iTSensing Documentation Portal
Central index for current Remote Sensing feature guides, scientific modules, satellite-data specifications, export references and extended documentation. Search is handled from a compact prebuilt metadata index, so the browser does not scan every HTML document while you type.
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Remote Sensing Core
15 documentsSpectral PreprocessingPrepare multispectral or hyperspectral imagery before spectral analysis. The feature can apply radiometric scaling, optional scene-based atmospheric correction, and band selection while preserving the geospatial raster structure.Hydro PreprocessingPrepare optical imagery for aquatic analysis by generating a water mask, reducing sunglint, and optionally deriving depth-invariant spectral information for shallow-water studies.Raster Spectral & Texture AnalysisCalculate spectral indices and local texture measures from raster bands. Spectral methods combine physically meaningful bands; GLCM methods quantify spatial texture from local gray-level co-occurrence patterns.Edge DetectionDetect sharp spatial transitions such as object boundaries, roads, field edges, structural lines, or coastal boundaries from a selected raster band.Shoreline ExtractionExtract a landwater boundary from optical imagery using a water index, thresholding, mask cleanup, and optional edge refinement.Layer StackingCombine selected bands from one or more rasters into a single aligned multiband raster. It can also reorder or subset bands from one raster.Raster ModellerBuild a raster prediction model from training points with a numeric target field, then predict that continuous variable across the predictor raster.Supervised ClassificationCreate a thematic class raster from labelled training samples. Spectral classifiers learn pixel-feature relationships; CNN/U-Net use spatial neighborhoods or semantic segmentation context.Unsupervised ClassificationAutomatically groups pixels with similar multiband values without labelled training data. The result is a cluster map that must be interpreted before it becomes a semantic land-cover map.OBIA ClassificationObject-Based Image Analysis (OBIA) first segments neighboring pixels into image objects, calculates object attributes, then classifies those objects. This reduces the purely pixel-by-pixel view and can use shape, texture, and context.Image Matching DetectionDetect repeated visually similar objects from user-selected example points. The application builds one or more templates, searches for similar patterns over selected bands and scales, and suppresses duplicate detections.PansharpeningFuse the high spatial detail of a panchromatic image with the spectral content of a lower-resolution multispectral image.Image FusionFuse low-resolution multispectral information with a high-resolution raster using component-based or learned self-supervised fusion methods.ROI AnalysisExtract and analyze raster values inside Regions of Interest (ROI). It supports descriptive statistics, class separability, spectral plots, n-D exploration, scatter plots, histograms, and correlation analysis.Raster Change DetectionCompare two aligned rasters from different dates and produce a continuous or classified change map.
GeoAI
3 documentsGeoAI Object ExtractionExtract objects from high-resolution satellite, aerial, or UAV imagery using foundation models, specialized tree-crown models, pretrained detection models, or project-trained custom models.GeoAI Semantic ClassificationApply a trained semantic-segmentation model to a high-resolution raster and produce a pixel-level classified raster.GeoAI Model TrainingTrain reusable GeoAI models from high-resolution raster imagery and labelled vector features for object detection, instance segmentation, or semantic segmentation.
Accuracy & Validation
1 documentsSAR / InSAR
3 documentsInSAR SLC ApplicationsApplication-oriented processing for complex SAR SLC pairs or stacks. It uses interferometric phase/coherence to derive deformation, terrain, or coherence-change products depending on the selected application.SAR GRD ApplicationsApplication-oriented analysis for calibrated/terrain-corrected SAR GRD imagery using backscatter intensity, polarization combinations and optional before/after comparison.DInSAR / InSAR AdvancedRun a selected advanced DInSAR/InSAR processing stage. This is intended for analysts who need control over individual interferometric processing steps and intermediate products.
Shared Raster Tools
8 documentsRaster to PolygonConvert connected raster cells with the same value/class into vector polygon features.Raster to PointConvert raster cells into point features, normally using pixel-center coordinates and carrying the selected raster value(s) as attributes.Raster ClipClip a raster using a polygon/multipolygon boundary and optionally crop the output extent to the mask.Raster CalculatorPerform raster algebra using one or more raster/band variables. Inputs are aligned to a reference grid before the mathematical expression is evaluated.Raster MosaicMerge two or more raster scenes into one union-extent raster while aligning coordinate system, resolution and pixel grid.Vector to Raster / RasterizeConvert vector geometry into raster cells using a field value or constant burn value on a defined output grid.Raster ResampleChange raster pixel size/grid resolution using a selected interpolation method.Raster ReclassifyReplace continuous or categorical raster values according to user-defined rules, producing a new classified/recoded raster.
Accuracy & Rectification
3 documentsRaster RectificationGeometrically align an image using matched control points. Reference points can come from known ground points, another image, or a basemap.Horizontal Accuracy AssessmentAssess orthophoto horizontal positional accuracy using independent check points. Each reference point is paired with the corresponding visible location in the orthophoto.Vertical Accuracy AssessmentAssess DEM vertical accuracy by sampling DEM elevation at independent point checkpoints with known reference elevation.
Terrain / Elevation
6 documentsGenerate ContourGenerate vector contour lines from a continuous elevation raster at a chosen interval.DEM to SlopeCalculate terrain slope from a DEM using local elevation gradients.DEM AspectCalculate the compass direction of maximum downslope gradient from a DEM.HillshadeSimulate terrain illumination from a chosen light azimuth and altitude using DEM slope and aspect.Viewshed / Visibility AnalysisDetermine which DEM cells are visible from an observer location using terrain line-of-sight analysis.DEM Cut & Fill AnalysisCompare two elevation surfaces to estimate areas and volumes of excavation (cut) and embankment (fill).
Export & Data Delivery
2 documentsRaster Analysis
3 documentsFocal / Neighborhood StatisticsCalculate a statistic in a moving neighborhood around each raster cell.Raster Proximity / DistanceCalculate distance from each pixel to the nearest target pixel defined by nonzero values, a specific value, or a value range.Fill Nodata / Gap FillInterpolate small nodata gaps from surrounding valid raster values.
Hydrology
5 documentsDEM Fill SinksRemove artificial/internal depressions from a DEM to create a hydrologically connected surface for flow modelling.Flow DirectionCalculate the downslope flow direction from each DEM cell, typically using an eight-neighbor (D8) grid.Flow AccumulationCount or accumulate upstream contributing cells according to the flow-direction network.Watershed DelineationDelineate the upstream catchment draining to one or more outlet/pour points using a flow-direction raster or DEM-derived flow network.Stream ExtractionExtract a stream network by thresholding flow accumulation, optionally expressing the threshold as contributing-cell count or drainage area.