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Create Spatially Balanced Points and Densify Sampling Network Tools

Create Spatially Balanced Points

أداة إنشاء نقاط متوازنة مكانيًا

ArcMap ArcGIS

How to use Create Spatially Balanced Points Tool in Arc Toolbox ArcMap ArcGIS??

كيفية استخدام أداة إنشاء نقاط متوازنة مكانيًا ؟؟

Path to access the toolمسار الوصول الى الأداة

:

Create Spatially Balanced Points Tool, Sampling Network Design Toolset, Geostatistical Analyst Tools Toolbox

 

Create Spatially Balanced Points

Generates a set of sample points based on inclusion probabilities, resulting in a spatially balanced sample design. This tool is generally used for designing a monitoring network by suggesting locations to take samples, and a preference for particular locations can be defined using an inclusion probability raster.

يولد مجموعة من نقاط العينة بناءً على احتمالات التضمين ، مما يؤدي إلى تصميم عينة متوازن مكانيًا. تُستخدم هذه الأداة بشكل عام لتصميم شبكة مراقبة من خلال اقتراح مواقع لأخذ عينات ، ويمكن تحديد تفضيل مواقع معينة باستخدام البيانات النقطية لاحتمالية التضمين.

1.    Input inclusion probability raster إدخال احتمالية النقطية

This raster defines the inclusion probabilities for each location in the area of interest. The location values range from 0 (low inclusion probability) to 1 (high inclusion probability).

تحدد هذه البيانات النقطية احتمالات التضمين لكل موقع في منطقة الاهتمام. تتراوح قيم الموقع من 0 (احتمال إدراج منخفض) إلى 1 (احتمال إدراج مرتفع).

Number of output points

Specify how many sample locations to generate.

Output point feature class

The output feature class contains the selected sample locations and their inclusion probabilities.

2.    Number of output points عدد نقاط الإخراج

Specify how many sample locations to generate.

حدد عدد مواقع العينات المراد إنشاؤها.

Output point feature class

The output feature class contains the selected sample locations and their inclusion probabilities.

3.    Output point feature class فئة ميزة نقطة الإخراج

The output feature class contains the selected sample locations and their inclusion probabilities.

تحتوي فئة معلم الإخراج على مواقع العينة المحددة واحتمالات تضمينها.

Densify Sampling Network

أداة تكثيف شبكة أخذ العينات

ArcMap ArcGIS

How to use Densify Sampling Network Tool in Arc Toolbox ArcMap ArcGIS??

كيفية استخدام أداة تكثيف شبكة أخذ العينات ؟؟

Path to access the toolمسار الوصول الى الأداة

:

Densify Sampling Network Tool, Sampling Network Design Toolset, Geostatistical Analyst Tools Toolbox

 

Densify Sampling Network

Uses a predefined geostatistical kriging layer to determine where new monitoring stations should be built. It can also be used to determine which monitoring stations should be removed from an existing network.

يستخدم طبقة كريغ إحصائية جغرافية محددة مسبقًا لتحديد المكان الذي يجب أن تُبنى فيه محطات المراقبة الجديدة. يمكن استخدامه أيضًا لتحديد محطات المراقبة التي يجب إزالتها من شبكة موجودة.

1.    Input geostatistical layer إدخال طبقة إحصائية جغرافية

Input a geostatistical layer resulting from a Kriging model.

أدخل طبقة إحصائية جغرافية ناتجة عن نموذج Kriging.

Number of output points

Specify how many sample locations to generate.

Output point feature class

The name of the output feature class.

Selection criteria (optional)

Methods to densify a sampling network.

·      STDERR—Standard error of prediction criteria

·      STDERR_THRESHOLD—Standard error threshold criteria

·      QUARTILE_THRESHOLD — Lower quartile threshold criteria

·      QUARTILE_THRESHOLD_UPPER — Upper quartile threshold criteria

The Standard error of prediction option will give extra weight to locations where the standard error of prediction is large. The Standard error threshold, Lower quartile threshold, and Upper quartile threshold options are useful when there is a critical threshold value for the variable under study (such as the highest admissible ozone level). The Standard error threshold option will give extra weight to locations whose values are close to the threshold. The Lower quartile threshold option will give extra weight to locations that are least likely to exceed the critical threshold. The Upper quartile threshold option will give extra weight to locations that are most likely to exceed the critical threshold.

The equations for each option are:

Standard error of prediction = stderr

 

 Standard error threshold = stderr(s)(1 - 2 · abs(prob[Z(s) > threshold] - 0.5))

 

 Lower quartile threshold = (Z0.75(s) - Z0.25(s)) · (prob[Z(s) < threshold])

 

 Upper quartile threshold = (Z0.75(s) - Z0.25(s)) · (prob[Z(s) > threshold])

Threshold value (optional)

The threshold value used to densify the sampling network.

This parameter is only applicable when STDERR_THRESHOLD, QUARTILE_THRESHOLD, or QUARTILE_THRESHOLD_UPPER selection criteria is used.

Input weight raster (optional)

A raster used to determine which locations to weight for preference.

Input candidate point features (optional)

Sample locations to pick from.

Inhibition distance (optional)

Used to prevent any samples being placed within this distance from each other.

2.    Number of output points عدد نقاط الإخراج

Specify how many sample locations to generate.

حدد عدد مواقع العينات المراد إنشاؤها.

Output point feature class

The name of the output feature class.

Selection criteria (optional)

Methods to densify a sampling network.

·      STDERR—Standard error of prediction criteria

·      STDERR_THRESHOLD—Standard error threshold criteria

·      QUARTILE_THRESHOLD — Lower quartile threshold criteria

·      QUARTILE_THRESHOLD_UPPER — Upper quartile threshold criteria

The Standard error of prediction option will give extra weight to locations where the standard error of prediction is large. The Standard error threshold, Lower quartile threshold, and Upper quartile threshold options are useful when there is a critical threshold value for the variable under study (such as the highest admissible ozone level). The Standard error threshold option will give extra weight to locations whose values are close to the threshold. The Lower quartile threshold option will give extra weight to locations that are least likely to exceed the critical threshold. The Upper quartile threshold option will give extra weight to locations that are most likely to exceed the critical threshold.

The equations for each option are:

Standard error of prediction = stderr

 

 Standard error threshold = stderr(s)(1 - 2 · abs(prob[Z(s) > threshold] - 0.5))

 

 Lower quartile threshold = (Z0.75(s) - Z0.25(s)) · (prob[Z(s) < threshold])

 

 Upper quartile threshold = (Z0.75(s) - Z0.25(s)) · (prob[Z(s) > threshold])

Threshold value (optional)

The threshold value used to densify the sampling network.

This parameter is only applicable when STDERR_THRESHOLD, QUARTILE_THRESHOLD, or QUARTILE_THRESHOLD_UPPER selection criteria is used.

Input weight raster (optional)

A raster used to determine which locations to weight for preference.

Input candidate point features (optional)

Sample locations to pick from.

Inhibition distance (optional)

Used to prevent any samples being placed within this distance from each other.

3.    Output point feature class فئة ميزة نقطة الإخراج

The name of the output feature class.

اسم فئة ميزة الإخراج.

Selection criteria (optional)

Methods to densify a sampling network.

·      STDERR—Standard error of prediction criteria

·      STDERR_THRESHOLD—Standard error threshold criteria

·      QUARTILE_THRESHOLD — Lower quartile threshold criteria

·      QUARTILE_THRESHOLD_UPPER — Upper quartile threshold criteria

The Standard error of prediction option will give extra weight to locations where the standard error of prediction is large. The Standard error threshold, Lower quartile threshold, and Upper quartile threshold options are useful when there is a critical threshold value for the variable under study (such as the highest admissible ozone level). The Standard error threshold option will give extra weight to locations whose values are close to the threshold. The Lower quartile threshold option will give extra weight to locations that are least likely to exceed the critical threshold. The Upper quartile threshold option will give extra weight to locations that are most likely to exceed the critical threshold.

The equations for each option are:

Standard error of prediction = stderr

 

 Standard error threshold = stderr(s)(1 - 2 · abs(prob[Z(s) > threshold] - 0.5))

 

 Lower quartile threshold = (Z0.75(s) - Z0.25(s)) · (prob[Z(s) < threshold])

 

 Upper quartile threshold = (Z0.75(s) - Z0.25(s)) · (prob[Z(s) > threshold])

Threshold value (optional)

The threshold value used to densify the sampling network.

This parameter is only applicable when STDERR_THRESHOLD, QUARTILE_THRESHOLD, or QUARTILE_THRESHOLD_UPPER selection criteria is used.

Input weight raster (optional)

A raster used to determine which locations to weight for preference.

Input candidate point features (optional)

Sample locations to pick from.

Inhibition distance (optional)

Used to prevent any samples being placed within this distance from each other.

4.    Selection criteria (optional) معايير الاختيار (اختياري)

Methods to densify a sampling network.

· STDERR—Standard error of prediction criteria

· STDERR_THRESHOLD—Standard error threshold criteria

· QUARTILE_THRESHOLD — Lower quartile threshold criteria

· QUARTILE_THRESHOLD_UPPER — Upper quartile threshold criteria

The Standard error of prediction option will give extra weight to locations where the standard error of prediction is large. The Standard error threshold, Lower quartile threshold, and Upper quartile threshold options are useful when there is a critical threshold value for the variable under study (such as the highest admissible ozone level). The Standard error threshold option will give extra weight to locations whose values are close to the threshold. The Lower quartile threshold option will give extra weight to locations that are least likely to exceed the critical threshold. The Upper quartile threshold option will give extra weight to locations that are most likely to exceed the critical threshold.

طرق تكثيف شبكة أخذ العينات.

• STDERR - الخطأ القياسي لمعايير التنبؤ

• STDERR_THRESHOLD — معايير عتبة الخطأ القياسية

• QUARTILE_THRESHOLD - معايير العتبة الربعية الأدنى

• QUARTILE_THRESHOLD_UPPER - معايير عتبة الربع الأعلى

سيعطي خيار الخطأ القياسي للتنبؤ وزناً إضافياً للمواقع التي يكون فيها الخطأ القياسي للتنبؤ كبيراً. تعتبر خيارات عتبة الخطأ القياسية ، وعتبة الربيع الأدنى ، وخيارات عتبة الربعية الأعلى مفيدة عندما تكون هناك قيمة عتبة حرجة للمتغير قيد الدراسة (مثل أعلى مستوى أوزون مقبول). سيعطي خيار حد الخطأ القياسي وزنًا إضافيًا للمواقع التي تكون قيمها قريبة من الحد الأدنى. سيعطي خيار العتبة الربعية الأدنى وزناً إضافياً للمواقع الأقل احتمالاً لتجاوز العتبة الحرجة. سيعطي خيار عتبة الربع الأعلى وزنًا إضافيًا للمواقع التي يُرجح أن تتجاوز العتبة الحرجة.

المعادلات الخاصة بكل خيار هي:

The equations for each option are:

Standard error of prediction = stderr

 

 Standard error threshold = stderr(s)(1 - 2 · abs(prob[Z(s) > threshold] - 0.5))

 

 Lower quartile threshold = (Z0.75(s) - Z0.25(s)) · (prob[Z(s) < threshold])

 

 Upper quartile threshold = (Z0.75(s) - Z0.25(s)) · (prob[Z(s) > threshold])

 

5.    Threshold value (optional) قيمة الحد (اختياري)

The threshold value used to densify the sampling network.

This parameter is only applicable when STDERR_THRESHOLD, QUARTILE_THRESHOLD, or QUARTILE_THRESHOLD_UPPER selection criteria is used.

القيمة الحدية المستخدمة لتكثيف شبكة أخذ العينات.

هذه المعلمة قابلة للتطبيق فقط عند استخدام معايير اختيار STDERR_THRESHOLD أو QUARTILE_THRESHOLD أو QUARTILE_THRESHOLD_UPPER.

Input weight raster (optional)

A raster used to determine which locations to weight for preference.

Input candidate point features (optional)

Sample locations to pick from.

Inhibition distance (optional)

Used to prevent any samples being placed within this distance from each other.

6.    Input weight raster (optional) وزن الإدخال النقطي (اختياري)

A raster used to determine which locations to weight for preference.

نقطية تستخدم لتحديد المواقع التي يجب ترجيحها حسب التفضيل.

Input candidate point features (optional)

Sample locations to pick from.

Inhibition distance (optional)

Used to prevent any samples being placed within this distance from each other.

7.    Input candidate point features (optional) إدخال ميزات نقطة مرشح (اختياري)

Sample locations to pick from.

عينة من المواقع للاختيار من بينها.

Inhibition distance (optional)

Used to prevent any samples being placed within this distance from each other.

8.    Inhibition distance (optional) مسافة التثبيط (اختياري)

Used to prevent any samples being placed within this distance from each other.

تستخدم لمنع أي عينات يتم وضعها ضمن هذه المسافة من بعضها البعض.

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