GeoJamal Toolbox is currently in its beta stage and will be updated in future releases with additional tools and improved performance. Your feedback,
Many researchers face difficulties when applying spatial models or spectral indices in ArcGIS due to time constraints or complexity. To address these challenges, we developed Geojamal Toolbox Pro v20.0803.38 beta, a collection of over 38 tools designed to simplify and speed up geospatial tasks within ArcGIS 10.x environments.
Included Categories in GeoJamal Toolbox
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🖼️ Remote Sensing - Image Processing Tools
These tools enhance raw satellite data, making imagery more interpretable and suitable for geospatial analysis and cartographic outputs.
- Contrast Stretching Based on Min/Max Values: Automatically adjust pixel brightness and contrast based on the actual image range, improving feature clarity and image aesthetics.
- Convert Pixel Values To and From NoData: Accurately handle invalid or missing pixel values. Convert arbitrary values into NoData for masking or convert NoData into valid integers for reprocessing.
- Image Clipping and Sharpening Tools: Crop imagery to your area of interest and apply spatial sharpening techniques to enhance detail and improve edge detection.
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🌄 DEM Analysis Tools in GeoJamal Toolbox
Digital Elevation Models (DEMs) are foundational for terrain modeling and hydrological studies. These tools allow topographic feature extraction and elevation data processing with ease.
- Aspect Classification into Four Slope Directions: Automatically categorize slope directions into North, South, East, and West exposures. Useful for landscape ecology, solar energy planning, and habitat modeling.
- Hydrological Network and Stream Order Extraction: Generate drainage patterns and classify stream order using Strahler method to support watershed delineation, hydrological simulations, and flood risk mapping.
- DEM Mosaicking: Combine multiple elevation tiles into one continuous DEM layer, preserving spatial accuracy and creating seamless terrain maps for larger regions.
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🌧️ Soil Erosion Modeling
Model and assess erosion risks using satellite data and empirical approaches. These tools support sustainable land use planning and soil conservation studies.
- EPM Model with Satellite Imagery: Apply the Erosion Potential Method (EPM) using land cover, slope, and rainfall indices extracted from remote sensing data to estimate erosion potential under various land management scenarios.
- PAP/CAR Model for Mediterranean Erosion Estimation: Specifically designed for semi-arid and Mediterranean landscapes, this model helps estimate erosion risk using rainfall erosivity, landform, and vegetative cover indices.
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🌱 Spectral Index Calculation
Spectral indices are powerful tools for extracting thematic information from satellite images. These tools allow automated calculation of various indices related to water, vegetation, soil, and environmental monitoring.
- Water and Moisture Indices: Includes NDWI, MNDWI, and similar indices that highlight surface water bodies and detect moisture variation in vegetation and soil — essential for drought monitoring and hydrological assessments.
- Soil-Related Indices: Analyze soil brightness, color, moisture, and organic matter content with indices such as NDSI and SAVI. These indices help detect erosion, salinization, and land degradation.
- Vegetation and Fire Indices: Use NDVI, EVI, NBR, and more to monitor vegetation health, biomass changes, and post-fire recovery. Ideal for forestry, agriculture, and climate impact studies.
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🛰️ Landsat Image Correction Tools
Preprocessing tools for converting raw Landsat image bands into radiometrically and atmospherically corrected data, making them ready for scientific analysis.
- Conversion to Radiance: Translate digital numbers (DN) to Top-of-Atmosphere (TOA) Radiance using sensor-specific metadata. This prepares the image for physics-based analyses like LST and reflectance calculations.
- Conversion to Reflectance: Convert TOA Radiance into Surface Reflectance to correct atmospheric effects and enable accurate multi-temporal and multi-sensor comparisons.
- Land Surface Temperature (°C) Estimation: Calculate ground surface temperature using thermal bands and emissivity correction. This tool is vital for heat island studies, climate research, and land-atmosphere interaction analysis.
- Sun Angle Correction: Adjust surface reflectance values according to sun elevation and azimuth, reducing shadow and illumination discrepancies, especially in mountainous terrain or multi-date imagery.
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📊 Image Correlation Tool
Compare two raster layers to evaluate spatial similarity or change over time. Useful for change detection, monitoring vegetation dynamics, or validating classification results.
- Image Correlation and Change Detection: Calculates correlation coefficients between input rasters to detect trends, anomalies, or consistent patterns across time — crucial for land use change studies and environmental monitoring.
This GeoJamal Toolbox is currently in its beta stage and will be updated in future releases with additional tools and improved performance. Your feedback, suggestions, and reports of any bugs encountered during use are most welcome and will help us improve future versions.
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