Query Shell Module GeoLIMIS Query Shell

It is the main display analysis and query shell module (Figure 7) which facilitates display of spatial and non-spatial data, identification of theme attributes, overlay of themes, visual query of single of multiple themes, generation of integrated layers, building queries for suitable locust sites and habitat suitability map in desired scale as well as statistics generation. Besides query shell hosts a number of other functionalities viz. symbol updating, choice of text font and color, zooming/panning, saving of map output in various formats etc.

Figure 7: Query shell main menu

Figure 7: Query shell main menu

SELECT_AOD (Selection of area of display): This is the first option which facilitates user to select desired area of display (Figure 8). Selection could be made for one or more polygons, by defining as irregular area or by specifying the geographic coordinates. The area could be selected by clicking on the graphics or by name through a pull down menu. The selected area of display (AOD) will be used for all display purpose. Area outside the AOD will be virtually masked.

SPATIAL_DISPLAY (Spatial display of themes, Primary or Derived): The option is used for display of selected theme (primary or derived) pertaining to the AOD (Figure 9a, b, c, d). Along with map the legend, display scale, north arrow and index map is also displayed.

NON_SPATIAL _DISPLAY (For displaying of locust and meteorological data): This facility provides display of locust related information viz. density of egg/hopper/adult etc in the form of spot/ratio (Figure 10a, b) as well as meteorological data of selected variable on monthly basis in graphical form. The size of the spot varies proportionately with the value of density. The detailed information of any locust sight could be visualized as a text file using sight-info button. The some of the climate data that could be plotted include temperature, humidity, wind velocity, cloudiness and rainfall in the form of bar or line diagram. For climate data display the EXCEL file must be available in the user's workspace. The package automatically coverts .xls files for corresponding meteorological station into INFO file. In the EXCEL to INFO conversion interface, the user can specify the name of the station along with the year of interest.

Figure 8: Selection of area of display

Figure 9: Spatial display of themes

Figure 9: Spatial display of themes

IDENTIFY (To identify attribute of the themes at user specified location): It helps the user to identify attributes at user specified location (Figure 11). Identification could be for currently displayed theme, selected themes or multi-themes.

OVERLAY (For overlaying selected features of a theme on the displayed theme): It facilitates the user to overlay selected features of a theme on the displayed theme. Overlaid theme is displayed in the form of polygon, lines, points or hatched polygons (for themes of GRID type) with selected color/ pattern (Figure 12).

VIS_QUERY (For visual query of single or multiple themes): The purpose of this option is to perform visual query of single theme or across multiple themes i.e. to display selected subset of features (attributes) using query builder. The area satisfying the user defined query is only displayed (Figure 13). In the query builder menu the name of the selected theme appears along with

K:fr.f.-KH J:S.bji33 -i HIP; H.:.VIV

Figure 10: Non-spatial data display

Figure 10: Non-spatial data display

Figure 11: Attribute identification specific location
Figure 12: Overlay of themes (a) polygon-polygon (b) polygon-line

relational operators - AND, OR along with choice for the attribute. Once the attribute of a theme is selected it can be added to the query set. The existing query can however, be added or edited. Once all the theme specific queries are put together in the query set the 'DRAW' button executes plotting of areas satisfying the criteria defined in the query set.

COMPOSITE (To generate integrated layers viz. SOLSCAPE and SOMVI and the final composite layer): The layers to be used for the generation of habitat suitability can be grouped into tow broad derived layers based on temporal sampling requirements for analysis. It is presumed that landform and soil texture are relative static geophysical properties in temporal scale and could be generated afresh once in 7-10 years time frame. Similarly is the case of broad landuse, which remained almost unchanged over the years in Kazakhstan except the current fallows are becoming permanent. Only the biomass cover changes drastically with summer and spring. Hence it was felt logical to integrate these three layers to generate SOLSCAPE layer, which could be used as it is for 2 or more consecutive seasons.

Figure 13: Visual query for single and multiple themes

On the other hand vegetation density and soil moisture are highly dynamic in temporal and spatial scale. Hence there is a need to map both of these parameters in every 7-10 days interval. Coarse resolution satellite data thought to be adequate for such dynamic features as the locust activity is a regional phenomena and not does not affect by local changes. These two parameters were combined together to generate an integrated layer called SOMVI. Integration of both SOLSCAPE and SOMVI generate final COMPOSITE layer which is the precursor for habitat suitability analysis.

LOC_DATA_ANAL (Analysis of locust data for input to query builder): Locust information in conjunction with ground and meteorological data is a prerequisite for developing expert system through the process of "knowledge gain". Historic locust data such as swarm type, species type, egg/hopper/adult density, area infested vis-à-vis concurrent weather during infestation will help the modeler to predict optimal range and combination of weather parameters in relation to locust response (Figure 14).

Besides climatic suitability locust data is also utilized to analyze in reference to in situ condition in the ground segment. The land condition underneath buffer area gives valuable input about locust preference for soil moisture, texture, vegetation etc and cohort distribution based on known sampling area. The buffer area generates report across multiple themes and displays as per cent distribution of various classes of each theme.

HABITAT_SUITABILITY (To generate habitat suitability layer): Based on locust data analysis the query set is generated and each set is given a class name such as most favourable, favourable, medium favourable and not favourable (Figure 15). This file is saved as .qry file for eventual use in habitat suitability map generation.

Figure 14: Locust data analysis interface

Figure 15: Habitat suitability map

TOOLS (Miscellaneous functions): The other functions include zooming and panning, saving of image in desired format, statistics generation, setting of text font and color, viewing of symbolset, updating of symbols and execution of ARCPLOT commands externally.

Renewable Energy Eco Friendly

Renewable Energy Eco Friendly

Renewable energy is energy that is generated from sunlight, rain, tides, geothermal heat and wind. These sources are naturally and constantly replenished, which is why they are deemed as renewable.

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