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Esri inc random points tool
Random Points Tool, supplied by Esri inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/randomization+tool/random+points+tool/pmc06119120-146-4-7
Average 90 stars, based on 1 article reviews
random points tool - by Bioz Stars, 2026-10
90/100 stars

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Article Title: King Rail ( Rallus elegans ) presence in the Midwestern United States is predicted by local‐scale factors and avian community
Article Snippet: We selected random points, where camera traps were placed, using the random points tool in ArcMap 10.4 (ESRI, Redlands, CA).

Article Title: Modeling Climate Suitability of the Western Blacklegged Tick in California
Article Snippet: We used the random points tool in ESRI ArcMap (Environmental Systems Research Institute; Redlands, CA) to generate a set of background (pseudo-absence) data, at a rate of ~four background points per presence point; points were confined within the state borders, and no background points were located within 1.415 km of each other or of any location where I. pacificus was present. table ft1 table-wrap mode="anchored" t5 caption a7 County No. tick locations % area classified as suitable 90% sensitivity 99% sensitivity Alameda 21 46.28 62.56 Alpine 0 0.00 2.00 Amador 8 63.62 76.65 Butte 6 51.29 63.42 Calaveras 14 73.06 89.55 Colusa 6 26.20 49.05 Contra Costa 17 39.40 53.77 Del Norte 4 11.30 75.10 El Dorado 25 46.60 68.07 Fresno 0 8.61 30.10 Glenn 2 11.32 57.86 Humboldt 18 33.32 85.31 Imperial 0 0.00 0.00 Inyo 1 0.00 0.00 Kern 2 0.00 18.57 Kings 1 0.00 9.51 Lake 28 66.37 83.89 Lassen 1 0.00 0.01 Los Angeles 30 23.18 47.31 Madera 8 19.02 47.21 Marin 14 71.03 71.04 Mariposa 14 59.32 79.93 Mendocino 62 75.34 90.74 Merced 0 0.00 33.16 Modoc 0 0.00 0.04 Mono 0 0.00 0.00 Monterey 12 18.45 83.71 Napa 11 74.94 74.94 Nevada 19 48.60 57.36 Orange 7 25.80 40.31 Placer 20 31.74 50.86 Plumas 3 3.19 33.21 Riverside 10 7.18 20.71 Sacramento 5 9.44 31.26 San Benito 4 4.12 82.97 San Bernardino 19 1.31 4.21 San Diego 10 16.66 59.40 San Francisco 0 5.26 5.26 San Joaquin 5 1.17 20.98 San Luis Obispo 6 18.21 81.90 San Mateo 15 66.89 66.89 Santa Barbara 18 32.12 87.12 Santa Clara 15 57.56 71.62 Santa Cruz 20 82.62 82.62 Shasta 36 41.77 75.01 Sierra 4 5.29 26.56 Siskiyou 7 6.05 45.62 Solano 5 19.87 31.14 Sonoma 13 75.49 75.52 Stanislaus 3 4.19 47.75 Sutter 2 1.44 15.88 Tehama 5 51.36 80.46 Trinity 21 22.37 64.66 Tulare 8 5.18 31.18 Tuolumne 9 41.50 54.83 Ventura 12 51.58 74.11 Yolo 4 27.39 35.90 Yuba 11 54.92 64.48 Open in a separate window Percentage of Californian counties classified as forest, grass, scrub-shrub or riparian and estimated to be climatically suitable for I. pacificus by three or more models having sensitivities of 90% or 99%

Article Title: Modeling Climate Suitability of the Western Blacklegged Tick in California
Article Snippet: We used the random points tool in ESRI ArcMap (Environmental Systems Research Institute; Redlands, CA) to generate a set of background (pseudo-absence) data, at a rate of ~four background points per presence point; points were confined within the state borders, and no background points were located within 1.415 km of each other or of any location where I. pacificus was present. table ft1 table-wrap mode="anchored" t5 caption a7 County No. tick locations % area classified as suitable 90% sensitivity 99% sensitivity Alameda 21 46.28 62.56 Alpine 0 0.00 2.00 Amador 8 63.62 76.65 Butte 6 51.29 63.42 Calaveras 14 73.06 89.55 Colusa 6 26.20 49.05 Contra Costa 17 39.40 53.77 Del Norte 4 11.30 75.10 El Dorado 25 46.60 68.07 Fresno 0 8.61 30.10 Glenn 2 11.32 57.86 Humboldt 18 33.32 85.31 Imperial 0 0.00 0.00 Inyo 1 0.00 0.00 Kern 2 0.00 18.57 Kings 1 0.00 9.51 Lake 28 66.37 83.89 Lassen 1 0.00 0.01 Los Angeles 30 23.18 47.31 Madera 8 19.02 47.21 Marin 14 71.03 71.04 Mariposa 14 59.32 79.93 Mendocino 62 75.34 90.74 Merced 0 0.00 33.16 Modoc 0 0.00 0.04 Mono 0 0.00 0.00 Monterey 12 18.45 83.71 Napa 11 74.94 74.94 Nevada 19 48.60 57.36 Orange 7 25.80 40.31 Placer 20 31.74 50.86 Plumas 3 3.19 33.21 Riverside 10 7.18 20.71 Sacramento 5 9.44 31.26 San Benito 4 4.12 82.97 San Bernardino 19 1.31 4.21 San Diego 10 16.66 59.40 San Francisco 0 5.26 5.26 San Joaquin 5 1.17 20.98 San Luis Obispo 6 18.21 81.90 San Mateo 15 66.89 66.89 Santa Barbara 18 32.12 87.12 Santa Clara 15 57.56 71.62 Santa Cruz 20 82.62 82.62 Shasta 36 41.77 75.01 Sierra 4 5.29 26.56 Siskiyou 7 6.05 45.62 Solano 5 19.87 31.14 Sonoma 13 75.49 75.52 Stanislaus 3 4.19 47.75 Sutter 2 1.44 15.88 Tehama 5 51.36 80.46 Trinity 21 22.37 64.66 Tulare 8 5.18 31.18 Tuolumne 9 41.50 54.83 Ventura 12 51.58 74.11 Yolo 4 27.39 35.90 Yuba 11 54.92 64.48 Open in a separate window Percentage of Californian counties classified as forest, grass, scrub-shrub or riparian and estimated to be climatically suitable for I. pacificus by three or more models having sensitivities of 90% or 99% Climate Data Sources Thirty-five candidate climatic predictor variables were selected based on our knowledge of the biological and ecological requirements of I. pacificus ( ).

Article Title: Density and nest survival of golden‐cheeked warblers: Spatial scale matters
Article Snippet: Conservation and management plans often rely on indicators such as species occupancy or density to define habitat quality, ignoring factors that influence reproductive success, and potentially limiting conservation achievements.. We examined relationships between predicted density and nest survival with environmental features at multiple spatial scales for the golden-cheeked warbler (Setophaga chrysoparia) in a large preserve within an urbanizing landscape.. Larger-scale features of the forest and landscape composition best predicted density, whereas small-scale vegetation features best predicted nest success.

Article Title: Spatial distribution of potential wild turkey nest predators in west‐central Louisiana
Article Snippet: Funding information Louisiana Department of Wildlife and Fisheries; School of Renewable Natural Resources; Louisiana State University Agricultural Center; Warnell School of Forestry and Natural Resources at the University of Georgia Abstract Wild turkey nest success is variable spatially and temporally, with predation being the primary driver of nest loss.. Historically, characteristics of nest site vegetation have been used to predict the probability of a nest being successful, a corollary to not being preyed upon.. Implicit in nest success studies is that the density, distribution, and habitat preferences of predator species, relative to wild turkey nest distribution, drive the predation risk of nests on the landscape.

Article Title: Western chimpanzees (Pan troglodytes verus) access a nutritionally balanced, high energy, and abundant food, baobab (Adansonia digitata) fruit, with extractive foraging and reingestion.
Article Snippet: Department of Anthropology, Purdue University, West Lafayette, Indiana, USA Department of Anthropology, Hunter College of the City University of New York, New York, New York, USA New York Consortium in Evolutionary Primatology, New York, New York, USA Department of Evolutionary Ecology, Leibniz Institute for Zoo and Wildlife Research, Berlin, Germany Department of Anthropology, Texas State University, San Marcos, Texas, USA

Article Title: Applying a Low Cost, Mini Remotely Operated Vehicle (ROV) to Assess an Ecological Baseline of an Indigenous Seascape in Canada
Article Snippet: For the underwater transect aspect of the project, we used the random points tool in ArcMap 10.6. (ESRI, 2011) to generate stratified random starting points.

Sampling:

Article Title: Computer Corner: A GIS-Based Technique for Randomly Selecting Sample Units on the Landscape
Article Snippet: .. The script “Random points in polygon” (Cederholm 1999) was downloaded from the Environmental Systems Research Institute (ESRI) web site (http://gis.esri.com/arcscripts/scripts.cfm) in order to generate the sampling point locations. ..



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