Examples

Use CARS with Pleiades images …

Note

CARS is used in the same way with Pléiades and Pléiades Neo data.

… with raw data

If you want to generate a 3D model with the following pair:

IMG_PHR1B_MS_003
IMG_PHR1B_MS_004
IMG_PHR1B_P_001
IMG_PHR1B_P_002

You should find in each folder the following data:

...
DIM_PHR1B_***.XML
IMG_PHR1B_***.TIF
RPC_PHR1B_***.XML

For each product, the user must provide the path to the pancromatic data (P.TIF) with its geomodel, all contained in the DIMAP file (DIMAP*P*.XML):

{
"inputs": {
    "sensors" : {
        "one": {
            "image": "IMG_PHR1B_P_001/DIM_PHR1B_***.XML"
        },
        "two": {
            "image": "IMG_PHR1B_P_002/DIM_PHR1B_***.XML",
        }
    },
    "pairing": [["one", "two"]]
    }
}

If you want to add the colors, a P+XS fusion must be done, to specify a color.tif with the same shape and resolution than the Pancromatic data. It can be performed with otbcli_BundleToPerfectSensor as explained in Make a simple pan sharpening.

{
"inputs": {
    "sensors" : {
        "one": {
            "image": "IMG_PHR1B_P_001/DIM_PHR1B_***.XML",
            "color": "color_one.tif"
        },
        "two": {
            "image": "IMG_PHR1B_P_002/DIM_PHR1B_***.XML",
            "color": "color_two.tif"

        }
    },
    "pairing": [["one", "two"]]
    }
}

… with a region of interest

There are two different ways to use a ROI in CARS:

• Crop input images: the whole pipeline will be done with cropped images

• Use input roi parameter: the whole images will be used to compute grid correction and terrain + epipolar a priori. Then the rest of the pipeline will use the given roi. This allows a better correction of epipolar rectification grids.

If you want to work with cropped image by using a region of interest for the whole pipeline, use cars-extractroi:

cars-extractroi -il DIM_PHR1B_***.XML -out ext_dir -bbx -58.5896 -34.4872 -58.5818 -34.4943

It generates a .tif and .geom to be used as:

{
"inputs": {
    "sensors" : {
        "one": {
            "image": "ext_dir/***.tif",
            "geomodel": "ext_dir/***.geom",
            "color": "color_one.tif"
        }
}

Then use the generated data as you would with raw data.

If you want to compute the grid correction and compute the epipolar/terrain a priori on the whole image, keep the same input images but specify the terrain ROI to use:

{
    "inputs":
    {
        "roi" : {
            "type": "FeatureCollection",
            "features": [
                {
                "type": "Feature",
                "properties": {},
                "geometry": {
                    "coordinates": [
                    [
                        [5.194, 44.2064],
                        [5.194, 44.2059],
                        [5.195, 44.2059],
                        [5.195, 44.2064],
                        [5.194, 44.2064]
                    ]
                    ],
                    "type": "Polygon"
                }
                }
            ]
        }
    }
}

See Usage Sensors Images Inputs configuration for more information.

Note

CARS also works with other types of data: SPOT 6-7, WorldView, etc.