كل ما يخص نظم المعلومات الجغرافية (GIS) وأي شخص مهتم في مجال علم نظم المعلومات الجغرافية وخاصةً برامج ArcGIS يستفيد من هذا الموقع، هناك الكثير من البرنامج التي يتم شرح طريقة تنزيلها بالإضافة الى مقالات كثيرة في نظم المعلومات الجغرافية، تستطيع من خلالها التعلم وتبادل العلم والمعرفة في مجال هذا العلم ، يمكن لأي شخص متابعة هذا الموقع ومتابعة أي مقال جديد لحظة بلحظة، هناك دورات مجانية وبمستويات متعددة لتعلم على برامج ArcGIS وأي برامج تهتم في GIS.
Given incident points or
weighted features (points or polygons), creates a map of statistically
significant hot spots, cold spots, and spatial outliers using the Anselin Local
Moran's I statistic. It evaluates the characteristics of the input feature class
to produce optimal results.
بالنظر إلى نقاط الحادث أو الميزات الموزونة
(النقاط أو المضلعات) ، يُنشئ خريطة النقاط الساخنة ذات الدلالة الإحصائية ،
والنقاط الباردة ، والقيم المتطرفة المكانية باستخدام إحصاء Anselin Local Moran I. يقوم بتقييم خصائص فئة ميزة الإدخال للحصول على أفضل النتائج.
1.Input Features ادخل المعالم
The point or polygon
feature class for which the cluster and outlier analysis will be performed.
فئة معلم النقطة أو المضلع التي سيتم إجراء تحليل
الكتلة والتحليل الخارجي لها.
Output Features
The output feature class to receive the result fields.
Analysis Field (optional)
The numeric field (number of incidents, crime rates, test scores, and so
on) to be evaluated.
Incident Data Aggregation Method
(optional)
The aggregation method to use to create weighted features for analysis
from incident point data.
·COUNT_INCIDENTS_WITHIN_FISHNET_POLYGONS—A fishnet polygon mesh will
overlay the incident point data and the number of incidents within each polygon
cell will be counted. If no bounding polygon is provided in the Bounding
Polygons Defining Where Incidents Are Possible parameter, only cells with at
least one incident will be used in the analysis; otherwise, all cells within
the bounding polygons will be analyzed.
·COUNT_INCIDENTS_WITHIN_HEXAGON_POLYGONS—A hexagon polygon mesh will
overlay the incident point data and the number of incidents within each polygon
cell will be counted. If no bounding polygon is provided in the Bounding
Polygons Defining Where Incidents Are Possible parameter, only cells with at
least one incident will be used in the analysis; otherwise, all cells within
the bounding polygons will be analyzed.
·COUNT_INCIDENTS_WITHIN_AGGREGATION_POLYGONS—You provide aggregation
polygons to overlay the incident point data in the Polygons For Aggregating
Incidents Into Counts parameter. The incidents within each polygon are counted.
·SNAP_NEARBY_INCIDENTS_TO_CREATE_WEIGHTED_POINTS—Nearby incidents will be
aggregated together to create a single weighted point. The weight for each
point is the number of aggregated incidents at that location.
Bounding Polygons Defining Where
Incidents Are Possible (optional)
A polygon feature class defining where the incident Input Features could
possibly occur.
Polygons For Aggregating Incidents
Into Counts (optional)
The polygons to use to aggregate the incident Input Features in order to
get an incident count for each polygon feature.
Performance Adjustment (optional)
This analysis utilizes permutations to create a reference distribution.
Choosing the number of permutations is a balance between precision and
increased processing time. Choose your preference for speed versus precision.
More robust and precise results take longer to calculate.
·QUICK_199—With 199 permutations, the smallest possible pseudo p-value is
0.005 and all other pseudo p-values will be even multiples of this value.
·BALANCED_499—With 499 permutations, the smallest possible pseudo p-value
is 0.002 and all other pseudo p-values will be even multiples of this value.
·ROBUST_999—With 999 permutations, the smallest possible pseudo p-value is
0.001 and all other pseudo p-values will be even multiples of this value.
Cell Size (optional)
The size of the grid cells used to aggregate the Input Features. When
aggregating into a hexagon grid, this distance is used as the height to
construct the hexagon polygons.
This tool only supports kilometers, meters, miles and feet.
Distance Band (optional)
The spatial extent of the analysis neighborhood. This value determines
which features are analyzed together in order to assess local clustering.
This tool only supports kilometers, meters, miles and feet.
2.Output Features المعالم المخرجة
The output feature class
to receive the result fields.
فئة معلم الإخراج لتلقي حقول النتائج.
Analysis Field (optional)
The numeric field (number of incidents, crime rates, test scores, and so
on) to be evaluated.
Incident Data Aggregation Method (optional)
The aggregation method to use to create weighted features for analysis
from incident point data.
·COUNT_INCIDENTS_WITHIN_FISHNET_POLYGONS—A fishnet polygon mesh will
overlay the incident point data and the number of incidents within each polygon
cell will be counted. If no bounding polygon is provided in the Bounding
Polygons Defining Where Incidents Are Possible parameter, only cells with at
least one incident will be used in the analysis; otherwise, all cells within
the bounding polygons will be analyzed.
·COUNT_INCIDENTS_WITHIN_HEXAGON_POLYGONS—A hexagon polygon mesh will
overlay the incident point data and the number of incidents within each polygon
cell will be counted. If no bounding polygon is provided in the Bounding
Polygons Defining Where Incidents Are Possible parameter, only cells with at
least one incident will be used in the analysis; otherwise, all cells within
the bounding polygons will be analyzed.
·COUNT_INCIDENTS_WITHIN_AGGREGATION_POLYGONS—You provide aggregation
polygons to overlay the incident point data in the Polygons For Aggregating
Incidents Into Counts parameter. The incidents within each polygon are counted.
·SNAP_NEARBY_INCIDENTS_TO_CREATE_WEIGHTED_POINTS—Nearby incidents will be
aggregated together to create a single weighted point. The weight for each
point is the number of aggregated incidents at that location.
Bounding Polygons Defining Where
Incidents Are Possible (optional)
A polygon feature class defining where the incident Input Features could
possibly occur.
Polygons For Aggregating Incidents
Into Counts (optional)
The polygons to use to aggregate the incident Input Features in order to
get an incident count for each polygon feature.
Performance Adjustment (optional)
This analysis utilizes permutations to create a reference distribution.
Choosing the number of permutations is a balance between precision and
increased processing time. Choose your preference for speed versus precision.
More robust and precise results take longer to calculate.
·QUICK_199—With 199 permutations, the smallest possible pseudo p-value is
0.005 and all other pseudo p-values will be even multiples of this value.
·BALANCED_499—With 499 permutations, the smallest possible pseudo p-value
is 0.002 and all other pseudo p-values will be even multiples of this value.
·ROBUST_999—With 999 permutations, the smallest possible pseudo p-value is
0.001 and all other pseudo p-values will be even multiples of this value.
Cell Size (optional)
The size of the grid cells used to aggregate the Input Features. When
aggregating into a hexagon grid, this distance is used as the height to
construct the hexagon polygons.
This tool only supports kilometers, meters, miles and feet.
Distance Band (optional)
The spatial extent of the analysis neighborhood. This value determines
which features are analyzed together in order to assess local clustering.
This tool only supports kilometers, meters, miles and feet.
3.Analysis Field (optional) مجال
التحليل (اختياري)
The numeric field
(number of incidents, crime rates, test scores, and so on) to be evaluated.
الحقل الرقمي (عدد الحوادث ، ومعدلات الجريمة ،
ودرجات الاختبار ، وما إلى ذلك) المراد تقييمه.
Incident Data Aggregation Method
(optional)
The aggregation method to use to create weighted features for analysis
from incident point data.
·COUNT_INCIDENTS_WITHIN_FISHNET_POLYGONS—A fishnet polygon mesh will
overlay the incident point data and the number of incidents within each polygon
cell will be counted. If no bounding polygon is provided in the Bounding
Polygons Defining Where Incidents Are Possible parameter, only cells with at
least one incident will be used in the analysis; otherwise, all cells within
the bounding polygons will be analyzed.
·COUNT_INCIDENTS_WITHIN_HEXAGON_POLYGONS—A hexagon polygon mesh will
overlay the incident point data and the number of incidents within each polygon
cell will be counted. If no bounding polygon is provided in the Bounding
Polygons Defining Where Incidents Are Possible parameter, only cells with at
least one incident will be used in the analysis; otherwise, all cells within
the bounding polygons will be analyzed.
·COUNT_INCIDENTS_WITHIN_AGGREGATION_POLYGONS—You provide aggregation
polygons to overlay the incident point data in the Polygons For Aggregating
Incidents Into Counts parameter. The incidents within each polygon are counted.
·SNAP_NEARBY_INCIDENTS_TO_CREATE_WEIGHTED_POINTS—Nearby incidents will be
aggregated together to create a single weighted point. The weight for each
point is the number of aggregated incidents at that location.
Bounding Polygons Defining Where
Incidents Are Possible (optional)
A polygon feature class defining where the incident Input Features could
possibly occur.
Polygons For Aggregating Incidents
Into Counts (optional)
The polygons to use to aggregate the incident Input Features in order to
get an incident count for each polygon feature.
Performance Adjustment (optional)
This analysis utilizes permutations to create a reference distribution.
Choosing the number of permutations is a balance between precision and
increased processing time. Choose your preference for speed versus precision.
More robust and precise results take longer to calculate.
·QUICK_199—With 199 permutations, the smallest possible pseudo p-value is
0.005 and all other pseudo p-values will be even multiples of this value.
·BALANCED_499—With 499 permutations, the smallest possible pseudo p-value
is 0.002 and all other pseudo p-values will be even multiples of this value.
·ROBUST_999—With 999 permutations, the smallest possible pseudo p-value is
0.001 and all other pseudo p-values will be even multiples of this value.
Cell Size (optional)
The size of the grid cells used to aggregate the Input Features. When
aggregating into a hexagon grid, this distance is used as the height to
construct the hexagon polygons.
This tool only supports kilometers, meters, miles and feet.
Distance Band (optional)
The spatial extent of the analysis neighborhood. This value determines
which features are analyzed together in order to assess local clustering.
This tool only supports kilometers, meters, miles and feet.
4.Incident Data Aggregation Method (optional) طريقة تجميع بيانات الحادث (اختياري)
The aggregation method
to use to create weighted features for analysis from incident point data.
·COUNT_INCIDENTS_WITHIN_FISHNET_POLYGONS—A fishnet polygon mesh
will overlay the incident point data and the number of incidents within each
polygon cell will be counted. If no bounding polygon is provided in the
Bounding Polygons Defining Where Incidents Are Possible parameter, only cells
with at least one incident will be used in the analysis; otherwise, all cells
within the bounding polygons will be analyzed.
·COUNT_INCIDENTS_WITHIN_HEXAGON_POLYGONS—A hexagon polygon mesh
will overlay the incident point data and the number of incidents within each
polygon cell will be counted. If no bounding polygon is provided in the
Bounding Polygons Defining Where Incidents Are Possible parameter, only cells
with at least one incident will be used in the analysis; otherwise, all cells
within the bounding polygons will be analyzed.
·COUNT_INCIDENTS_WITHIN_AGGREGATION_POLYGONS—You provide
aggregation polygons to overlay the incident point data in the Polygons For
Aggregating Incidents Into Counts parameter. The incidents within each polygon
are counted.
·SNAP_NEARBY_INCIDENTS_TO_CREATE_WEIGHTED_POINTS—Nearby incidents
will be aggregated together to create a single weighted point. The weight for
each point is the number of aggregated incidents at that location.
طريقة التجميع المراد استخدامها لإنشاء ميزات
مرجحة للتحليل من بيانات نقطة الحادث.
• COUNT_INCIDENTS_WITHIN_FISHNET_POLYGONS - ستتراكب شبكة مضلع
شبكة صيد السمك على بيانات نقطة الحادث وسيتم حساب عدد الحوادث داخل كل خلية مضلع.
إذا لم يتم توفير مضلع محيط في معلمة تحديد مكان وقوع الحوادث ، فسيتم استخدام
الخلايا التي بها حادثة واحدة على الأقل في التحليل ؛ خلاف ذلك ، سيتم تحليل جميع
الخلايا داخل المضلعات المحيطة.
• COUNT_INCIDENTS_WITHIN_HEXAGON_POLYGONS - ستغطي شبكة مضلعة
سداسية الشكل بيانات نقطة الحادث وسيتم حساب عدد الحوادث داخل كل خلية مضلع. إذا
لم يتم توفير مضلع محيط في معلمة تحديد مكان وقوع الحوادث ، فسيتم استخدام الخلايا
التي بها حادثة واحدة على الأقل في التحليل ؛ خلاف ذلك ، سيتم تحليل جميع الخلايا
داخل المضلعات المحيطة.
• COUNT_INCIDENTS_WITHIN_AGGREGATION_POLYGONS - أنت توفر مضلعات تجميع
لتراكب بيانات نقطة الحادث في معلمة Polygons For Aggregating Inco Counts. يتم حساب الحوادث داخل كل مضلع.
• SNAP_NEARBY_INCIDENTS_TO_CREATE_WEIGHTED_POINTS - سيتم تجميع الأحداث
القريبة معًا لإنشاء نقطة مرجحة واحدة. وزن كل نقطة هو عدد الحوادث المجمعة في ذلك
الموقع.
Bounding Polygons Defining Where
Incidents Are Possible (optional)
A polygon feature class defining where the incident Input Features could
possibly occur.
Polygons For Aggregating Incidents
Into Counts (optional)
The polygons to use to aggregate the incident Input Features in order to
get an incident count for each polygon feature.
Performance Adjustment (optional)
This analysis utilizes permutations to create a reference distribution.
Choosing the number of permutations is a balance between precision and
increased processing time. Choose your preference for speed versus precision.
More robust and precise results take longer to calculate.
·QUICK_199—With 199 permutations, the smallest possible pseudo p-value is
0.005 and all other pseudo p-values will be even multiples of this value.
·BALANCED_499—With 499 permutations, the smallest possible pseudo p-value
is 0.002 and all other pseudo p-values will be even multiples of this value.
·ROBUST_999—With 999 permutations, the smallest possible pseudo p-value is
0.001 and all other pseudo p-values will be even multiples of this value.
Cell Size (optional)
The size of the grid cells used to aggregate the Input Features. When
aggregating into a hexagon grid, this distance is used as the height to
construct the hexagon polygons.
This tool only supports kilometers, meters, miles and feet.
Distance Band (optional)
The spatial extent of the analysis neighborhood. This value determines
which features are analyzed together in order to assess local clustering.
This tool only supports kilometers, meters, miles and feet.
5.Bounding Polygons Defining Where Incidents Are Possible
(optional) المضلعات المحيطة التي تحدد مكان وقوع
الحوادث (اختياري)
A polygon feature class
defining where the incident Input Features could possibly occur.
فئة معلم مضلع تحدد مكان حدوث ميزات إدخال الحادث.
Polygons For Aggregating Incidents
Into Counts (optional)
The polygons to use to aggregate the incident Input Features in order to
get an incident count for each polygon feature.
Performance Adjustment (optional)
This analysis utilizes permutations to create a reference distribution.
Choosing the number of permutations is a balance between precision and
increased processing time. Choose your preference for speed versus precision.
More robust and precise results take longer to calculate.
·QUICK_199—With 199 permutations, the smallest possible pseudo p-value is
0.005 and all other pseudo p-values will be even multiples of this value.
·BALANCED_499—With 499 permutations, the smallest possible pseudo p-value
is 0.002 and all other pseudo p-values will be even multiples of this value.
·ROBUST_999—With 999 permutations, the smallest possible pseudo p-value is
0.001 and all other pseudo p-values will be even multiples of this value.
Cell Size (optional)
The size of the grid cells used to aggregate the Input Features. When
aggregating into a hexagon grid, this distance is used as the height to
construct the hexagon polygons.
This tool only supports kilometers, meters, miles and feet.
Distance Band (optional)
The spatial extent of the analysis neighborhood. This value determines
which features are analyzed together in order to assess local clustering.
This tool only supports kilometers, meters, miles and feet.
6.Polygons For Aggregating Incidents Into Counts (optional) المضلعات لتجميع الحوادث في أعداد (اختياري)
The polygons to use to
aggregate the incident Input Features in order to get an incident count for
each polygon feature.
المضلعات التي سيتم استخدامها لتجميع ميزات إدخال
الحادث من أجل الحصول على عدد الحوادث لكل معلم مضلع.
Performance Adjustment (optional)
This analysis utilizes permutations to create a reference distribution.
Choosing the number of permutations is a balance between precision and
increased processing time. Choose your preference for speed versus precision.
More robust and precise results take longer to calculate.
·QUICK_199—With 199 permutations, the smallest possible pseudo p-value is
0.005 and all other pseudo p-values will be even multiples of this value.
·BALANCED_499—With 499 permutations, the smallest possible pseudo p-value
is 0.002 and all other pseudo p-values will be even multiples of this value.
·ROBUST_999—With 999 permutations, the smallest possible pseudo p-value is
0.001 and all other pseudo p-values will be even multiples of this value.
Cell Size (optional)
The size of the grid cells used to aggregate the Input Features. When
aggregating into a hexagon grid, this distance is used as the height to
construct the hexagon polygons.
This tool only supports kilometers, meters, miles and feet.
Distance Band (optional)
The spatial extent of the analysis neighborhood. This value determines
which features are analyzed together in order to assess local clustering.
This tool only supports kilometers, meters, miles and feet.
This analysis utilizes
permutations to create a reference distribution. Choosing the number of
permutations is a balance between precision and increased processing time.
Choose your preference for speed versus precision. More robust and precise
results take longer to calculate.
·QUICK_199—With 199 permutations, the smallest possible pseudo
p-value is 0.005 and all other pseudo p-values will be even multiples of this
value.
·BALANCED_499—With 499 permutations, the smallest possible pseudo
p-value is 0.002 and all other pseudo p-values will be even multiples of this
value.
·ROBUST_999—With 999 permutations, the smallest possible pseudo
p-value is 0.001 and all other pseudo p-values will be even multiples of this
value.
يستخدم هذا التحليل التباديل لإنشاء توزيع مرجعي.
اختيار عدد التباديل هو توازن بين الدقة وزيادة وقت المعالجة. اختر ما تفضله من
حيث السرعة مقابل الدقة. يستغرق حساب النتائج الأكثر قوة ودقة وقتًا أطول.
• QUICK_199 - مع 199 من التباديل ، فإن أصغر قيمة p زائفة
ممكنة هي 0.005 وجميع القيم الزائفة الأخرى ستكون مضاعفات هذه القيمة.
• BALANCED_499 - مع 499 تبديلًا ، تكون أصغر قيمة p زائفة
ممكنة هي 0.002 وستكون جميع قيم p
الزائفة الأخرى مضاعفات هذه القيمة.
• ROBUST_999— مع 999 تبديلًا ، فإن أصغر قيمة p زائفة
ممكنة هي 0.001 وجميع القيم الزائفة الأخرى ستكون مضاعفات هذه القيمة.
Cell Size (optional)
The size of the grid cells used to aggregate the Input Features. When
aggregating into a hexagon grid, this distance is used as the height to
construct the hexagon polygons.
This tool only supports kilometers, meters, miles and feet.
Distance Band (optional)
The spatial extent of the analysis neighborhood. This value determines
which features are analyzed together in order to assess local clustering.
This tool only supports kilometers, meters, miles and feet.
8.Cell Size (optional) حجم الخلية
(اختياري)
The size of the grid
cells used to aggregate the Input Features. When aggregating into a hexagon
grid, this distance is used as the height to construct the hexagon polygons.
This tool only supports
kilometers, meters, miles and feet.
حجم خلايا الشبكة المستخدمة لتجميع ميزات الإدخال.
عند التجميع في شبكة سداسية ، يتم استخدام هذه المسافة كارتفاع لبناء المضلعات
السداسية.
هذه الأداة تدعم فقط الكيلومترات والأمتار
والأميال والقدم.
Distance Band (optional)
The spatial extent of the analysis neighborhood. This value determines
which features are analyzed together in order to assess local clustering.
This tool only supports kilometers, meters, miles and feet.
9.Distance Band (optional) نطاق
المسافة (اختياري)
The spatial extent of
the analysis neighborhood. This value determines which features are analyzed
together in order to assess local clustering.
This tool only supports
kilometers, meters, miles and feet.
المدى المكاني لحي التحليل. تحدد هذه القيمة
الميزات التي يتم تحليلها معًا لتقييم المجموعات المحلية.
هذه الأداة تدعم فقط الكيلومترات والأمتار
والأميال والقدم.
اليك صفحه ومجموعة على الفيس بوك لتعلم أكثر بما يخص نظم المعلومات الجغرافية (GIS) و برنامج ArcGIS Pro من خلال هذه الروابط:
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