Latest Contributions by larryzhang

The most recent version of imaging radar, known as spotlight-mode SAR, can produce imagery with spatial resolution that begins to approach that of remote optical imagers. For all of these reasons, 'airborne' synthetic spotlight aperture radar imaging is rapidly becoming a key technology in the world of modern remote sensing for high-resolution generation of DEM, except for higher cost and different imagery processing workflows (than scan-mode /InSAR or LiDAR). With the wide use of SPOTLIGHT polarization technology applied to satellite,  'spaceborne' spotlight SAR sensors like COSMO-SkyMed, TerraSAR-X, and TanDEM-X enable us to handle high-resolution stereo-pair HH/ VV SAR images (up to 1-m), to 'accurately & cost-effectively' generate 3-5 m resolution  of DEM for large coverage, via the following rigorous workflow. For spotlight-mode SAR imagery registration and processing, refer to the attachement. ++++++++++++++++++++++++ PS., The techniques of generating high-resolution DEM (0.15-5 m resolution) are widely discussed and used in operation, including Interferometric Synthetic Aperture Radar (InSAR) and Light Detection and Ranging (LiDAR) along with advancements in the ability to extract elevation data using conventional stereo-pair photogrammetric methods for airborne and spaceborne OPTICAL /near-IR sensors (GeoEye-1, WorldView-2/3, Pleiades-1A/1B, SPOT-6/7, etc.). Among those, modern airborne & spaceborne imaging radars, known as synthetic 'scan-mode' aperture radars (SARs), are capable of producing high-quality pictures of the earth's surface while avoiding some of the shortcomings of certain other forms of remote imaging systems. Primarily,  radar overcomes the nighttime limitations of optical cameras, and the cloud- cover limitations of both optical and infrared imagers. In addition, because imaging radars use a form of coherent illumination, they can be used in certain special modes such as 'interferometry', to produce some unique derivative image products that 'incoherent' systems cannot. ... View more

In practice, many customers like hydrologists and water management are not satified with flooding analysis and prediction studies, especially, when those results are from GIS-based flooding modeling applications. To improve the reliability of Flooding Disaster Prediction and Mapping, GIS experts with many hydrologists usally concentrate acquisition and processing high-resolution geospatial data like cloud points for higher DEM generation.  Some flooding applications improve their analysis also via simulation... However, the experiences show that those efforts would not produce more reliable analysis, because of differences in roughness, rock hardness of geological formations, flow depth, and slope, the timing of runoff from most parts of a watershed differing from that along the principal flow path (which is generally used to compute times of concentration). Those GIS-based flooding apps are just 'simplified' hydrologic models. Besides, uncertainty analysis in those flooding models mostly ignores geological (and some of very important hydrologic) factors, which are usually major impacts on the reliability of flooding analysis and mapping. Hydrological modelling - Wikipedia, the free encyclopedia and Hydrological transport model - Wikipedia, the free encyclopedia As well known, people commonly apply 3D geological modeling techology into groundwater analysis applications (attachment). In fact, when dealing with surface and surface-subsuface water applications, we also shouldn't ignore this important geological approach. For example, when applying SWMM/RUNOFF algorithm in GIS-based flooding model, different rock hardness of geological formations, faults,  soil and trees for infiltration, upland erosion (like CASC2D-SED, which simulates soil erosion from overland flow and routes sediment by size fractions to the outlet of a watershed) are hardly considered, even in some famous Surface Runoff Models (rainfalls, simplified recharges)… Illustration of water cycle A similar intention (BUT, different implementation at all) to combine large quantities of outcrop data into a geodatabase can be referred at The SAFARI geodatabase: Exploring geological outcrop analogues for reservoir modeling | ArcGIS Blog Certainly, without the details on both 3D surface and subsurface geology and hydrology, it is really chanlenging to get reliable flooding analysis and prediction... ... View more