Resource Mapping Research Articles

Enabling Medicago truncatula forward genetics: identification of genetic crossing partner for R108 and development of mapping resources for Tnt1 mutants.

Though Medicago truncatula Tnt1 mutants are widely used by researchers in the legume community, they are mainly used for reverse genetics because of the availability of the BLAST-searchable large-scale flanking sequence tags database. However, these mutants should have also been used extensively for forward genetic screens, an effort that has been hindered due to the lack of a compatible genetic crossing partner for the M. truncatula genotype R108, from which Tnt1 mutants were generated. In this study, we selected three Medicago HapMap lines (HM017, HM018 and HM022) and performed reciprocal genetic crosses with R108. After phenotypic analyses in F1 and F2 progenies, HM017 was identified as a compatible crossing partner with R108. By comparing the assembled genomic sequences of HM017 and R108, we developed and confirmed 318 Indel markers evenly distributed across the eight chromosomes of the M. truncatula genome. To validate the effectiveness of these markers, by employing the map-based cloning approach, we cloned the causative gene in the dwarf mutant crs isolated from the Tnt1 mutant population, identifying it as gibberellin 3-β-dioxygenase 1, using some of the confirmed Indel markers. The primer sequences and the size difference of each marker were made available for users in the web-based database. The identification of the crossing partner for R108 and the generation of Indel markers will enhance the forward genetics and the overall usage of the Tnt1 mutants.

The scientific use of topographic maps

The article discusses the problem of an unused scientific resource of topographic maps. For resolve this issue, the methodological research has been carried out and the ways and means of solution have been proposed in this paper.

Interplay of resource mappings and evolutionary diffusion: Competitive exclusion and coexistence analysis

We study a directed dynamical reaction–diffusion model with no-flux boundary conditions where two populations interact in a spatial heterogeneous closed environment state. Both populations growths are proportional to the same growth law, but the dispersal policies with the migration coefficients differ. The population is diffusing according to their resource functions, and the carrying capacity is bounded in a heterogeneous habitat. This paper’s main results are: if the dispersion functions are non-proportional, then the coexistence is not possible unless the whole environment is homogeneous; and in case of proportionality, the species shows similar behavior. The coexistence is possible if the resource phase and the distribution function of a second organism are identical and non-constant. A few numerical examples verify that the extinction of one species by the other and the coexistence are visible in a non-homogeneous environment.

Optimum Phenological Phases for Deciduous Species Recognition: A Case Study on Quercus acutissima and Robinia pseudoacacia in Mount Tai

Tree species recognition is important for remote–sensing mapping and dynamic monitoring of forest resource. However, the complex phenological cycle poses a challenge to remote–sensing recognition of deciduous tree species in mountainous areas, and the selection of temporal phase is particularly important to improve recognition accuracy. Multispectral images of Ziyuan–1 02C (ZY–1 02C) and Ziyuan–3 (ZY–3) at three phenological phases of spring, autumn and winter (12 May, 29 September and 7 December, recorded as T5–12, T9–29 and T12–7) are selected to optimize sensitive spectral indices. Support vector machine (SVM) and maximum likelihood model (MLE) are constructed to explore the optimum phase of recognizing on Quercus acutissima (O. acutissima ) and Robinia pseudoacacia (R. pseudoacacia) in Mount Tai. The results showed the average spectral reflection intensity of O. acutissima was higher than that of R. pseudoacacia Compared to other phenological periods, the most significant spectral differences between O. acutissima and R. pseudoacacia were found in the spring (12 May), which was identified as the optimum phenological phase. Band 4 is the most sensitive band in all the three phases for the tree species recognition. Moreover, the overall recognition accuracy of deciduous tree species on 12 May reached 89.25%, which was significantly higher than the other two phases. On 12 May, the recognition accuracies of SVM based on sensitive spectral indices of up to 93.59% for O. acutissima and 85.44% for R. pseudoacacia, were higher overall than that of the MLE. Sensitive spectral indices introduced were shown to significantly improve the recognition accuracy for tree species over a single sensitive band. The study is expected to facilitate the precise recognition and forestry management on Mount Tai.

Featured Cover

The cover image is based on the Research Article Machine learning-based statistical downscaling of wind resource maps using multi-resolution topographical data by Myeongchan Oh et al., https://doi.org/10.1002/we.2718.

UTILIZING SINGLE PHOTON LASER SCANNING DATA FOR ESTIMATING INDIVIDUAL TREE ATTRIBUTES

Abstract. Mapping and monitoring forest resources require collection of spatially explicit and timely remote sensing (RS) data. Although field measurements are still important, the RS-based forest inventory helps mapping large areas to be cheaper, faster, less labor intensive, and spatially more explicit. The single-photon laser (SPL) scanning data has been exploited for different forestry applications but lacks deep examination in mapping individual trees as well as being compared with ordinary laser scanning (Linear-mode, LML) data and different individual tree detection (ITD) methods. Hence, this research focuses on applying and comparing two datasets (SPL and LML) for extracting attributes of individual trees by applying two tree crown segmentation methods (local maxima and watershed segmentation) on both datasets. The results were validated over 49 field measured plots of different species, located in southern boreal forest.The SPL yielded more accurate results for both tree density and height estimation. Watershed segmentation method yielded more accurate results for tree density and height estimation in both LML and SPL datasets. Tree density was underestimated by 4.7% (rRMSE: 32.3%) for all species. Comparing tree density estimation of different species, it was most accurate in deciduous plots (rBias: −9.5, rRMSE: 17.0%). Tree height estimation with SPL explained the variations of field-measured height very well (R2 = 0.93), and was reliably accurate, underestimated by 3.4% (rRMSE: 7.0%). The mean tree height estimation was most accurate in pine plots (rBias: 4.9%, rRMSE: 1.1%). In this research, SPL represented reliable and usable point cloud data for estimating tree height and density.

Blockchain-Enabled Joint Resource Allocation for Virtualized Video Service Functions

Power information is an important guarantee for energy security. As an important technical means of safety management and risk control, video monitoring is widely used in the power industry. Power video monitoring system uses efficient processing of multimodal video data and automatically identifies abnormal events and equipment status, replacing human monitoring with machine. Video monitoring data of power substations usually contain both visual information and auditory information, and the data types are diversified. The multimodal video data provides a rich underlying data source for the intelligent monitoring function, but it requires multiple service forms for efficient processing. Most intelligent edge monitoring equipment are only equipped with lightweight computing resources and limited battery supply, limited resources, and weak local processing data capabilities. Power video monitoring system has the characteristics of distribution, openness, interconnection, and intellectualization. Its intelligent edge video equipment is widely distributed, which also brings convenience and also brings security risks in terms of data security and reliability. For the outdoor multimodal power video monitoring system scenario, this paper adopts the edge-cloud distributed system architecture to solve the problem of resource shortage and adopts the first proposed service function virtualization (SFV) to solve the problem of multimodal video data processing. At the same time, the problem of security protection is solved by introducing blockchain to establish trust among intelligent video equipment and service providers. Under the security protection of virtualized service consortium blockchain (VSCB), virtualization technology is introduced into the service function chain (SFC) to realize SFV and solve the resource optimal allocation problem of multimodal video data processing. The work mainly involves the joint mapping of virtual resources, physical resources, and the joint optimization of computing and communication resources. Problems such as large state space and high dimensionality of action space have an impact on resource allocation. The stochastic optimization problem of resource allocation is established as a Markov decision process (MDP) model, and SFV technology is used to optimize cost and delay. The resource allocation optimization algorithm (RAOA-A3C) based on asynchronous advantage actor-critic algorithm (A3C) is proposed. Simulation experiments show that the RAOA-A3C proposed in this paper is more suitable for high-dynamic, multidimensional, and distributed power video monitoring system scenario and has achieved better optimization results in reducing time delay and deployment costs.

Mining and validation of novel simple sequence repeat (SSR) markers derived from coconut (Cocos nucifera L.) genome assembly

BackgroundIn the past, simple sequence repeat (SSR) marker development in coconut is achieved through microsatellite probing in bacterial artificial chromosome (BAC) clones or using previously developed SSR markers from closely related genomes. These coconut SSRs are publicly available in published literatures and online databases; however, the number is quite limited. Here, we used a locally established, coconut genome-wide SSR prediction bioinformatics pipeline to generate a vast amount of coconut SSR markers. ResultsA total of 7139 novel SSR markers were derived from the genome assembly of coconut ‘Catigan Green Dwarf’ (CATD). A subset of the markers, amounting to 131, were selected for synthesis based on motif filtering, contig distribution, product size exclusion, and success of in silico PCR in the CATD genome assembly. The OligoAnalyzer tool was also employed using the following desired parameters: %GC, 40–60%; minimum ΔG value for hairpin loop, −0.3 kcal/mol; minimum ΔG value for self-dimer, −0.9 kcal/mol; and minimum ΔG value for heterodimer, −0.9 kcal/mol. We have successfully synthesized, optimized, and amplified 131 novel SSR markers in coconut using ‘Catigan Green Dwarf’ (CATD), ‘Laguna Tall’ (LAGT), ‘West African Tall’ (WAT), and SYNVAR (LAGT × WAT) genotypes. Of the 131 SSR markers, 113 were polymorphic among the analyzed coconut genotypes. ConclusionThe development of novel SSR markers for coconut will serve as a valuable resource for mapping of quantitative trait loci (QTLs), assessment of genetic diversity and population structure, hybridity testing, and other marker-assisted plant breeding applications.

Wind power generation and appropriate feed-in-tariff under limited wind resource in central Thailand

The objective of this paper is to assess the wind energy resource in the central region of Thailand for wind power generation, along with analyzing the economic feasibility and appropriate feed-in-tariff (FIT) of a proposed 15 MW wind power plant. A microscale wind resource map was created using measured wind data, a computational fluid dynamics wind flow modeling and high-resolution topography databases. Five utility-scale wind turbine generators (WTG), with hub heights ranging from 80 to 120 m above ground level (agl), were used to estimate the annual energy production (AEP). Considering the available wind resource, the most appropriate WTG was identified, and a wind power plant layout was achieved to maximize the AEP as well as minimizing the wake losses. The maximum net AEP, capacity factor (CF), %AEP improvement, %wake loss reduction, and CO2eq emission avoidance were also analyzed. Several financial indices and the levelized cost of energy (LCOE) were analyzed on the basis of a cost–benefit analysis. The economic sensitivity of the costs was used to determine the most appropriate FIT for the project. Results reveal that the mean annual wind speed at 120 m agl in the central region of Thailand reaches 5.8 m/s. The net AEP, CF, %AEP improvement, %wake loss, and CO2eq emission avoidance for a 15 MW wind power plant are estimated at 41 GWh/year, 30%, 6%, 10% and 231 ktonnes CO2eq/year, respectively. The LCOE for a base case scenario is estimated at 0.093 US$/kWh, with a FIT of 0.195 US$/kWh. Finally, the results of this work can be used as guidelines for wind power project development in the central region of Thailand and in other regions of the world where the wind resource is low to moderate under current existing WTG technology.

Land resource inventorying (LRI) on 1:10K – National soil priority of India

• LRI includes soil resource mapping and other collateral data for land use planning on a scale of 1: 10K. • High resolution remote sensing data, digital elevation model, and legacy data used in mapping • Evaluation of arable and non-arable land for sustainable area of land uses and best management practices • Area specific recommendations set for high productivity, restricted land degradation and climate resilient agriculture

On Finding a Projected Coordinate Reference System

The digital age has brought about an explosion in the growth of data, of which data with a geographical component stands out. Proper use of geographical data comes with the need for correct coordinate reference systems (CRSs). They are considered the ultimate binder for interoperability between geospatial data actors and stakeholders. Moreover, CRSs are crucial for the visual and analytical integration of geospatial data from disparate data sources. However, CRSs might be—for numerous reasons—incorrectly assigned or even missing. The result is a time-consuming study of the map, literature, and available resources to ultimately find the alleged right CRS. This study provides a summary of prevailing resources from national mapping agencies of some European countries to address the above problem. Secondly, and most importantly, is the development of an open-source Python-based software package. This software package aims to accurately estimate the best candidate CRS, given a tuple of coordinates at a priori an approximately known location. It is controlled by geocoding the known location and intersecting the resulting coordinate with the bounding box of all CRSs in the EPSG-database. An in-depth review of CRS tools by mapping authorities reveals, in particular, limitations concerning the countries’ spatial areas, in combination with often required know-how of local CRSs. To address these shortcomings, our tool is developed to enable a more generic extraction of CRSs for any given location worldwide. Testing proved successful for 30 different maps, with a grid present on the map and the CRS of the map being included in the EPSG-database.

Effects of temporal floral resource availability and non-crop habitats on broad bean pollination

ContextFlowering plants can enhance wild insect populations and their pollination services to crops in agricultural landscapes, especially when they flower before the focal crop. However, characterizing the temporal availability of specific floral resources is a challenge.ObjectivesDeveloping an index for the availability of floral resources at the landscape scale according to the specific use by a pollinator. Investigating whether detailed and temporally-resolved floral resource maps predict pollination success of broad bean better than land cover maps.MethodsWe mapped plant species used as pollen source by bumblebees in 24 agricultural landscapes and developed an index of floral resource availability for different times of the flowering season. To measure pollination success, patches of broad bean (Vicia faba), a plant typically pollinated by bumblebees, were exposed in the center of selected landscapes.ResultsHigher floral resource availability before bean flowering led to enhanced seed set. Floral resource availability synchronous to broad bean flowering had no effect. Seed set was somewhat better explained by land cover maps than by floral resource availability, increasing with urban area and declining with the cover of arable land.ConclusionsThe timing of alternative floral resource availability is important for crop pollination. The higher explanation of pollination success by land cover maps than by floral resource availability indicates that additional factors such as habitat disturbance and nesting sites play a role in pollination. Enhancing non-crop woody plants in agricultural landscapes as pollen sources may ensure higher levels of crop pollination by wild pollinators such as bumblebees.

An interpretable prediction of FCM driven by small samples for energy analysis based on air quality prediction

ABSTRACT In order to achieve prevention and control of air pollution through energy consumption adjustment in advance, the paper proposes an Fuzzy Cognitive Map (FCM) of various energy resources affecting air quality, an incremental prediction algorithm of FCM and gradient descending method used to learn the FCM based on the small sample data on various energy consumptions and concentration of air pollutants. The FCM as an interpretable prediction method not only can predict future air quality more accurately, but also can analyze and interpret the affecting of various energy types on the future air quality. As the time delay of various energy consumptions affecting concentration of air pollutants, the quantitative time sequence influencing relationships (causality) in the FCM is mined directly from these data, and the air quality affected by various types of energy consumptions is predicted based on the FCM. Accordingly, the energy types affecting air pollution can be obtained for prior decision of energy consumption structure adjustment. The experimental results in Beijing-Tianjin-Hebei show that the FCM modeling is better than Support Vector Regression (SVR), Linear Regression (LR), Principal Component Analysis (PCA)-based forecasting, Convolutional Neural Networks (CNN) and Long-Short Term Memory (LSTM) methods in predicting air quality affected by energy resources, meanwhile according to the interpretable prediction results of the FCM, we obtain some interesting results and suggestions on energy consumption types in Beijing-Tianjin-Hebei regions in advance. Implications: At present, China’s air pollution control has entered the deep-water area, and the biggest challenge is how to adjust the energy (consumption) structure. Therefore, this study completed the two important tasks: (1) driven by small sample data of energy consumptions, the paper provides an interpretable prediction model and method with better performance to achieve prevention and control of air pollution through energy consumption adjustment in advance; (2) according to the interpretable prediction results, the paper obtains some interesting results used to guide energy consumption adjustment in Beijing-Tianjin-Hebei regions. This study will provide beneficial suggestions and strategies for air pollution prevention and control in Beijing-Tianjin-Hebei, will help improve the air quality and energy consumption structure in Beijing-Tianjin-Hebei, and also can be extended to other regions.

Factors affecting possibility of ecotourism development and sustaining natural resources using SWOT approach in west Iran

The impacts of mass and unsupervised ecotourism on natural resources have tremendously increased. As natural resources conservation and ecotourism issues are now at the forefront of public opinion, this study was conducted in Kermanshah Province, Iran (KPI) which is suitable for ecotourism due to its attractive landscapes, biodiversity, and traditional agricultural productions. This research was carried out through field survey and interview with relevant experts (March 2019–March 2020). Accordingly, the strategies for combining ecotourism development and natural resources protection were explored using strength-weakness-opportunity-threat (SWOT) approach. The respondents were specialized in the field of geography, watershed management, ecotourism, economy, forest, rangeland, agriculture and extension. Results showed that ecotourism destinations mostly included some parts of attractive mountains, forests, rangelands, caves, rivers, springs, tourism villages and urban gardens. Moreover, the strategy solutions based on opportunities- strengths (S-O) included legal documentation and cadastral mapping of natural resources, increasing public participation and awareness, livelihood resilience and job creation for inhabitants through development of local markets, and construction of welfare facilities for visitors. Meanwhile, considering strengths that can curtail vulnerability to the external threats (S-T strategies) include combating corruption and lobbying forces, regular and strict field monitoring, heavy penalties on degradation activities (mainly arson fire, tree cutting and rubbish disposal), security guaranty and financial support for investors, increasing protected reserve areas, preserving the traditional village, and proper pathways building for public walking in the natural heritages. These strategies can assist the governments in balancing ecotourism development and sustainability of natural resources at local scale such as KPI.

New Zealand O&M instructors’ perspectives about, and experience in, the use of tactile maps with people with vision impairment

This qualitative study explored the perspectives and experience of New Zealand O&M instructors in the use of tactile maps with people with vision impairment. In-depth, open-ended, and semi-structured interviews were used to gather information from four participants, who were qualified O&M instructors. The interviews were analysed using thematic analysis. Three inter-related themes emerged from the data that effected the O&M’s tactile map usage: (1) the tactile map and the O&M instructor, (2) student needs and experiences, and (3) time and resources. Microcapsule and thermoform maps were the least used map medium, with collage map techniques used frequently by half of the participants. The most preferred tactile maps were ready-made tactile map kits, and instructors drawing directly on the students’ hand or back. Tactile maps were used mostly by the participants to meet the orientation needs of motivated students, who were blind, had no visual memory, or did not use their vision for orientation purposes. Tactile maps were considered a vital orientation tool when the participants were teaching such students, and the participants did not believe Global Positioning System (GPS) applications would fully replace tactile maps. However, in general, the participants revealed that tactile maps were used infrequently as an orientation tool in New Zealand because of caseload makeup, limited time, and limited resources. In order to increase the use of tactile maps, tactile map resources may need to be more readily available. In addition, further research is needed about the characteristics of people with a vision impairment, who benefit from tactile maps, along with the effect of tactile maps usage on an O&M instructor’s caseload and time, so that O&M instructors can plan accordingly and people with a vision impairment can continue to benefit from this important orientation tool.

Geothermal Resources of the Asian Continent: A regional Assessment

The present work is an attempt for regional assessment of geothermal resources of the continental region of Asia. It is based on integrated analysis of the results of experimental data on heat transfer by conduction as well as hydrothermal and magmatic processes in the upper crust. The current compilation makes use of geothermal data reported at the website of IHFC but also estimates based on available information on occurrences thermal springs and volcanic events. The resource assessment has been carried out for 11260 sites distributed in 46 countries. A modified method of magmatic heat budget (MHB) has been employed in deriving estimates of geothermal resources in areas of recent volcanic activity. These datasets were reevaluated and spatially gridded using kigrid interpolation to construction of regional distribution maps of geothermal resources and interpreted on the basis of available information on tectonic setting and geological characteristics. According to results obtained the total resource base (RB) is estimated to be 47024 ± 4525 GJ. The mean resource base per unit area (RBUA) is 1765 GJ. The most prominent features in geothermal maps are the significantly high values of resource base of greater than 1000 GJ in countries such as Japan, Indonesia, China, Bhutan, Nepal and Pakistan. In addition, vertical distributions of temperatures were calculated in such areas for depths reaching down to 6 km. The results obtained indicate potential availability of high temperature resources in vast regions of the Asian continent.

ASSESSMENT OF SOLAR ENERGY POTENTIAL OF NIGERIA FOR SOLAR POWER GENERATION THROUGH NUMERICAL SOLAR IRRADIANCE MAPPING

Any thorough analysis of solar energy applications in the country requires a solar resources map. Many maps have been developed, but they only show distributions presented in colour intensities. Solar irradiance can only be estimated from such maps. Using on the spot experimental data for solar map production does not provide accurate maps because various climatic and environmental conditions such as dust haze and cloud cover affect the amount of solar energy that reaches the ground in various locations in Nigeria. This is particularly true during the harmattan period. Therefore data generated from such methods cannot be used to develop accurate numerical solar maps. Data for such applications should be collected from outer space and over a long time for various locations. The National Aeronautics and Space Administration (NASA) provides a resources base for such data. The data used in this study covered 25 years (1994-2018). The average daily global solar irradiance for various longitude-latitude nodes is calculated from such data. With these data available, it is possible to estimate the average daily global solar irradiance for any location provided the longitude and latitude is known. Irradiance values for 300 locations in the country are evaluated from details presented by the maps. To validate the map, experimental irradiance values for selected locations are compared with values extracted from the solar irradiance map. Calculated irradiance values are found to agree satisfactorily with experimental values. The maximum percentage difference between calculated and experimental values is 6.8%. This proved that the solar map developed is a satisfactory provides a satisfactory representation of solar data for the various locations and can be used for other locations where such data does not exist. KEYWORDS: Solar Energy, Solar Maps, Irradiance, Energy Patterns,

ASSESSMENT OF SOLAR ENERGY POTENTIAL OF NIGERIA FOR SOLAR POWER GENERATION THROUGH NUMERICAL SOLAR IRRADIANCE MAPPING

Any thorough analysis of solar energy applications in the country requires a solar resources map. Many maps have been developed, but they only show distributions presented in colour intensities. Solar irradiance can only be estimated from such maps. Using on the spot experimental data for solar map production does not provide accurate maps because various climatic and environmental conditions such as dust haze and cloud cover affect the amount of solar energy that reaches the ground in various locations in Nigeria. This is particularly true during the harmattan period. Therefore data generated from such methods cannot be used to develop accurate numerical solar maps. Data for such applications should be collected from outer space and over a long time for various locations. The National Aeronautics and Space Administration (NASA) provides a resources base for such data. The data used in this study covered 25 years (1994-2018). The average daily global solar irradiance for various longitude-latitude nodes is calculated from such data. With these data available, it is possible to estimate the average daily global solar irradiance for any location provided the longitude and latitude is known. Irradiance values for 300 locations in the country are evaluated from details presented by the maps. To validate the map, experimental irradiance values for selected locations are compared with values extracted from the solar irradiance map. Calculated irradiance values are found to agree satisfactorily with experimental values. The maximum percentage difference between calculated and experimental values is 6.8%. This proved that the solar map developed is a satisfactory provides a satisfactory representation of solar data for the various locations and can be used for other locations where such data does not exist. KEYWORDS: Solar Energy, Solar Maps, Irradiance, Energy Patterns,

Relation of migration trend and gender of RMG labour force in Industrial areas in Bangladesh

Legitimate labour migration has, no doubt, got much attention in various economies and labour force irrespective of gender tempt for diverse employment. Industrial employment and job concentration in industrial cluster always provoke work driven migration. People relocate their whereabouts based on their secure livelihoods. And, economic centralization and targeted migration thus associate each other with no exception in Bangladesh. In the 5-decade long industrial history, many changes, reforms and challenges were noticed throughout our industrial ecosystem and labour dynamics. Labour force is a critical strength for efficient and low-cost productivity. In this regard, our mixed labour force, skilled, semi and unskilled workforce, has shaped our local industry and positioned as the most competitive regionally and contributed to gain productivity momentum and foreign trade growth. RMG industry, the forefront export-oriented sector of economy, has emerged as the largest employer of local migrated workforce of all contemporary industries in Bangladesh encouraging labour migration in urban area. This industry shares relatively large in GDP and export earning. With unprecedented contribution by RMG to economy, this study attempted to know whether any relationship of migration trend and gender status since this industry is a female dominant industry. The assessment of correlation is justifiably demanded due to women employment intensity since inception. But, this quantitative research-cause and effect study resulted that gender and migration condition and flow have no positive relationship and integration upon applying non-parametric test Chi-square test of significance. Around 252 independent samples from RMG factories in Dhaka and nearby districts where industrial hubs are located. It has obtained the null and rejected alternative hypothesis. These findings may help for national perspective planning and development planning. The drawn outcomes may also enable us national resource planning, mapping and human development index. As well, we can measure labour productivity in RMG industry and plan for future facility as well urban living and economic development.

NWP-CFD 축소화에 의한 육상풍력 자원지도 고해상도화

An accurate prediction of the wind energy production is essential in the initial design process of wind farms. Many researchers use meteorological data obtained from Numerical Weather Prediction (NWP) methods to predict wind energy production. The NWP method does not consider the influence of local topography and surface roughness on wind conditions. In Korea, most of onshore wind farms are installed in mountainous areas with complex topography, which makes the meteorological data obtained from only NWP method not applicable for the generation of wind resource map. The NWP-CFD coupled method, which uses the meteorological data from NWP method as the boundary condition of the CFD simulation, is adopted to overcome the limitations inherent in the NWP method. In this way, the spatial resolution of onshore wind resource map is downscaled to 100m-level considering the effects of the complex topography on the wind conditions.