Natural Resource Management Research Articles

The establishment, persistence, and scaling of marine community-based natural resource management in four coastal districts in Tanzania

Community-based natural resource management (CBNRM) is common in most types of ecosystems that are characterized by common property practices. However, the emergence and spread of CBNRM has varied across geographies and contexts. This study explores factors that have enabled the modern emergence, persistence, and spread of marine CBNRM in four coastal districts in Tanzania. It also investigates how CBNRM—particularly local ownership and management of marine resources —is implemented and developed. It draws on a document review of the grey and scientific literature, and in-depth qualitative field work carried out in four coastal districts on mainland Tanzania. The field work involved 15 key informant interviews, 12 focus groups discussion, and participant observation, documenting the perceptions of resource users. The findings indicate that marine CBNRM – operationalized largely through local organizations called Beach Management Units (BMUs) – have strong support from local communities, but emerged, persist, and scaled largely through government and donor led initiatives. The local communities' strong desire to safeguard fisheries resources and reduce overexploitation, caused by illegal harvesting practices, promoted the quick expansion of BMUs, which in turn ensured the continuation of CBNRM. The positive experience and lessons learned from BMUs established early in the process encouraged the spread and ultimately scaling out of CBNRM. Expanding and sustaining marine CBNRM beyond its current form, which relies heavily on external support, will require innovative approaches that foster collective action, identify sustainable financing mechanisms, provide clarity in roles and responsibilities, and identify cost-effective and scalable CBNRM approaches.

An improved framework for quantifying the contribution of climatic and anthropogenic factors to vegetation dynamics - A case study of China

Accurately quantifying the impact of climatic and anthropogenic factors on vegetation change is critical for developing and evaluating ecological management strategies. However, most presented studies typically ignore the climate temporal effects and assume that all pixels are affected by both climate change (CC) and human activities (HA), which often introduce uncertainties. In this study, Leaf area index (LAI), temperature, precipitation, solar radiation, and land cover data from 1982 to 2020 were used to detect and attribute vegetation dynamics in China. We used partial correlation analysis, generalize linear model, trend analysis, and improved RESTREND to analyze the spatiotemporal variation characteristics of vegetation LAI from 1982 to 2020 and to quantify the effects of CC and HA on vegetation dynamics since the implementation of the Grain for Green Project (GGP). The results indicate that significant vegetation greening appeared in most areas (66.2%) between 2000 and 2020. Both CC and HA have positive effects on vegetation greening. In arid and semi-arid regions, precipitation was the primary driver of vegetation change, while in high-latitude areas of southern and southwestern China, temperature was the primary determinant. After considering the temporal effects, the explanatory power of climate variables for vegetation dynamics increased by 4.0% compared to ignoring the temporal effects, accounting for 72.81%. After dividing the pixels into those affected by CC and those affected by both CC and HA, the contribution of HA was decreased from 31.19% to 25.96%. Although the contribution of HA is lower than that of CC, ecological engineering has effectively promoted vegetation greening. These research findings provide scientific data and theoretical basis for ecological environment protection and natural resource management.

Applications of remote sensing technology in agriculture: A review of contributions to food security challenges and strategies in developing countries

In the agricultural sphere, particularly in developing countries where food security is still a major concern, remote sensing technology has also surfaced as an important tool. In this review, the usages of remote sensing in agricultural areas and its contributions to food security are surveyed; The overall framework is illustrated dynamically by indicating available image platforms that were instrumental for agriculture application paradigms. This research identifies certain areas where some selected case studies and existing literature are reviewed to serve as proof that remote sensing technology has been tremendously impactful. Areas like crop monitoring, yield prediction, or natural resource management have been very well reported by the literature review process adopted. This field analysis of related studies used highly sophisticated RS sensor data. The challenges like data availability, technological limitations, and socio-economic factors have been discussed besides the strategies, for instance, capacity building, policy interventions, and prospects for technological advancements. These results underscore the vitality and adoption of remote sensing technologies in agricultural practices and policies which is the key driver of improved food security in developing countries.

Seasonal forecasts have sufficient skill to inform some agricultural decisions.

Abstract Seasonal forecasts, which look several months into the future, are currently underutilized in active decision-making, particularly for agricultural and natural resource management. This underutilization can be attributed to the absence of forecasts for decision-relevant variables at the required spatiotemporal resolution and at the time when the decisions are made and a perception of poor skill by decision-makers. Addressing these constraints, we quantified the skill of seasonal forecasts in informing two agricultural decisions with differing decision timeframes and influencer variables: (a) whether to apply fertilizer in fall or wait until spring based on expected winter temperatures, and (b) drought response, such as whether to lease water based on expectations of drought. We also looked into how early the forecast can be provided without significant degradation in skill. Currently, drought response decisions are typically formulated in April, utilizing drought forecasts issued in the same month, while fall fertilization decisions are generally made between August and September. There is growing interest among stakeholders in the availability of earlier forecasts to inform these critical choices. We utilized the North American Multi-Model Ensemble (NMME) hindcasts for the time period 1982 - 2020 over the Pacific Northwest US to obtain meteorological variables. Runoff was estimated via simulations of the coupled crop-hydrology VIC-CropSyst model. The skill assessment with the Heidke Skill Score (HSS) yielded promising outcomes in both decisions for the entire Pacific Northwest region. Notably, NMME’s positive skill (median HSS of 30%) in predicting warmer winters identifies years when fertilizer application should be avoided to prevent fertilizer loss through mineralization (and associated costs). Similarly, there is skill in forecasting drought conditions in most irrigated watersheds for up to two months in advance of April, the current decision time. In conclusion, our findings affirm that contrary to the perception of low skill and resulting underutilization, current seasonal forecasts hold the potential to inform at least some key agricultural decisions.

The effects of global product design on supply chain efficiency and natural resources management

The significance of global product design as a primary factor in determining supply chain efficiency and natural resource management. This study examines the impact of global product design changes on process and supply chain practices. Specifically, it seeks to understand in promoting sustainable practices across global supply chains. This study, utilizes the fuzzy Analytical Hierarchy Process (AHP) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods to evaluate the criteria, sub-criteria, and various significant opportunities influencing sustainable product design and supply chain management. The fuzzy AHP method is used to assess the key criteria and their respective sub-criteria. The fuzzy TOPSIS method is used to rank the opportunities in driving sustainable practices across global supply chains. The results of fuzzy AHP show that innovation and product differentiation (C4), economic viability (C1), and supply chain efficiency (C5) are the crucial criteria. While the results of fuzzy TOPSIS present that supply chain transparency (O2) is the most suitable opportunity, followed by circular economy practices (O1) and policy advocacy and compliance (O6) in adopting global product design on supply chain efficiency and natural resources management. Thus, this study is highly relevant to the governments, industry specialists, and policymakers who aim at enhancing the dynamic business environment and sustainable development.

Human–wildlife interactions on the tidal flats of the Bijagós Archipelago: does shellfishing affect migratory shorebirds?

The Bijagós Archipelago in West Africa is home to an ethnic group with a rich cultural heritage that is tightly linked to nature. The Bijagós people have a shared cultural identity, but management of natural resources varies between islands due to island‐specific context with regards to socio‐political organization and strength of cultural heritage. Across the archipelago, bivalves harvested manually from the mudflats are an important part of the Bijagós people's diet, economy, and culture. Migratory shorebirds share the use of these mudflats during their non‐breeding season, consuming macrobenthos such as crustaceans and bivalves, including those harvested by local people. At the end of their stay in the Bijagós, just before taking off for their migratory flight, it is particularly important that shorebirds have access to undisturbed feeding areas with suitable food resources. In this study we start by exploring shellfishing patterns across different management regimes (via questionnaires to local shellfishers), then assess seasonal variation in the direct impact of shellfishing on shorebirds (through competition for resources and space), and finally quantify the indirect impact of sediment disturbance due to shellfishing upon shorebird prey availability with an experimental approach. Results indicate that bivalve resources are better managed in areas with formal protection, while traditional management based on cultural beliefs results in poorer stock conditions. Interestingly, the high density of shellfishers in mid‐winter (14.4 ind. km−2) decreased markedly towards shorebirds' fuelling period, when they benefit the most from reduced disturbance on the mudflats. Regardless of the season, no direct competition for resources was detected due to differences in targeted sizes. Indirect impacts caused by sediment disturbance during shellfishing were also mostly absent, causing only a small reduction on shorebirds prey density but with no effect on the available biomass.

Tracing offshore marine ecosystem asset changes based on physical accounting: A case of Xiamen Sea Area

Assessing temporal and spatial changes in marine ecosystem assets is critical for the capitalized management of natural resources and their contribution to human well-being. However, quantifying these changes using different inclusion methods in the System National Account is a challenge. Ecosystem accounting has become a popular topic in recent years, particularly after the System of Environmental and Economic Accounting-Ecosystem Accounting was published in 2021. However, few practical studies have been conducted on offshore marine ecosystem accounting, including marine ecosystem assets and services. This study provides a systematic framework to prioritize the assessment of offshore marine ecosystem assets (extent and condition) in physical terms, including the determined indicators of physical accounts and the presentation of accounting results. We then used this framework to assess marine ecosystem assets in the Xiamen Sea Area selected from 2006 to 2020. The results show that: (a) The extent of the marine ecosystem in Xiamen decreased by 8.34% from 349.64 km2 to 320.49 km2, mainly caused by converting intertidal ecosystem into the land due to the demand for urban and industrial use sea. (b) The area of intertidal vegetation habitats (mangroves and salt marshes) increased from 23.22 hm2 to 132.2 hm2, with an increase of 4.7 times. The results also show that the restoration of the marine ecology in Xiamen has achieved remarkable results. (c) The marine ecosystem condition comprehensive index in Xiamen increased by 3.13% from 0.32 to 0.33. This shows that the marine ecosystem conditions in Xiamen remain well and have even slightly improved under the pressure of a rapidly developing economy and increasing population. This study provides practical technical methods for assessing offshore marine ecosystem in physical term to support integrated coastal management in coastal cities, and is important for assessing marine ecosystem services in the future.

Strengthening Community Resilience in the Face of Environmental and Economic Challenges in Southeast Mexico

Objective: The problems in the sustainable management of natural resources in their fishing practices in the community of Aztlán Quinta Seccion Palomillal in Tabasco, Mexico, are analyzed to develop community solutions and improve sustainability and socioeconomic results. Theoretical Framework: It is based on the theory of sustainability (World Commission on Environment and Development, 1987, p. 43), the natural resources management model (Natural Resources Commission, 2012, p. 3) and the theory of participatory research (Reason & Bradbury, 2008, p. These frameworks are the context in which fishing practices are developed in the community, serving as a relevant case study for southeastern Mexico, facilitating the analysis of the problems and proposed solutions. Method: A qualitative case study design focused on community-based participatory research was applied, involving key community actors, including fishermen and leaders of the fishing cooperative. Data collection was through semi-structured interviews, focus groups and participant observation. The interviews were designed to learn about challenges in resource management, while focus groups facilitated discussions about possible solutions. Participant observations were carried out during community meetings and the sociocultural and environmental context. Results and Discussion: The problems of sediment accumulation, the presence of invasive species, the lack of adequate infrastructure and low educational levels were identified. There is an urgency to implement strategies that combine traditional knowledge with modern practices to improve the sustainability of fishing activities. The importance of community participation is highlighted. Research Implications: It has significant practical and theoretical implications for sustainable resource management in rural fishing communities and can be applied in other similar rural contexts and contributes to the theoretical development of community-based participatory research. Originality/Value: An innovative community-based participatory research approach is applied for sustainable natural resource management in a rural fishing community, replicable for sustainable resource management in vulnerable contexts.

Building ties at multi-stakeholder engagement events to facilitate social learning about contentious issues in natural resource management

Building ties at multi-stakeholder engagement events to facilitate social learning about contentious issues in natural resource management

Mapping landforms of a hilly landscape using machine learning and high-resolution LiDAR topographic data

Landform maps are important tools in assessment of soil- and eco-hydrogeomorphic processes and hazards, hydrological modeling, and natural resources and land management. Traditional techniques of mapping landforms based on field surveys or from aerial photographs can be time and labor intensive, highlighting the importance of remote sensing products based automatic or semi-automatic approaches. In addition, the time-intensive manual labeling can also be subjective rather than an objective identification of the landform. Here we implemented such an objective approach applying a random forest machine learning algorithm to a set of observed landform data and 1m horizontal resolution bare-earth digital elevation model (DEM) developed from airborne light detection and ranging (LiDAR) data to rapidly map various landforms of a hilly landscape. The landform classification includes upland plateaus, ridges, convex slopes, planar slopes, concave slopes, stream channels, and valley bottoms, across a 400 km2 hilly landscape of the Ozark Mountains in northeastern Oklahoma. We used 4200 landform observations (600 per landform) and eight topographic indices derived from 2 m, 5 m and 10 m resolution LiDAR DEM in random forest algorithm to develop 2 m, 5 m and 10 m resolution landform models. We test the effectiveness of DEM resolution in mapping landforms via comparison of observed landforms with modeled landforms. Results showed that the approach mapped ∼84% of observed landforms when covariates were at 2 m resolution to ∼89% when they were at 10 m resolution. However, predicted maps showed that the 2 m resolution covariates performed better at capturing accurate landform boundaries and details of small-sized landforms such as stream channels and ridges. The approach presented here significantly reduces the time required for mapping landforms compared to traditional techniques using aerial imagery and field observations and allows incorporation of a wide variety of covariates. The landform map developed using this approach has several potential applications. It could be utilized in hydrological modeling, natural resource management, and characterizing soil-geomorphic processes and hazards in a hilly landscape.

The Hybridisation, Resilience, and Loss of Local Knowledge and Natural Resource Management in Zambia

AbstractThe contribution of Indigenous and local knowledge (ILK) to natural resource management has recently gained increasing prominence in academia, policymaking, and civil society. However, persistent knowledge gaps concerning the contribution of ILK to sustainable landscape management remain. We investigate existing local knowledge and practices of the Tonga of Kalomo District, Zambia, and their contribution to sustainable landscape management by combining walking interviews with photovoice. Especially Tonga women and youth are important knowledge holders for land management, agricultural practices, and tree conservation. We found that local knowledge is often ‘hybridised’ with ‘external knowledge’ when local knowledge alone is deemed insufficient. In some cases, introduced ‘external knowledges’ are simply reconstituted long-standing local practices. Nevertheless, local communities often perceive external knowledge holders as “knowing better.” Finally, we show how local knowledge and associated practices have been simultaneously eroded and lost and describe those that have remained resilient to provide insights into the complexity of hybridisation processes where different knowledge systems interact.

Description of a relict aspen parkland-associated grassland in the Peace River region of British Columbia, Canada

The aspen parkland-associated grasslands of the Peace River region, British Columbia (BC), have been severely reduced in area, primarily because of agricultural and urban development. In this region, the species composition of plant communities is similar to that of prairie grasslands and is topographically influenced, occurring primarily on warm-aspect slopes along the Peace River and some of its tributaries. Historical records show that non-forested grass- and sedge-dominated plant communities occurred on flat and gently rolling terrain in a parkland ecosystem near what are now the communities of Dawson Creek and Fort St. John. The Peace grasslands are not represented in BC’s biogeoclimatic ecosystem classification, perhaps leading to their neglect in regional natural resource management and conservation planning. Here, I describe the vascular plant community of a level-terrain relict aspen parkland-associated grassland in the Peace River region. Its species composition differs from nearby warm-aspect grasslands and includes provincially listed plant species. Increased awareness of grassland communities may support conservation, ecosystem restoration, and climate change adaptation in the southern boreal region of BC.

Data visualisation for decision making under deep uncertainty: current challenges and opportunities

Abstract This perspective article explores the role of data visualisation in decision-making under deep uncertainty (DMDU), a growing discipline tackling complex socio-environmental challenges, such as climate impacts and adaptation, natural resource management, and preparedness for extreme events. We discuss the role of visualisation for both analysis (or exploratory) purposes, as well as communication (or explanatory) purposes, including to stakeholders and the public. We identify a lack of comprehensive guidelines on how visualisations are currently used and their potential in enhancing DMDU processes. Drawing on literature and insights from a recent workshop, we identify key challenges DMDU analysts face when visualising data: managing complexity and dimensionality, effectively communicating uncertainty, and ensuring user engagement and interpretability. We propose a research agenda to address these challenges, by taxonomising and evaluating the effectiveness of different visual forms in decision-making contexts, and fostering interdisciplinary collaboration. We argue that, through these efforts, we can improve the communication and usability of DMDU analyses, ultimately aiding in more informed and adaptive decision-making in the face of deep uncertainty.

Pattern determination of the territory local factors influence on the land plots’ cadastral value of gardening and horticultural non-profit partnerships

In recent decades, the state has been tasked with the effective management of natural resources, among which land resources hold particular importance due to the necessity of their rational use and sustainable development. The value of land resources and their indispensable role in ensuring the socio-economic development of the country is most clearly reflected in the state’s tax policy, specifically in land taxation. The amount of land tax depends on the cadastral value, which is often subject to methodological shortcomings and challenges. This study, using the Belgorod Region as a case study, proposes an algorithm for determining the cadastral value of land plots within gardening and horticultural non-profit partnerships, taking local factors into account. To determine the specific indicator of cadastral value (SICV) of land plots, a linear regression model was developed. The results, tested for homoscedasticity, confirmed the model’s adequacy and reliability. The findings showed that the cadastral value decreased by an average of 12.2% compared to the current results of the state cadastral assessment in the Belgorod Region, highlighting the influence of local factors and the importance of considering them in the cadastral evaluation of the land plots in question.

Achieving Sustainability in the Management of Natural Resources Given to a Concession

The sustainable management of resources is part of the strategic objectives of the European economic policy for the transition from a linear to a circular economy. One of its aspects, at the national level, is the protection of deposits of underground wealth and mineral waters on the territory of the Republic of Bulgaria from depletion and improper exploitation. The purpose of the article is to present the main requirements for the users of this type of natural resources when granting concessions by the state, in order to determine whether there are mechanisms for achieving sustainability in their management. By studying the current legislation and analyzing data from the National Concession Register, the most frequently used practices for sustainable management of these valuable resources used for economic purposes are presented: establishment of environmental requirements; limiting the rights to extract and exploit the deposits to predetermined limits and volumes, for a certain period of time; requirements for preparation of work plans, reports and reporting documentation; delivery of the concession object in a condition suitable for subsequent operation; requirements for reclamation, enhanced administrative control, which covers the entire project cycle of realization of investments in the extraction of this type of resources, etc. As a result of the study, the article formulates recommendations for expanding the sustainability requirements and strengthening the control in their application. This will ensure a wider time horizon for their economic exploitation and will contribute to achieving one of the EU’s fundamental goals: to ensure suitable conditions for economic growth for future generations without resource dependence.

Counting Cattle in Argentina with AI and Satellite Images

Abstract. From a specific need of the national institution responsible for plant and animal health in Argentina, SENASA, this collaborative work between the public sectors together with academia arises. The objective was the development of a Deep Learning algorithm for the detection of livestock, cows in particular, in very high-resolution satellite images (provided by the Argentine Space Agency (CONAE)) and its subsequent counting. The basic elements involved in the development of artificial intelligence are detailed, such as the selection and acquisition of satellite images, their very thorough preprocessing and labelling, details of the training stage and some forms of error quantification. The image database is made up of about 320 scenes (based on very high resolution (VHR) satellite data from the Pleiades and Pleiades NEO sensors, ©Airbus 2022, distributed by CONAE) of the Pampas and Patagonian regions in Argentina. Around 8,000 labels of different types of animals were generated, the most common were cows and sheep. Also labels that did not represent animals to contribute to training. Finally, some very promising preliminary results are presented, such as the average error in the count that was achieved was ± four cows. The usefulness of these tools is reflected in better management of renewable natural resources linked to animal health issues, fiscal issues and within the framework of the 2030 Agenda and Sustainable Development Goals #12, #15 and #17.

Analysis Of Village SDGS System In Sustainable Development In Loloana'a Gido Village, Gido District, Nias Regency

The phenomena that occurred at the research location were as follows: 1) lack of active participation of village communities in the development process; 2) lack of basic infrastructure development such as roads, electricity, and internet access is very important for village progress; 3) lack of sustainable management of natural resources to protect the environment and ensure the availability of resources for future generations. The purpose of this research is to find out how the Village SDGs System and sustainable development in Loloana'a Gido Village, Gido District, Nias Regency. The research approach used in this study is a qualitative approach. The data collection techniques used are observation, documentation and interviews. And the data analysis techniques used are data collection, data reduction, data presentation and drawing conclusions. Based on the results of the interview above, it can provide an explanation of the Analysis of the Village SDGs System in Sustainable Development in Loloana'a Gido Village, Gido District, Nias Regency. Analysis of the Village SDGs system is an important approach to understanding the objectives of SDGs can be implemented in an integrated manner at the village level.

Інституційне забезпечення екологічної резильєнтності

Current issues of the formation of a modern system of institutional support of resilience based on the ecological component in Ukraine are considered. Attention is focused on the development of conceptual methodological postulates aimed at creating an effective institutional environment for sustainable and resilient nature management. The purpose of the article is the formation of a modern institutional environment for nature management, which will be based on an effective combination of formal and informal institutions, which will directly or indirectly, with the help of appropriate tools, ensure the involvement of natural resources in economic circulation. The research was conducted using a complex of general scientific and special methods, which made it possible to ensure the conceptual integrity and reliability of the obtained results. With the help of abstract logical analysis method, conceptual methodological postulates on institutional support for the sustainability of resilient nature management were formed. Structural and functional analysis is used to study the functional features of institutions within the framework of resilient spatial development. Based on the modeling method, a scheme for the distribution of institutional tools by components of ensuring resilience in the natural resource sphere was developed, and the relationships between these tools were identified and visualized. The novelty of the work consists in the development of an algorithm for the implementation of institutional transformations regarding the management of territorial entities’ resilience (in terms of natural-resource / ecological component) taking into account the European experience of municipal management of spatial development. The principles of institutional transformations in resilience management, which are of a universal nature, have been improved with an interpretation in the field of natural-resource (ecological) relations. Attention is focused on the importance of forming multi-subject corporate structures of territorial development management using modern platform mechanisms. This approach makes it possible to balance the interests of various stakeholders — the state, local self-government bodies, businesses and the population, and, accordingly, to ensure a consensus regarding the directions of resilient development of territorial entities. The article also examines the issue of consolidation of financial resources in the natural and economic sphere and the mechanisms of their effective use to achieve the goals of resilient development. Innovative approaches to the management of natural resources are proposed, including their capitalization and involvement in economic circulation, taking into account environmental limitations. Conclusions have been made regarding promising directions for further research in this field, including the development of specific mechanisms for implementing relevant institutional transformations, evaluating their effectiveness in various regions of Ukraine, as well as studying the possibilities of adapting international resilience management experience to Ukrainian realities.

Establishing Natural Resources Monitoring Systems in China: Situation, Problem and Suggestion

Abstract. In order to fundamentally support work for achieve "climate action, life below water, and life on land" 3 Sustainable Development Goals of the United Nations, and to realize unified monitoring and refined management of natural resources, this paper collects, organizes, analyzes, and summarizes national policy, management department documents, relevant papers, and the latest industry development trends through the literature induction method. It systematically studies current monitoring networks from the perspectives of land resources monitoring, mineral resources monitoring, forest resources monitoring, grassland resources monitoring, water resources monitoring, wetland resources monitoring, marine resources monitoring. It indicates such problems as inconsistent classification standards and monitoring technical standards for natural resources, lack of smooth connection among monitoring networks, and insufficient high-tech applications. It proposes suggestions of building 1+N monitoring system, coordinating multi-level and multi-category monitoring mechanisms, improving monitoring intelligence level, strengthening the ability to obtain multi-source spatiotemporal data, and constructing an information sharing platform, to better build a unified natural resource monitoring system, and serve the refined management of natural resources.

Database Construction and Application of Large-scale Geospatial Data

Abstract. Geospatial data refers to data that related to spatial location. It is the abstract representation of objects, events, or other characteristic information located on or near the surface of the Earth. It characterizes attribute features, spatial features, and associated information of geospatial features. Geospatial data commonly include various data types such as point, polyline, polygon, and so on. Geospatial database is the basic method to store and manage geospatial data. It is also the important component of geographic information systems (GIS). Geospatial database generally stores data in a specific structure in a medium, which can achieve efficient management of geospatial data. Users can add, modify, and delete data efficiently. Furthermore, query retrieval and statistical analysis can be quickly performed based on geospatial database. In this paper, distributed geospatial database is constructed by using database partition tables storage technology. Meanwhile, database construction software is developed to achieve the construction, management, and application of large-scale geospatial data. It can improve data import, query and retrieval efficiency significantly. The database application service system can directly connect to the database for displaying statistical analysis results. At the same time, geospatial data are processed to vector tiles, which stored in the tile database. Furthermore, standard online service is then published, which can be used for database management and application service system. It can be used for natural resource management work such as basic surveying, survey and monitoring, and so on.