NRS 415 Remote Sensing of Environment

Transcription

1 NRS 415 Remote Sensing of Environment 1

2 High Oblique Perspective (Side) Low Oblique Perspective (Relief) 2

3 Aerial Perspective (See What s Hidden) An example of high spatial resolution true color remote sensing imagery 3

4 Vertical imagery: Can be used to develop a map for the subjects of interests Low Oblique Perspective: Can not be used to produce an accurate map Remote Sensing Remote sensing is the art, science, and technology of obtaining reliable information about physical objects and the environment, through the process of recording, measuring and interpreting imagery and digital representations of energy patterns derived from non-contact sensor systems (Colwell, 1997). Colwell, R.N., History and place of photographic interpretation, Manual of Photographic interpretation, W.R. Philipson (Ed.) 2 nd Ed., Bethesda: American Society for Photogrammetry & Remote Sensing,

5 Remote Sensing is the observation of the Earth from satellites or aircrafts. Sensors mounted on these platforms capture images of the Earth that reveal features may or may not apparent to the naked eye. The end users/image analysts interpret the data, extract information, and use it to answer real world questions. A remote sensing instrument collects information about an object or phenomenon within the instantaneous-field-ofview (IFOV) of the sensor system without being in direct physical contact with it. 5

6 Vertical Aerial Photograph 5/15/

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8 10/26/

9 2006 QuickBird Satellite Panchromatic Images (0.6-m Spatial Resolution) 9

10 Multispectral images acquired by QuickBird satellite with 2.5-m spatial resolution Pseudo-color (left) / True-color (right) Remote Sensing of Vegetation Remote sensing techniques can be applied to study vegetated landscapes, from local to global scales. 1. Agriculture 2. Forest 3. Rangeland 4. Wetland 5. Urban vegetation 6. Carbon science 7. Climate change

11 Aerial photo (natural color) Landsat Imagery (natural color) Satellite imagery (pseudo color) Field photo (True color) 11

12 Remote Sensing of Soil and Minerals Soil is a mixture of inorganic mineral particles and organic matters of varying size and composition. Remote sensing can play a role in the identification, inventory, and mapping of soils, especially when surface soils are not covered with dense vegetation. Remote sensing can provide information about the chemical composition of rocks and minerals that are on the Earth's surface, and not completely covered by vegetation. 12

13 Remote Sensing of Water and Wetlands Water exists in various states on Earth, including: freshwater, saltwater, water vapor, rain, snow, and ice. It is always challenging to obtain spatial information about water for a number of important hydrologic variables, such as: Water-surface area (rivers, ponds, lakes, reservoirs, and oceans) Water constituents (organic and inorganic) Water-surface temperature Snow-surface area and snow-water equivalent Ice-surface area and ice-water equivalent Precipitation and water vapor Wetland areas and spatial distributions Wetland properties (vegetation, habitats, ecosystem functions ) Remote sensing has the advantages of obtaining such types of data. True-color SeaWiFS image of the Eastern U.S. on September 30, 1997 and the derivative of Chlorophyll a distribution 13

14 Sedge Meadow Bog Dry Green light Reflectance Red light Reflectance Near Infrared (IR) Near IR Reflectance The higher the reflectance The brighter the image Green Light Reflectance Red Light Reflectance 14

15 Remote Sensing the Urban Landscape Urban landscape are composed of a diverse assemblage of materials (concrete, asphalt, metal, plastic, shingles, glass, water, grass, shrubbery, trees, and soil) arranged by humans in complex ways to build housing, transportation, utilities, commercial and industrial facilities, and recreational landscape. Remote Sensing data collection and processing provide basic human spatial services for urban studies and applications. Landsat MSS September 26, 1977 August 8, 2008 Emergency Response Monitoring of impacts from natural and manmade disasters (e.g. hurricanes, earthquakes, land slides, flooding, wildfires, snow and ice storms, war damages, biotic infestation, effects of climate change ) March 14,

16 Mapping is about Information Extraction True-color Orthophoto Impervious Surface Areas 16

17 Remote Sensing: Advantages 1. Remote sensing is unobtrusive, i.e., a passive remote sensing does not disturb the object or area of interest. 2. Remote sensing devices are often programmed to collect data systematically (size, time ). This systematic data collection can remove the sampling bias introduced in some in situ investigations. 3. Remote sensing can provide fundamental biophysical data, including: x,y location, z elevation or depth, biomass, temperature, moisture content, etc. 4. Remote sensing can cover large areas and some of the areas are very difficult or impossible in in situ data collection (wetlands, forests, deserts, ). Typical Remote Sensing Process 1. Statement of the problem 2. Data collection 3. Image processing and information extraction (e.g., photo interpretation) 4. Information presentation 17

18 Fundamental Image Analysis Tasks Analog (visual/manual) image interpretation Digital image processing Integration of remote sensing, GIS and other related scientific fields Rhode Island Land-Cover Maps and Change Detection (based on digital image processing from Landsat data)

19 Rhode Island Land-Cover Maps and Change Detection (based on digital image processing from Landsat data)

20 Thematic information extraction? Class Goals Develop an understanding of spectral reflectance properties of various earth surface materials on remote sensing data (vegetation, soil, water/wetland, urban, ) Become familiar with the concepts in computer-assisted data analysis Apply various strategies for extraction of thematic information through image classification process. Evaluate the utility of multitemporal remote sensing data for change detection and analysis Gain experience in the use of state-of-the-art software systems for digital image processing and natural resource mapping and management. 20