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Warp from File Tool

أداة اعوجاج من الملف

ArcMap ArcGIS

How to Warp from File Tool in ArcToolbox ArcMap ArcGIS??

كيفية استخدام أداة اعوجاج من الملفArcToolbox ArcMap ArcGIS   ؟؟

Path to access the toolمسار الوصول الى الأداة

:

Warp from File Tool, Projections and Transformations Toolset, Raster Box, Data Management Tools Toolbox

 

Warp from File

Transforms a raster dataset using an existing text file containing source and target control points.

يحول مجموعة بيانات نقطية باستخدام ملف نصي موجود يحتوي على نقاط تحكم المصدر والهدف.

1.    Input Raster نقطية الإدخال

The raster that you want to transform.

البيانات النقطية التي تريد تحويلها.

Output Raster Dataset

The name, location, and format for the dataset you are creating. When storing a raster dataset in a geodatabase, do not add a file extension to the name of the raster dataset. When storing your raster dataset to a JPEG file, a JPEG 2000 file, a TIFF file, or a geodatabase, you can specify a compression type and compression quality using environment settings.

·      .bil—Esri BIL

·      .bip—Esri BIP

·      .bmp—BMP

·      .bsq—Esri BSQ

·      .dat—ENVI DAT

·      .gif—GIF

·      .img—ERDAS IMAGINE

·      .jpg—JPEG

·      .jp2—JPEG 2000

·      .png—PNG

·      .tif—TIFF

·      .mrf—MRF

·      .crf—CRF

·      No extension for Esri Grid

Link File

The text, CSV, or TAB file containing the coordinates to warp the input raster. This can be generated from the Register Raster tool or from the Georeferencing toolbar.

Transformation Type (optional)

Select a method for shifting the raster dataset.

·      POLYORDER0— This method uses a zero-order polynomial to shift your data. This is commonly used when your data is already georeferenced, but a small shift will better line up your data. Only one link is required to perform a zero-order polynomial shift.

·      POLYSIMILARITY— This is a first order transformation that attempts to preserve the shape of the original raster. The RMS error tends to be higher than other polynomial transformations because the preservation of shape is more important than the best fit.

·      POLYORDER1—A first-order polynomial (affine) fits a flat plane to the input points.

·      POLYORDER2—A second-order polynomial fits a somewhat more complicated surface to the input points.

·      POLYORDER3—A third-order polynomial fits a more complicated surface to the input points.

·      ADJUST— This method combines a polynomial transformation and uses a triangulated irregular network (TIN) interpolation technique to optimize for both global and local accuracy.

·      SPLINE— This method transforms the source control points precisely to the target control points. In the output, the control points will be accurate, but the raster pixels between the control points are not.

·      PROJECTIVE— This method warps lines so they remain straight. In doing so, lines that were once parallel may no longer remain parallel. The projective transformation is especially useful for oblique imagery, scanned maps, and for some imagery products.

Resampling Technique (optional)

Choose an appropriate technique based on the type of data you have.

·      NEAREST— Nearest neighbor is the fastest resampling method; it minimizes changes to pixel values since no new values are created. It is suitable for discrete data, such as land cover.

·      BILINEAR— Bilinear interpolation calculates the value of each pixel by averaging (weighted for distance) the values of the surrounding four pixels. It is suitable for continuous data.

·      CUBIC— Cubic convolution calculates the value of each pixel by fitting a smooth curve based on the surrounding 16 pixels. This produces the smoothest image but can create values outside of the range found in the source data. It is suitable for continuous data.

·      MAJORITY—Majority resampling determines the value of each pixel based on the most popular value in a 3 by 3 window. Suitable for discrete data.

The NEAREST and MAJORITY options are used for categorical data, such as a land-use classification. The NEAREST option is the default since it is the quickest and also because it will not change the cell values. Do not use either of these for continuous data, such as elevation surfaces.

The BILINEAR option and the CUBIC option are most appropriate for continuous data. It is recommended that neither of these be used with categorical data because the cell values may be altered.

2.    Output Raster Dataset إخراج مجموعة البيانات النقطية

The name, location, and format for the dataset you are creating. When storing a raster dataset in a geodatabase, do not add a file extension to the name of the raster dataset. When storing your raster dataset to a JPEG file, a JPEG 2000 file, a TIFF file, or a geodatabase, you can specify a compression type and compression quality using environment settings.

· .bil—Esri BIL

· .bip—Esri BIP

· .bmp—BMP

· .bsq—Esri BSQ

· .dat—ENVI DAT

· .gif—GIF

· .img—ERDAS IMAGINE

· .jpg—JPEG

· .jp2—JPEG 2000

· .png—PNG

· .tif—TIFF

· .mrf—MRF

· .crf—CRF

· No extension for Esri Grid

اسم وموقع وتنسيق مجموعة البيانات التي تقوم بإنشائها. عند تخزين مجموعة بيانات نقطية في قاعدة بيانات جغرافية ، لا تضف امتداد ملف إلى اسم مجموعة البيانات النقطية. عند تخزين مجموعة البيانات النقطية في ملف JPEG أو ملف JPEG 2000 أو ملف TIFF أو قاعدة بيانات جغرافية ، يمكنك تحديد نوع الضغط وجودة الضغط باستخدام إعدادات البيئة.

Link File

The text, CSV, or TAB file containing the coordinates to warp the input raster. This can be generated from the Register Raster tool or from the Georeferencing toolbar.

Transformation Type (optional)

Select a method for shifting the raster dataset.

·      POLYORDER0— This method uses a zero-order polynomial to shift your data. This is commonly used when your data is already georeferenced, but a small shift will better line up your data. Only one link is required to perform a zero-order polynomial shift.

·      POLYSIMILARITY— This is a first order transformation that attempts to preserve the shape of the original raster. The RMS error tends to be higher than other polynomial transformations because the preservation of shape is more important than the best fit.

·      POLYORDER1—A first-order polynomial (affine) fits a flat plane to the input points.

·      POLYORDER2—A second-order polynomial fits a somewhat more complicated surface to the input points.

·      POLYORDER3—A third-order polynomial fits a more complicated surface to the input points.

·      ADJUST— This method combines a polynomial transformation and uses a triangulated irregular network (TIN) interpolation technique to optimize for both global and local accuracy.

·      SPLINE— This method transforms the source control points precisely to the target control points. In the output, the control points will be accurate, but the raster pixels between the control points are not.

·      PROJECTIVE— This method warps lines so they remain straight. In doing so, lines that were once parallel may no longer remain parallel. The projective transformation is especially useful for oblique imagery, scanned maps, and for some imagery products.

Resampling Technique (optional)

Choose an appropriate technique based on the type of data you have.

·      NEAREST— Nearest neighbor is the fastest resampling method; it minimizes changes to pixel values since no new values are created. It is suitable for discrete data, such as land cover.

·      BILINEAR— Bilinear interpolation calculates the value of each pixel by averaging (weighted for distance) the values of the surrounding four pixels. It is suitable for continuous data.

·      CUBIC— Cubic convolution calculates the value of each pixel by fitting a smooth curve based on the surrounding 16 pixels. This produces the smoothest image but can create values outside of the range found in the source data. It is suitable for continuous data.

·      MAJORITY—Majority resampling determines the value of each pixel based on the most popular value in a 3 by 3 window. Suitable for discrete data.

The NEAREST and MAJORITY options are used for categorical data, such as a land-use classification. The NEAREST option is the default since it is the quickest and also because it will not change the cell values. Do not use either of these for continuous data, such as elevation surfaces.

The BILINEAR option and the CUBIC option are most appropriate for continuous data. It is recommended that neither of these be used with categorical data because the cell values may be altered.

3.    Link File ملف الارتباط

The text, CSV, or TAB file containing the coordinates to warp the input raster. This can be generated from the Register Raster tool or from the Georeferencing toolbar.

ملف نصي أو CSV أو TAB يحتوي على الإحداثيات لتشويه المدخلات النقطية. يمكن إنشاء هذا من أداة Register Raster أو من شريط أدوات Georeferencing.

Transformation Type (optional)

Select a method for shifting the raster dataset.

·      POLYORDER0— This method uses a zero-order polynomial to shift your data. This is commonly used when your data is already georeferenced, but a small shift will better line up your data. Only one link is required to perform a zero-order polynomial shift.

·      POLYSIMILARITY— This is a first order transformation that attempts to preserve the shape of the original raster. The RMS error tends to be higher than other polynomial transformations because the preservation of shape is more important than the best fit.

·      POLYORDER1—A first-order polynomial (affine) fits a flat plane to the input points.

·      POLYORDER2—A second-order polynomial fits a somewhat more complicated surface to the input points.

·      POLYORDER3—A third-order polynomial fits a more complicated surface to the input points.

·      ADJUST— This method combines a polynomial transformation and uses a triangulated irregular network (TIN) interpolation technique to optimize for both global and local accuracy.

·      SPLINE— This method transforms the source control points precisely to the target control points. In the output, the control points will be accurate, but the raster pixels between the control points are not.

·      PROJECTIVE— This method warps lines so they remain straight. In doing so, lines that were once parallel may no longer remain parallel. The projective transformation is especially useful for oblique imagery, scanned maps, and for some imagery products.

Resampling Technique (optional)

Choose an appropriate technique based on the type of data you have.

·      NEAREST— Nearest neighbor is the fastest resampling method; it minimizes changes to pixel values since no new values are created. It is suitable for discrete data, such as land cover.

·      BILINEAR— Bilinear interpolation calculates the value of each pixel by averaging (weighted for distance) the values of the surrounding four pixels. It is suitable for continuous data.

·      CUBIC— Cubic convolution calculates the value of each pixel by fitting a smooth curve based on the surrounding 16 pixels. This produces the smoothest image but can create values outside of the range found in the source data. It is suitable for continuous data.

·      MAJORITY—Majority resampling determines the value of each pixel based on the most popular value in a 3 by 3 window. Suitable for discrete data.

The NEAREST and MAJORITY options are used for categorical data, such as a land-use classification. The NEAREST option is the default since it is the quickest and also because it will not change the cell values. Do not use either of these for continuous data, such as elevation surfaces.

The BILINEAR option and the CUBIC option are most appropriate for continuous data. It is recommended that neither of these be used with categorical data because the cell values may be altered.

4.    Transformation Type (optional) نوع التحويل (اختياري)

Select a method for shifting the raster dataset.

· POLYORDER0— This method uses a zero-order polynomial to shift your data. This is commonly used when your data is already georeferenced, but a small shift will better line up your data. Only one link is required to perform a zero-order polynomial shift.

· POLYSIMILARITY— This is a first order transformation that attempts to preserve the shape of the original raster. The RMS error tends to be higher than other polynomial transformations because the preservation of shape is more important than the best fit.

· POLYORDER1—A first-order polynomial (affine) fits a flat plane to the input points.

· POLYORDER2—A second-order polynomial fits a somewhat more complicated surface to the input points.

· POLYORDER3—A third-order polynomial fits a more complicated surface to the input points.

· ADJUST— This method combines a polynomial transformation and uses a triangulated irregular network (TIN) interpolation technique to optimize for both global and local accuracy.

· SPLINE— This method transforms the source control points precisely to the target control points. In the output, the control points will be accurate, but the raster pixels between the control points are not.

· PROJECTIVE— This method warps lines so they remain straight. In doing so, lines that were once parallel may no longer remain parallel. The projective transformation is especially useful for oblique imagery, scanned maps, and for some imagery products.

حدد طريقة لتحويل مجموعة البيانات النقطية.

• POLYORDER0 - تستخدم هذه الطريقة كثيرة الحدود ذات الترتيب الصفري لتحويل بياناتك. يستخدم هذا بشكل شائع عندما تكون بياناتك مسجلة جغرافيًا بالفعل ، ولكن تغييرًا صغيرًا سيحدد بياناتك بشكل أفضل. مطلوب ارتباط واحد فقط لإجراء إزاحة متعددة الحدود بترتيب صفري.

• تعدد التشابه - هذا تحويل من الدرجة الأولى يحاول الحفاظ على شكل البيانات النقطية الأصلية. يميل خطأ RMS إلى أن يكون أعلى من التحويلات كثيرة الحدود الأخرى لأن الحفاظ على الشكل أكثر أهمية من أفضل ملاءمة.

• POLYORDER1 - متعدد الحدود من الدرجة الأولى (أفيني) يناسب مستوى مسطحًا لنقاط الإدخال.

• POLYORDER2 - كثير الحدود من الدرجة الثانية يناسب سطحًا أكثر تعقيدًا إلى حد ما لنقاط الإدخال.

• POLYORDER3 - متعدد الحدود من الدرجة الثالثة يناسب سطحًا أكثر تعقيدًا لنقاط الإدخال.

• ADJUST - يجمع هذا الأسلوب بين التحويل متعدد الحدود ويستخدم تقنية الاستيفاء الشبكي غير المنتظم المثلث (TIN) لتحسين الدقة العالمية والمحلية.

• SPLINE - تقوم هذه الطريقة بتحويل نقاط التحكم في المصدر بدقة إلى نقاط التحكم المستهدفة. في الإخراج ، ستكون نقاط التحكم دقيقة ، لكن وحدات البكسل النقطية بين نقاط التحكم ليست كذلك.

• استباقية - تقوم هذه الطريقة بإلتواء الخطوط بحيث تظل مستقيمة. عند القيام بذلك ، قد لا تظل الخطوط التي كانت متوازية ذات يوم متوازية. يعتبر التحويل الإسقاطي مفيدًا بشكل خاص للصور المائلة والخرائط الممسوحة ضوئيًا وبعض منتجات الصور.

Resampling Technique (optional)

Choose an appropriate technique based on the type of data you have.

·      NEAREST— Nearest neighbor is the fastest resampling method; it minimizes changes to pixel values since no new values are created. It is suitable for discrete data, such as land cover.

·      BILINEAR— Bilinear interpolation calculates the value of each pixel by averaging (weighted for distance) the values of the surrounding four pixels. It is suitable for continuous data.

·      CUBIC— Cubic convolution calculates the value of each pixel by fitting a smooth curve based on the surrounding 16 pixels. This produces the smoothest image but can create values outside of the range found in the source data. It is suitable for continuous data.

·      MAJORITY—Majority resampling determines the value of each pixel based on the most popular value in a 3 by 3 window. Suitable for discrete data.

The NEAREST and MAJORITY options are used for categorical data, such as a land-use classification. The NEAREST option is the default since it is the quickest and also because it will not change the cell values. Do not use either of these for continuous data, such as elevation surfaces.

The BILINEAR option and the CUBIC option are most appropriate for continuous data. It is recommended that neither of these be used with categorical data because the cell values may be altered.

5.    Resampling Technique (optional) تقنية إعادة التشكيل (اختياري)

Choose an appropriate technique based on the type of data you have.

· NEAREST— Nearest neighbor is the fastest resampling method; it minimizes changes to pixel values since no new values are created. It is suitable for discrete data, such as land cover.

· BILINEAR— Bilinear interpolation calculates the value of each pixel by averaging (weighted for distance) the values of the surrounding four pixels. It is suitable for continuous data.

· CUBIC— Cubic convolution calculates the value of each pixel by fitting a smooth curve based on the surrounding 16 pixels. This produces the smoothest image but can create values outside of the range found in the source data. It is suitable for continuous data.

· MAJORITY—Majority resampling determines the value of each pixel based on the most popular value in a 3 by 3 window. Suitable for discrete data.

The NEAREST and MAJORITY options are used for categorical data, such as a land-use classification. The NEAREST option is the default since it is the quickest and also because it will not change the cell values. Do not use either of these for continuous data, such as elevation surfaces.

The BILINEAR option and the CUBIC option are most appropriate for continuous data. It is recommended that neither of these be used with categorical data because the cell values may be altered.

اختر أسلوبًا مناسبًا بناءً على نوع البيانات التي لديك.

• الأقرب - أقرب جار هو أسرع طريقة لإعادة التشكيل. تقلل التغييرات على قيم البكسل نظرًا لعدم إنشاء قيم جديدة. إنها مناسبة للبيانات المنفصلة ، مثل الغطاء الأرضي.

• BILINEAR - يحسب الاستيفاء ثنائي الخطي قيمة كل بكسل عن طريق حساب متوسط ​​(مرجح للمسافة) لقيم وحدات البكسل الأربعة المحيطة. إنها مناسبة للبيانات المستمرة.

• CUBIC - يحسب الالتواء التكعيبي قيمة كل بكسل عن طريق ملاءمة منحنى ناعم بناءً على 16 بكسل المحيطة. ينتج عن ذلك الصورة الأكثر تجانسًا ولكن يمكنه إنشاء قيم خارج النطاق الموجود في بيانات المصدر. إنها مناسبة للبيانات المستمرة.

• الأغلبية - تحدد عملية إعادة تشكيل الأغلبية قيمة كل بكسل بناءً على القيمة الأكثر شيوعًا في نافذة 3 × 3. مناسب للبيانات المنفصلة.

يتم استخدام خياري NEAREST و MAJORITY للبيانات الفئوية ، مثل تصنيف استخدام الأراضي. الخيار NEAREST هو الخيار الافتراضي لأنه الأسرع وأيضًا لأنه لن يغير قيم الخلية. لا تستخدم أيًا منهما للبيانات المستمرة ، مثل أسطح الارتفاع.

يعد الخيار BILINEAR وخيار CUBIC أكثر ملاءمة للبيانات المستمرة. يوصى بعدم استخدام أيٍّ من هذه البيانات مع البيانات الفئوية لأنه قد يتم تغيير قيم الخلية.

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