Ground Surface Characteristics Research Articles

Evaluations of ground surface heat fluxes and its potential vegetation effects in the permafrost region of northeastern China

Ground surface-air temperature difference (GATD) is the primary source of sensible heat flux from the ground surface, and vegetation inevitably affects it by altering the ground surface characteristics. However, the relationship between vegetation and GATD in the permafrost region has not been well-elucidated. Using meteorological station data, National Oceanic and Atmospheric Administration Climate Data Record Normalized Difference Vegetation Index (NOAA CDR NDVI) data, and some auxiliary data, this study aims to investigate the patterns of GATD in the Northeast China permafrost region and quantify the response of GATD to vegetation changes. The study employs trend analysis, Geodetector, and correlation analysis methods. The results show that the GATD in the Northeast China permafrost region decreased from west to east and the annual mean GATD exhibited an upward from 1982 to 2020. The relationship between NDVI and GATD trend is non-linear, in areas with low vegetation, vegetation changes amplify the GATD trend, while in areas with high vegetation, vegetation changes inhibit the GATD trend. Furthermore, the rate of GATD increase is higher in the discontinuous permafrost (DP) region than in the sporadic permafrost (SP) and isolated permafrost (IP) regions, suggesting that the DP region may have experienced a faster ground surface state change process. The findings of this study will provide new insights for evaluating permafrost degradation and studying the resulting ecological environmental effects in the permafrost region.

Simulation of urban surface temperature and surface heat balance in the Tokyo metropolitan area

This study aimed to propose a method for simulating ground surface temperature and surface heat balance using thermal infrared remote sensing and an urban surface heat balance model and to conduct a simulation in the Tokyo metropolitan area. Previous studies have typically employed ground surface temperatures obtained through satellite remote sensing to analyze urban thermal environments. However, these studies were limited to using surface temperature data available only at the time of satellite passage. Therefore, in this study, we conducted a simulation for the Tokyo metropolitan area by integrating a one-dimensional heat balance model with ground surface temperatures observed by satellites. The novelty of this study lies in the utilization of parameters related to heat balance obtained through calculations of physical processes, as opposed to relying on empirical formulas or parameters. Consequently, realistic ground surface characteristics, including parameters such as evaporation efficiency and thermal inertia essential for the simulation, were derived by this combined method. Furthermore, diurnal variations in ground surface temperature distributions were accurately represented by using realistic surface temperature data based on satellite remote sensing, considering the effect of heat storage in urban areas—an aspect challenging to reproduce using conventional local meteorological models.

Spatio-Temporal Evolution of Loading and Deformation of Surface Gas Pipelines for High-Intensity Coalbed Mining and Its Integrity Prediction Methodology

In recent years, the integrity of the gas pipeline in the coal-gas co-mining subsidence area has become a critical problem, restricting the safe and efficient mining of coal resources. This paper establishes a theoretical model for the safety prediction of gas pipelines in mining subsidence areas based on elastic free theory, constructs a 3D model of pipe-sand soil by using ABAQUS simulation software (2021), analyzes the characteristics of ground surface and pipeline settlement combined with the measured data on-site, and reveals the temporal and spatial evolution law of the pipeline load and deformation under the condition of diagonal intersections of the pipeline and high-strength mining working face. The results show that during the mining cycle, the pipe and the sandy soil body experienced the stage of cooperative deformation, the stage of increasing non-cooperative deformation, and the stage of weakening non-cooperative deformation; the pipe body is most vulnerable to yield failure in the circumferential direction of 180°, 45°, 225°, and 0°; the relative deformation rate of the pipe experienced a slow and rapid increase in the stage, and tends to flatten out when the advancement length is about 1.5–2 times the distance at the taken cross-section. The study’s results are conducive to accurately predicting the pipe failure orientation under high-intensity mining conditions in coal seams, improving the diagnostic efficiency of pipes, and optimizing the advancement speed of the working face.

Aridification alters the diversity of airborne bacteria in drylands of China

Dryland ecosystems, which vary sensitively to drought owing to climate change and human activities, frequently cause large-scale aeolian dispersal of terrestrial-mineral and biological particles. To date, very few studies have focused on the atmosphere-land exchange of bacteria in drylands. To understand the bacterial transport from the terrestrial environment to the atmosphere over drylands, soil and aerosol samples were collected at 19 sites in arid and semi-arid regions across drylands of China in the summer of 2017. The 16S rRNA gene sequencing revealed that the bacterial diversity in the atmosphere was significantly lower than that in terrestrial ecosystems for all the collected samples. Moreover, bacterial diversity in the atmosphere increases in arid regions compared to semi-arid regions, while those of the terrestrial environment were maintained regardless of the region. Additionally, the terrestrial bacterial sources contributed to the airborne bacteria more significantly in arid regions than those in semi-arid regions (accounting for 10.0 ± 1.1% and 3.5 ± 1.1%, respectively). The arid conditions tended to enhance the atmospheric emissions of Chloroflexi, while the members of Bacteroidetes were dominant in both the atmospheres of the semi-arid and arid regions. The differences in bacterial community structures between the terrestrial and atmospheric ecosystems are thought to depend on the ground surface characteristics such as vegetation and terrestrial substrates. Meteorological drought may alter terrestrial characteristics, which regulate airborne bacterial dispersal from dryland to its downwind regions, suggesting that more attention should be paid to the bacterial roles in the biology-health-climate process in the future.

Effects of feed direction on material removal behavior in belt grinding of titanium alloys

For abrasive belt grinding, although machine processing selection has been well studied to achieve good machinability, there is still a lack of understanding regarding the influence of feed direction and its mechanism, even though it is a common matter. This paper investigates the differences between up- and down-grinding in belt grinding of TC4, where the grinding forces, material removal performance, surface quality, and chip morphology are captured for the grinding process evaluation and mechanistic analysis In up grinding, it was observed that approximately 21.1 % more material removal can be achieved due to the larger penetration depth of scratching grains when maintaining a constant normal grinding force. Furthermore, the higher tangential grinding force resulting from increased cutting behavior and an additional sliding phase leads to more severe abrasive belt wear, as evidenced by a 22.7 % higher grinding ratio. Comparatively, down grinding mode generates a machined surface with lower roughness in the transverse and longitudinal direction, which can be explained by the minimum chip thickness effect and undeformed chip thickness model. The microscopic characteristics of chips and ground surface provide more evidence on the different chip formation mechanisms between two grinding modes.

NEAR SURFACE AIR TEMPERATURE ESTIMATION THROUGH PARAMETRIZATION OF MODIS PRODUCTS

Abstract. Near-surface air temperature is a key factor in many studies and its spatiotemporal patterns are highly dependent on the ground surface characteristics and vary over time and space. So Land Surface Temperature (LST) is an important parameter for air temperature estimation. In this study, it is tried to model the air temperature by deploying some of the parameters that affect it . The parameters that have been taken into account in this study include land surface temperature, Normalized Difference Vegetation Index (NDVI), Vapor Pressure (VP) and Lifted Index (LI) as a measure of atmospheric stability. To assess the impact of each of these parameters, different linear regression models, were tested. Support Vector Regression (SVR) and hybrid artificial neural network methods were also performed. To model and evaluate the time series data of Georgia State in The United States of America over 1 year have been used. The NDVI, Total Precipitable Water (TPW), LST and LI parameters are products of MODIS. VP is calculated by using a logarithmic model from the TPW. Finally, it was found out that the LST and VP have positive effects, LI has negative and NDVI had a slightly positive impact on the air temperature at 2 meters height. The achieved accuracy in the linear model when all parameters are involved was 2.29 °C with a correlation coefficient of R=0.96. Next, the SVR model was examined and applied to the linear model taking all parameters into account. It was found that it does not end up to any significant increase in accuracy but certainly increases the computation time. The accuracy of this model was about 2.25 °C with a correlation coefficient of 0.96. Finally, a hybrid artificial neural network was examined. It was found that it increases the accuracy but certainly increases the computation time. The achieved accuracy of this model was about 2.14 °C with a correlation coefficient of 0.96.

Assessment of the effect of surface roughness on electrochemical characteristics of AZ80 magnesium alloy treated by PEO

The main purpose of this article, is to provide the evaluation of the influence of selected pre-treatment method, mainly grinding by various emery papers, which were used before the plasma electrolytic oxidation (PEO) process to assess the electrochemical characteristics of AZ80 magnesium alloy in 0.1 M NaCl solution. Moreover, the exposure time of the PEO pretreatment was set on 14 min. Subsequently, the surface roughness of PEO coatings was analyzed by confocal microscope. In the next step, electrochemical characteristics of ground surfaces with prepared PEO coatings were determined by the potentiodynamic polarization (PDP) at the laboratory temperature.

Quantifying effects of explicit representation of buildings in tsunami inundation simulations

One of the critical steps in quantifying tsunami hazard is modelling of inundation. There are many factors influencing the complex inundation process, including the role played by features such as buildings affecting flow patterns which, if not simulated well, can affect the accuracy of tsunami intensity measure (IM) estimates (e.g. flow depth) and consequently, the reliability of outputs produced (e.g. economic loss estimates) by other models that utilise the estimated IM. In this paper, the effects of two alternative approaches to represent buildings in inundation modelling are investigated: (a) Equivalent Surface Roughness (ESR) approach, in which buildings and other ground surface features are removed and their effects on tsunami flows are approximated by spatially averaged surface roughness values; and (b) Explicitly Represented Building (ERB) approach, in which buildings are explicitly presented in the simulations to directly influence tsunami inundation. Using comparative simulations, this study quantifies the effects of explicit representation of buildings in inundation modelling on tsunami flow depth estimates and investigate how such effects consequently influence loss modelling results. We assess four plausible major earthquake-triggered tsunami scenarios for Napier, New Zealand. The modelling results suggest that the ERB approach better captures tsunami flow patterns and hence provides more realistic hazard and loss estimates. However, the difference in the estimated loss arising from potential direct damage caused by tsunami inundation (i.e. ERB vs. ESR) is shown to reduce in scenarios causing large-scale inundation, both in terms of severity and spatial extent, over the built-up area in the study region.

Spatial Distribution of Permafrost in the Xing’an Mountains of Northeast China from 2001 to 2018

Permafrost is a key element of the cryosphere and sensitive to climate change. High-resolution permafrost map is important to environmental assessment, climate modeling, and engineering application. In this study, to estimate high-resolution Xing’an permafrost map (up to 1 km2), we employed the surface frost number (SFN) model and ground temperature at the top of permafrost (TTOP) model for the 2001–2018 period, driven by remote sensing data sets (land surface temperature and land cover). Based on the comparison of the modeling results, it was found that there was no significant difference between the two models. The performances of the SFN model and TTOP model were evaluated by using a published permafrost map. Based on statistical analysis, both the SFN model and TTOP model efficiently estimated the permafrost distribution in Northeast China. The extent of Xing’an permafrost distribution simulated by the SFN model and TTOP model were 6.88 × 105 km2 and 6.81 × 105 km2, respectively. Ground-surface characteristics were introduced into the permafrost models to improve the performance of models. The results provided a basic reference for permafrost distribution research at the regional scale.

Surface generation in high-speed grinding of brittle and tough ceramics

Grinding induced sub-surface defects substantially impair the functionality of ceramic components. Effective control of such defects is possible through identification and understanding the governing factors. The present work investigates the interaction of abrasive grits over the ground surface to identify the governing factors for effective control of such defects during high-speed grinding of a brittle (alumina) and a tough (yttria-stabilized zirconia (YSZ)) ceramic. High-speed grinding was carried out using single-layer electroplated diamond grinding wheels in the speed range of 40–200 m/s. The important grinding characteristics, such as material removal mode, residual stress, surface roughness, etc., were correlated with the maximum uncut chip thickness (hm) and the scallop height (Sg). The hm represents the interaction of active grits at the exit of the grinding zone, whereas the interaction of active grits while entering the grinding zone (at ground surface) leads to the formation of scallops. Instead of hm, material removal mode and other related grinding characteristics are found to be governed by the Sg. An efficient reduction of approximately 90 % in Sg is realized by increasing the grinding speed from 40 m/s to 200 m/s. For a brittle ceramic like alumina, such a drastic reduction in Sg reduced grinding induced defects by more than 75 %. For a tougher ceramic like YSZ, a reduction of more than 30 % in the magnitude of compressive residual stress is observed with a reduction in Sg at a higher grinding speed of 200 m/s. This study manifests Sg as a predominant factor in governing the ground surface characteristics during ceramic grinding, which can be effectively utilized to control grinding induced defects in ground ceramic parts.

Influence of alumina abrasive tool wear on ground surface characteristics and corrosion properties of K444 nickel-based superalloy

K444 nickel-based superalloy is an important material to manufacture the gas turbine due to its excellent mechanical properties at high temperatures and corrosion resistance. Currently, grinding is the mostly used method for the surface finish of the K444 alloy components. However, few studies worked on the effects of the abrasive tool wear on the ground surface characteristics and corrosion properties of K444 alloy. This study uses two different-type alumina abrasive tools, i.e., white alumina (WA) and microcrystalline alumina (MA) wheels, to grind the K444 alloy. The influence of the alumina abrasive tool wear on ground surface characteristics and corrosion resistance performance are investigated. It is discovered that the MA wheel presents a slighter wheel wear and higher self-sharpening than the WA wheel. Compared to the WA wheel, the MA wheel has less material adhesion, which leads to a better surface finish. In the corrosion testing, the maximum corrosion depth is 80 μm in the surface ground by the MA wheel but 100 μm in the surface ground by the WA wheel, which demonstrates that the MA wheel grinding benefits the surface corrosion resistance of K444 alloy. Therefore, this study could provide a guide to selecting the abrasive tools and optimizing the grinding process of the K444 alloy.

A Machine Learning Approach to Objective Identification of Dust in Satellite Imagery

AbstractAirborne dust has broad adverse effects on human activity, including aviation, human health, and agriculture. Remote sensing observations are used to detect dust and aerosols in the atmosphere using long established techniques. False color Red‐Green‐Blue (RGB) imagery using band differences sensitive to dust absorption (Dust RGB) is currently used operationally to assist forecasters and decision‐makers in identifying dust at night, but there are still limitations, subjectivity, and nuances to image interpretation making night‐time dust identification difficult even for experts. This study applies machine learning to the problem of night‐time dust detection with a simple random forest (RF) model using Geostationary Operational Environmental Satellite‐16 (GOES‐16) Advanced Baseline Imager (ABI) infrared imagery, band differences sensitive to dust absorption, and Dust RGB color components as inputs to the model. The RF model achieves an Area‐Under‐Curve (AUC) of 0.97 with a standard deviation of 0.04 for dust cases. For images with dust present, the model correctly labels 85% of dust pixels and 99.96% of no‐dust pixels for all dust images in the validation data set. The addition of a single null case to the training data set drastically reduces error in labeling no‐dust pixels as dust from 45% to 14.5%. Application of the machine learning model to the April 13–14, 2019 dust event demonstrates the ability of the model to identify dust during night‐time hours when visual dust detection is limited by the cooling ground surface characteristics.

SARF: A Simple, Adjustable, and Robust Fusion Method

Pansharpening aims to sharpen a low spatial resolution (LR) multispectral (MS) image using a high spatial resolution (HR) panchromatic (PAN) image to obtain the HR MS image. Though large numbers of pansharpening methods have been proposed, and many advanced methods have shown high quantitative results, few of them are widely used in real applications. This may be attributed to their instability for different images with different ground surface features, or the complexity to be implemented and the time-consuming process for some state-of-the-art methods. In this letter, we proposed a simple, adjustable, and robust fusion (SARF) method. In the proposed method, a spatial-spectral coenhanced strategy was proposed, and several details of the proposed fusion model were specifically designed for the “simple, adjustable, robust” features. It was tested and verified by four-band and eight-band MS images based on reduced resolution (RR) and full resolution (FR) experiments. The experimental results demonstrated the promising spatial visuality of the proposed method, and the spectral fidelity was more robust than most of component substitution (CS)-based and multiresolution analysis (MRA)-based methods.

Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

Evaluation of Grinding Wheel Surface Shape on Difference Multiple Helical Dressing Condition

In the grinding process, a grinding wheel surface is a tool that is directly applied to the workpiece. As the condition of the grinding wheel surface is determined by its dressing conditions, the ability to accurately measure the grinding wheel surface with an applied dressing would enable the prediction of the ground surface characteristics of the workpiece as well as the determination of optimum dressing conditions. Recently, a new dressing method called the multiple helical dressing was proposed, which has led to improvements in the grinding performance. However, there is still no method to quantitatively evaluate the changes in the grinding wheel surface condition caused by multiple helical dressings. In this study, we measured the grinding wheel surface applied with multiple helical dressings using a so-called measured focus position recalculation method to determine whether we can quantitatively evaluate the measured dressing grooves generated on the grinding wheel surface by multiple helical dressings, and the resultant undulated grinding wheel surface shapes. We ground an actual workpiece to demonstrate the effects of changes in the grinding wheel surface shape due to multiple helical dressings on the ground surface of the workpiece. The experimental results show that our proposed measuring method can accurately measure the changes in the grinding wheel surface condition due to multiple helical dressings. We also proposed a method to evaluate the dressing grooves to prove that we can quantitatively evaluate the measurement results of dressing grooves generated by multiple helical dressings. In addition, we evaluated undulated grinding wheel surface shapes as its cylindricities by extracting only the undulation shapes generated by multiple helical dressings. Finally, we performed groove grinding with a grinding wheel applied with multiple helical dressings to reveal the relationship between the ground surface of the workpiece and the grinding wheel surface condition, which demonstrated the effectiveness of multiple helical dressings.

Nesting habitat of ground‐nesting bees: a review

About 3/4 of all wild bee species nest in the soil and spend much of their life cycle underground. These insects require suitable environmental conditions for nest construction and for the development and survival of their offspring. However, there is little quantitative information on the nesting habitat requirements and preferences of ground‐nesting bees. Moreover, there are almost no data on the effects of nesting conditions on these bees' fitness. Here, to better understand the factors that influence nest‐site selection in ground‐nesting bees, we synthesise the literature on the nesting‐habitat associations of these important pollinators. We also review techniques that can be used to study the nesting preferences of ground‐nesting bees. Our review reveals enormous variation among bee species in their associations with such nesting‐habitat attributes as soil texture, compaction, moisture, temperature, ground surface features, and proximity to conspecifics or floral resources. However, more studies—particularly experimental ones—are needed to segregate the influence of each factor on bees' choices of nesting location, since multiple factors are often correlated. It is also unclear whether nesting‐habitat associations vary geographically or seasonally within species, or phylogenetically among ground‐nesting bee species, partly because we lack information on nesting habitat for many species. We argue that studies using established habitat‐selection methods are essential to properly identify nesting‐habitat preferences of ground‐nesting species. Finally, more research on nesting ecology is needed (especially in agroecosystems) to determine how best to support this diverse group of bees and the vital ecosystem service they provide.

An investigation of the surface waviness features of ground surface in parallel grinding process

The high precision tungsten carbide (WC) and silicon carbide (SiC) optical mold inserts used in glass molding are usually machined by ultra-precision grinding, but the residual surface waviness error is difficult to be eliminated. This paper mainly focused on the surface waviness features related to the grinding wheel run-out error and the non-integer rotation-speed-ratio (RSR) in parallel grinding process. After the integrate consideration of grinding kinematics and microscopic material removal, the generation mechanism and distribution trend of surface waviness features were revealed. In order to simulate the surface waviness topography of parallel ground components, a mathematical model was developed and experimentally proved, which was appropriate for both integer and non-integer RSR. Besides, the mechanism of surface waviness reduction was explained when RSR was non-integer, which was due to the material removal again by the secondary grinding zone of grinding wheels. Then prediction models for the surface-waviness-period-feature (SWPF) and surface-waviness-amplitude-feature (SWAF) was built and experimentally verified, which was based on the waviness profiles overlapping effect. It found that the wave-shift resulted from the non-integer RSR had significant influence upon the surface waviness features. In the end, a convenient method was proposed to reduce the surface waviness error of parallel ground components through proper adjustment of grinding wheel rotation speed to achieve proper non-integer RSR and wave-shift, which was proved practically feasible and effective for both plane components and Fresnel components.

Research in Meteorological Modeling Oriented Comprehensive Surface Complexity (CSC)

Ground surface characteristics (i.e., topography and landscape patterns) are important factors in geographic dynamics. Thus, the complexity of ground surface is a valuable indicator for designing multiscale modeling concerning the balance between computational costs and the accuracy of simulations regarding the resolution of modeling. This study proposes the concept of comprehensive surface complexity (CSC) to quantity the degree of complexity of ground by integrating the topographic complexity indices and landscape indices representing the land use and land cover (LULC) complexity. Focusing on the meteorological process modeling, this paper computes the CSC by constructing a multiple regression model between the accuracy of meteorological simulation and the surface complexity of topography and LULC. Regarding the five widely studied areas of China, this paper shows the distribution of CSC and analyzes the window size effect. The comparison among the study areas shows that the CSC is highest for the Chuanyu region and lowest for the Wuhan region. To investigate the application of CSC in meteorological modeling, taking the Jingjinji region for instance, we conducted Weather Research and Forecasting Model (WRF) modeling and analyzed the relationship between CSC and the mean absolute error (MAE) of the temperature at 2 meters. The results showed that the MAE is higher over the northern and southern areas and lower over the central part of the study area, which is generally positively related to the value of CSC. Thus, it is feasible to conclude that CSC is helpful to indicate meteorological modeling capacity and identify those areas where finer scale modeling is preferable.

Research on ground surface characteristics of prism-plane sapphire under the orthogonal grinding direction

Abstract As a typical single crystal material, the ground surface characteristics of sapphire are influenced by the relationship between machining direction and crystalline orientation. In this paper, the effects of grinding direction on the surface characteristics of the prism-plane sapphire were investigated by a series of sapphire grinding experiments under the orthogonal machining directions. The ground surface topography, surface layer lattice residual stress and degree of lattice distortion were measured. The results show that the grinding force with the grinding direction along the c-axis is greater than the grinding force along the m-axis or the a-axis, and serious damage was generated to the ground surface with grinding direction along the c-axis. The full width at half maximum intensity value of the X-ray rocking curve indicates that the residual stress of the ground surface with machining direction along the c-axis is greater than that along the m-axis or the a-axis, and the molten KOH etching analysis results manifest that the degree of lattice distortion of the ground surface with machining direction along the c-axis is higher than that along the m-axis or the a-axis. Therefore, the grinding direction along the m-axis or the a-axis is better suited to process prism sapphire.

Policy Directions of Geothermal Potential at Sembalun District of East Lombok Regency in Nusa Tenggara Barat Province, Indonesia

This research attempted to study physical characteristics of geothermal and formulate policy directions of geothermal potential through the process of ISM (Interpretative Structural Modelling) analysis in Sembalun District of East Lombok Regency. This descriptive qualitative research design used observation, interview, and documentation for collecting the data. Two types of data were collected, namely primary and secondary data. The result of ISM analysis on the data found that the geology of Sembalun area is the remains of an old volcano which has gone through destruction process with today’s remains’ characteristics of rough, rocky and steep ground surface and 550-2250 masl height. The geomorphology of Sembalun is classified into three units, namely morphology of steep volcano, morphology of sloping volcanic hills, and morphology of denudational plains. Sloping volcanic hills stretch from the northwestern to the southwestern areas and some in the southeastern area as a part of protected forest and national park of Mount Rinjani. The slope is between 30-70 degrees and arranged by volcanic rocks. Policy directions of geothermal potential are 1) as geothermal power plants for power sources, 2) geothermal energy for crop drying, 3) geothermal energy for sterilization of planting media in the future, and 4) geothermal energy for tourism sector.