Land Use Planning Platform

Objective

Benefits

Nature Conservation, Ecosystem studies and Environmental Impact Assessment, Monitoring Pollution; Pest Control

Study of Soil Erosion;

Management of Protected Areas;

Mapping Biodiversity;

Remote Areas Development;

Regional Planning;

Resource Management;

Geologic Surveying and Prospecting;

Nation-wide Land Use Planning

In general, it serves Satellite Imaging retrieval and management

Components

Tools

The Platform supports several tools, applied in User Assisted Mode, or Automated Batch.

Shape Recognition and Feature Extraction

Core Tool is shape recognition and identification of “anchor points”, as explained in Ghabbour, 2008, under “Methodology”.

This Project, is unique as it

- relates, using also AI techniques, spectral sensor characteristics to texture information (tree-top shadows, foliage size, density, as applied to species classification, see Fassnacht, et al., 2016).

- Use heavily the published literature (part of the Data Space, below) to build its feature library (that is, based on the pool of academic research for feature identification).

Thematic Mapper Landsat image compared to Morphotectonic map (example from South Sinai, Egypt)

Source: El-Rakaiby, M.L. and El-Aassy, I.A., 1990, figures 2 and 3.

Tools Library

The Shape Recognition Tool is coupled with others that has a proven record, in different consequential applications (for example, Hermasa, et al., 2012, as applied in Egypt).

User-assisted Coregistration of Optically Sensed Images and Correlation, applied to sand dunes monitoring, Sinai, Egypt (used for demonstration purposes)

Source: Hermasa, et al., 2012.

Architecture

To support dynamic discovery of location related features (topographic, archeological, …) and data of different focus areas, a Universal Architecture has been developed.

Land Use Planning Universal Architecture

Source: Ghabbour, 2008

It allows linking Biome characteristics to Taxa (plant and animal species) to Ecosystem Services.

Taxa related location information from a number of Museum specimen collections.

Source: Ghabbour, 2006

Data Space

Terabytes of remote sensing data covering earth, of several resolutions, wide range of sensor characteristics, processed and feature-extracted, unprocessed, and converted to entity based tuples, are the main source. In terms of information theory, the discipline is well developed. Elevation Models, maps, published research, surveys, mission reports, over centuries, are also rich sources.

Evidence of biological origin, at a specific stratigraphic layer, Dababiya Natural Protected Area, Egypt (proposed World Heritage Site) … Paint is used to indicate Boundaries (here, showing Unit 2, within Dababiya Quarry Member)

Source: Ghabbour, 2010 (author copy)

Since the Project inception, unique Data Sets (eg, Ghabbour, 2006) and Material has been fed into the Platform.

Dr Rafik Ghabbour during preparation of St. Catherine area, South Sinaï, Egypt, as a mixed World Cultural and Natural Heritage Site Nomination File

Source: A “Consolidated Replacement Text” for the Nomination of THE ST. CATHERINE AREA, SOUTH SINAÏ, EGYPT, AS A MIXED WORLD CULTURAL AND NATURAL HERITAGE SITE.

Data Source Layers

Features are extracted, stored and viewed in its different presentations across Data Source Layers.

Data Source Layers of a selected territorial footprint

Source: Ghabbour, 2008

Continuous Process

Data, from several sources, as field sampling readings, sat images, elevation models, remote sensing and literature are collected from primary sources. Eventually Field data are digitized. Then data is brought to the Model (tabulated, formalized, values normalized, …).

Visualization

For this data richness, the Platform offers association-based Navigation, integrated View Layers, information windows, etc.

Knowledge Navigation (actual screen)

Bibliography

Commission des sciences et arts d’Egypte, 1809–22, Description de l’Égypte, ou Recueil des observations et des recherches qui ont été faites en Égypte pendant l’expédition de l’armée française, Paris.

Fassnacht, Fabian Ewald; Hooman Latifi; Krzysztof Stereńczak; Aneta Modzelewska; Michael Lefsky; Lars T. Waser; Christoph Straub; Aniruddha Ghosh, 2016, “Review of studies on tree species classification from remotely sensed data”, Remote Sensing of Environment, Vol: 186, Page: 64-87. DOI: 10.1016/j.rse.2016.08.013.

Hermasa, ElSayed; Leprince, Sebastien and Abou El-Magd, Islam, 2012, “Retrieving sand dune movements using sub-pixel correlation of multi-temporal optical remote sensing imagery, northwest Sinai Peninsula, Egypt”, Remote Sensing of Environment, Volume 121, June 2012, Pages 51–60.

Ghabbour, Rafik, 2006, “A Global Database for Arab Biodiversity Specimens in Foreign Natural History Museums: A Cognitive Approach”. Egypt Mab Bulletin, Egyptian National MAB Committee, Cairo, V. 30, N. 5 Suppl. P. 115-137. (Preview).

Ghabbour, Rafik, 2008, Land Use Planning Using Satellite Imaging: An Artificial Intelligence Approach, Science and Technology Development Fund, Cairo.

Ghabbour, Rafik, 2010, “Dababiya Natural Protected Area: A First View”, Egypt Mab Bulletin, Egyptian National MAB Committee, Cairo.

El-Rakaiby, M.L. and El-Aassy, I.A., 1990, “Structural interpretation of Paleozoic-Mesozoic rocks, Southwestern Sinai, Egypt”, Annals Geological Survey Egypt, Vol 16, (1986–1989), 269–273.

See Also

Dabbabiah Protected Area, 30 km drive South of Luxor. Dr Rafik Ghabbour interviewing IUGS Prof Marie-Pierre Aubry, International leader of the Chair of UNESCO/IUGS IGCP Project 308 on the Paleocene/Eocene Boundary Stratotype, at Location [French].

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Part of Vision 5

Initiative Sponsored by Dr Rafik Ghabbour