Plant Mapping System Using Remote Sensing and Route Generation
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Solution Overview
Problem
Environmental impact studies, particularly in non-urban environments like forests, face challenges in efficiently identifying and sampling plant species due to the lack of connecting roads and obstacles, which increases costs, time, and risks in data collection.
Innovation Solution
A system utilizing digital image processing and automatic routing to characterize flora ecosystems by identifying homogenous and heterogenous flora clusters through remote sensing images, generating optimal routes for data collection, and identifying plant species through morphological analysis of foliar images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual plant identification and sampling is performed in non-urban environments, then plant species can be identified, but the time, effort, and costs increase significantly due to lack of roads and obstacles
Solution Approach 1:
The system performs preliminary actions by using remote sensing to pre-identify and locate plant clusters before field data collection. This allows researchers to plan their routes and sampling locations in advance, avoiding time-consuming manual searching in the field while maintaining accurate plant identification through the integrated system.
Solution Approach 2:
The patent introduces an intermediary system that combines remote sensing technology with route generation algorithms. This intermediary layer processes satellite or aerial imagery to identify plant clusters, then generates optimized routes to these locations, serving as a mediator between the research objective and the physical fieldwork, thereby reducing time and effort.
2Quantity of substance
If researchers access remote plant clusters, then plant samples can be collected, but risks and costs increase due to obstacles such as rivers and mountains
Solution Approach 1:
The system performs preliminary route planning and risk assessment using remote sensing data before field collection. By pre-identifying accessible plant clusters and generating optimized routes that avoid or minimize exposure to obstacles like rivers and mountains, the system reduces risks to researchers while ensuring adequate plant sample collection.
Solution Approach 2:
The system enables self-service by automatically generating safe routes and identifying accessible plant clusters without requiring researchers to manually assess terrain risks. The algorithm analyzes the environment and autonomously determines optimal paths that minimize exposure to harmful factors while still allowing sample collection.
3Measurement precision
If comprehensive flora characterization is performed, then environmental impact assessment is improved, but costs and time requirements increase
Solution Approach 1:
The system performs preliminary identification of plant clusters and generation of optimized sampling routes before fieldwork begins. This preliminary characterization using remote sensing allows the team to focus field efforts on specific, pre-identified locations, maintaining comprehensive flora assessment accuracy while significantly improving productivity by eliminating random or inefficient searching.
Solution Approach 2:
The patent segments the study area into distinct plant clusters identified through remote sensing imagery. By dividing the comprehensive flora characterization task into discrete, geographically separated clusters with optimized routes between them, the system maintains thorough assessment coverage while improving productivity through structured, efficient fieldwork organization.
Data Source
AI summary
The present invention relates to a system and method for mapping of plants. Homogenous and heterogeneous flora areas called clusters are identified in remote sensing images and routes to the plant clusters are generated. The plants are classified using morphological data from foliar images of plants present in the clusters.