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.
اليك صفحه ومجموعة على الفيس بوك لتعلم أكثر بما يخص نظم المعلومات الجغرافية (GIS) و برنامج ArcGIS Pro من خلال هذه الروابط:
مجموعة على الفيس بوك
ArcGIS Pro من
هنا.
مجموعة على الفيس بوك
GIS for WE - ArcGIS Pro من
هنا.صفحة الفيس بوك
GIS for WE من
هنا.
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