Resource Appraisal with Remote Sensing techniques A perspective from Land-use/Land-cover by Basudeb Bhatta Computer Aided design Centre Computer Science and Engg. Dept. Jadavpur University kolkata

Introduction There can be almost endless applications of remote sensing for the monitoring and management of land-use and land-cover. Each application itself has specific demands, for sensor (optical, thermal, microwave), resolutions, attribute data, and procedures. With the availability of very high spatial resolution satellites and advanced geospatial analytical techniques in the recent years, the applications have been multiplied.

LAND USE Or LAND COVER

Study of Land-use/Land-cover Important for: Change monitoring (to balance conservation, conflicting uses, and development pressure) Resource management (sustainable management and protection of land-use/land-cover resources) Planning activities (for future development)

Some Application Areas Natural resource management Wildlife habitat protection Baseline mapping for GIS input Urban expansion/encroachment Routing and logistics planning for seismic/exploration/resource extraction activities Damage delineation (tornadoes, flooding, volcanic, seismic, and fire activities) Legal boundaries for tax and property evaluation Target detection (identification of earth surface features)

Land Cover Identification and Mapping Data requirements Multispectral optical image (preferably post monsoon) Radar image Thermal image

Land Cover Identification and Mapping Multispectral day-time optical image

Land Cover Identification and Mapping Multispectral night-time optical image Night-time image shows urban areas

Land Cover Identification and Mapping Thermal Image DayBefore dawn

Land Cover Identification and Mapping Day-time thermal image of Kolkata

Land Cover Identification and Mapping Thermal Image Band 1, Day Band 1, Night CC, Day CC, Night Thermal Infrared Multi-spectral Scanner Courtesy: NASA

Land Cover Identification and Mapping Radar Image Radar image for flood monitoring

Land Cover Identification and Mapping Radar Image R : C-band HV G : L-band HV B : L-band VV Bright blue-green: forest Reddish-brown: grassland Dark blue: rough lava flow Black: smooth lava flow Courtesy: Microimages Inc. Kilauea volcano, Hawaii, USA

Land-use/Land-cover Change

March 14, 2010 March 13, 2003

Land-use/Land-cover Change

June 17, 1975July 10, 1992August 1, 2000

Land-use/Land-cover Change Courtesy: NASA March 14, 2011 August 8, 2008 Ishinomaki, Japan

Identification of Changes Visual (manual) Identification Automatic Identification Semi-automatic (man-machine interactive) Identification

Visual Comparison

Multi-temporal Colour Composite

Multi-temporal Colour Composite

Automatic Change Detection Image Image Output

Automatic Change Detection Continuous Image

Automatic Change Detection

Semi-automatic Change Detection Classification of multi-temporal image stack

Semi-automatic Change Detection Classifying multi-temporal images individually Converting the classified images in to vector Aggregation of vector polygons Vector overlay

Vector Overlay Land-cover 1990Land-cover

Land-use/Land-cover Change What to identify? Momentarily change or seasonal change or annual change? Seasonal change and annual change are mixed within the same image. Cycle of seasonal change can be rather complex. Spatial resolution is a challenge for long temporal gap.

Momentarily Change

Momentarily Change Imaging

Scene Specific Momentarily Change

Examples – Urban growth/sprawl

Examples – Illegal Construction

Examples – Crop type Landsat-TM and SAR data merged to identify crop type

Examples – Crop Damage Courtesy: CCRS

Examples – Burn Mapping Courtesy: NASA

Examples – Monitoring Afforestation

Examples – Crop Phenology