Remote Sensing Of Critical Hydrologic Paramters: Soil Moisture .
Remote Sensing of Critical Hydrologic Paramters:Soil Moisture, Topography and VegetationKlaus Scipal & Wolfgang WagnerVienna University of TechnologyInstitute of Photogrammetry and Remote Sensing
Introduction Content- No „edge cutting“ technologies, but realistic- Operational products, proven in pilot applications- Compare competing technologiesRemote Sensing (as understood here)- is not just about land cover classification using statistical imageprocessing approaches- should be better regarded as a suite of techniques that aim to makephysical measurements of geophysical parameters/processesActive Remote Sensing Products- Topography- Vegetation- Soil Moisture
Scaling Issues The term “scale” refers to a- characteristic length- characteristic time The concept of scale can be applied to- Process typical time and length scales at which a processtakes place- Measurement spatial and temporal samplingcharacteristics of the sensor system- Model Mathematical/physical description of a process Ideally: Process Measurement Model Scale Remote sensing offers a large suit of sensors- Scaling issues must be understood in order to makeappropriate use of sensors
Measurement Scales
Topography Lidar (Airborne Laser Scanning)- Highly accurate 1 m DEMs- High-costs- Special software and expertise neededERS-1/2 tandem interferometry- 30-100 m DEM- Data from years 1995-1998 available for most parts of the world- Data costs moderate, but special software and expertise needed- Accuracy highly variable depending on land cover and topography- reasonable accuracy ( 10m) for non-vegetated, flat terrainShuttle Radar Topography Mission (SRTM)- 100 m DEM with almost global coverage- Data are free
Digital Surface Model from LidarLaser scanner mounted on an airplaneLaser ScannerFlight of Almtal,Upper Austria
Digital Terrain Model after Filtering
DEM from ERS-1/2 Tandem InterferometryDEM from ERS-1/2tandem data producedwith commerciallyavailable software,Bregenzer See,Vorarlberg
Shuttle Radar Topography MissionStreet of Gibraltar (DEM with overlay of a Landsat image) NASA
Vegetation Lidar- Airborne laser scanning--High-quality 1m vegetation height models, but expansive forlarge areasResearch is still in the beginning- Full-waveform satellite lidars for vegetation mapping haverepeatedly been proposed, but so far not approved SAR and SAR Interferomery- Broad vegetation categories can be distinguished- Not suited at local scale ( 100 m)- Data costs moderate, but specialised software and highlevel of expertise needed
Vegetation Height from LidarInfrared OrthophotoNormalised surface modelfrom airborne lidar data LandesvermessungsamtFeldkirch
Vegetation Parameters from SAR InterferometryERS-1/2 TandemCoherence,Bregenzer See,Vorarlberg
Biomass Mapping using SAR InterferometryLegend:Masked AreasWaterSmooth SurfacesForest:0-20 m3/ha20-50 m3/ha50-80 m3/ha 80 m3/haSIBERIA forest mapof a 1 Mio. km2 largearea from ERS tandemcoherence and JERSSAR Data
Soil Moisture Local-scale soil moisture ( 1 km)- Synthetic Aperture Radar (SAR)- Still in an experimental stage, no operational products- All satellite SAR systems are multi-purpose missions, i.e. notwell suited for the task of soil moisture monitoring Large-scale soil moisture ( 10 km): 2005-2015 Decade ofSoil Moisture Remote Sensing- Dedicated, experimental soil moisture missions-SMOS: ESA Earth Explorer Opportunity Mission (2007)HYDROS: NASA Hydrosphere State Mission (2010)- Operational “soil moisture” missions-METOPAMSR, CMIS- First experimental products are becoming now available
Soil Moisture from SARSoil moisture derived from SAR using a change detection approach DLR and I.P.F.
Seasonal Soil Moisture DynamicsClosed Forest CoverAzimuthal EffectsFrozen Soil/Snow CoverDry SoilWilting PointWet SoilField Capacity
Integrated Data-Modelling Approaches Remote sensing can provide spatial data productsfor hydrologic model validation, calibration or input Only a limited number of geophysical parameters can bederived Integration of- In-situ observationi.e synoptic observations- Remotely sensedgeophysical products- Modelling approachesWhat parameters can be measured using RS?
Droughts in South Africa temrelatedtowarmElNiñoeventskeptsystem related to warm El Niño events ncountriesAfrica dry. Most of southern African orth-westernpartfrom severe droughts. In the north-western thelowesteverrecorded.Cerealproductionfellnear the lowest ever recorded. Cereal production oversixmillionpeopleneededemergencythat over six million people needed gesthroughoutsouthernAfrica.throughout southern Africa.
Floods in South Africa xcessiveheavy rainfall to the area. According to USAID the rovincesProvincesandandininMozambique.Mozambique.
Potential for Large-Scale Hydrologic ModelsSambesi – Nana‘s Farm60 days shiftRunoffCatchment-Average SWITime Axisshifted RunoffRunoff
Catchment Modelling –Case Study Zambezi River
Crop Performance IndexWaterPlant ParametersSoil Moisture TrendSWISoil ParametersAvailable Water Coeff.Rooting Depth RdEvaporation Coeff. Kc AWC FC-WLCrop Performance IndexCPI (%) ((SWI* Rd * AWC) – (Kc * AWC))/ (Kc * AWC)) * 100
Drought Indicators for Africa and ChinaMaliChinaDrought conditions were confirmedby Malinese expertsDrought conditions were confirmed bystatisticsDrought conditionsCONCLUSIONS:CONCLUSIONS: SimpleSimpleyetyetpowerfulpowerfulmethodmethod tewellwell minatingdominatingfactorfactor cropscrops
Conclusions Remote sensing is not just about land cover classification- it is tool for monitoring geophysical parameters/processes-soil moisture, topography, vegetation height, biomass,evapotranspiration, etc. Despite there has been yet few commercial success storiesfor satellite remote sensing, major advances are beingmade- It is not always spatial resolution that counts- tremendous potential in hydrologic and agronomicapplications- In collaboration with the user communities, new modellingapproaches must be developed-Integration with in-situ observations and models (hydrology,agronomy, etc.)
Soil Moisture Local-scale soil moisture ( 1 km) - Synthetic Aperture Radar (SAR) - Still in an experimental stage, no operational products - All satellite SAR systems are multi-purpose missions, i.e. not well suited for the task of soil moisture monitoring Large-scale soil moisture ( 10 km): 2005-2015 Decade of Soil Moisture Remote Sensing
PRINCIPLES OF REMOTE SENSING Shefali Aggarwal Photogrammetry and Remote Sensing Division Indian Institute of Remote Sensing, Dehra Dun Abstract : Remote sensing is a technique to observe the earth surface or the atmosphere from out of space using satellites (space borne) or from the air using aircrafts (airborne). Remote sensing uses a part or several parts of the electromagnetic spectrum. It .
Scope of remote sensing Remote sensing: science or art? The remote sensing process Applications of remote sensing Information flow in remote sensing The EMRreflected, emitted, or back-scattered from an object or geographic area is used as a surrogatefor the actual property under investigation.
Proximity Sensor Sensing object Reset distance Sensing distance Hysteresis OFF ON Output Proximity Sensor Sensing object Within range Outside of range ON t 1 t 2 OFF Proximity Sensor Sensing object Sensing area Output (Sensing distance) Standard sensing object 1 2 f 1 Non-metal M M 2M t 1 t 2 t 3 Proximity Sensor Output t 1 t 2 Sensing .
Jul 28, 2014 · imagery analysis are forms of remote sensing. Remote sensing, a term which refers to the remote viewing of the surrounding world, including all forms of photography, video and other forms of visualization (Parcak 2012) can be used to view live societies. Satellite remote sensing allows
Remote Sensing 15.1 REMOTE SENSING Remote sensing is the science of gathering information from a location that is distant from the data source. Image analysis is the science of interpreting specific criteria from a remotely sensed image. An individual may visually, or with the assistance of computer enhancement, extract information from an image, whether it is furnished in the form of an .
Chapter 3 Introduction to Remote Sensing and Image Processing 17 Introduction to Remote Sensing and Image Processing Of all the various data sources used in GIS, one of the most important is undoubtedly that provided by remote sensing. Through the use of satellites, we now have a continuing program of data acquisition for the entire world with time frames ranging from a couple of weeks to a .
ii wildfire-landslide-risk-dss.uark.edu Terrestrial Remote Sensing User Manual -- Welcome to the Terrestrial Remote Sensing User Manual prepared by the Remote Sensing for Geotechnics research group based at the University of Arkansas, Fayetteville. Contained within this user manual are guidelines and resources for the operation of
4 Swiss Re Institute Remote sensing innovation: progressing sustainability goals and expanding insurability August 2021 Swiss Re Institute Remote sensing innovation: progressing sustainability goals and expanding insurability August 2021 5 Supply side and economic factors driving adoption Remote sensing, which includes both space and earth observation (EO), is the
