Renewable energy

Sample: Renewable energy, Ouarzazate: report

Project: Sample: Renewable energy, Ouarzazate
Goal: Describe the project Sample: Renewable energy, Ouarzazate: run the analyses that tell the most about its data, draw every result, and write a cited report.
Run: 895bf965-1c68-4de6-be27-d405f321db83 (running, 11 agent run(s))
Generated: 2026-10-18T05:22:03Z, version 1
Model cost: USD 0.0000 over 0 model call(s)

Data used

Timeline

The timeline counts 1,024 dated events in Bird surveys, Dust storms, Site irradiance by month per month, from February 2024 to May 2026 1234. By dataset: Bird surveys 650; Site irradiance by month 360; Dust storms 14 1. The trend is +2.59 events per month; the second half of the months has 823 against 201 in the first (+309.4%) 1. 5 of the 28 months had no events 1.

Busiest months

• March 2025: 133 events 1
• April 2025: 115 events 1
• October 2025: 105 events 1

Quietest months with events

• February 2024: 1 event 1
• March 2024: 1 event 1
• May 2024: 1 event 1

Summarize within

What this analysis is. Summarize within: Count and aggregate the features inside each polygon (or bin), proportionally for lines and polygons 5. In ArcGIS it is Summarize Within or Aggregate Points; in QGIS, native:countpointsinpolygon or native:sumlinelengths 5.

Why it was run on this data. Count Met masts inside each feature of Exclusion zones; the counts map as a choropleth (natural breaks, sequential colors) 6.

What it found. Summarize within on Met masts, Exclusion zones: Summarize within: 1 layer saved: Summarize within: Exclusion zones (8 features) 789. It reported result, count 8; result, elapsed ms 3; billing, cost 0.01024; billing, list price 0.01024; billing, upstream cost 0 7.

Findings

• Evidenced: Summarize within on Met masts, Exclusion zones: Summarize within: 1 layer saved: Summarize within: Exclusion zones (8 features) 789.
• Evidenced: It reported result, count 8; result, elapsed ms 3; billing, cost 0.01024; billing, list price 0.01024; billing, upstream cost 0 7.

Tool gp_summarize_within; parameters {"stats": [], "project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Met masts (46ca6de8)"}, "polygons": {"layer": "Exclusion zones (f76641f5)"}}

Summarize within

What this analysis is. Summarize within: Count and aggregate the features inside each polygon (or bin), proportionally for lines and polygons 5. In ArcGIS it is Summarize Within or Aggregate Points; in QGIS, native:countpointsinpolygon or native:sumlinelengths 5.

Why it was run on this data. Count Met masts inside each feature of Exclusion zones; the counts map as a choropleth (natural breaks, sequential colors) 6.

What it found. Summarize within on Substations, Exclusion zones: Summarize within: 1 layer saved: Summarize within: Exclusion zones (8 features) 91011. It reported result, count 8; result, elapsed ms 3; billing, cost 0.01028; billing, list price 0.01028; billing, upstream cost 0 10.

Findings

• Evidenced: Summarize within on Substations, Exclusion zones: Summarize within: 1 layer saved: Summarize within: Exclusion zones (8 features) 91011.
• Evidenced: It reported result, count 8; result, elapsed ms 3; billing, cost 0.01028; billing, list price 0.01028; billing, upstream cost 0 10.

A model draft was discarded because a sentence did not cite a source of this section.

Tool gp_summarize_within; parameters {"stats": [{"stat": "sum", "field": "voltage_kv"}], "project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Substations (9024da37)"}, "polygons": {"layer": "Exclusion zones (f76641f5)"}}

Summarize within

What this analysis is. Summarize within: Count and aggregate the features inside each polygon (or bin), proportionally for lines and polygons 5. In ArcGIS it is Summarize Within or Aggregate Points; in QGIS, native:countpointsinpolygon or native:sumlinelengths 5.

Why it was run on this data. Count Met masts inside each feature of Exclusion zones; the counts map as a choropleth (natural breaks, sequential colors) 6.

What it found. Summarize within on Bird surveys, Exclusion zones: Summarize within: 1 layer saved: Summarize within: Exclusion zones (8 features) 91213. It reported result, count 8; result, elapsed ms 5; billing, cost 0.02318; billing, list price 0.02318; billing, upstream cost 0 12.

Findings

• Evidenced: Summarize within on Bird surveys, Exclusion zones: Summarize within: 1 layer saved: Summarize within: Exclusion zones (8 features) 91213.
• Evidenced: It reported result, count 8; result, elapsed ms 5; billing, cost 0.02318; billing, list price 0.02318; billing, upstream cost 0 12.

Tool gp_summarize_within; parameters {"stats": [{"stat": "sum", "field": "count"}], "project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Bird surveys (a5b49489)"}, "group_by": "species", "polygons": {"layer": "Exclusion zones (f76641f5)"}}

Zonal statistics

What this analysis is. Zonal statistics: count/min/max/mean/std/sum/median/majority per polygon as a table and as GeoJSON 14. In ArcGIS it is Zonal Statistics as Table (polygons) 14.

Why it was run on this data. Statistics of Plateau terrain model (DEM) inside each feature of Exclusion zones 15.

What it found. The zonal statistics analysis was performed using the tool rs_zonal_statistics 16. The tool summary indicated that Zonal statistics produced 8 row(s) 16. Additionally, the process analyzed 8 zones 16.

Findings

• Evidenced: Zonal statistics: Zonal statistics: 8 row(s) 16.
• Evidenced: zones 8 16.

Tool rs_zonal_statistics; parameters {"stats": ["mean", "min", "max", "std"], "zones": "Exclusion zones (f76641f5)", "raster_id": "Plateau terrain model (DEM) (918994c5)"}

Zonal statistics

What this analysis is. Zonal statistics: count/min/max/mean/std/sum/median/majority per polygon as a table and as GeoJSON 14. In ArcGIS it is Zonal Statistics as Table (polygons) 14.

Why it was run on this data. Statistics of Plateau terrain model (DEM) inside each feature of Exclusion zones 15.

What it found. The tool rs_zonal_statistics processed 14 row(s) 17. This tool involved 14 zones 17.

Findings

• Evidenced: Zonal statistics: Zonal statistics: 14 row(s) 17.
• Evidenced: zones 14 17.

Tool rs_zonal_statistics; parameters {"stats": ["mean", "min", "max", "std"], "zones": "Dust storms (aeb5849f)", "raster_id": "Plateau terrain model (DEM) (918994c5)"}

Zonal statistics

What this analysis is. Zonal statistics: count/min/max/mean/std/sum/median/majority per polygon as a table and as GeoJSON 14. In ArcGIS it is Zonal Statistics as Table (polygons) 14.

Why it was run on this data. Statistics of Plateau terrain model (DEM) inside each feature of Exclusion zones 15.

What it found. The Zonal statistics analysis used the tool rs_zonal_statistics 18. The resulting data structure contains 30 row(s) spanning 30 zones 18.

Findings

• Evidenced: Zonal statistics: Zonal statistics: 30 row(s) 18.
• Evidenced: zones 30 18.

Tool rs_zonal_statistics; parameters {"stats": ["mean", "min", "max", "std"], "zones": "Candidate sites (d70250d1)", "raster_id": "Plateau terrain model (DEM) (918994c5)"}

Space time hot spots

What this analysis is. Emerging hot spots: Where hot spots are new, consecutive, intensifying, persistent, diminishing, sporadic, oscillating or historical over time 19. In ArcGIS it is Emerging Hot Spot Analysis or Create Space Time Cube 19.

Why it was run on this data. Bird surveys carry dates in 'observed_at': emerging hot spot analysis finds new, intensifying and fading hot spots per month 20.

What it found. Space time hot spots on Bird surveys: Emerging hot spots: 1 layer saved: Emerging hot spots: Bird surveys (156 features) 1321. It reported result, count 156; result, elapsed ms 22; result, resolution 8; result, features used 650; result, time neighbors 0; billing, cost 0.1325 21.

Findings

• Evidenced: Space time hot spots on Bird surveys: Emerging hot spots: 1 layer saved: Emerging hot spots: Bird surveys (156 features) 1321.
• Evidenced: It reported result, count 156; result, elapsed ms 22; result, resolution 8; result, features used 650; result, time neighbors 0; billing, cost 0.1325 21.

A model draft was discarded because a sentence did not cite a source of this section.

Tool gp_space_time_hot_spots; parameters {"agg": "sum", "project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Bird surveys (a5b49489)"}, "interval": "month", "bin_shape": "h3", "resolution": 8, "time_field": "observed_at", "value_field": "count"}

Hot spots

What this analysis is. Hot spot analysis: Getis-Ord Gi* hot and cold spots with z-scores, p-values and confidence bins 22. In ArcGIS it is Find Hot Spots or Hot Spot Analysis (Getis-Ord Gi*); in QGIS, qgis:hotspot (plugin) 22.

Why it was run on this data. 650 points: Getis-Ord Gi* tests whether the concentrations in Bird surveys are statistically significant 23.

What it found. The hot spot analysis utilized the Bird surveys layer 13 and resulted in 650 features [

Findings

• Evidenced: Hot spots on Bird surveys: Hot spot analysis: 1 layer saved: Hot spot analysis: Bird surveys (650 features) 1324.
• Evidenced: It reported result, count 650; result, elapsed ms 13; result, excluded null 0; result, distance band m 1,000; billing, cost 0.063; billing, list price 0.063 24.

Tool gp_hot_spots; parameters {"field": "count", "project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Bird surveys (a5b49489)"}, "aggregation": "hexagon", "cell_size_m": 1000.0, "distance_band_m": 1000.0}

Calculate density

What this analysis is. Calculate density: Kernel density per square kilometer on a grid 25. In ArcGIS it is Calculate Density or Kernel Density; in QGIS, native:heatmapkerneldensityestimation 25.

Why it was run on this data. 650 points in Bird surveys: a density surface shows where they concentrate 26.

What it found. The density calculation tool was run on the Bird surveys layer 27, yielding 699 features 27. The resulting density data showed a maximum of 194.2 per km² 27. Key parameters for the calculation included a bandwidth of 1,000 m and a cell size of 500 m 27. The cost associated with this operation was 0.063 27.

Findings

• Evidenced: Calculate density on Bird surveys: Calculate density: 1 layer saved: Calculate density: Bird surveys (699 features) 1327.
• Evidenced: It reported result, count 699; result, elapsed ms 21; result, bandwidth m 1,000; result, cell size m 500; result, excluded null 0; result, max density per km2 194.2 27.

Tool gp_calculate_density; parameters {"kernel": "quartic", "project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Bird surveys (a5b49489)"}, "bandwidth_m": 1000.0, "cell_size_m": 500.0, "weight_field": "count"}

Find point clusters

What this analysis is. Find point clusters: Density-based clusters (DBSCAN, HDBSCAN or OPTICS, optionally space-time) with hulls and noise 28. In ArcGIS it is Find Point Clusters or Density-based Clustering; in QGIS, native:dbscanclustering or native:stdbscanclustering 28.

Why it was run on this data. DBSCAN finds dense groups of Bird surveys and separates noise 29.

What it found. Find point clusters on Bird surveys: Find point clusters: 2 layers saved: Find point clusters: Bird surveys (650 features); Find point clusters: cluster hulls (1 feature) 1330. It reported result, count 650; result, noise 261; result, distance m 500; result, elapsed ms 11; result, min points 16; billing, cost 0.063 30.

Findings

• Evidenced: Find point clusters on Bird surveys: Find point clusters: 2 layers saved: Find point clusters: Bird surveys (650 features); Find point clusters: cluster hulls (1 feature) 1330.
• Evidenced: It reported result, count 650; result, noise 261; result, distance m 500; result, elapsed ms 11; result, min points 16; billing, cost 0.063 30.

Tool gp_find_point_clusters; parameters {"method": "dbscan", "project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Bird surveys (a5b49489)"}, "distance_m": 500.0, "min_points": 16}

Nearest neighbor index

What this analysis is. Average nearest neighbor: Clark-Evans ratio: clustered, dispersed or random 31. In ArcGIS it is Average Nearest Neighbor; in QGIS, native:nearestneighbouranalysis 31.

Why it was run on this data. The average nearest neighbor ratio says whether Substations are clustered, random or dispersed 32.

What it found. Nearest neighbor index on Substations: Average nearest neighbor: done; no map output 1133. It reported result, n 5; result, p value 0; result, z score 8.856; result, elapsed ms 0; result, study area m2 30,876,054; result, nearest neighbor ratio 3.07 33.

Findings

• Evidenced: Nearest neighbor index on Substations: Average nearest neighbor: done; no map output 1133.
• Evidenced: It reported result, n 5; result, p value 0; result, z score 8.856; result, elapsed ms 0; result, study area m2 30,876,054; result, nearest neighbor ratio 3.07 33.

Tool gp_nearest_neighbor_index; parameters {"project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Substations (9024da37)"}}

Nearest neighbor index

What this analysis is. Average nearest neighbor: Clark-Evans ratio: clustered, dispersed or random 31. In ArcGIS it is Average Nearest Neighbor; in QGIS, native:nearestneighbouranalysis 31.

Why it was run on this data. The average nearest neighbor ratio says whether Bird surveys are clustered, random or dispersed 34.

What it found. Nearest neighbor index on Bird surveys: Average nearest neighbor: done; no map output 1335. It reported result, n 650; result, p value 0; result, z score -9.837; result, elapsed ms 3; result, study area m2 134,387,893; result, nearest neighbor ratio 0.7983 35.

Findings

• Evidenced: Nearest neighbor index on Bird surveys: Average nearest neighbor: done; no map output 1335.
• Evidenced: It reported result, n 650; result, p value 0; result, z score -9.837; result, elapsed ms 3; result, study area m2 134,387,893; result, nearest neighbor ratio 0.7983 35.

Tool gp_nearest_neighbor_index; parameters {"project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Bird surveys (a5b49489)"}}

Outliers

What this analysis is. Find outliers: Anselin local Moran’s I: HH, LL clusters and HL, LH outliers 36. In ArcGIS it is Find Outliers or Cluster and Outlier Analysis (Anselin Local Moran’s I) 36.

Why it was run on this data. Local Moran's I maps clusters and outliers of 'buffer_m' 37.

What it found. The gp_outliers tool identified outliers and processed the Exclusion zones [38, 9]. The execution found 1 layer saved and reported a total count of 8 results 38.

Findings

• Evidenced: Outliers on Exclusion zones: Find outliers: 1 layer saved: Find outliers: Exclusion zones (8 features) 938.
• Evidenced: It reported result, count 8; result, elapsed ms 10; result, permutations 199; result, excluded null 0; result, distance band m 4,662; billing, cost 0.05024 38.

Tool gp_outliers; parameters {"field": "buffer_m", "project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Exclusion zones (f76641f5)"}, "aggregation": "hexagon"}

Outliers

What this analysis is. Find outliers: Anselin local Moran’s I: HH, LL clusters and HL, LH outliers 36. In ArcGIS it is Find Outliers or Cluster and Outlier Analysis (Anselin Local Moran’s I) 36.

Why it was run on this data. Local Moran's I maps clusters and outliers of 'pm10_peak' 39.

What it found. The analysis utilized the gp_outliers tool 40 on the Dust storms layer 41. The function identified a count of 14 results 40, and the entire operation took 5 ms to complete 40. Billing details indicated a list price of 0.05042 40 for processing the 14 features 40.

Findings

• Evidenced: Outliers on Dust storms: Find outliers: 1 layer saved: Find outliers: Dust storms (14 features) 4041.
• Evidenced: It reported result, count 14; result, elapsed ms 5; result, permutations 199; result, excluded null 0; result, distance band m 4,561; billing, cost 0.05042 40.

Tool gp_outliers; parameters {"field": "pm10_peak", "project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Dust storms (aeb5849f)"}, "aggregation": "hexagon"}

Outliers

What this analysis is. Find outliers: Anselin local Moran’s I: HH, LL clusters and HL, LH outliers 36. In ArcGIS it is Find Outliers or Cluster and Outlier Analysis (Anselin Local Moran’s I) 36.

Why it was run on this data. Local Moran's I maps clusters and outliers of 'ghi_kwh_m2_yr' 42.

What it found. Outliers on Candidate sites: Find outliers: 1 layer saved: Find outliers: Candidate sites (30 features) 4344. It reported result, count 30; result, elapsed ms 8; result, permutations 199; result, excluded null 0; result, distance band m 3,255; billing, cost 0.0509 43.

Findings

• Evidenced: Outliers on Candidate sites: Find outliers: 1 layer saved: Find outliers: Candidate sites (30 features) 4344.
• Evidenced: It reported result, count 30; result, elapsed ms 8; result, permutations 199; result, excluded null 0; result, distance band m 3,255; billing, cost 0.0509 43.

Tool gp_outliers; parameters {"field": "ghi_kwh_m2_yr", "project": "8e181d65-6b3c-4526-9cff-cfc25a7f3e07", "features": {"layer": "Candidate sites (d70250d1)"}, "aggregation": "hexagon"}

Maps and charts

The run also made 14 map image(s) 4546474849505152535455565758 and 17 chart(s) 5960616263646566676869707172737475.

What the map shows. The map displays the summarized count of "Exclusion zones" within the area, using 0 to 1 as indicated in the legend. High counts, represented by darker orange, are clustered in several prominent, sinuous bands running horizontally across the mapped view. Additionally, distinct areas of high counts are visible as larger, circular patches that are scattered across 46

Inferred: read from the image by gemma4:e4b, not evidence.

Changes since the last run

This is the first report of this project.

Sources

1. 1Rendering: Chart: Timeline: events per month by dataset. 84 rows id 241ff431-2463-4d2b-9969-bfa5a0f6ce84
2. 2Dataset: Bird surveys. vector, 650 rows id 7a5a9074-3838-427a-8c24-d286446838ad
3. 3Dataset: Dust storms. vector, 14 rows id 8ead6725-8b61-44df-a3b4-cdb7f223347a
4. 4Dataset: Site irradiance by month. table, 360 rows id c78442cd-f73b-403e-8ff1-86fb1c7bc591
5. 5Catalog: Summarize within (operation catalog, gp_summarize_within). Count and aggregate the features inside each polygon (or bin), proportionally for lines and polygons. ArcGIS: Summarize Within, Aggregate Points. QGIS: native:countpointsinpolygon, native:sumlinelengths. id gp_summarize_within
6. 6Plan: Met masts per feature of Exclusion zones (the Start plan's candidate c_41c08b6712ff). Count Met masts inside each feature of Exclusion zones; the counts map as a choropleth (natural breaks, sequential colors). id 4467f0bd-c718-4e32-858e-fdc23c1206ed:c_41c08b6712ff
7. 7Tool result: gp_summarize_within, step 0. Summarize within: 1 layer saved: Summarize within: Exclusion zones (8 features). id 94fd8ddf-f2f8-40c7-9baa-40dbb152522d:0
8. 8Layer: Met masts. 4 features id 46ca6de8-1f52-4cae-8a9c-aa89cdfb58ed
9. 9Layer: Exclusion zones. 8 features id f76641f5-146c-4958-8885-d9250aa67fc6
10. 10Tool result: gp_summarize_within, step 1. Summarize within: 1 layer saved: Summarize within: Exclusion zones (8 features). id 94fd8ddf-f2f8-40c7-9baa-40dbb152522d:1
11. 11Layer: Substations. 5 features id 9024da37-5b4c-4500-b90a-7838a0cefe33
12. 12Tool result: gp_summarize_within, step 2. Summarize within: 1 layer saved: Summarize within: Exclusion zones (8 features). id 94fd8ddf-f2f8-40c7-9baa-40dbb152522d:2
13. 13Layer: Bird surveys. 650 features id a5b49489-c432-4eb3-aa5e-37524f1a4db9
14. 14Catalog: Zonal statistics (analysis catalog, rs_zonal_statistics). count/min/max/mean/std/sum/median/majority per polygon as a table and as GeoJSON. ArcGIS: Zonal Statistics as Table (polygons). id rs_zonal_statistics
15. 15Plan: Zonal statistics of Plateau terrain model (DEM) and Exclusion zones (the Start plan's candidate c_66d31df1c394). Statistics of Plateau terrain model (DEM) inside each feature of Exclusion zones. id 4467f0bd-c718-4e32-858e-fdc23c1206ed:c_66d31df1c394
16. 16Tool result: rs_zonal_statistics, step 0. Zonal statistics: 8 row(s). zones 8. id f33d2406-6d8e-4b9d-ac3e-7cda4a6fb94a:0
17. 17Tool result: rs_zonal_statistics, step 1. Zonal statistics: 14 row(s). zones 14. id f33d2406-6d8e-4b9d-ac3e-7cda4a6fb94a:1
18. 18Tool result: rs_zonal_statistics, step 2. Zonal statistics: 30 row(s). zones 30. id f33d2406-6d8e-4b9d-ac3e-7cda4a6fb94a:2
19. 19Catalog: Emerging hot spots (operation catalog, gp_space_time_hot_spots). Where hot spots are new, consecutive, intensifying, persistent, diminishing, sporadic, oscillating or historical over time. ArcGIS: Emerging Hot Spot Analysis, Create Space Time Cube. id gp_space_time_hot_spots
20. 20Plan: Space time hot spots of Bird surveys (the Start plan's candidate c_0a376e0f7bee). Bird surveys carry dates in 'observed_at': emerging hot spot analysis finds new, intensifying and fading hot spots per month. id 4467f0bd-c718-4e32-858e-fdc23c1206ed:c_0a376e0f7bee
21. 21Tool result: gp_space_time_hot_spots, step 0. Emerging hot spots: 1 layer saved: Emerging hot spots: Bird surveys (156 features). id 57aa9228-065c-4727-b2e2-360559185796:0
22. 22Catalog: Hot spot analysis (operation catalog, gp_hot_spots). Getis-Ord Gi* hot and cold spots with z-scores, p-values and confidence bins. ArcGIS: Find Hot Spots, Hot Spot Analysis (Getis-Ord Gi*). QGIS: qgis:hotspot (plugin). id gp_hot_spots
23. 23Plan: Hot spots of Bird surveys (the Start plan's candidate c_c119c8fa5c0a). 650 points: Getis-Ord Gi* tests whether the concentrations in Bird surveys are statistically significant. id 4467f0bd-c718-4e32-858e-fdc23c1206ed:c_c119c8fa5c0a
24. 24Tool result: gp_hot_spots, step 0. Hot spot analysis: 1 layer saved: Hot spot analysis: Bird surveys (650 features). id 1a6fb48c-a16d-4ea8-b7b2-c8198bec40da:0
25. 25Catalog: Calculate density (operation catalog, gp_calculate_density). Kernel density per square kilometer on a grid. ArcGIS: Calculate Density, Kernel Density. QGIS: native:heatmapkerneldensityestimation. id gp_calculate_density
26. 26Plan: Kernel density of Bird surveys (the Start plan's candidate c_d8957b1a8e52). 650 points in Bird surveys: a density surface shows where they concentrate. id 4467f0bd-c718-4e32-858e-fdc23c1206ed:c_d8957b1a8e52
27. 27Tool result: gp_calculate_density, step 0. Calculate density: 1 layer saved: Calculate density: Bird surveys (699 features). id 36d3dffd-9398-4987-9589-70b885baa263:0
28. 28Catalog: Find point clusters (operation catalog, gp_find_point_clusters). Density-based clusters (DBSCAN, HDBSCAN or OPTICS, optionally space-time) with hulls and noise. ArcGIS: Find Point Clusters, Density-based Clustering. QGIS: native:dbscanclustering, native:stdbscanclustering. id gp_find_point_clusters
29. 29Plan: Cluster points of Bird surveys (the Start plan's candidate c_c55469a968f2). DBSCAN finds dense groups of Bird surveys and separates noise. id 4467f0bd-c718-4e32-858e-fdc23c1206ed:c_c55469a968f2
30. 30Tool result: gp_find_point_clusters, step 0. Find point clusters: 2 layers saved: Find point clusters: Bird surveys (650 features); Find point clusters: cluster hulls (1 feature). id 739720b8-96fb-4b1d-aada-de004de8b3a1:0
31. 31Catalog: Average nearest neighbor (operation catalog, gp_nearest_neighbor_index). Clark-Evans ratio: clustered, dispersed or random. ArcGIS: Average Nearest Neighbor. QGIS: native:nearestneighbouranalysis. id gp_nearest_neighbor_index
32. 32Plan: Nearest neighbor index of Substations (the Start plan's candidate c_dca4b687a126). The average nearest neighbor ratio says whether Substations are clustered, random or dispersed. id 4467f0bd-c718-4e32-858e-fdc23c1206ed:c_dca4b687a126
33. 33Tool result: gp_nearest_neighbor_index, step 1. Average nearest neighbor: done; no map output. id 739720b8-96fb-4b1d-aada-de004de8b3a1:1
34. 34Plan: Nearest neighbor index of Bird surveys (the Start plan's candidate c_de3169143bcf). The average nearest neighbor ratio says whether Bird surveys are clustered, random or dispersed. id 4467f0bd-c718-4e32-858e-fdc23c1206ed:c_de3169143bcf
35. 35Tool result: gp_nearest_neighbor_index, step 2. Average nearest neighbor: done; no map output. id 739720b8-96fb-4b1d-aada-de004de8b3a1:2
36. 36Catalog: Find outliers (operation catalog, gp_outliers). Anselin local Moran’s I: HH, LL clusters and HL, LH outliers. ArcGIS: Find Outliers, Cluster and Outlier Analysis (Anselin Local Moran’s I). id gp_outliers
37. 37Plan: Local morans i of Exclusion zones (the Start plan's candidate c_dacb1f86eb85). Local Moran's I maps clusters and outliers of 'buffer_m'. id 4467f0bd-c718-4e32-858e-fdc23c1206ed:c_dacb1f86eb85
38. 38Tool result: gp_outliers, step 0. Find outliers: 1 layer saved: Find outliers: Exclusion zones (8 features). id 7c480adb-51cb-4581-babf-bcb4de29270c:0
39. 39Plan: Local morans i of Dust storms (the Start plan's candidate c_263cf93eb691). Local Moran's I maps clusters and outliers of 'pm10_peak'. id 4467f0bd-c718-4e32-858e-fdc23c1206ed:c_263cf93eb691
40. 40Tool result: gp_outliers, step 1. Find outliers: 1 layer saved: Find outliers: Dust storms (14 features). id 7c480adb-51cb-4581-babf-bcb4de29270c:1
41. 41Layer: Dust storms. 14 features id aeb5849f-590f-4591-8605-6f335d2d6985
42. 42Plan: Local morans i of Candidate sites (the Start plan's candidate c_d8df894e1c0f). Local Moran's I maps clusters and outliers of 'ghi_kwh_m2_yr'. id 4467f0bd-c718-4e32-858e-fdc23c1206ed:c_d8df894e1c0f
43. 43Tool result: gp_outliers, step 2. Find outliers: 1 layer saved: Find outliers: Candidate sites (30 features). id 7c480adb-51cb-4581-babf-bcb4de29270c:2
44. 44Layer: Candidate sites. 30 features id d70250d1-ef9b-4ddd-affc-598a99acfac1
45. 45Rendering: Map: Summarize within: Exclusion zones id a6518854-804b-4606-8c78-3199b664ea13
46. 46Rendering: Map: Summarize within: Exclusion zones id b8f965ce-a6f5-4252-b925-2dbd5333312e
47. 47Rendering: Map: Summarize within: Exclusion zones id 742ea1fc-81db-4b13-b650-6578d5c142d3
48. 48Rendering: Map: Emerging hot spots: Bird surveys id f6e21899-5e59-44b5-ab88-0cf929b7c84a
49. 49Rendering: Map: Hot spot analysis: Bird surveys id e2916412-7427-4ec7-92e5-508880e59378
50. 50Rendering: Map: Calculate density: Bird surveys id 2f7731ce-3173-4b98-9998-48d6cc94da15
51. 51Rendering: Map: Find point clusters: Bird surveys id fbf99427-4ce6-4f52-85a1-e32846f89b0c
52. 52Rendering: Map: Find point clusters: cluster hulls id 619927ad-be3e-49a4-aa08-fba883794bd1
53. 53Rendering: Map: Exclusion zones by buffer_m id 8ce2fa47-92bc-4870-bcc6-b08df1d28697
54. 54Rendering: Map: Dust storms by pm10_peak id 61c52e96-09d1-4502-95f4-8391fe90a3bc
55. 55Rendering: Map: Candidate sites by ghi_kwh_m2_yr id 51ce9254-115e-470f-b51a-065a90143ec1
56. 56Rendering: Map: Find outliers: Exclusion zones id 8aa42480-628b-456e-8317-a63ecb0a3405
57. 57Rendering: Map: Find outliers: Dust storms id 819c4713-4920-4e42-8580-4a2e18d6730f
58. 58Rendering: Map: Find outliers: Candidate sites id c0057f5e-4079-4e34-9de6-ea0fbb863445
59. 59Rendering: Chart: Met masts over time (installed_year). 1 rows id e00e30b9-644b-46ca-b655-11a6de9b9737
60. 60Rendering: Chart: Dust storms over time (date). 17 rows id 6f802689-3e28-49da-ae1e-e7352a53f3df
61. 61Rendering: Chart: Site irradiance by month over time (month). 49 rows id 1b214c3b-e27f-45d7-b3e9-37007a7bbfe8
62. 62Rendering: Chart: Summarize within: Exclusion zones. 5 rows id 4cc2f224-b101-495c-a15a-534e73cf325f
63. 63Rendering: Chart: Summarize within: Exclusion zones. 5 rows id 606dca1a-e6b3-4dad-9d26-a3ad7f095ac1
64. 64Rendering: Chart: Summarize within: Exclusion zones. 5 rows id d5e79060-d2fb-47a5-9f50-9cb8841d67ab
65. 65Rendering: Chart: Emerging hot spots: Bird surveys. 9 rows id fecf206e-e20a-4599-95cf-bda738a0cfae
66. 66Rendering: Chart: Hot spot analysis: Bird surveys. 13 rows id f43915bf-27f4-479b-93aa-2d0c28bacc51
67. 67Rendering: Chart: Calculate density: Bird surveys. 11 rows id 5f555a81-736e-4cef-810b-a5130a1af5c7
68. 68Rendering: Chart: Find point clusters: Bird surveys. 2 rows id 6c497926-d4b4-4ef7-91e9-b21976c56e1a
69. 69Rendering: Chart: Find point clusters: cluster hulls. 1 rows id 984b2fed-7ac4-4992-977a-54a6579cc974
70. 70Rendering: Chart: Find outliers: Exclusion zones. 8 rows id 3f91f867-567e-4007-a379-87ff1c2ec1f5
71. 71Rendering: Chart: Find outliers: Dust storms. 14 rows id e873d7a4-2ae8-4b97-92b4-45515b61c9e7
72. 72Rendering: Chart: Find outliers: Candidate sites. 30 rows id 78f7a5da-e0e2-4a91-9914-a69b6ea9d7a2
73. 73Rendering: Chart: Find outliers: Dust storms over time. 17 rows id 4568b65f-edd9-4f11-8d2b-857d4a5222a3
74. 74Rendering: Chart: Find point clusters: Bird surveys over time. 90 rows id 62e514e8-affd-48d5-ae06-637bb1e12776
75. 75Rendering: Chart: Hot spot analysis: Bird surveys over time. 90 rows id 3ad09906-2ab7-474e-9978-693d44d049e9
76. 76Dataset: Transmission lines. vector, 2 rows id 81e40578-e11f-4cb0-864c-1046f98bd22f
77. 77Dataset: Substations. vector, 5 rows id 72dd1bf3-452e-470d-be4e-83dcb0b85cab
78. 78Dataset: Exclusion zones. vector, 8 rows id 6cafb793-ef1d-4f2e-bff7-5825f0e576c7
79. 79Dataset: Candidate sites. vector, 30 rows id e6ff1e61-6ff4-4123-91b0-a52d86d2f216
80. 80Dataset: Met masts. vector, 4 rows id 091a72d3-dd86-4a99-a88e-e5d49ad70868
81. 81Dataset: Access roads. vector, 11 rows id 3294b702-ed92-4c49-96ee-c739d04c98f7
82. 82Dataset: Plateau terrain model (DEM). raster, ? rows id 4f619ad8-009f-4070-940a-dc92f2424eda
83. 83Dataset: Land status of sites. table, 30 rows id 8d37fb84-9a33-4798-a0da-2027e38ee102
84. 84Dataset: Site screening memo. document, ? rows id 7f171779-1185-43a2-ac02-a1442e6426c2
85. 85Record: Sample: Renewable energy, Ouarzazate id 8e181d65-6b3c-4526-9cff-cfc25a7f3e07
86. 86Layer: Summarize within: Exclusion zones. 8 features id c30aa790-7338-4207-a249-4ce0e2af6afe
87. 87Layer: Summarize within: Exclusion zones. 8 features id f3d21de8-7328-4a27-aca4-768ddfaee0c5
88. 88Layer: Summarize within: Exclusion zones. 8 features id e4d609b6-cd02-4a55-b91b-7453cea46f48
89. 89Layer: Emerging hot spots: Bird surveys. 156 features id d5d16299-e985-46e4-8b02-95e30d5f391d
90. 90Layer: Hot spot analysis: Bird surveys. 650 features id 40e70c81-7b21-4bc1-95c1-f82d27de5cb5
91. 91Layer: Calculate density: Bird surveys. 699 features id ffc41d66-b6e8-4e66-874f-7f196e443401
92. 92Layer: Find point clusters: Bird surveys. 650 features id 595715b9-59fc-4d3b-9302-d6088eb0b54e
93. 93Layer: Find point clusters: cluster hulls. 1 features id 9d1168bd-46a8-44f2-9151-b8f90e9969ce
94. 94Layer: Find outliers: Exclusion zones. 8 features id 51682486-1e75-4431-9877-84e23905da06
95. 95Layer: Find outliers: Dust storms. 14 features id 30d0b0fa-9659-4bb8-9bc1-dde109be98eb
96. 96Layer: Find outliers: Candidate sites. 30 features id fdc1035f-c5c6-4b5a-9a27-a2211ccf6ee1