Mapping Of Natural Resources Research Articles

Community Resource Mapping in Sustainable Natural Resource Management: A Case Study of SW Uganda

AbstractSouthwestern Uganda represents a fragile ecosystem of complex and interrelated ecology with extreme socio‐cultural and biophysical diversity. The area has productive soils and receives bimodal rainfall promoting varied agricultural systems and land use practices. With population growth of 2.2% per annum, this ecosystem is exposed to environmental and socio‐economic problems like land degradation, soil erosion, low‐income, poor nutrition, fragmented farms and low agricultural output. To mitigate these environmental and socio‐economic uncertainties, and continue exploiting these rich natural resources areas, ICRAF and FORRI developed intervention strategies ranging from integrated watershed management to tree germplasm production and distribution. These intervention strategies were supported by community resource mapping for integrating predefined‐research areas into community knowledge of their own resources. Acquired geospatial data were analyzed to support community resource mapping and scientific analysis was used for assessment of impacts of land management practices, conservation and conflict resolution. Community–based resource managers and local policy makers were trained in geospatial tools and applications. A GIS node was established in Kabale district to support future spatial analysis and information management. This paper reviews how integrated natural resource intervention strategies and community resource mapping were complemented to realize sustainable development action planning in SW Uganda. It also reviews the benefits of community resource mapping in property rights and geospatial technology transfer. IN this paper, technical backstopping of community effort and capacity building are recommended for sustainable community resource mapping activities.

Using Aerial Video to Train the Supervised Classification of Landsat Tm Imagery for Coral Reef Habitats Mapping

Management of coral reef resources is a challenging task, in many cases, because of the scarcity or inexistence of accurate sources of information and maps. Remote sensing is a not intrusive, but powerful tool, which has been successfully used for the assessment and mapping of natural resources in coral reef areas. In this study we utilized GIS to combine Landsat TM imagery, aerial photography, aerial video and a digital bathymetric model, to assess and to map submerged habitats for Alacranes reef, Yucatán, México. Our main goal was testing the potential of aerial video as the source of data to produce training areas for the supervised classification of Landsat TM imagery. Submerged habitats were ecologically characterized by using a hierarchical classification of field data. Habitats were identified on an overlaid image, consisting of the three types of remote sensing products and the bathymetric model. Pixels representing those habitats were selected as training areas by using GIS tools. Training areas were used to classify the Landsat TM bands 1, 2 and 3 and the bathymetric model by using a maximum likelihood algorithm. The resulting thematic map was compared against field data classification to improve habitats definition. Contextual editing and reclassification were used to obtain the final thematic map with an overall accuracy of 77%. Analysis of aerial video by a specialist in coral reef ecology was found to be a suitable source of information to produce training areas for the supervised classification of Landsat TM imagery in coral reefs at a coarse scale.

Knowledge Discovery from Area‐Class Resource Maps: Data Preprocessing for Noise Reduction

AbstractSpatial data mining techniques have been investigated to extract valuable knowledge from natural resource maps. One challenge in applying general‐purpose data mining algorithms to knowledge discovery from these maps is that the unavoidable existence of errors in traditional area‐class resource maps introduces noise to the process and impacts the accuracy of the extracted knowledge. This paper examines the effect of data preprocessing in knowledge discovery from area‐class resource maps. Presented here is a sampling method designed to obtain samples that exclude noise and are representative of the central concepts of the mapped classes. The method is based on selecting only the pixels that fall in modes of environmental histograms for each individual class. A case study in extracting knowledge from soil maps shows that data preprocessing plays an important role in the knowledge discovery process, and that the sampling method based on environmental histograms significantly improves the knowledge discovery performance.

Knowledge discovery from soil maps using inductive learning

This paper develops a knowledge discovery procedure for extracting knowledge of soil-landscape models from a soil map. It has broad relevance to knowledge discovery from other natural resource maps. The procedure consists of four major steps: data preparation, data preprocessing, pattern extraction, and knowledge consolidation. In order to recover true expert knowledge from the error-prone soil maps, our study pays specific attention to the reduction of representation noise in soil maps. The data preprocessing step has exhibited an important role in obtaining greater accuracy. A specific method for sampling pixels based on modes of environmental histograms has proven to be effective in terms of reducing noise and constructing representative sample sets. Three inductive learning algorithms, the See5 decision tree algorithm, Naïve Bayes, and artificial neural network, are investigated for a comparison concerning learning accuracy and result comprehensibility. See5 proves to be an accurate method and produces the most comprehensible results, which are consistent with the rules (expert knowledge) used in producing the soil map. The incorporation of spatial information into the knowledge discovery process is found not only to improve the accuracy of the extracted knowledge, but also to add to the explicitness and extensiveness of the extracted soil-landscape model.

Principles of regional assessment and mapping of natural groundwater resources

The modern state of scientific investigations for regional assessment and mapping of the natural groundwater resources is characterized. The main methods for regional assessment of the natural groundwater resources (river hydrograph separation by genetic recharge species for a long-term period, hydrodynamic methods, methods for perennial water-balance assessment for water recharge or discharge areas), their advantages and limitations are discussed. It is noted that the use of these methods for regional assessment of natural groundwater resources and groundwater runoff is based on analyzing and processing available hydrological and hydrogeological information and does not demand special expensive drilling and pumping tests. It is suggested to assess specific groundwater discharge modules, characterizing groundwater flow in 1 l/s per 1 km2, the coefficient of groundwater discharge, characterizing groundwater recharge by infiltration in percent from the precipitation volume, and the coefficient of river recharge by groundwater, indicating the contribution of groundwater in the total river runoff, as the main quantitative characteristics of natural groundwater resources. The above-mentioned methods and quantitative characteristics of natural groundwater resources were used for compiling different scale maps of groundwater discharge for separate large regions, countries, central and eastern Europe, as well as the map of hydrogeological conditions and groundwater discharge of the world.

CARTOGRAPHY IN THE USSR ACADEMY OF SCIENCES, 1917–1991

The principal stages in the development of cartography in the USSR Academy of Sciences before and during World War II, as well as during the postwar period, are examined. Among the major accomplishments described are those involved in mapping of Russia's natural resources; the development of the principal branches of thematic cartography; comprehensive mapping of the Earth and individual countries in the form of comprehensive global and national atlases; and the development of new theoretical concepts in cartography and new scientific schools and directions in thematic cartography. Translated by Edward Torrey, Alexandria, Virginia from: Izvestiya Akademii Nauk, seriya geograficheskaya, 1999, No. 4, pp. 98-111.

A personal construct-based knowledge acquisition process for natural resource mapping

This paper presents an iterative, structured knowledge-acquisition process for extracting human understanding of relationships between a natural resource and its environment. This understanding can then be used to map natural resources as spatial continua. The knowledge acquisition process is based on personal construct theory and consists of several iterations. Each iteration has five structured interview sessions: preparation, key development, description, comparison, and quantification. The knowledge derived from each iteration is represented as a set of membership functions that describes the degree to which a given environmental condition impacts the status of the given resource. The final set of membership functions, which is the final version of knowledge, is derived through the comparison and 'fusion' of the membership functions from each iteration. The comparison of the membership functions among different iterations is also used to measure the consistency (integrity) of an expert's understanding of the relationships. In a soil mapping case study, knowledge on soil-environment relationships was acquired from a local soil scientist using the knowledge acquisition process. The case study shows that knowledge sets extracted a year apart were consistent with each other. The study also shows that the soil expert was more familiar with the relationships between soils and some environmental variables than with other environmental variables. The expert's understanding about soil-environmental relationships also differed among soil series. Although it was designed to extract expert knowledge for mapping natural resources as spatial continua under a GIS environment, this knowledge elicitation process can be easily adapted to extract expert knowledge for other knowledge-based applications.

Surveying and mapping of natural resources by remote sensing

Sustainable economic development requires detailed knowledge of the natural resources of any nation. Acquiring the needed information by conventional means may require a large investment in time, personnel, and therefore, in cost. A viable alternative is space‐age technology which provides the necessary tools to conduct surveys of natural resources in a timely manner. Such technologies can obtain the required data by means of digital sensors, radar imaging systems and stereo cameras. These data can be utilized to map structures that may contain oil and gas deposits, recognize high concentrations of economic minerals, and discover regions with fertile soils and good potential for groundwater. Those applications warrant greater use of remote sensing methods and techniques by the international scientific community, particularly for the development of natural resources in the Third World. This paper represents a general review of the available, and easily interpretable, space‐borne data that are useful in the mapping of natural resources.

Modelling soil map-unit inclusions by Monte Carlo simulation

Abstract Error and uncertainty in spatial databases have gained considerable attention in recent years. The concern is that, as in other computer applications and, indeed, all analyses, poor quality input data will yield even worse output. Various methods for analysis of uncertainty have been developed, but none has been shown to be directly applicable to an actual geographical information system application in the area of natural resources. In spatial data on natural resources in general, and in soils data in particular, a major cause of error is the inclusion of unmapped units within areas delineated on the map as uniform. In this paper, two alternative algorithms for simulating inclusions in categorical natural resource maps are detailed. Their usefulness is shown by a simplified Monte Carlo testing to evaluate the accuracy of agricultural land valuation using land use and the soil information. Using two test areas it is possible to show that errors of as much as 6 per cent may result in the process of...

Особенности использования космической информации для картографирования природных кормовых ресурсов

Особенности использования космической информации для картографирования природных кормовых ресурсов

Satellite remote sensing for resources development

1. General Aspects of the Use of Satellite Remote Sensing for Resources Exploration in Developing Countries.- 2. Present Status of Microwave Remote Sensing from Space with Respect to Natural Resources Monitoring.- 3. SPOT: The First Operational Remote Sensing Satellite.- 4. Spacelab Metric Camera Experiments.- 5. Coastal Zone Color Scanner (CZCS) and Related Technologies.- 6. Selected Features of the SEASAT Satellite.- 7. First Results of the European Spacelab Photogrammetric Camera Mission.- 8. Thematic Mapping of Natural Resources with the Modular Optoelectronic Multispectral Scanner (MOMS).- 9. Availability of Remotely Sensed Data and Information from the U.S. National Oceanic and Atmospheric Administration's Satellite Data Services Division.- 10. A Future Outlook.- 11. Interpretation and Application of Spaceborne Imaging Radar Data to Geologic Problems.- List of Participants.

A LANDSCAPE-TYPOLOGY REGIONALIZATION OF MONGOLIA BASED ON SPACE IMAGERY

A joint Soviet-Mongolian project of 1978-80 using space imagery for the mapping of Mongolia's natural resources is described. The novelty of using space photographs called for the development of new techniques. The remote sensing approach enabled the investigators to compile within a relatively short time a map of natural territorial complexes of Mongolia, distinguished by a high degree of detail, and to gain a new understanding about many aspects of the Mongolian Physical environment. Translated from: Izvestiya Akademii Nauk SSSR, seriya geograficheskaya, 1984, No. 4, pp. 5-14.