Coarse Satellite Field Boundary Detection With GIS Refinement

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing methods struggle to accurately detect small agriculture field boundaries using coarse resolution satellite data due to limited information content, and high-resolution data is costly and resource-intensive.

Innovation Solution

A multi-layer crop segmentation approach using coarse resolution satellite data combined with GIS topology operations to refine field boundaries, incorporating soil, crop, and within-crop segmentation, followed by raster-to-vector conversion and error removal, enabling precise delineation of small field boundaries.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If high resolution satellite images are used for field boundary detection, then measurement precision of field boundaries is improved, but resource consumption (processing power, memory, time) and cost increase significantly

Engineering Contradiction:

Improvefield boundary detection accuracyVSAvoidresource consumption

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent segments the field boundary detection process into multiple layers: coarse resolution satellite data for initial boundary identification, followed by refinement using additional data sources. This segmentation allows the system to process only relevant areas at high detail levels, reducing overall resource consumption while maintaining detection accuracy for small fields

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent merges coarse resolution satellite data with other data sources (such as GIS data, terrain information, and contextual data) to compensate for the lower resolution. By combining multiple data sources, the system achieves accurate field boundary detection without relying solely on expensive high-resolution satellite imagery

Inventive Principle:

Principle #5Merging (Combining)

2Productivity

If coarse resolution satellite data is used for field boundary detection, then resource consumption and cost are reduced, but measurement precision deteriorates especially for small fields

Engineering Contradiction:

Improveresource efficiencyVSAvoidfield boundary detection accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent applies local quality by focusing computational resources on areas where field boundaries are likely to occur, such as areas with agricultural characteristics. Instead of uniformly processing all coarse resolution data at high detail, the system identifies and concentrates processing efforts on relevant local areas, improving precision where needed while maintaining resource efficiency elsewhere

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent transitions from two-dimensional coarse resolution satellite imagery to three-dimensional spatial understanding by incorporating elevation data, terrain information, and contextual layers. This dimensional enrichment allows the system to detect field boundaries in coarse data by utilizing vertical and contextual dimensions rather than relying solely on horizontal resolution

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

3Measurement precision

If manual updating of cadastral maps is performed, then measurement precision of land boundaries is maintained, but time consumption and labor requirements increase significantly

Engineering Contradiction:

Improvecadastral map accuracyVSAvoidupdate time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent implements self-service by enabling the system to automatically detect, process, and update field boundary information without human intervention. The automated pipeline processes satellite data, identifies boundaries, validates results, and updates cadastral maps independently, eliminating the need for manual field visits and manual map updating while maintaining high precision

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual process of field boundary surveying and map updating with an automated computational system. Instead of physical field visits and manual drafting, the system uses satellite image processing algorithms, automated boundary detection, and digital map updating mechanisms to achieve the same or better precision much faster

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentEP4246462B1Method and system for detection of field boundaries using coarse resolution satellite data and gis

Publication Date: 2025.07.30 TATA CONSULTANCY SERVICES LTD

Figure 1
Figure 2

AI summary

Coarse resolution satellite data has limited information content of land captured in the images and small area field boundary detection is technically challenging. Embodiments of the present disclosure provide a method and system for detection of field boundaries using coarse resolution satellite data and GIS. Multi-layer crop segmentation approach is used over RoI, wherein agricultural land related segments are derived from a soil layer, a temporal stack for a current season and a temporal change layer from the coarse resolution satellite data of the RoI. Segmentation based on different aspects captures various details at each segmentation layer. The segments are then combined, which aggregates all information related to the land to accurately detect the field boundaries in the RoI. The field boundaries are further refined using GIS topology operations. Baseline cadastral maps are updated using information from maps generated using refined field boundaries identified in real time for each season.