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Scholarships & exams

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+91 88943 57155
Pune, Maharashtra, India

Duration

4 Years

Land Management

Institute of Land and Disaster Management
Duration
4 Years
Land Management UG OFFLINE

Duration

4 Years

Land Management

Institute of Land and Disaster Management
Duration
Apply

Fees

₹8,50,000

Placement

92.0%

Avg Package

₹8,00,000

Highest Package

₹18,00,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Land Management
UG
OFFLINE

Fees

₹8,50,000

Placement

92.0%

Avg Package

₹8,00,000

Highest Package

₹18,00,000

Seats

120

Students

1,200

ApplyCollege

Seats

120

Students

1,200

Curriculum

Course Structure Overview

The Land Management program at Institute of Land and Disaster Management is structured over 8 semesters, with a blend of core courses, departmental electives, science electives, laboratory sessions, and project-based learning. The curriculum is designed to provide students with a comprehensive understanding of land use systems, environmental challenges, and technological solutions.

SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
1LM-101Introduction to Land Management3-0-0-3-
1LM-102Fundamentals of Environmental Science3-0-0-3-
1LM-103Basic Surveying Techniques2-0-2-4-
1LM-104Introduction to GIS2-0-2-4-
1SC-101Physics for Engineers3-0-0-3-
1SC-102Chemistry for Engineers3-0-0-3-
1SC-103Mathematics I4-0-0-4-
2LM-201Remote Sensing and Image Analysis3-0-0-3LM-104
2LM-202Soil Classification and Management3-0-0-3-
2LM-203Urban Land Use Planning3-0-0-3-
2LM-204Environmental Impact Assessment3-0-0-3-
2SC-201Mathematics II4-0-0-4SC-103
2SC-202Physics Lab0-0-2-2-
3LM-301Advanced GIS Applications3-0-0-3LM-104
3LM-302Climate Change and Land Degradation3-0-0-3-
3LM-303Disaster Risk Management3-0-0-3-
3LM-304Sustainable Land Use Practices3-0-0-3-
3DE-301GIS Programming with Python2-0-2-4LM-104
3DE-302Remote Sensing Data Processing2-0-2-4-
4LM-401Land Use Policy and Regulation3-0-0-3-
4LM-402Community-Based Land Management3-0-0-3-
4LM-403Land Information Systems3-0-0-3LM-104
4LM-404Sustainable Agriculture Practices3-0-0-3-
4DE-401Machine Learning for Land Management2-0-2-4SC-201
4DE-402Urban Resilience Planning2-0-2-4-
5LM-501Research Methodology in Land Management3-0-0-3-
5LM-502Advanced Remote Sensing Techniques3-0-0-3LM-201
5LM-503GIS-Based Spatial Modeling3-0-0-3LM-301
5DE-501Big Data Analytics for Environmental Monitoring2-0-2-4DE-301
5DE-502Land Use Planning and Policy Simulation2-0-2-4-
6LM-601Field Research and Data Collection3-0-4-7-
6LM-602Capstone Project I3-0-0-3-
6DE-601Internship in Land Management0-0-4-4-
7LM-701Capstone Project II3-0-0-3-
7DE-701Advanced Topics in Land Use Planning2-0-2-4-
7DE-702Environmental Impact Assessment and Mitigation2-0-2-4-
8LM-801Final Year Thesis3-0-0-3-
8DE-801Professional Internship and Industry Exposure0-0-4-4-

Advanced Departmental Elective Courses

The Land Management program includes a range of advanced departmental electives designed to deepen students' expertise in specialized areas. These courses are typically offered in the third and fourth years, allowing students to build upon foundational knowledge while exploring emerging trends and applications.

GIS Programming with Python (DE-301)

This course introduces students to programming languages such as Python and their application in GIS environments. Students learn how to automate data processing tasks, perform spatial analysis using libraries like GeoPandas and Shapely, and develop custom tools for land management applications. The course emphasizes hands-on coding exercises and real-world case studies.

Remote Sensing Data Processing (DE-302)

This elective delves into the technical aspects of processing satellite and aerial imagery for land use and environmental monitoring. Students gain experience with tools like ENVI, ERDAS IMAGINE, and QGIS, learning how to extract meaningful information from remote sensing data and apply it in land management contexts.

Machine Learning for Land Management (DE-401)

This course explores the application of machine learning algorithms to solve complex problems in land management. Topics include supervised and unsupervised learning, neural networks, and deep learning techniques for land classification, change detection, and predictive modeling.

Big Data Analytics for Environmental Monitoring (DE-501)

As environmental data becomes increasingly voluminous and complex, this course teaches students how to leverage big data technologies for monitoring and analyzing land conditions. Students learn about Hadoop, Spark, and cloud-based platforms used in environmental research.

Land Use Planning and Policy Simulation (DE-502)

This course focuses on using computational models to simulate land use scenarios and evaluate policy interventions. Students develop skills in scenario planning, stakeholder engagement, and policy impact assessment.

Field Research and Data Collection (LM-601)

This intensive field-based course provides students with practical experience in collecting and analyzing spatial data using modern tools. Students conduct surveys, gather soil samples, and use GPS devices to map land features.

Capstone Project I (LM-602)

The first phase of the capstone project involves selecting a research topic, conducting literature reviews, and developing a methodology for data collection and analysis. Students work closely with faculty mentors to refine their projects.

Advanced Topics in Land Use Planning (DE-701)

This elective covers advanced concepts in land use planning, including smart city development, green infrastructure, and sustainable transportation systems. Students engage in critical discussions about urban design and policy frameworks.

Environmental Impact Assessment and Mitigation (DE-702)

This course teaches students how to conduct environmental impact assessments for large-scale development projects. Students learn about regulatory compliance, mitigation strategies, and stakeholder consultation processes.

Project-Based Learning Philosophy

The Land Management program places a strong emphasis on project-based learning as a means of integrating theory with practice. This approach is embedded throughout the curriculum, from early-year mini-projects to comprehensive capstone projects in the final year.

Mini-projects are assigned in the second and third years to help students apply concepts learned in class to real-world situations. These projects often involve collaboration with local communities, government agencies, or private firms. For example, students may work on mapping land use changes in a specific region or developing a GIS-based tool for tracking deforestation.

The capstone project, undertaken in the seventh and eighth semesters, is a significant undertaking that allows students to explore a topic of personal interest within the field of land management. Projects are selected based on student interests, faculty expertise, and current industry needs. Students receive guidance from faculty mentors throughout the process, ensuring that their work meets academic standards and has practical relevance.

Assessment criteria for projects include originality, methodology, data quality, analytical depth, and presentation skills. Students must submit written reports and deliver oral presentations to demonstrate their findings and contribute to ongoing discussions in the field.