General Studies 2025 GS Paper I 15 marks 250 words Compulsory How

Q15

How can Artificial Intelligence (AI) and drones be effectively used along with GIS and RS techniques in locational and areal planning ? (Answer in 250 words) 15

हिंदी में प्रश्न पढ़ें

स्थानीय और क्षेत्रीय योजना बनाने में जी.आई.एस. और आर.एस. तकनीकों के साथ कृत्रिम बुद्धिमत्ता (ए.आई.) और ड्रोन का प्रभावी ढंग से उपयोग कैसे किया जा सकता है ? (उत्तर 250 शब्दों में दीजिए) 15

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Directive word: How

This question asks you to how. The directive word signals the depth of analysis expected, the structure of your answer, and the weight of evidence you must bring.

See our UPSC directive words guide for a full breakdown of how to respond to each command word.

How this answer will be evaluated

Approach

The directive 'How' demands a methodical explanation of mechanisms and processes through which AI-drones-GIS-RS integration enables planning. Structure: brief introduction defining the technology convergence → body with 2-3 thematic areas (urban/rural/regional planning) showing specific applications → conclusion with challenges and way forward. Maintain 250-word precision with technical clarity.

Key points expected

AI-powered drone imagery processing for real-time land use mapping and change detection in urban sprawl management
Integration of Remote Sensing (RS) satellite data with GIS layers for terrain analysis, slope assessment and disaster-prone zone identification
Machine learning algorithms on GIS platforms for predictive modeling in infrastructure siting (highways, reservoirs, industrial corridors)
Drone-based LiDAR and photogrammetry for precision agriculture planning and watershed management in rural areas
AI-driven spatial analytics for smart city projects (e.g., MoHUA's Smart Cities Mission) and AMRUT scheme implementation
Challenges: data security, digital divide, regulatory framework (DGCA drone rules), interoperability issues between platforms

Evaluation rubric

Dimension	Weight	Max marks	Excellent	Average	Poor
Demand-directive understanding	20%	3	Answer explicitly addresses 'how' by detailing operational workflows, integration mechanisms and sequential processes rather than merely listing technologies; shows clear grasp that locational planning requires spatial precision while areal planning demands regional synthesis	Partially addresses 'how' with some process description but mixes it with 'what' and 'why'; technology listing dominates over mechanism explanation	Misinterprets directive as 'what' or 'describe'; provides only definitions of AI, drones, GIS, RS without explaining their integrated application in planning
Content depth & accuracy	20%	3	Demonstrates accurate technical understanding: AI as predictive analytics layer, drones as data acquisition platforms, GIS as spatial database, RS as satellite-based monitoring; correctly distinguishes locational (site-specific) vs areal (regional) planning applications	Generally accurate but superficial coverage; some confusion between GIS and RS functions or treats AI-drones as separate rather than integrated system; limited technical precision	Significant technical errors: conflates GIS with GPS, treats drones only as delivery devices not data platforms, or presents AI as standalone without spatial context; factual inaccuracies about Indian planning frameworks
Structure & flow	20%	3	Logical progression from data acquisition (drones+RS) → processing/analysis (AI+GIS) → planning outputs; clear thematic organization (urban/rural/disaster); smooth transitions; adheres to 250-word limit with balanced sections	Adequate structure but uneven weightage; either introduction too long or conclusion missing; some thematic jumping; word management issues with either underutilization or exceeding limit	Disorganized or haphazard arrangement; no clear introduction-body-conclusion; bullet points without integration; severe word management failure (sub-150 or over-300 words)
Examples / case-law / data	20%	3	Specific Indian examples: SVAMITVA scheme (drone-based rural property mapping), ISRO's Bhuvan/NDEM platforms, AI-powered flood forecasting by CWC, smart city GIS command centers (Surat, Pune), NDMA's drone use in disaster damage assessment; recent data mentions (2023-24)	Generic or outdated examples; only international references without Indian context; mentions schemes without linking to technology integration; no specific data or years	No examples at all; or irrelevant examples (military drone usage, commercial AI applications); factually wrong scheme attributions
Conclusion & analytical edge	20%	3	Balanced conclusion acknowledging challenges (digital divide, data sovereignty, DGCA regulatory constraints) with forward-looking suggestions (capacity building, open data policies, ethical AI frameworks); shows critical awareness that technology is enabler not substitute for participatory planning	Routine summary of points without critical reflection; generic 'way forward' without specific recommendations; either overly optimistic or purely pessimistic tone	No conclusion; abrupt ending; or irrelevant philosophical statement; conclusion contradicts body content; missing any critical or forward-looking element

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