisture estimation model designed based on the presented methodology, ground truth measurements were carried out. Specifically, they included soil samples retrieving for the gravimetric soil moisture. In addition, the soil acidity and temperature were measured by applying the GM1312 differential thermometer and WALCOM multifunction device. The estimated parameters and ground truth data were used in order to retrieve the soil moisture based on the multivatiative regression dependence. Root mean square error of soil moisture retrieving was estimated as 4,73 %. Such accuracy is completely acceptable for the soil moisture monitoring of natural-reserved fund territories

IGS-CMAES: A Two-Stage Optimization for Ground Deformation and DEM Error Estimation in Time Series InSAR Data

Interferometric synthetic aperture radar (InSAR) has become an increasingly recognized remote sensing technology for earth surface monitoring. Slow and subtle terrain displacements can be estimated using time-series InSAR (TSInSAR) data. However, a substantial increase in the availability of exclusive time series data necessitates the development of more efficient and effective algorithms. Research in these areas is usually carried out by solving complicated optimization problems, which is very computationally expensive and time-consuming. This work proposes a two-stage black-box optimization framework to jointly estimate the average ground deformation rate and terrain digital elevation model (DEM) error. The method performs an iterative grid search (IGS) to acquire coarse candidate solutions, and then a covariance matrix adaptive evolution strategy (CMAES) is adopted to obtain the final local results. The performance of our method is evaluated using both simulated and real datasets. Both quantitative and qualitative comparisons using different optimizers support the reliability and effectiveness of our work. The proposed IGS-CMAES achieves higher accuracy with a significantly fewer number of objective function evaluations than other established algorithms. It offers the possibility for wide-area monitoring, where high precision and real-time processing is essential.

Research on Flood Disaster Simulation of Hongqi River Basin Based on HEC-RAS

At present, flood disasters are one of the main natural disasters in the world, and the research on flood disasters in current geography is also a research hotspot in recent years. Floods pose a serious threat to people’s lives and properties such as farmland and urban areas. Research on flood simulation can help reduce such losses to a certain extent. This paper takes the Hongqi River Basin in the upper reaches of the Tumen River as the research area, applies the Terrain Digital Elevation Model (DEM), uses the HEC-RAS model, and combines the HEC-GeoRAS module under the ArcGIS platform to build on the Tumen River as the terrain is more complicated. The hydrodynamic simulation of flood water flow when flood disaster occurs in the river basin, the rough visual analysis of the flood situation in the Hongqi River Basin, and the comparison and analysis with the measured data, will be used for future flood control early warning, disaster assessment, and Project site selection and other work provide reference data. The simulation analysis shows that HEC-RAS has a good simulation effect in this area and can provide decision support for flood prevention and control.

Analysis of terrain of site Mamatkheda Ratlam through wind modeling tool ArcGIS and WAsP

The influence of slope, height, and Weibull wind characteristics of terrain highly affect the wind power capacity of the wind farm. Before the installation of a wind farm, it is very beneficial to know about the complexity of our using site. This complexity of terrain is decided by RIX (Ruggedness Index) value. The economic profit in wind farm investment is purely dependent on energy production is forecasted before the installation of the wind turbine. This paper is about the complexity of terrain and wind resources assessment at Mamatkheda Ratlam [M.P.]. The digital elevation model of terrain on the selected site is obtained using ArcGIS software and then later on digitized roughness model in WAsP software. The wind data is further extrapolated at height heights while considering the effect of different roughness length. The result indicates the ruggedness index factor for the terrain is 0.2 which satisfies the condition of flat terrain.

Evaluation of the Vertical Accuracy of Open Global DEMs over Steep Terrain Regions Using ICESat Data: A Case Study over Hunan Province, China.

The global digital elevation model (DEM) is important for various scientific applications. With the recently released TanDEM-X 90-m DEM and AW3D30 version 2.2, the open global or near-global coverage DEM datasets have been further expanded. However, the quality of these DEMs has not yet been fully characterized, especially in the application for regional scale studies. In this study, we assess the quality of five freely available global DEM datasets (SRTM-1 DEM, SRTM-3 DEM, ASTER GDEM2, AW3D30 DEM and TanDEM-X 90-m DEM) and one 30-m resampled TanDEM-X DEM (hereafter called TDX30) over the south-central Chinese province of Hunan. Then, the newly-released high precision ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) altimetry points are introduced to evaluate the accuracy of these DEMs. Results show that the SRTM1 DEM offers the best quality with a Root Mean Square Error (RMSE) of 8.0 m, and ASTER GDEM2 has the worst quality with the RMSE of 10.1 m. We also compared the vertical accuracies of these DEMs with respect to different terrain morphological characteristics (e.g., elevation, slope and aspect) and land cover types. It reveals that the DEM accuracy decreases when the terrain elevation and slope value increase, whereas no relationship was found between DEM error and terrain aspect. Furthermore, the results show that the accuracy increases as the land cover type changes from vegetated to non-vegetated. Overall, the SRTM1 DEM, with high spatial resolution and high vertical accuracy, is currently the most promising dataset among these DEMs and it could, therefore, be utilized for the studies and applications requiring accurate DEMs.

Quantitative assessment of the influence of terrace and check dam construction on watershed topography

Terrace and check dam construction has substantially changed land surface morphology, which in turn affects modern surface processes. Digital elevation models (DEMs) provide an effective way to quantitatively analyze surface morphology and processes. However, existing DEMs lack sufficient ability to express artificial terrain. Based on 1:10000 topographic maps of the Zhifanggou watershed, a series of artificial terrain DEMs for the study site were constructed by both field investigation and remote sensing images from 1938 to 2010. Digital terrain analysis was used to quantitatively assess the influence of terrace and check dam construction on the watershed terrain. The results showed that the artificial terrain DEM could capture the spatial distribution patterns of terraces and dam lands and improved the ability of DEM to express terrain. The construction of terraces and check dams clearly changed the surface elevation. The average elevation change of each terrace mainly ranged between —1.5 and 1.5 m, while the annual average deposition height of the dam lands was 9.16 cm. The average slope, slope length, and slope length and steepness factor of the watershed decreased with the effect of the artificial terrain on the surface, and their averages decreased by 0.65°, 6.75 m, and 0.83, respectively, from 1938 to 2010. Although the construction of terraces reduced their surface slope to nearly 0°, the slope of terrace embankments rapidly increased, to more than 45°, which may lead to gravitational erosion and potential terrace damage. Terracing reduced the slope length in both the terrace distribution area and downslope of the terraces. Check dam deposition reduced the slope and slope length of the channel. This study contributes to a better understanding of the topographic change rules after terrace and check dam construction, and aids in elucidating the mechanisms of soil erosion process influenced by artificial topography.

Integrated 1D and 2D model for better assessing runoff quantity control of low impact development facilities on community scale

This study proposes a modelling framework of integrated one-dimensional (1D) and two-dimensional (2D) hydrodynamic modelling to evaluate the effectiveness of sponge city construction at community scale. Through a case study in Zhuhai, we integrate Stormwater Management Model (SWMM) and Cellular Automata Dual-DraInagE Simulation (CADDIES) 2D model to analyze the rainfall-runoff process involving green infrastructures. SWMM is applied to analyze the change of surface runoff control effects before and after the implementation of sponge city low impact development (LID) facilities, and CADDIES is adopted to simulate the propagation of excess runoff on the surface. The results show that the LID facilities can effectively reduce the runoff volume of small and medium-sized rainfall events since the maximum runoff reduction rate is 94.4%. For long-term operation, the LID can capture 52.9% of annual rainfall volume and reduce annual runoff by 28.0%. However, the CADDIES 2D model simulations indicate that LID facilities have little effect on flood alleviation in specific regions under extreme rainfall conditions. In addition, we compared the modelling performance using four different terrain Digital Elevation Model (DEM) resolutions and found that 1 m terrain DEM resolution can produce comparable results to 0.25 m DEM with a fraction of computational time. We also find that the MIKE FLOOD model and the integrated model of SWMM and CADDIES 2D can obtain similar simulation results, the p-value = 0.09 which is >0.05, but SWMM-CADDIES integrated model is more suitable for small-scale simulation.

ESTIMATION OF MAIZE BIOMASS USING UNMANNED AERIAL VEHICLES

ABSTRACT Unmanned aerial vehicles (UAVs) are a promising tool for technology development and transfer and for the economic success of the agricultural sector. The objective of this study is to assess the validity of biomass estimation in a commercial maize plantation using aerial images obtained by a UAV. The proposed methodology involved analyzing images acquired in scheduled flights, processing orthophoto (georeferenced image) data, evaluating digital terrain elevation models, and assessing the quality of dense point clouds. Data were collected using two cameras, one with a 16-megapixel flat lens and the other with a 12-megapixel fish-eye lens coupled to a UAV, at two flight altitudes (30 and 60 meters) over hybrid maize (AG1051) crop irrigated by center pivot in the municipality of Limoeiro do Norte, Ceara, Brazil. Crop biomass was estimated in 1 m2 plots sampled randomly, and data were validated by interpreting aerial images of target areas. The measurements of biomass using UAV-based aerial images were promising. The estimated values were more accurate using the fish-eye lens at 30 m altitude, corresponding to 2.97 kg m-2, which is very close to the values measured in the field (2.92 kg m-2).

Combined Use of Terrestrial Laser Scanning and UAV Photogrammetry in Mapping Alpine Terrain

Airborne and terrestrial laser scanning and close-range photogrammetry are frequently used for very high-resolution mapping of land surface. These techniques require a good strategy of mapping to provide full visibility of all areas otherwise the resulting data will contain areas with no data (data shadows). Especially, deglaciated rugged alpine terrain with abundant large boulders, vertical rock faces and polished roche-moutones surfaces complicated by poor accessibility for terrestrial mapping are still a challenge. In this paper, we present a novel methodological approach based on a combined use of terrestrial laser scanning (TLS) and close-range photogrammetry from an unmanned aerial vehicle (UAV) for generating a high-resolution point cloud and digital elevation model (DEM) of a complex alpine terrain. The approach is demonstrated using a small study area in the upper part of a deglaciated valley in the Tatry Mountains, Slovakia. The more accurate TLS point cloud was supplemented by the UAV point cloud in areas with insufficient TLS data coverage. The accuracy of the iterative closest point adjustment of the UAV and TLS point clouds was in the order of several centimeters but standard deviation of the mutual orientation of TLS scans was in the order of millimeters. The generated high-resolution DEM was compared to SRTM DEM, TanDEM-X and national DMR3 DEM products confirming an excellent applicability in a wide range of geomorphologic applications.

Airborne Waveform Lidar Simulator Using the Radiative Transfer of a Laser Pulse

An airborne lidar simulator creates a lidar point cloud from a simulated lidar system, flight parameters, and the terrain digital elevation model (DEM). At the basic level, the lidar simulator computes the range from a lidar system to the surface of a terrain using the geomatics lidar equation. The simple computation effectively assumes that the beam divergence is zero. If the beam spot is meaningfully large due to the large beam divergence combined with high sensor altitude, then the beam plane with a finite size interacts with a ground target in a realistic and complex manner. The irradiance distribution of a delta-pulse beam plane is defined based on laser pulse radiative transfer. The airborne lidar simulator in this research simulates the interaction between the delta-pulse and a three-dimensional (3D) object and results in a waveform. The waveform will be convoluted using a system response function. The lidar simulator also computes the total propagated uncertainty (TPU). All sources of the uncertainties associated with the position of the lidar point and the detailed geomatics equations to compute TPU are described. The boresighting error analysis and the 3D accuracy assessment are provided as examples of the application using the simulator.

Innovative use of GIS and drone photogrammetry for cliff stability modelling

Evaluating the condition and stability of coastal cliffs and assessing longevity of significant overhangs and undercuts in an active marine environment is a challenge. As part of cliff management studies undertaken for the Coastal Zone Management Unit of the government of Barbados, a programme of innovative cliff profile mapping was conducted around the island of Barbados. A combination of land-based field mapping information and fixed wing aircraft collected high-resolution LiDAR imagery was utilised for cliff geometry assessments, supplemented for specific cliff profiles by fill-in high-precision three-dimensional (3D) digital terrestrial imagery, captured by low level wide wingspan UAV drone flights. Comprehensive photogrammetric processing of this imagery, combined with detailed geographic information system software evaluation of the collected point cloud data, allowed generation of full 3D wireframe digital terrain and digital elevation models (DTMs and DEMs). Multiple representative cliff areas around the island were identified, allowing thorough 3D stability assessment to be accomplished of key problematic areas using Flac3D. Vertical cross-section profiles were also cut so that undercut and notched cliffs could be analysed in detail in two dimensions using Voronoi tessellation approaches applied within the universal distinct element code UDEC as a means to replicate the characteristics of the vuggy coralline limestone cliffs.

Uncertainty modeling and analysis of surface area calculation based on a regular grid digital elevation model (DEM)

ABSTRACTIn the field of digital terrain analysis (DTA), the principle and method of uncertainty in surface area calculation (SAC) have not been deeply developed and need to be further studied. This paper considers the uncertainty of data sources from the digital elevation model (DEM) and SAC in DTA to perform the following investigations: (a) truncation error (TE) modeling and analysis, (b) modeling and analysis of SAC propagation error (PE) by using Monte-Carlo simulation techniques and spatial autocorrelation error to simulate DEM uncertainty. The simulation experiments show that (a) without the introduction of the DEM error, higher DEM resolution and lower terrain complexity lead to smaller TE and absolute error (AE); (b) with the introduction of the DEM error, the DEM resolution and terrain complexity influence the AE and standard deviation (SD) of the SAC, but the trends by which the two values change may be not consistent; and (c) the spatial distribution of the introduced random error determines the size and degree of the deviation between the calculated result and the true value of the surface area. This study provides insights regarding the principle and method of uncertainty in SACs in geographic information science (GIScience) and provides guidance to quantify SAC uncertainty.

Building digital topography model of the intertidal zone between Caofeidian Nanpu town and Tanggu district using multi-period remote sensing data

The intertidal zone, a change zone of land and sea interaction, has abundant land reserves, tourism and other resources, which has a location advantage of great engineering construction in China’s coastal areas and thus is very important to investigate and monitor the topography of the tidal zone and also keep track of its topographic changes. In this study, the new section of the Bohai sea coastal zone from Nanpu to Tianjin Bohai sea area has been chosen as an example. Based on the terrain feature of the information expressed by the multi-period remote sensing image information and the tidal water level information as well as the tidal data acquisition time in the remote sensing image data, we have been calculated the water line (or edge point) digital elevation topography inversion analysis, and also constructed the digital terrain elevation model, and most importantly have provided a kind of quantitative method to get tidal zone (tide beach) terrain information.

Uncertainty modelling and analysis of volume calculations based on a regular grid digital elevation model (DEM)

The accuracy of earthwork calculations that compute terrain volume is critical to digital terrain analysis (DTA). The uncertainties in volume calculations (VCs) based on a DEM are primarily related to three factors: 1) model error (ME), which is caused by an adopted algorithm for a VC model, 2) discrete error (DE), which is usually caused by DEM resolution and terrain complexity, and 3) propagation error (PE), which is caused by the variables' error. Based on these factors, the uncertainty modelling and analysis of VCs based on a regular grid DEM are investigated in this paper. Especially, how to quantify the uncertainty of VCs is proposed by a confidence interval based on truncation error (TE). In the experiments, the trapezoidal double rule (TDR) and Simpson's double rule (SDR) were used to calculate volume, where the TE is the major ME, and six simulated regular grid DEMs with different terrain complexity and resolution (i.e. DE) were generated by a Gauss synthetic surface to easily obtain the theoretical true value and eliminate the interference of data errors. For PE, Monte-Carlo simulation techniques and spatial autocorrelation were used to represent DEM uncertainty. This study can enrich uncertainty modelling and analysis-related theories of geographic information science.

A new method for estimation of spatially distributed rainfall through merging satellite observations, raingauge records, and terrain digital elevation model data

This study develops a new method to estimate spatially distributed rainfall through merging the satellite observation, the raingauge record, and the terrain digital elevation model (DEM) data, including the following four steps: (1) to select a suitable satellite observation dataset, (2) to downscale the selected satellite observation dataset with the DEM data, (3) to determine the weighted differences between the raingauge record and the downscaled satellite observation dataset, and (4) to calculate the spatially distributed rainfall through merging the downscaled satellite observation dataset and the weighted differences. The rainstorm occurred on 21 July 2012 in Beijing, China, was considered as a case study to validate the method. Three satellite observation datasets (i.e., TMPA 3B41RT, 3B42RT and CMORPH) were compared with the related raingauge record. Using the new method, this study generated the spatially distributed rainfall data, which were further compared with the three rainfall datasets, i.e., two original rainfall datasets (the selected satellite observation dataset and the raingauge record) and one merged rainfall dataset without consideration of topographic influence. The result revealed that the merged spatially distributed rainfall data is a more rational representation of the actual rainfall than the three other datasets. Furthermore, using this data merging method and a hydrological model, the Digital Yellow River Integrated Model (DYRIM), this study simulated the streamflow process at the Dashi River basin in the southwest of Beijing and the Qingjian River basin in the middle Yellow River. The simulation results showed that the spatially distributed rainfall data could have better performance than those three other datasets, especially for the peak flow simulation. Overall, it is concluded that this data merging method can enhance our capability in estimating the spatial distribution of rainfall.

The Integration of Ecosystem Services in Planning: An Evaluation of the Nutrient Retention Model Using InVEST Software

Mapping ecosystem services (ES) increases the awareness of natural capital value, leading to building sustainability into decision-making processes. Recently, many techniques to assess the value of ES delivered by different scenarios of land use/land cover (LULC) are available, thus becoming important practices in mapping to support the land use planning process. The spatial analysis of the biophysical ES distribution allows a better comprehension of the environmental and social implications of planning, especially when ES concerns the management of risk (e.g., erosion, pollution). This paper investigates the nutrient retention model of InVEST software through its spatial distribution and its quantitative value. The model was analyzed by testing its response to changes in input parameters: (1) the digital terrain elevation model (DEM); and (2) different LULC attribute configurations. The paper increases the level of attention to specific ES models that use water runoff as a proxy of nutrient delivery. It shows that the spatial distribution of biophysical values is highly influenced by many factors, among which the characteristics of the DEM and its interaction with LULC are included. The results seem to confirm that the biophysical value of ES is still affected by a high degree of uncertainty and encourage an expert field campaign as the only solution to use ES mapping for a regulative land use framework.