Remote Sensing

Manipulating Satellite Imagery

Processing and analyzing raw satellite data derive meaningful insights for various engineering, environmental, and geographical applications. Using specialized tools like ENVI, ERDAS, and SNAP, this includes enhancing image quality, extracting information, or combining data with other datasets for deeper analysis.

At GEOCONSOL, we utilize multi-temporal remote sensing datasets from different dates and sensors to enable engineers, planners, and researchers to gain valuable insights into the environment, land use, infrastructure, and more.

Image Pre-Processing

Preprocessing steps make raw satellite data usable for analysis. Common tasks include:

• Radiometric Correction: Adjusts for sensor errors or atmospheric distortions to improve image quality.
• Geometric Correction (Georeferencing): Aligns images with real-world locations for overlaying with other spatial data.
• Atmospheric Correction: Removes atmospheric effects (e.g., scattering, absorption) for surface property analysis.
• Cloud Masking: Identifies and removes clouds from optical satellite images to reveal the area of interest.

At GEOCONSOL, we offer all these preprocessing services to ensure high-quality imagery for analysis.

Enhancing Satellite Imagery

Enhancing image quality or highlighting features is critical for analysis. Techniques include:

• Contrast Adjustment: Enhances feature visibility by modifying contrast.
• Histogram Equalization: Improves image contrast by stretching pixel intensity values.
• Band Combination: Uses spectral bands (e.g., infrared, red, green, blue) to emphasize specific features like vegetation or water.
• Pan-sharpening: Merges high-resolution panchromatic and multispectral images for better spatial resolution.

At GEOCONSOL, we provide these enhancement techniques to improve image analysis quality.

Digital Image Classification

Categorizing image pixels into predefined classes supports land cover classification, vegetation analysis, and urban planning:

• Supervised Classification: Uses training areas to classify image pixels into known categories.
• Unsupervised Classification: Groups pixels into statistical clusters without prior knowledge.
• Change Detection: Compares images over time to identify changes in land use, vegetation, or infrastructure.

GEOCONSOL provides classification services for extracting information, detecting changes, and assessing classification accuracy.

Vegetation or Water Analysis

Using spectral indices like NDVI (Normalized Difference Vegetation Index) and NDWI (Normalized Difference Water Index), we collect and analyze data on vegetation health, water presence, and soil moisture for applications in agriculture, forestry, environment, or land administration.

• NDVI: Assesses vegetation health for farms, forests, and urban areas.
• NDWI: Monitors water features and detects changes in water levels over time.

At GEOCONSOL, we use multiple spectral indices to support land use and land cover analysis for diverse applications.

GEOCONSOL SERVICES:

At GEOCONSOL, we deliver a tailored suite of the following services to accommodate RS applications in multi-disciplinary projects:

• Use of remote sensing data to detect change.
• Use of remote sensing data to extract required information.
• Pre and post processing of satellite imagery to ensure quality of data and to interpret the image accurately.
• Determine different indices that may be further used in other studies related to geology, agriculture, forestry, and environment.

GEOCONSOL has certified resources to provide the above services.