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Missing pixels when extracting each pixel value
Extract pixel value for corresponding point location in Rextract all pixel values from a raster record to put in another tableR - extract georeferenced raster pixel colorHow to buffer pixels by their associated pixel values?Extract longitudinal pixel values from raster.list, save to data frameExtraction of pixel values in lines to each number of pixelsextracting residuals from pixel by pixel regressionHow to get each pixel value of raster, and compare with another image using gdal/python/bash/freeware?Extract raster pixel values along a polyline in PostGISDistance from each cell of value 1 to each cell of value 0
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
enter image description hereWe are trying to convert lzw compressed raster(tiff) into text format(meaning extracting each pixel centroid and band1 value.. We see that some parts of the raster is missed while conversion.. however there is a pattern in miss data (data is coming in unequal striped pattern) Please see snapshot up .. Yellow dots shows the centroid converted while no overlap with yellow the data is missed while converting..
we have tried the tile size 128 and 256 but the output was different in both the cases
List<String> tiffExtensions = new ArrayList<>();
tiffExtensions.add(".tif");
tiffExtensions.add(".TIF");
tiffExtensions.add(".tiff");
tiffExtensions.add(".TIFF");
final scala.Option<CRS> crsNone = scala.Option.apply(null);
final scala.Option<Object> objectNone = scala.Option.apply(null);
final scala.Option<Object> numPartitionsObject = scala.Option.apply(new Integer(10));
final scala.Option<Object> tileSize = scala.Option.apply(Integer.parseInt("256"));
final scala.Option<Object> partitionBytes = scala.Option.apply(128l * 1024 * 1024);
HadoopGeoTiffRDD.Options options = new HadoopGeoTiffRDD.Options$().apply(
JavaConverters.asScalaIteratorConverter(tiffExtensions.iterator()).asScala().toSeq(), crsNone,
HadoopGeoTiffRDD.GEOTIFF_TIME_TAG_DEFAULT(), HadoopGeoTiffRDD.GEOTIFF_TIME_FORMAT_DEFAULT(), tileSize,
numPartitionsObject, partitionBytes, objectNone);
RDD<Tuple2<ProjectedExtent, Tile>> rasterImageRdd = HadoopGeoTiffRDD.spatial(new Path(rastedImageDir), options,
javaSparkContext.sc());
JavaRDD<Tuple2<ProjectedExtent, Tile>> rasterImageJavaRdd = rasterImageRdd.toJavaRDD();
JavaRDD<String> pixelRdd = rasterImageJavaRdd
.flatMap(new FlatMapFunction<Tuple2<ProjectedExtent, Tile>, String>()
private static final long serialVersionUID = -6395159549445351446L;
public Iterator<String> call(Tuple2<ProjectedExtent, Tile> v1) throws Exception
ArrayList<String> list = new ArrayList<String>();
Tile t = v1._2;
ProjectedExtent projectedExtent = v1._1;
ProjectedRaster<CellGrid> r = new ProjectedRaster<CellGrid>(
new Raster<CellGrid>(t, projectedExtent.extent()), projectedExtent.crs());
GeometryFactory geometryFactory = new GeometryFactory(new PrecisionModel(), 4283);
WKTWriter wktWriter = new WKTWriter();
for (int i = 0; i < t.rows(); i++)
for (int j = 0; j < t.cols(); j++)
StringBuilder sb = new StringBuilder();
if (!Double.isNaN(t.getDouble(j, i)))
Double elevation = t.getDouble(j, i);
Tuple2<Object, Object> longLatTupel = r.raster().rasterExtent().gridToMap(j, i);
if (longLatTupel._2() != null && longLatTupel._1() != null)
Double latitude = Double.parseDouble(longLatTupel._2() + "");
Double longitude = Double.parseDouble(longLatTupel._1() + "");
Point point = geometryFactory.createPoint(new Coordinate(longitude, latitude));
sb.append(elevation).append(TAB_SEP);
sb.append(point);
list.add(sb.toString());
return list.iterator();
);
_
raster geotrellis
asked Mar 27 at 11:50
ashishashish
84 bronze badges
add a comment |
enter image description hereWe are trying to convert lzw compressed raster(tiff) into text format(meaning extracting each pixel centroid and band1 value.. We see that some parts of the raster is missed while conversion.. however there is a pattern in miss data (data is coming in unequal striped pattern) Please see snapshot up .. Yellow dots shows the centroid converted while no overlap with yellow the data is missed while converting..
we have tried the tile size 128 and 256 but the output was different in both the cases
List<String> tiffExtensions = new ArrayList<>();
tiffExtensions.add(".tif");
tiffExtensions.add(".TIF");
tiffExtensions.add(".tiff");
tiffExtensions.add(".TIFF");
final scala.Option<CRS> crsNone = scala.Option.apply(null);
final scala.Option<Object> objectNone = scala.Option.apply(null);
final scala.Option<Object> numPartitionsObject = scala.Option.apply(new Integer(10));
final scala.Option<Object> tileSize = scala.Option.apply(Integer.parseInt("256"));
final scala.Option<Object> partitionBytes = scala.Option.apply(128l * 1024 * 1024);
HadoopGeoTiffRDD.Options options = new HadoopGeoTiffRDD.Options$().apply(
JavaConverters.asScalaIteratorConverter(tiffExtensions.iterator()).asScala().toSeq(), crsNone,
HadoopGeoTiffRDD.GEOTIFF_TIME_TAG_DEFAULT(), HadoopGeoTiffRDD.GEOTIFF_TIME_FORMAT_DEFAULT(), tileSize,
numPartitionsObject, partitionBytes, objectNone);
RDD<Tuple2<ProjectedExtent, Tile>> rasterImageRdd = HadoopGeoTiffRDD.spatial(new Path(rastedImageDir), options,
javaSparkContext.sc());
JavaRDD<Tuple2<ProjectedExtent, Tile>> rasterImageJavaRdd = rasterImageRdd.toJavaRDD();
JavaRDD<String> pixelRdd = rasterImageJavaRdd
.flatMap(new FlatMapFunction<Tuple2<ProjectedExtent, Tile>, String>()
private static final long serialVersionUID = -6395159549445351446L;
public Iterator<String> call(Tuple2<ProjectedExtent, Tile> v1) throws Exception
ArrayList<String> list = new ArrayList<String>();
Tile t = v1._2;
ProjectedExtent projectedExtent = v1._1;
ProjectedRaster<CellGrid> r = new ProjectedRaster<CellGrid>(
new Raster<CellGrid>(t, projectedExtent.extent()), projectedExtent.crs());
GeometryFactory geometryFactory = new GeometryFactory(new PrecisionModel(), 4283);
WKTWriter wktWriter = new WKTWriter();
for (int i = 0; i < t.rows(); i++)
for (int j = 0; j < t.cols(); j++)
StringBuilder sb = new StringBuilder();
if (!Double.isNaN(t.getDouble(j, i)))
Double elevation = t.getDouble(j, i);
Tuple2<Object, Object> longLatTupel = r.raster().rasterExtent().gridToMap(j, i);
if (longLatTupel._2() != null && longLatTupel._1() != null)
Double latitude = Double.parseDouble(longLatTupel._2() + "");
Double longitude = Double.parseDouble(longLatTupel._1() + "");
Point point = geometryFactory.createPoint(new Coordinate(longitude, latitude));
sb.append(elevation).append(TAB_SEP);
sb.append(point);
list.add(sb.toString());
return list.iterator();
);
_
raster geotrellis
asked Mar 27 at 11:50
ashishashish
84 bronze badges
[enter image description here] at the beginning has the image that we are talking off
– ashish
Mar 27 at 11:52
The issue is that the yellow dots should be fully overlapped with the black points (We are simply extracting Lat/long and elevation values from a Raster Image). The portion of the image where yellow dots are not overlapped means the data has not been extracted for those points. The no data has been handled in line "Double.isNaN(t.getDouble(j, i)". There is nothing in-memory We have converted everything back into disk and visualizing the image on QGIS, I have updated the code snippet with comments which might help you in further understanding. I appreciate you helping on this
– ashish
Mar 28 at 5:28
add a comment |
enter image description hereWe are trying to convert lzw compressed raster(tiff) into text format(meaning extracting each pixel centroid and band1 value.. We see that some parts of the raster is missed while conversion.. however there is a pattern in miss data (data is coming in unequal striped pattern) Please see snapshot up .. Yellow dots shows the centroid converted while no overlap with yellow the data is missed while converting..
we have tried the tile size 128 and 256 but the output was different in both the cases
List<String> tiffExtensions = new ArrayList<>();
tiffExtensions.add(".tif");
tiffExtensions.add(".TIF");
tiffExtensions.add(".tiff");
tiffExtensions.add(".TIFF");
final scala.Option<CRS> crsNone = scala.Option.apply(null);
final scala.Option<Object> objectNone = scala.Option.apply(null);
final scala.Option<Object> numPartitionsObject = scala.Option.apply(new Integer(10));
final scala.Option<Object> tileSize = scala.Option.apply(Integer.parseInt("256"));
final scala.Option<Object> partitionBytes = scala.Option.apply(128l * 1024 * 1024);
HadoopGeoTiffRDD.Options options = new HadoopGeoTiffRDD.Options$().apply(
JavaConverters.asScalaIteratorConverter(tiffExtensions.iterator()).asScala().toSeq(), crsNone,
HadoopGeoTiffRDD.GEOTIFF_TIME_TAG_DEFAULT(), HadoopGeoTiffRDD.GEOTIFF_TIME_FORMAT_DEFAULT(), tileSize,
numPartitionsObject, partitionBytes, objectNone);
RDD<Tuple2<ProjectedExtent, Tile>> rasterImageRdd = HadoopGeoTiffRDD.spatial(new Path(rastedImageDir), options,
javaSparkContext.sc());
JavaRDD<Tuple2<ProjectedExtent, Tile>> rasterImageJavaRdd = rasterImageRdd.toJavaRDD();
JavaRDD<String> pixelRdd = rasterImageJavaRdd
.flatMap(new FlatMapFunction<Tuple2<ProjectedExtent, Tile>, String>()
private static final long serialVersionUID = -6395159549445351446L;
public Iterator<String> call(Tuple2<ProjectedExtent, Tile> v1) throws Exception
ArrayList<String> list = new ArrayList<String>();
Tile t = v1._2;
ProjectedExtent projectedExtent = v1._1;
ProjectedRaster<CellGrid> r = new ProjectedRaster<CellGrid>(
new Raster<CellGrid>(t, projectedExtent.extent()), projectedExtent.crs());
GeometryFactory geometryFactory = new GeometryFactory(new PrecisionModel(), 4283);
WKTWriter wktWriter = new WKTWriter();
for (int i = 0; i < t.rows(); i++)
for (int j = 0; j < t.cols(); j++)
StringBuilder sb = new StringBuilder();
if (!Double.isNaN(t.getDouble(j, i)))
Double elevation = t.getDouble(j, i);
Tuple2<Object, Object> longLatTupel = r.raster().rasterExtent().gridToMap(j, i);
if (longLatTupel._2() != null && longLatTupel._1() != null)
Double latitude = Double.parseDouble(longLatTupel._2() + "");
Double longitude = Double.parseDouble(longLatTupel._1() + "");
Point point = geometryFactory.createPoint(new Coordinate(longitude, latitude));
sb.append(elevation).append(TAB_SEP);
sb.append(point);
list.add(sb.toString());
return list.iterator();
);
_
raster geotrellis
asked Mar 27 at 11:50
ashishashish
84 bronze badges
enter image description hereWe are trying to convert lzw compressed raster(tiff) into text format(meaning extracting each pixel centroid and band1 value.. We see that some parts of the raster is missed while conversion.. however there is a pattern in miss data (data is coming in unequal striped pattern) Please see snapshot up .. Yellow dots shows the centroid converted while no overlap with yellow the data is missed while converting..
we have tried the tile size 128 and 256 but the output was different in both the cases
List<String> tiffExtensions = new ArrayList<>();
tiffExtensions.add(".tif");
tiffExtensions.add(".TIF");
tiffExtensions.add(".tiff");
tiffExtensions.add(".TIFF");
final scala.Option<CRS> crsNone = scala.Option.apply(null);
final scala.Option<Object> objectNone = scala.Option.apply(null);
final scala.Option<Object> numPartitionsObject = scala.Option.apply(new Integer(10));
final scala.Option<Object> tileSize = scala.Option.apply(Integer.parseInt("256"));
final scala.Option<Object> partitionBytes = scala.Option.apply(128l * 1024 * 1024);
HadoopGeoTiffRDD.Options options = new HadoopGeoTiffRDD.Options$().apply(
JavaConverters.asScalaIteratorConverter(tiffExtensions.iterator()).asScala().toSeq(), crsNone,
HadoopGeoTiffRDD.GEOTIFF_TIME_TAG_DEFAULT(), HadoopGeoTiffRDD.GEOTIFF_TIME_FORMAT_DEFAULT(), tileSize,
numPartitionsObject, partitionBytes, objectNone);
RDD<Tuple2<ProjectedExtent, Tile>> rasterImageRdd = HadoopGeoTiffRDD.spatial(new Path(rastedImageDir), options,
javaSparkContext.sc());
JavaRDD<Tuple2<ProjectedExtent, Tile>> rasterImageJavaRdd = rasterImageRdd.toJavaRDD();
JavaRDD<String> pixelRdd = rasterImageJavaRdd
.flatMap(new FlatMapFunction<Tuple2<ProjectedExtent, Tile>, String>()
private static final long serialVersionUID = -6395159549445351446L;
public Iterator<String> call(Tuple2<ProjectedExtent, Tile> v1) throws Exception
ArrayList<String> list = new ArrayList<String>();
Tile t = v1._2;
ProjectedExtent projectedExtent = v1._1;
ProjectedRaster<CellGrid> r = new ProjectedRaster<CellGrid>(
new Raster<CellGrid>(t, projectedExtent.extent()), projectedExtent.crs());
GeometryFactory geometryFactory = new GeometryFactory(new PrecisionModel(), 4283);
WKTWriter wktWriter = new WKTWriter();
for (int i = 0; i < t.rows(); i++)
for (int j = 0; j < t.cols(); j++)
StringBuilder sb = new StringBuilder();
if (!Double.isNaN(t.getDouble(j, i)))
Double elevation = t.getDouble(j, i);
Tuple2<Object, Object> longLatTupel = r.raster().rasterExtent().gridToMap(j, i);
if (longLatTupel._2() != null && longLatTupel._1() != null)
Double latitude = Double.parseDouble(longLatTupel._2() + "");
Double longitude = Double.parseDouble(longLatTupel._1() + "");
Point point = geometryFactory.createPoint(new Coordinate(longitude, latitude));
sb.append(elevation).append(TAB_SEP);
sb.append(point);
list.add(sb.toString());
return list.iterator();
);
_
raster geotrellis
raster geotrellis
asked Mar 27 at 11:50
ashishashish
84 bronze badges
asked Mar 27 at 11:50
ashishashish
84 bronze badges
asked Mar 27 at 11:50
ashishashish
84 bronze badges
asked Mar 27 at 11:50
ashishashish
84 bronze badges
asked Mar 27 at 11:50
ashishashish
84 bronze badges
84 bronze badges
[enter image description here] at the beginning has the image that we are talking off
– ashish
Mar 27 at 11:52
The issue is that the yellow dots should be fully overlapped with the black points (We are simply extracting Lat/long and elevation values from a Raster Image). The portion of the image where yellow dots are not overlapped means the data has not been extracted for those points. The no data has been handled in line "Double.isNaN(t.getDouble(j, i)". There is nothing in-memory We have converted everything back into disk and visualizing the image on QGIS, I have updated the code snippet with comments which might help you in further understanding. I appreciate you helping on this
– ashish
Mar 28 at 5:28
add a comment |
[enter image description here] at the beginning has the image that we are talking off
– ashish
Mar 27 at 11:52
The issue is that the yellow dots should be fully overlapped with the black points (We are simply extracting Lat/long and elevation values from a Raster Image). The portion of the image where yellow dots are not overlapped means the data has not been extracted for those points. The no data has been handled in line "Double.isNaN(t.getDouble(j, i)". There is nothing in-memory We have converted everything back into disk and visualizing the image on QGIS, I have updated the code snippet with comments which might help you in further understanding. I appreciate you helping on this
– ashish
Mar 28 at 5:28
[enter image description here] at the beginning has the image that we are talking off
– ashish
Mar 27 at 11:52
[enter image description here] at the beginning has the image that we are talking off
– ashish
Mar 27 at 11:52
The issue is that the yellow dots should be fully overlapped with the black points (We are simply extracting Lat/long and elevation values from a Raster Image). The portion of the image where yellow dots are not overlapped means the data has not been extracted for those points. The no data has been handled in line "Double.isNaN(t.getDouble(j, i)". There is nothing in-memory We have converted everything back into disk and visualizing the image on QGIS, I have updated the code snippet with comments which might help you in further understanding. I appreciate you helping on this
– ashish
Mar 28 at 5:28
The issue is that the yellow dots should be fully overlapped with the black points (We are simply extracting Lat/long and elevation values from a Raster Image). The portion of the image where yellow dots are not overlapped means the data has not been extracted for those points. The no data has been handled in line "Double.isNaN(t.getDouble(j, i)". There is nothing in-memory We have converted everything back into disk and visualizing the image on QGIS, I have updated the code snippet with comments which might help you in further understanding. I appreciate you helping on this
– ashish
Mar 28 at 5:28
add a comment |
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[enter image description here] at the beginning has the image that we are talking off
– ashish
Mar 27 at 11:52
The issue is that the yellow dots should be fully overlapped with the black points (We are simply extracting Lat/long and elevation values from a Raster Image). The portion of the image where yellow dots are not overlapped means the data has not been extracted for those points. The no data has been handled in line "Double.isNaN(t.getDouble(j, i)". There is nothing in-memory We have converted everything back into disk and visualizing the image on QGIS, I have updated the code snippet with comments which might help you in further understanding. I appreciate you helping on this
– ashish
Mar 28 at 5:28