2 rAgriculture and forestry rResource and environment rUrban and regional development rOther applications Remote Sensing Applications
3 Agriculture and forestry rAgriculture u Resource inventory u Monitoring and prediction u Management rForestry u Planning and management u Environment protection and management
4 Agriculture resource inventory Landsat TM colour infrared composite showing a marginal agriculture area in Fukang County of Xinjiang, western China. The agriculture and life rely on water supply so that a reliable irrigation system is fundamental for agriculture. Note the existing farmlands are clearly shown on the image. In between there are potential farmlands but currently suffered from lack of irrigation, salinity and sand shifting. The sand dunes are shown in the north with a clear boundary to the farmlands.
5 Yield prediction rCropped area u The larger the cropped area, the higher yield probability rGrowth condition u temperature u water u pests control
6 Cropped area Landsat TM image acquired in spring 1998 showing the winter wheat crop land (green colour) in the North China Plain south of Beijing. The Beijing city is shown on the mid-top of the image (dark grey colour). Note during the early spring season, the winter wheat is almost the only green vegetation shown in the area.
7 Growth conditions and prediction method rUse historical data over a number of growth seasons to calibrate model. u Climate: temperature and rainfall u Final harvest yield rDerive NDVI images at key periods of growth rDerive relationships between NDVI images, climatic conditions prior to and at image acquisition and the final yield. rFavourable climate and High NDVI will probably result in high yield.
8 Growth conditions Evaluation of reflectance in NIR will show the variation between healthy and stressed vegetation. Comparison between vegetation indices acquired during critical growth period will reveal growth status of the crop. BNIR Reflectance Stressed Healthy GRBand Soil t1t1 Climate condition Time t2t2 Harvest Yield NDVI norm NDVI season
9 Precision farming rPrecision agriculture is the customization of soil and crop management according to conditions found within fields. rAt its core is variable rate technology (VRT), i.e. vary crop inputs according to the need u fertilizer u water rThe key issue is to define the need u ground sampling u remotely sensing
10 Reports for agriculture input for GIS models Soil classification Crop emergence Weed pressure Pest detection Nutrient problems Water problems Other anomalies Change detection Site specific crop management Variable Rate Technology (VRT) Maps: Yield Soil properties Pests VRTVRT GPS Remote sensing images satellites aeroplane Use of remote sensing technology
12 Crop conditions A low-altitude colour infrared airphoto acquired in May 1998 showing an agriculture winter wheat field. Note the variations of the crop growth condition due to the micro-relief, local soil varieties and minor differences in management (fertilising and irrigation).
13 Soil conditions A low-altitude colour infrared airphoto acquired in May 1998 showing an agriculture field with or without winter wheat crops. Note the variations of the soil condition, ploughed or not, also varied in moisture.
14 Forestry rPlanning and management u Timber reserves u Log planning rEnvironment protection and management u Forest regeneration u Wildlife protection and reserves
15 Forest condition IKONOS 4-m resolution colour infrared composite acquired on 12/10/99 showing the mountains and ski runs near Copper Mountain, Colorado. Note the clear-cut area and forest health difference that can be interpreted by the shade of red colour (the darker the healthier). (courtesy spaceimaging.com)
16 Fire detection The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image shows the Clear Creek fire in Idaho of USA on the morning of 30 August (courtesy NASA)
17 Evaluating fire damage IKONOS 4-m resolution colour infrared composite acquired on 14/6/00 showing the Hi Meadows fire in Jefferson and Park Counties, Colorado. Note the heavily burned areas (dark blue), the haze of smoke and areas not yet burned (red). (courtesy spaceimaging.com)
18 Resource and environment rResource inventory u land resources (e.g. farmland) u water resources u mineral resources rEnvironment management u rangeland management u coastal zone management u natural hazards and disasters
19 Mineral exploration The composite of Radarsat image and Total Field MAG. The image is produced by rasterising 500m line spacing GSC Survey to 200m pixel spacing and integrated with Radarsat image through IHS as: Intensity: Radarsat SAR Hue: MAG Total Field Saturation: DN=75 (constant) (courtesy Canadian Space Agency)
20 Geological structure The perspective view shows a proportion of the 1200km San Andreas Fault and was generated using data from the Shuttle Radar Topography Mission (SRTM), which flew on NASA's Space Shuttle in February 2000, and an enhanced Landsat TM natural colour composite. (courtesy NASA)
21 Low-altitude airphoto pair acquired in July 1997 showing distribution of shrub vegetation and soil erosion features in Fowlers Gap Station at western New South Wales, Australia. The height of the shrubs can be measured using digital photogrammetric methods so that the total volumes of vegetation and biomass can be modelled. Rangeland vegetation resources
22 Rangeland management Landsat MSS image acquired on 15 December 1989 showing the rangeland environment around Pooncarie, western New South Wales, Australia. A series of ancient dry lakes are clearly shown with the most famous Lake Mango national park - a natural heritage of the world. Note the clear boundaries between properties indicating the management differences between land owners.
23 Airborne multispectral images showing coastal zone features such as waves, sand bars, lagoon and landuse features. The image on the left is natural colour composite while the one on the right is the colour infrared composite. (courtesy Mercator GIS and Environmental Corporation) Coastal zone management
24 Natural hazards and disasters Airborne multispectral scanner images showing South Padre Island, Texas, USA. The "cuts" shown on the right image were created by Hurricane Bret and the imagery (acquired in September 1999) shows substantial coastal erosion when compared with the one taken in 1996 (left). (courtesy Mercator GIS and Environmental Corporation)
25 Flood Classified Radarsat (C- band) image for mid-reach of Yangtze River flooded area (near the city of Wuhan) on 22/8/1998.
26 Volcano activity Landsat 7 Enhanced Thematic Mapper (ETM+) natural colour composite acquired on 13 February 2000 showing the active Kagoshima Volcano, Japan. There are many people living in close proximity to the volcano (top left) regardless the inconvenience of the high density of volcano ash and potential danger. (Courtesy USGS)
27 Earthquake In radar interferometry, two or more radar images are combined to give measurements of surface height and surface change, making it useful for the detection of earthquake centre. This can be seen on the right image showing 1995 earthquake in Kobe, Japan.
28 Geological hazards Zhou Qu landslide and mudflow (August 2010): high-resolution images were used to detect the change of land cover for the assessment of the damage. - Courtesy of State Bureau of Surveying and Mapping, China, and PanSpace
29 Urban and regional development rRegional landuse change detection rUrban expansion rLiving conditions and housing standards rPlanning
30 Regional development TM image for Pearl River Delta, one of the most rapidly developed region in the world. Note the five international airports in a very closed proximity (A: Hong Kong, B: Shenzhen, C: Macau, D: Zhuhai and E: Guangzhou). How many more are there to be built? A B C D E
Landsat TM images acquired in 1988 and 1998 showing the dramatic landuse change in Dongguan City at eastern Pearl River Delta. Note the industrial belt from Humen to Dongguan shown on the 1998 image did not exist at all on the image acquired 10 years ago. Landuse and land cover change
32 Urban planning Airphotos showing urban area change in Hong Kong in the last 50 years. The up photo shows Central in 1945 and right photo shows Wanchai in 1999.
33 Other applications rWeather forecasting rGlobal studies: El Nino and La Nina phenomena rMilitary interest rAstronomic studies and exploration
34 Weather forecasting rCloud imagery is now the default part for TV weather report rTropical cyclone (typhoon) warning rSandstorm forecasting
35 Tropical cyclone Meteorological satellite image showing a tropical cyclone hitting Hong Kong.
36 Sandstorm Meteorological satellite image showing a sandstorm swiping North China on 22 March 2010.
37 Sandstorm forecasting 17 March March March April April April 2000 Images showing the progress of the sandstorm over North China in spring The image acquired on 9 April was from Chinese Fengyun meteorological satellite. The rest were acquired from NOAA meteorological satellites. (courtesy Institute of Remote Sensing Applications of Chinese Academy of Sciences)
38 Global studies rOceanography rEl nino and La Nina phenomena rGlobal warming rThe global carbon circulation (CO and CO 2 emission) rOzone layer monitoring El Nino phenomenon shown by NOAA satellite image. Note the high temperature current along equator.
39 Ocean temperature The global ocean temperature distribution by NOAA satellites. (courtesy NOAA)
40 Ocean current CZCS image of the Gulf Stream and northeastern coast of the US. Several large Gulf Stream warm core rings are visible in this image. (courtesy daac.gsfc.nasa.gov)
41 Changing global land surface rThe carbon cycle rEvapotranspiration and greenhouse warming rPlants on the move rSnow and ice
42 Global climatic change GERES images showing the global short-wave (upper) and long-wave (lower) radiation, measuring the balance of solar energy received by the Earth and the energy reflected and emitted back into space. Understanding the energy balance of the Earth system is critical for assessing scientific models of climatic change. (courtesy terra.nasa.gov)
43 Deforestation Landsat image showing deforestation in the Amazon region, taken from the Brazilian state of Para on 15 July The dark areas are forest, the white is deforested areas, and the grey is re- growth. The pattern of deforestation spreading along roads is obvious (lower part of the image). (courtesy terra.nasa.gov)
44 Snow and ice These Landsat images, acquired 13 years apart, show the retreat of the Muir Glacier (A) in southeastern Alaska. Between 12 September 1973 (left image) and 6 September 1986 (right image), the Muir Glacier retreated to the northwest more than 7 km. (courtesy terra.nasa.gov)
45 Military interest A digital orthophoto quadrangle image showing a "parking yard" of B52 bombers located 17km southeast of Tucson, Arizona, USA. The image was acquired on 5 December 1994, while the most B52s retired from military service. (courtesy USGS)
46 Target recognition Airphotos showing objects of military interest. Above: pentagon building (US Department of Defence), Right: a battle ship (USS Intrepid) at New York City Harbour. (courtesy USGS)
47 IKONOS 1-m resolution images showing downtown Grozny, Chechnya. The left image was acquired on 16 December 1999 and the right image was acquired on 16 March It is evident that several buildings surrounding Minutka Square (lower-right) have been severely damaged. (courtesy spaceimaging.com) Damage caused by war
48 Military campaign assessment Military spy satellite images showing the Heart Airfield, Afghanistan during the anti-terrorism strike by the U.S. military force in October The left is the pre-strike image and the left is the post-strike image. The damage on the parking aircraft is clearly shown on the post-strike image. (courtesy sina.com.cn)
49 Astronomic Studies and Exploration Remote sensing technology does not only look down the earth, but also look out the universe. Right: surface of the moon; Top left: the Jupiter; Top: the Saturn. (courtesy spaceimaging.com)
50 Summary rRemotely sensed data have been widely used in many fields of applications. rIn early dates, because of the low resolution, remote sensing images were mostly used in environment and natural resource studies. rWith the largely improved availability of high resolution data, the technology is now widely used in urban and regional applications, as well as management. rThe technology will soon become an important part of daily life.