Impervious surface estimation using remote sensing images and gis : how accurate is the estimate at subdivision level?

Impervious surface has long been accepted as a key environmental indicator linking development to its impacts on water. Many have suggested that there is a direct correlation between degree of imperviousness and both quantity and quality of water. Quantifying the amount of impervious surface, however, remains difficult and tedious especially in urban areas. Lately more efforts have been focused on the application of remote sensing and GIS technologies in assessing the amount of impervious surface and many have reported promising results at various pixel levels. This paper discusses an attempt at estimating the amount of impervious surface at subdivision level using remote sensing images and GIS techniques. Using Landsat ETM+ images and GIS techniques, a regression tree model is first developed for estimating pixel imperviousness. GIS zonal functions are then used to estimate the amount of impervious surface for a sample of subdivisions. The accuracy of the model is evaluated by comparing the model-predicted imperviousness to digitized imperviousness at the subdivision level. The paper then concludes with a discussion on the convenience and accuracy of using the method to estimate imperviousness for large areas

Program on Earth Observation Data Management Systems (EODMS)

An assessment was made of the needs of a group of potential users of satellite remotely sensed data (state, regional, and local agencies) involved in natural resources management in five states, and alternative data management systems to satisfy these needs are outlined. Tasks described include: (1) a comprehensive data needs analysis of state and local users; (2) the design of remote sensing-derivable information products that serve priority state and local data needs; (3) a cost and performance analysis of alternative processing centers for producing these products; (4) an assessment of the impacts of policy, regulation and government structure on implementing large-scale use of remote sensing technology in this community of users; and (5) the elaboration of alternative institutional arrangements for operational Earth Observation Data Management Systems (EODMS). It is concluded that an operational EODMS will be of most use to state, regional, and local agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products

Geoscience-aware deep learning:A new paradigm for remote sensing

Information extraction is a key activity for remote sensing images. A common distinction exists between knowledge-driven and data-driven methods. Knowledge-driven methods have advanced reasoning ability and interpretability, but have difficulty in handling complicated tasks since prior knowledge is usually limited when facing the highly complex spatial patterns and geoscience phenomena found in reality. Data-driven models, especially those emerging in machine learning (ML) and deep learning (DL), have achieved substantial progress in geoscience and remote sensing applications. Although DL models have powerful feature learning and representation capabilities, traditional DL has inherent problems including working as a black box and generally requiring a large number of labeled training data. The focus of this paper is on methods that integrate domain knowledge, such as geoscience knowledge and geoscience features (GK/GFs), into the design of DL models. The paper introduces the new paradigm of geoscience-aware deep learning (GADL), in which GK/GFs and DL models are combined deeply to extract information from remote sensing data. It first provides a comprehensive summary of GK/GFs used in GADL, which forms the basis for subsequent integration of GK/GFs with DL models. This is followed by a taxonomy of approaches for integrating GK/GFs with DL models. Several approaches are detailed using illustrative examples. Challenges and research prospects in GADL are then discussed. Developing more novel and advanced methods in GADL is expected to become the prevailing trend in advancing remotely sensed information extraction in the future.</p

Using airborne LiDAR Survey to explore historic-era archaeological landscapes of Montserrat in the eastern Caribbean

This article describes what appears to be the first archaeological application of airborne LiDAR survey to historic-era landscapes in the Caribbean archipelago, on the island of Montserrat. LiDAR is proving invaluable in extending the reach of traditional pedestrian survey into less favorable areas, such as those covered by dense neotropical forest and by ashfall from the past two decades of active eruptions by the Soufrière Hills volcano, and to sites in localities that are inaccessible on account of volcanic dangers. Emphasis is placed on two aspects of the research: first, the importance of ongoing, real-time interaction between the LiDAR analyst and the archaeological team in the field; and second, the advantages of exploiting the full potential of the three-dimensional LiDAR point cloud data for purposes of the visualization of archaeological sites and features

Use of remote sensing for land use policy formulation

The overall objectives and strategies of the Center for Remote Sensing remain to provide a center for excellence for multidisciplinary scientific expertise to address land-related global habitability and earth observing systems scientific issues. Specific research projects that were underway during the final contract period include: digital classification of coniferous forest types in Michigan's northern lower peninsula; a physiographic ecosystem approach to remote classification and mapping; land surface change detection and inventory; analysis of radiant temperature data; and development of methodologies to assess possible impacts of man's changes of land surface on meteorological parameters. Significant progress in each of the five project areas has occurred. Summaries on each of the projects are provided

Multidimensional Land-use Information for Local Planning and Land Resources Assessment in Indonesia: Classification Scheme for Information Extraction from High-Spatial Resolution Imagery

Suitable land-cover/land-use  information is rarely available in most developing countries, particularly when newness, accuracy, relevance, and compatibility are used as evaluation criteria.  In Indonesia, various institutions developed their own maps with considerable differences in classification schemes, data sources and scales, as well as in survey methods.  Redundant land-cover/land-use surveys of the same area are frequently carried out to ensure the data contains relevant information. To overcome this problem, a multidimensional land-use classification system was developed. The system uses satellite imagery as main data source, with a multi-dimensional approach to link  land-cover information to land-use-related categories.  The land-cover/land-use layers represent image-based land-cover (spectral), spatial, temporal, ecological and socio-economic dimensions.  The final land-cover/land-use database can be used to derive a map with  specific content relevant to particular planning tasks. Methods for mapping each dimension are described in this paper, with examples using Quickbird satellite imagery covering a small part the Semarang area, Indonesia.  The approaches and methods used in this study may be applied to other countries having characteristics similar to those of Indonesi

Remote Predictive Mapping 1. Remote Predictive Mapping (RPM): A Strategy for Geological Mapping of Canada’s North

Remote Predictive Mapping (RPM) techniques are being developed and refined by the Geological Survey of Canada for mapping Canada’s North. Remote Predictive Mapping should be considered an integral part of the geological mapping process designed to involve compilation, and re-compilation of data derived from existing geological maps, aerial photographs, satellite imagery, and airborne geophysical data. Predictive geological maps may be iteratively revised and upgraded to publishable geological maps by integrating remotely sensed data with newly acquired field and laboratory data, as RPM techniques are progressively tested and insight evolves. A predictive map, produced without collection of new, field-based data, may also serve as a first-order geologic map in areas where field-based studies cannot be accomplished due to expense of field access or remoteness. As a welcome consequence of adopting RPM into the normal work flow of any mapping or exploration project, there will, by necessity, be greater participation and integration of expertise of field geologists, geophysicists, Geographic Information System (GIS) and remote sensing specialists. Significantly, RPM also encourages geoscience organizations to make full use of all available geoscience data. This paper outlines a strategy for RPM and provides processing and interpretation examples based on a variety of geoscience data and interpretation techniques to be employed for geologic mapping. SOMMAIRE La Commission géologique du Canada développe et raffine des techniques de télécartographique prédictive (TCP) pour cartographier du Nord canadien. La télécartographie prédictive doit être perçue comme une composante intégrée d’un processus de cartographie géologique de compilation et de recompilation de données extraites de cartes géologiques, de photographies aériennes, d’imageries satellitaires, et de géophysiques aéroportées existantes. Les cartes géologiques prédictives peu-vent ainsi être révisées, mises à jour et publiées selon une approche itérative intégrant les données de télédétection avec les données de terrain et de laboratoire nouvellement acquises, au gré de l’évolution et du raffinement des techniques de TCP. Dans les cas de régions trop éloignées, ou parce que les coûts d’établissement de cartes géologiques de base régulières seraient prohibitifs, la TCP peut aussi être utilisée pour produire une carte géologique de base. D’entrée de jeu, on réalise que l’adoption de la TCP dans la routine de production normale de tout projet de cartographie ou d’exploration permettra, en soi, une meilleure prise en compte et une meilleure intégration des savoirs-faires des géologues de terrain, des géophysiciens et des spécialistes de la télédétection et des systèmes d’information géographique (SIG). Par sa nature même, la TCP permet aux organisations géoscientifiques de faire plein usage de toutes les données géoscientifiques dont elles disposent. Le présent article définit une stratégie de TCP et décrit des exemples de traitement et d’interprétation d’une variété de données géoscientifiques et de techniques d’interprétation utilisables pour la production de cartes géologiques

Land use classification in Bolivia

The Bolivian LANDSAT Program is an integrated, multidisciplinary project designed to provide thematic analysis of LANDSAT, Skylab, and other remotely sensed data for natural resource management and development in Bolivia, is discussed. Among the first requirements in the program is the development of a legend, and appropriate methodologies, for the analysis and classification of present land use based on landscape cover. The land use legend for Bolivia consists of approximately 80 categories in a hierarchical organization which may be collapsed for generalization, or expanded for greater detail. The categories, and their definitions, provide for both a graphic and textual description of the complex and diverse landscapes found in Bolivia, and are designed for analysis from LANDSAT and other remotely sensed data at scales of 1:1,000,000 and 1:250,000. Procedures and example products developed are described and illustrated, for the systematic analysis and mapping of present land use for all of Bolivia

Cornell University remote sensing program

There are no author-identified significant results in this report

Classification of areas using pixel-by-pixel and sample classifiers

There are no author-identified significant results in this report