AI Spatial Analysis

This project requires analysis of aerial imagery of a major metropolitan city and surrounding area to classify ground by type, looking particularly for water demand, and water absorption / runoff. Our data set consists of a number of images taken from overhead / aerial drones. There are two use cases your solution must solve for.

Use case 1: swimming pools

For each image we provide you, your solution must identify the unique number of swimming pools that are contained within this tile. It is desirable if you can also approximate the total area of the swimming pools within the image. It is highly desired that your solution can differentiate swimming pools as distinct from other open water areas such as lakes, rivers etc. It is highly desired your solution outputs a copy of each input image with identified swimming pools highlighted with a coloured border around the contour of the swimming pool, for verification purposes. We expect an accuracy rate of >= 95% compliance with human verification of number of swimming pools.

Use case 2: terrain types to determine water absorption

Each image in the data set will be processed as follows: you will need to subdivided it into smaller tiles, with the subdivision size controlled by a parameter in your solution (e.g. subdivide into a 5 x 5 grid, or subdivide into a 20 x 10 grid, for instance). For each tile within the image, your solution must determine whether it is predominantly natural or man-made. Natural would include: trees, bushes, grass, dirt, agriculture (fields) - anything natural and organic. Man-made would include "hard" surfaces, i.e. roads, footpaths, houses / roofs, industrial buildings. Most tiles will contain both natural and hard textures; we only need you to determine which is the most present within the tile (e.g. >= 50% coverage by area). We will provide you with a training set where some sample tiles have been subdivided and annotated by a human into natural or hard categories. We accept there will be some approximation or inaccuracy in the determination, however we will compare the output of your solution to a test data set and compare results between the human and your script. An acceptable accuracy rate is agreement with the human markup >= 90% of the time.

Your solution should ignore areas of ocean, if present in the images. Most images will not contain ocean.

Your solution should accept a batch of images and output a CSV file that states the original input image filename, index of X and Y offsets for the subdivided tiles, and which category the tile belongs to (ocean, natural, hard). A second CSV file should be produced that states the original input image filename, the number of swimming pools identified in the image, and optionally an approximation of total area of the swimming pools. Area can be calculated based upon pixel dimensions (e.g. 10 pixels by 20 pixels would have an area of "200" - you do not need to calculate what this area represents in real world terms, as the level of zoom of the input tiles may vary).

We would be interested in a discussion of your recommended approach, but we would prefer your solution to be developed in Python 3.7 or higher and ideally uses OpenCV for image analysis. Code should be clear with sufficient (not exhaustive) documentation, in English. A requirements file for installation of Python libraries via pip should be included in your solution.

Please provide your final and fixed price for this project., and expected duration to complete. We hope this work can be completed within one month. Successful completion of the project will be determined by a working solution that meets an accuracy target of 95% or higher for swimming pools, and 90% or higher compliance with human markup of tiles for terrain types, as described above. Failure to deliver with the stated success rates or on the agreed time will result in an unsuccessful project and will forfeit the associated payment

Skills: OpenCV, Python

See more: geospatial artificial intelligence, geoai, geo ai, esri ai, geospatial machine learning, cincinnati, spatial ai slam, spatial ai careers

About the Employer:
( 3 reviews ) Ulladulla, Australia

Project ID: #23965406

Awarded to:


My background lies in Systems Engineering with a focus on Satellite Systems (Master's degree from TU Delft, the Netherlands), where I built a strong foundation in Physics, CS and Applied Mathematics. Additionally, I ha More

$6000 AUD in 35 days
(10 Reviews)

14 freelancers are bidding on average $7798 for this job


Dear Employer, Hope you are doing great...!! I have read your job posting and found our skills best suited for the project scope and I have checked the ppt too. I would be glad if you connect with us and lets discuss More

$10000 AUD in 90 days
(13 Reviews)

Hi, I've read your job post extremely carefully and I am sure I can exceed your expectations. With the background in development with python I have been building various projects with Computer vision and Machine learni More

$5000 AUD in 15 days
(25 Reviews)

Hello. I just read your job posting and it sounds like you are looking for an expert in Computer Vision and Machine Learning. First of all, please check my channel: [login to view URL] More

$7500 AUD in 7 days
(6 Reviews)

Hello! I'd like to develop satelite imagery segmentator. I'm familiar with related deep learning architectures as well as have hands on experience on datasets annotation for the task. I'll do the job blazingly fast. Pl More

$6667 AUD in 1 day
(6 Reviews)

Hi, I have worked with OpenCV for image detection and recognition and can develop a system that will identify, to the accuracy of 95%, swimming pools and land surface cover including the area covered and in the case o More

$7500 AUD in 7 days
(9 Reviews)

Dear client Seeing your past reviews, I felt you are a cool client and so I am sending proposal to you like this. Meanwhile, I am very sad. There are 50+ volunteers with good reviews to do your project. In spite of bad More

$7500 AUD in 30 days
(1 Review)

Thank you for your posting job. I read your project description and I'm very interested in this project. As you can see via my profile, I have expertise skills to build C#& C++. If you hire me for this project, you wil More

$8000 AUD in 20 days
(1 Review)

Greetings!Much experience in Image processing/ML/DL with Python/R/[login to view URL],Pattern recognition,RNN with sophisticated python skills , specialized in tensorflow/keras/pytorch/scipy/pyteserract,etc. I have fully unders More

$7500 AUD in 20 days
(5 Reviews)

I WOULD LIKE TO PLACE MY BID FOR YOUR PROJECT NAMED AI Spatial Analysis I develop mobile Applications (iOS / Android) with backend. I always make sure that the client-side requirements are very clear. 1. Bug fixing, More

$7500 AUD in 50 days
(1 Review)

Hello, We have 10+ years of experience in this field and have worked with large enterprise clients like Johnson & Johnson Data Science, [login to view URL] rated #1 by NIST for face recognization, Remarkin E-Learning Pvt. Ltd, Cr More

$9000 AUD in 13 days
(0 Reviews)

Hello there, Is it possible to give you a budget before we can discuss these 2 Use cases by explaining our approach and solutions in the chat? We have experience in python and his libraries like OpenCV, TensorFlow, a More

$7500 AUD in 35 days
(0 Reviews)

Hi, I can create a system that uses aerial imagery to identify a set of objects or an object from a given scenarios using python and open CV. I have gone through the provided use cases. The devised solution will acce More

$12000 AUD in 90 days
(0 Reviews)

Hi, This is from BEAS Consultancy and Services Pvt Ltd ( [login to view URL] ). We are an India based CMMI level 5 and ISO Certified  Organization. We produce quality and Cost-effective solution for our inte More

$7500 AUD in 40 days
(0 Reviews)