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Master the ArcGIS ecosystem with this definitive collection of prompts designed to maximize your technical efficiency. From advanced automation with Python to critical BIM data integration and high-precision spatial analysis, this resource transforms complex workflows into agile, streamlined processes. It is the essential tool for GIS analysts seeking to lead in decision making based on geographic data. Each prompt has been structured following instructional design standards to guarantee immediate results and high professional quality. Optimize your geodatabase management, perfect your visual cartography, and exploit the potential of ArcGIS Online with ultra-specific technical instructions that eliminate ambiguity and enhance innovation in each territorial project.
Acts as a specialist in Remote Sensing and Advanced Spatial Analysis with deep proficiency in the ArcGIS Pro suite and the ArcPy processing engine. Your objective is to design a comprehensive technical protocol for the **Raster Noise Filtering** process applied to a [Product Type: DEM/MDT/Multispectral Image] with a resolution of [Resolution: 30m/12.5m/5m]. The purpose is to eliminate systematic artifacts, salt-and-pepper noise, and data anomalies that compromise the accuracy of derived analyzes such as the generation of contour lines, slope maps, or land cover classifications. Start the analysis by describing the application of neighborhood spatial filters using the 'Focal Statistics' tool. You must justify the choice between a [Statistics: Median/Mean/Majority] filter based on the preservation of the edges and the geomorphological characteristics of the terrain. Explains how a [Dimensions: 3x3/5x5] kernel influences surface smoothing and what the risks of overfiltering are in areas of complex topography or heterogeneous textures. Subsequently, integrate frequency domain filtering techniques or the use of classification cleaning tools such as 'Majority Filter' and 'Boundary Clean' if the raster is categorical in nature. Details the workflow for specific noises in Digital Elevation Models, such as the elimination of 'pits' and 'peaks' using tools from the Spatial Analyst toolbox (Hydrology tools), ensuring the hydrological integrity of the final model. To conclude, generate a Python script using the ArcPy module that automates the execution of these filters. The script must include the definition of the working environment, the management of Spatial Analyst extensions, the execution of the selected filter and a final validation step using a 'Raster Calculator' operation to perform an algebraic subtraction (Original - Filtered) that allows spatially evaluating the magnitude of the noise removed without affecting the base signal of the [Project Name]. If any key information needed to fill the bracketed fields is missing, ask me the necessary questions before answering.
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Acts as a Senior Consultant in Geospatial Intelligence and Advanced Logistics. Your objective is to design a complete strategic and technical framework for the optimization of transportation routes of [Type of Cargo] in the area of [Geographic Location], using the network analysis capabilities of ArcGIS Pro. The central problem lies in minimizing the annual operating costs, currently estimated in [Estimated Amount], by deeply restructuring the distribution network that connects [Number of Warehouses] logistics centers with more than [Number of Delivery Points] final destination points, facing challenges of urban congestion and access restrictions. To begin, it exhaustively details the spatial data preparation phase. I need you to describe how to structure a robust 'Network Dataset' that integrates not only road geometry, but also critical impedance variables such as dynamic speed limits, complex turning restrictions and historical traffic data. Explains the technical process for configuring road hierarchy attributes that ensure heavy vehicles in the [Company Name] fleet avoid sensitive residential areas or bridges with height and weight restrictions specific to [Vehicle Technical Specifications]. In the advanced modeling phase, it develops a solution based on the 'Vehicle Routing Problem' (VRP). The model must integrate multiple delivery time windows ([Delivery Schedule] SLA), heterogeneous loading capacities and the need to include mandatory rest times for drivers according to [Country/Region] regulations. Describes how to adjust the 'Order Clusters' and 'Max Violation Time' parameters to maximize the density of stops per route, minimizing empty mileage and fuel consumption in the [Area of Interest] zone. Provides an automation proposal using the ArcPy Python library. The script must be able to iterate over a daily order table in [File Format], geocode the addresses using a custom locator, run the VRP solver, and export the results to a spatial feature layer and an analytical report. Make sure your code considers exception handling for addresses with low geocoding accuracy or routes that exceed the maximum threshold of [Maximum Hours per Shift] daily driving hours. Finally, it defines the structure of an ArcGIS Dashboard for post-optimization monitoring. It proposes five critical geospatial KPIs, such as 'Route Efficiency Index', 'Avoided CO2 Emissions' and 'Time Window Compliance Rate'. The final objective is to project a roadmap that allows achieving a reduction of [Expected Percentage of Improvement]% in transit times and a tangible operational savings of [Percentage of Savings]% in the first semester of technological implementation. If any key information needed to fill the bracketed fields is missing, ask me the necessary questions before answering.
Acts as a Senior Geospatial Automation Engineer with specialization in the Esri ecosystem and developing advanced integrations. Your goal is to develop a professional-grade Python script using the **ArcGIS Python API** and a micro-framework (such as Flask or FastAPI) to act as a listener for Webhooks sent by **ArcGIS Survey123**. The script must be able to intercept the JSON payload sent after a form submission, validate the integrity of the data, and execute a series of automated geoprocessing and data updating tasks in real time. The system must process the variables sent by the webhook, focusing especially on the extraction of the geometry (latitude and longitude) and the attributes contained in the `feature` dictionary. You must implement logic that, upon receiving a submission from [ID_DEL_FORMULARIO], automatically performs a spatial intersection analysis against a layer of [ZONAS_DE_INTERES] to determine which jurisdiction the captured point belongs to. Once this information is obtained, the script must update the original Feature Layer of the survey or an external table in ArcGIS Online/Enterprise using the `edit_features()` method of the `arcgis.features` module. Additionally, the prompt should request the implementation of a smart notification system. If the value of a specific field like [ESTADO_CRITICO] meets an alert condition, the script should format a report in HTML and send it via a messaging API (such as the `smtplib` module for mail or a Slack/Teams integration). It is imperative that your code handles authentication securely, preferably using OAuth2 or saved ArcGIS Pro profiles using `GIS('pro')` or `GIS([URL_PORTAL], [USUARIO], [CONTRASENA])`. Finally, the generated code must be resilient and scalable. Includes detailed `try-except` blocks to capture network errors, API timeouts, or unexpected JSON schemas. Make sure the script includes a professional log that stores every successful or failed transaction, allowing for complete auditing of automation operations. The end result should be a 'ready-to-deploy' solution that dramatically optimizes the workflow between collecting data in the field with Survey123 and making decisions in ArcGIS Pro. If any key information needed to fill the bracketed fields is missing, ask me the necessary questions before answering.
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Based on 10 reviews
Best purchase I made this month. The prompts are really well thought out and the effort shows. I'll buy again without hesitation.
Exceeded my expectations. They saved me hours of work in the first week. An investment that pays for itself.
Worth every penny. The index is organized and I find what I need instantly. I'll buy again without hesitation.
Best purchase I made this month. They work just as well in ChatGPT and Claude. One hundred percent recommended.
I was impressed by the quality. They're easy to adapt to my case by just changing the fields. I'll buy again without hesitation.
I was impressed by the quality. They're easy to adapt to my case by just changing the fields. An investment that pays for itself.
I was impressed by the quality. The quality of the answers I get improved a lot. One hundred percent recommended.
I was impressed by the quality. They saved me hours of work in the first week. Totally recommend them.
Happy with the purchase. The prompts are useful and practical. I'd buy again.
Good value for money. The prompts are useful and practical. Came close to a five.