Mapping Of Natural Resources Research Articles

Recent innovations in land capability classification for sustainable development: a brief overview.

Land is a finite resource that must be managed wisely to ensure its sustainability. Consequently, land evaluation has become essential. Identifying and utilizing productive capacity of land efficiently and profitably is crucial; otherwise, resource degradation can severely impact natural ecosystems and food production. Over the years, various methodologies have been employed to assess land resources, and one such method is the Land Capability Classification (LCC). LCC is a widely used and fundamental approach to land-use planning, traditionally assessing land based on its intrinsic qualities and climate. This study aims to highlight new approaches and developments in land evaluation techniques. It provides a brief overview of recent technological and scientific advancements integrated into land evaluation. The findings suggest that LCC alone is inadequate for precise land assessment, emphasizing the need to integrate new technologies. Remote Sensing (RS) and Geographic Information System (GIS) technologies are becoming increasingly significant. Integrating various software, decision-making systems, and mathematical models can also enhance the accuracy of land assessment results. The continuous advancement of GIS and remote sensing technologies is paving the way for new tools to facilitate natural resource mapping, appraisal, surveillance, and management. Utilizing these technologies for future projections will be highly beneficial in accurately assessing the long-term impacts of current land management practices.

Regional perspective on prospects and risks of the renewable energy in Russia

AbstractThe expansion of renewable energy (RE) relies on both natural factors and socioeconomic conditions fostered at the regional level. This paper examines the key factors influencing RE development in selected Russian regions. We conducted a literature review, surveyed 250 industry experts, and analyzed reports from energy and rating agencies, along with natural resource maps, to identify specific risks and indicators. Our expert survey revealed that the most significant technical risks are low resource potential (68%), energy system surplus (68%), and the absence of transport logistics with neighboring regions (58%). Politically, the lack of additional sector initiatives (6%) was noted. Economically, the high cost of RE (56%) and insufficient experience with “green” investments (54%) were highlighted. Social factors included low unemployment rates (74%), and the absence of remote areas without power supply (72%). Environmentally, the lack of enterprises for energy unit utilization (84%), low greenhouse gas emissions (60%), and insufficient accessible territories for facilities (58%) were significant concerns. We developed risk profiles for nine Russian regions, categorizing them into leaders, intermediates, and nascent stages of RE market formation. Our findings indicate that the most impactful factors include resource potential, space limitations for energy facilities, proximity to equipment manufacturers, regional support measures, and the development of “green” investment instruments. Conversely, regional investment attractiveness had a lesser influence. On the basis of these insights, we recommend enhancing RE development through refined federal and regional support programs. We propose additional criteria for project selection: (1) minimum construction costs covered by “green” investments and (2) quantitative restrictions on new capacities, considering regional energy system status. Practical recommendations also include developing regional centers for servicing generating facilities and increasing the sector's investment attractiveness to stimulate private investment.

Comparative Study SVM and Random Forest Algorithms for the Classification of Terrestrial Visual Rock Types

Abstract The advancement in image processing technology, along with the increasing demand for classifying terrestrial visual rock types in diverse applications such as geological exploration and natural resource mapping, has prompted investigations into the application of machine learning algorithms to enhance classification accuracy. This research aims to assess the performance of the Support Vector Machine (SVM) and Random Forest algorithms in classifying terrestrial visual rock types. The study utilizes a dataset containing images of various rock types sourced from KAGGLE. Both Random Forest and Support Vector Machine methods are employed for rock type classification, and their performances are compared to determine the more effective method. Through experimental analysis on the KAGGLE rock dataset, the study provides evidence supporting the efficacy of the proposed method and identifies the Random Forest algorithm as the more suitable option for rock type classification. Evaluation criteria include accuracy, precision, recall, and F1-score metrics. The research findings reveal that the Random Forest algorithm achieves a higher accuracy rate of 86.25%, with a precision of 0.97, recall of 0.86, and an F1-Score of 0.91, establishing its superiority in rock type classification.

MULTISOURCE AND MULTITEMPORAL LAND COVER MAPPING OF GREATER LUZON ISLAND USING GOOGLE EARTH ENGINE

Abstract. A variety of research endeavors and practical applications necessitate the use of land cover maps. These maps are valuable for tasks such as change detection, forest monitoring, urban expansion monitoring, natural resource mapping, catering to diverse user requirements. While satellite sensors offer essential data for comprehending spatial and temporal variations in land cover, relying on a single satellite system can be limiting, especially considering the potential hindrance of cloud cover in the case of optical sensors. To enhance temporal frequency, it becomes essential to utilize multiple satellite systems, albeit requiring harmonization to ensure consistent outcomes. This study presents a large-scale annual land cover mapping which utilizes harmonized Landsat-8 and Sentinel-2 satellite imagery, in conjunction with supplementary data, and a machine learning algorithm. In addition, the use of powerful computational processing platforms such as Google Earth Engine and Google Colaboratory is now a requirement to manage big geospatial data as well as to run different algorithms for processing and analysis.

Uncertainty of spatial averages and totals of natural resource maps

AbstractGlobal, continental and regional maps of concentrations, stocks and fluxes of natural resources provide baseline data to assess how ecosystems respond to human disturbance and global warming. They are also used as input to numerous modelling efforts. But these maps suffer from multiple error sources and, hence, it is good practice to report estimates of the associated map uncertainty so that users can evaluate their fitness for use.We explain why quantification of uncertainty of spatial aggregates is more complex than uncertainty quantification at point support because it must account for spatial autocorrelation of the map errors. Unfortunately, this is not done in a number of recent high‐profile studies. We describe how spatial autocorrelation of map errors can be accounted for with block kriging, a method that requires geostatistical expertise. Next, we propose a new, model‐based approach that avoids the numerical complexity of block kriging and is feasible for large‐scale studies where maps are typically made using machine learning. Our approach relies on Monte Carlo integration to derive the uncertainty of the spatial average or total from point support prediction errors. We account for spatial autocorrelation of the map error by geostatistical modelling of the standardized map error.We show that the uncertainty strongly depends on the spatial autocorrelation of the map errors. In a first case study, we used block kriging to show that the uncertainty of the predicted topsoil organic carbon in France decreases when the support increases. In a second case study, we estimated the uncertainty of spatial aggregates of a machine learning map of the above‐ground biomass in Western Africa using Monte Carlo integration. We found that this uncertainty was small because of the weak spatial autocorrelation of the standardized map errors.We present a tool to get realistic estimates of the uncertainty of spatial averages and totals of natural resource maps. The method presented in this paper is essential for parties that need to evaluate whether differences in aggregated environmental variables or natural resources between regions or over time are statistically significant.

BITUMEN RESOURCES OF THE EAST SIBERIAN BASIN

The so‐called East Siberian “Basin” extends over an ancient continental block, the Siberian Platform, and is made up of a number of smaller‐scale basement arches and basins with a variable sedimentary cover of mostly Proterozoic and Palaeozoic ages. The basin hosts the oldest large‐scale petroleum systems known. Proterozoic (“Riphean”: 1650‐650 Ma) marine source rocks, which were deposited on the passive margins which surrounded much of the Platform, generated hydrocarbons as they were buried, folded and thermally matured during a series of mostly Late Proterozoic to Cambrian continental collisions, with the final collision taking place in the Early Cretaceous along the northeastern (Verkhoyan) margin. The hydrocarbons were transported by long‐distance migration to reservoirs in the sedimentary successions which drape basement uplifts, there forming giant oil and gas accumulations which were sealed by extensive Cambrian evaporites. Subsequent uplift and unroofing, especially in the north and east of the Platform where the seal is not present, led to degradation of the oil to leave giant accumulations of bitumen, defined here as petroleum with an API gravity of less than 10° which is immobile under reservoir conditions. A significantly younger petroleum system, which may still be active, is present in the Vilyui Basin in the NE of the Siberian Platform. This basin was initiated as a mid‐Devonian rift and has a later Palaeozoic and Mesozoic fill.Bitumen accumulations in the East Siberian Basin occur mainly in Precambrian, Cambrian and Permian reservoir rocks, and began to form from precursor oils during the Permian. Around twenty‐five named fields have been described, many of which comprise portions of more extensive belts of bitumen occurrence. Although geological mapping of natural resources in the East Siberian Basin has been carried out since the 19th century, the region remains under‐explored and none of the bitumen accumulations has yet been developed.An attempt is made in this paper to catalogue and map all recorded occurrences of bitumen throughout the East Siberian Basin. Regional geological studies have been conducted in order to understand the origin and habitat of each occurrence. So far as possible, data on the areal extent and stratigraphic thickness of each bitumen occurrence has been collated, together with data on bitumen saturations and quality. These data were used to calculate resource volumes for each accumulation from first principles. Thus the total bitumen resources within the East Siberian Basin have been calculated as 24,640 MM (million) tonnes. Disregarding accumulations regarded as either of insufficient resource‐density or too small to merit consideration, this figure has been reduced to 14,760 MM tonnes. Recoverable reserves, by analogy with comparable resources worldwide, are calculated as 6100 MM tonnes (approximately 33,900 MM brl)

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.

Application of remote sensing in environmental studies: advantages and challenges

Growing concern about environmental challenges has led to the development of new observation tools to perform monitoring and assessment in a broad range of environments, application to conservation management and for mapping of natural resources. Although, the emerging methods and technologies of remote sensing are a powerful tool, they meet some difficulties and limitations in their real applications. This paper overview several projects and initiatives in Lithuania and Bulgaria related with application of both unmanned aerial vehicles and satellite imagery in various types of environment assessments. The benefits and limitations that emerged during the investigations have been discussed in the international workshop organised by the EU project of LIFE programme ALGAESERVICE for LIFE.

Integrating landscape ecology into landscape practice in Central African Rainforests

ContextWe describe how large landscape-scale conservation initiatives involving local communities, NGOs and resource managers have engaged with landscape scientists with the goal of achieving landscape sustainability. We focus on two landscapes where local people, practitioners and landscape ecologists have co-produced knowledge to design conservation interventions.ObjectiveWe seek to understand how landscape ecology can engage with practical landscape management to contribute to managing landscapes sustainably.MethodsWe focus on two large tropical landscapes: the Sangha Tri-National landscape (Cameroon, Republic of Congo and the Central African Republic) and the Batéké-Léfini Landscape (Gabon and Republic of Congo). We evaluate (1) a participatory method used in the Sangha Tri-National landscape that embeds interdisciplinary researchers and practitioners within a landscape to apply transdisciplinary learning to landscape conservation and (2) a participatory landscape zoning method where interdisciplinary teams of conservation practitioners analyse local land and resource use in the Batéké-Léfini landscape.ResultsWe find that landscape ecology’s tradition of understanding the historical context of resource use can inform landscape conservation practice and natural resource mapping. We also find that the Sangha Group provides an example for landscape ecology on how to integrate local people and their knowledge to better understand and influence landscape processes.ConclusionsPlace-based engagement as well as the uptake of co-produced knowledge by policy makers are key in enabling sustainable landscapes. Success occurs when researchers, local communities and resource managers engage directly with landscape processes.

Multidisciplinarity, Citizen Participation and Geographic Information System, Cross-Cutting Strategies for Sustainable Development in Rural Heritage. The Case Study of Valverde de Burguillos (Spain)

The pace at which cities grow and its impact on heritage management has meant that those heritage assets not linked to the traditionally monumental have been directly doomed to oblivion. The purpose of this article is to present a research methodology backed up by multidisciplinarity and stakeholders’ diversity that allows us to highlight the values and singular aspects of this rural heritage. To achieve this, a methodology was devised that is divided into three phases: mapping of human, cultural, and natural resources based on studies undertaken by the Public Sector Administration, experts, and the citizens themselves. The second phase involved the establishment of what to protect amongst all the stakeholders involved. Finally, the third stage entails integration of the information within an urban development framework. In order to work on the development of a diagnosis from three highly different approaches, Geographic Information Systems was used as information management tools, as a means of contrasting it and performing a comprehensive analysis of the same. The development of such a holistic approach provided a patrimonial map of essential resources in the municipality to be taken into account to shape sustainable development strategies inherent to a rural environment of low density. The lack of this comprehensive approach when managing rural heritage in which citizens take on centre stage in decision-making processes unearths two fundamental issues: firstly, the ascertainment of the existence of cultural heritage hitherto abandoned, alongside the need to endow urban governance powers to the public administration, as it falls to them to spearhead this shift in public management.

Upper crustal tectono-structural geomorphology inferred from satellite gravity and aeromagnetic anomalies beneath a basement-sedimentary transition region, southwestern, Nigeria

This study interprets upper-crustal tectono structural geomorphology beneath a basement-sedimentary transition zone in southwestern Nigeria using aeromagnetic and satellite gravity data. The results are enhanced models of the tectono-structural relationships between the sedimentary basin (Dahomey) and its adjoining basement and basin which can guide further research and geological decision-making associated with natural resource mapping and development in the region.

Storage and analysis of natural resources information in various territories

The article is devoted to the creation of a system of cartographic models of natural resources for a specific territory. The reasons for the inefficient use of natural resource information in modern Russia are described. The place of natural resource mapping in the formation of a natural resource information space is characterized. The task of systematic consideration of natural resources when creating cartographic support for solving the problems of natural resource management and environmental management planning has been set. It is proposed to develop a program for processing images in the GeoTIFF format, intended for the analysis of natural resources. The structure of the program for the planning and management of environmental management is presented. The main functional types of CMRD are outlined: inventory, estimated, forecasted, recommended. The features of their use at various stages of environmental management are identified.

TOPOGRAPHIC AND GEODESIC SOFTWARE OF ECOLOGICAL AND ECONOMIC ESTIMATION OF TERRITORIAL AGROGEOSYSTEMS

The state of the environment under the conditions of application of information systems based on the achievements of geoinformation technologies and data of aerospace and ground observations is studied. The concept of agroecosystems is analyzed and their main function is established, which is the production of food, plant and animal raw materials for light and food industries. Problems of creation of cartographic materials for display of agrogeosystems in an information field are considered. It is proposed to develop criteria for economic and environmental assessment of agrogeosystems, as well as the behavior of society in the use of natural resources. Economic and ecological criteria for assessment of territorial agrogeosystems are determined. The structural, functional and genetic features inherent in agrogeosystems are formed. The structural organization of agrogeosystems is considered, which causes significant changes in such indicators as sustainability and reliability. A new direction in geodesy is identified — economic and ecological mapping, where the role of thematic maps as a control tool is growing significantly. Thus it is possible to speak about creation of complex economic and ecological maps, a series of thematic maps, complex atlases, etc. The role of space photoinformation in the study of mapping of natural resources and phenomena is determined. Thematic tasks for topographic and geodetic support of ecological and economic assessment of territorial agrogeosystems, which can serve as a basis for the classification of spacecraft and remote sensing of the Earth. It is proved that topographic and geodetic support of ecological and economic assessment of territorial agrogeosystems should be based on modern technologies of collecting and processing geospatial topographic and geodetic information about agrogeosystems, regularly updated, as well as to ensure the reliability of information, accuracy of spatial elements. The main stages of topographic and geodetic support of ecological and economic assessment of territorial agrogeosystems are given.

Satellite-based spectral mapping (ASTER and landsat data) of mineralogical signatures of beach sediments: a precursor insight

Detailed investigation on texture and mineralogy of beach sediments helps to understand their nature of deposition and potential targets of strategic mineral deposits. The beach sediments from the coast of Thiruvananthapuram, the southernmost district of Kerala, India, have been studied to understand the variation in grain size by using the spectral indices as derived from the visible-NIR-TIR bands of Landsat and ASTER remote sensing data. Further, an attempt has been made to map the distribution of strategic minerals present in beach sands using standardized hyperspectral analysis techniques. The grain size shows a remarkable variation from medium sand to fine sand. The THM (Total Heavy Minerals) content was estimated to about 80.04% and 52.33% along the coast of Kovalam and Varkala, respectively. The ilmenite mineral predominantly exists in these areas, followed by monazite, sillimanite, rutile, zircon, garnet, leucoxene, and Kyanite. The hyperspectral analysis extracts two endmembers of ilmenite and light minerals from the Landsat and ASTER imagery, which could be successfully, mapped using the SAM classification algorithm. The satellite-derived map showing texture and mineralogy has been validated with the results of laboratory analysis and shows strong correlation almost in all locations. This study illustrates the potential use of satellite remote sensing techniques for the mapping of natural resources, especially mineral resources.

Application of Geospatial Information System for Mapping and Management of Natural Resources – A Review

Management of available natural resources is of utmost importance for the economic prosperity of any region. Use of Geospatial Information System provides very useful information about available natural resources in space and time. Important policy decisions can be taken on the basis of such information. Remote sensing provides important information on land use and land cover, vegetation, soil, morphology and water resources of any region. Using various models, different layers/scenarios can be created for the planning. Geospatial Information System can be used for the real-time mapping of wastelands, sodic and acidic lands, crop acreage, estimation of crop yield, degraded lands, groundwater, runoff potential, delineation of watersheds etc. This tool very important for providing information from inaccessible areas and real-time monitoring of intervention undertaken in any area. The present paper provides details of these methodologies and features of Geospatial Information System.

Mapping of Natural Resources and Creation of Database of Natural Resources of Bhaderwah, Doda, Jammu and Kashmir

Mapping of Natural Resources and Creation of Database of Natural Resources of Bhaderwah, Doda, Jammu and Kashmir

Technique of Large Scale Soil Mapping using Remote Sensing Satellite Data in Basaltic Terrain of Peninsular Region in the North-West Gujarat, India

Techniques for large scale mapping of natural resources is region specific. The technique of large-scale soil mapping using remote sensing data in basaltic terrain of Peninsular Region. The data used for the study are toposheet of Survey of India (1: 50 000 scale); cadastral map of the Pata Meghpar village (1: 4000 scale); and IRS P6 LISS-IV digital data of August (kharif season) and December (rabi season) 2012. Images were interpreted visually and ground truths were collected manually and prepared landscape ecological units (LEUs) map which was used for conducting soil survey and generation of soil map. The LEU units explained a three-tier approach comprising land form, slope and land use characteristics of each parcel of land. Soils occurring in different LEU units were examined and a LEU-soil relationship was developed. The soil map depicting phases of soil series was prepared using ArcGIS 10.0 software.

Indian Satellite Remote Sensing: Focus on Selected Applications and Societal Needs

Indian Earth Observation programme, founded on the basis of self reliance and development catering to the needs of the nation, has come a long way on all fronts of satellite launch vehicles, sensors, data handling, space technology applications and capacity building. Remote sensing applications have grown from mapping of natural resources using hard copy aerial colour and InfraRed photographs in 70s to geophysical parameter retrieval and providing solutions by integrating space technologies inputs from satellite remote sensing, navigation systems and mobile services through satellite communication. Realising the potential of these technologies in nation building, necessary institutionalization and capacity building has been put in place in a structured manner by setting up National Natural Resources Management System and State Remote Sensing Applications Centres, respectively, at Central and State government levels. This invited article deals with the historical development of remote sensing applications to natural resources, providing timely support to disaster management, space inputs for improved efficiency and transparency in governance in addressing the societal needs and the space technology support in South Asian region.

Free satellite imagery and digital elevation model analyses enabling natural resource management in the developing world: Case studies from Eastern Indonesia

Decentralization of governance and natural resource management is an ongoing process in many parts of Africa and Asia. Natural resource management requires spatial land resource data for planning. However, currently the financial and human capacity for natural resource mapping, monitoring and modelling remains low in local governments. In this context, this paper explores how new opportunities provided by the increasing availability of free satellite imagery, digital elevation data and open source spatial analysis software, can be applied by local government and NGOs to conduct sophisticated natural resource mapping and modelling in ways that meet their needs and incorporates local knowledge. Reported are cases of a local government using free geospatial data and GIS software to improve evidence‐based natural resource management in the developing world with a focus on raster data applications for satellite image analysis and terrain modelling. It is argued that, through removing barriers to uptake, such applications provide a means of decentralizing landscape analysis skills to improve local natural resource management. This hypothesis is supported through examples of a local government applying these tools in eastern Indonesia, and within this context barriers to wider adoption are explored.

Natural Resource Mapping Using Landsat and Lidar towards Identifying Digital Elevation, Digital Surface and Canopy Height Models

Natural Resource Mapping Using Landsat and Lidar towards Identifying Digital Elevation, Digital Surface and Canopy Height Models