Land use and land cover (LULC) change have been recognized as a key driver of global climate change by influencing land surface processes. LULC is interlinked with environmental and socio-economic systems. The driver plays a leading role in LULC changes, and are derived from the interrelationship of the various elements such as altitude, slope, aspect, soil type, precipitation, etc. are grouped as environmental; and population, literacy rate, household, drinking water facility, medical facility, etc.
Remote sensing with its synoptic view, fast data acquisition and digital format suitable for computer processing, is one of the most successful and reliable data sources in the last few decades in recording Spatio-temporal LULC change. Modeling of potential future LULC assigning a set of defined conditions offers the opportunities to examine the probable spatiotemporal changes.
The prime objective of this proposed course is to provide participants with both the theoretical and practical experiences in all aspects of remote sensing applications in studying land sciences.
The course will mainly cover the particular fields on the use of open-source multi-sensor satellite remote sensing data for automated land cover mapping; use of R programming for geostatistical analysis; and use of open-source modeling platform for simulating LULC scenarios. The outcomes of these models have prominent applications, e.g., in planning, managing, policy formulation, studying the impact on climate and hydrological cycle, etc.
- Introduction to the basics of Remote Sensing
- Familiarization with various open-source Remote
- Sensing and Geospatial data
- Hands-on learning with image processing and GIS software
- Statistical and machine learning approaches for LULC classification
- Generation of landscape metrics for assessment of LULC dynamics
- Sources and generation of various geospatial data for modeling
- Hands-on with R programming language
- Geostatistical analysis to quantify and qualify the drivers of landscape changes
- Introduction to open-source models on LULC dynamics (Dyna-CLUE)
- A case study with Dyna-CLUE model
- Database generation, model simulation, calibration and validation
- LULC Projection and Discussion
Nil for AICTE-QIP sponsored participants
For others – INR 20,000/- (Twenty thousand) + GST @18% per participant
To register online for the course, click here.
The last date to register is Oct 5, 2019.
Phone Number: +91-3222-281802
Email ID: firstname.lastname@example.org