Catchment storm runoff modelling using the geomorphologic instantaneous unit hydrograph

A lumped empirical model, the Geomorphologic Instantaneous Unit Hydrograph (GIUH) rainfall-runoff model, is developed for the Can Le catchment in the upstream region of the Sai Gon river Basin (Vietnam). This model can serve to simulate catchment runoff into the Dau Tieng Reservoir and can be used as a flood forecasting tool for the ungauged Can Le catchment. The GIUH couples geomorphology and hydrology quantitatively. The obtained Unit Hydrograph is based on Horton's morphometric parameters; bifurcation, length and area ratios. A new functionality within the ILWIS GIS-RS package, namely ‘DEM-hydro processing’, is applied to effectively process a Digital Elevation Model to extract these ratios from the drainage network. To supplement the limited field data available, various satellites images have been used such as ASTER, SRTM (Shuttle Radar Topography Mission) and METEOSAT 5. A short field campaign to collect missing ground data was executed between September and October 2005. The data collected included discharge (and stage – discharge curve), meteorological data, soil, land use information that are used for paramerisation, calibration and validation of the GIUH. The model was successfully applied for the Can Le catchment. Using the Horton's morphometric parameters derived from the DEM with estimated overland and stream flow velocities, the model is easy-to-use.     

Assessing the Effect of Data Imports on the Completeness of OpenStreetMap – A United States Case Study

The assessment of OpenStreetMap (OSM) data quality has become an interdisciplinary research area over the recent years. The question of whether the OSM road network should be updated through periodic data imports from public domain data, or whether the currency of OSM data should rather rely on more traditional data collection efforts by active contributors, has led to perpetual debates within the OSM community. A US Census TIGER/Line 2005 import into OSM was accomplished in early 2008, which generated a road network foundation for the active community members in the US. In this study we perform a longitudinal analysis of road data for the US by comparing the development of OSM and TIGER/Line data since the initial TIGER/Line import. The analysis is performed for the 50 US states and the District of Columbia, and 70 Urbanized Areas. In almost all tested states and Urbanized Areas, OSM misses roads for motorized traffic when compared with TIGER/Line street data, while significant contributions could be observed in pedestrian related network data in OSM compared with corresponding TIGER/Line data. We conclude that the quality of OSM road data could be improved through new OSM editor tools allowing contributors to trace current TIGER/Line data.     

Field Measurements of Plant Emissivity Spectra: An Experimental Study on Remote Sensing of Vegetation in the Thermal Infrared Region

Spectral features of plant species in the visible to SWIR (0.4–2.5 μm) region have been studied extensively, but scanty attention has been given to plant thermal infrared (TIR: 4–14 μm) properties. This paper presents preliminary results of a study that was conducted first time in India to measure radiance and emissivity properties of eight plant species in TIR spectral region in the field conditions using a FTIR (Fourier Transform Infrared) field spectroradiometer working in 4–14 μm at an agriculture experimental farm. Several spectral features in the emissivity spectra of plant species were observed that are probably related to the leaf chemical constituents, such as cellulose and xylan (hemicellulose) and structural aspects of leaf surface like abundance of trichomes and texture. Observations and results from the field measurements were supported by the laboratory measurements like biochemical analysis. These preliminary field emissivity measurements of leaves in TIR show that there is useful spectral information that may be detectable by field-based instrument. More detailed field and laboratory measurements are underway to explore this research theme.     

马来西亚砂拉越州政府地理信息共享平台建设

智慧城市建设和地理信息共享化是当前GIS应用发展的主要方向.数据是信息共享的基础,在中国,共享平台建设已相对比较成熟,而马来西亚砂拉越州,在地理信息的集成管理上仍存在较大的问题,地理信息共享度低,建立基础地理信息共享平台尤为重要.本文以地理信息采集为重点,采用ESB企业总线技术建立砂拉越州政府地理信息共享平台,定义一整套数据库建设标准、数据服务标准以及应用接口标准,以标准来规范共享平台的建设,集成测绘数据管理、道路管理等应用系统,完善数据更新体系,实现地理信息的共享和资源的合理利用.     

Applications of generalized additive model (GAM) to satellite-derived variables and fishery data for prediction of fishery resources distributions in the Arabian Sea

This study aims to illustrate how remotely sensed oceanic variables and fishing operations data can be used to predict suitable habitat of fishery resources in Geographic Information System. We used sea surface height anomaly (SSHa), sea surface temperature (SST), chlorophyll concentration (CC), photosynthetically active radiation (PAR) and fishing depth as predictor variables. Fishery data of Indian squid (Loligo spp.) and catfish (Tachysurus spp.) for study period (1998–2004) were segregated randomly to create training and validation. Catch was normalized into Catch per unit Effort (kg h^?1). Generalized additive modelling was performed on training data and then tested on validation data. Suitable ranges of SST, CC, SSHa and PAR for different species distributions were derived and integrated to predict their spatial distributions. Results indicated good match between predicted and actual catch. Monthly probability maps of predicted habitat areas coincide with high catch of the particular month for the study period.     

High Resolution Köppen‐Geiger Classifications of Paleoclimate Simulations

The development and application of an algorithm to compute Köppen‐Geiger climate classifications from the Coupled Model Intercomparison Project (CMIP) and Paleo Model Intercomparison Project (PMIP) climate model simulation data is described in this study. The classification algorithm was applied to data from the PMIP III paleoclimate experiments for the Last Glacial Maximum, 21k years before present (yBP), Mid‐Holocene (6k yBP) and the Pre‐Industrial (0k yBP, control run) time slices. To infer detailed classification maps, the simulation datasets were interpolated to a higher resolution. The classification method presented is based on the application of Open Source Software, and the implementation is described with attention to detail. The source code and the exact input data sets as well as the resulting data sets are provided to enable the application of the presented approach.     

Inter sensor comparison between RESOURCESAT LISS III, LISS IV and AWiFS with reference to coastal landuse/landcover studies

Coastal zone assumes importance due to high productivity of ecosystems, man-made developmental activities, natural hazards and dynamic nature of the coast. As costal ecosystems are unique and fragile, understanding the impact of developmental activities on the sustainability of the coastal zone is very important. Remote sensing, because of repetitive and synoptic nature is an ideal tool for studying this. Time series data analyses for monitoring coastal zone require different type of sensors. Present study deals with atmospheric correction of satellite data, reflectance, selection of coastal features like, mudflat, mangroves, vegetated dune, coastal water, etc. and their inter-comparison using different sensor data of RESOURCESAT sensors. Reflectance values give better separateability for various coastal features in comparison to DN values. LISS IV can be used in place of LISS III or merged (LISS III + PAN) for long-term coastal zone studies.     

Modeling errors in upward continuation for INS gravity compensation

Accurate upward continuation of gravity anomalies supports future precision, free-inertial navigation systems, since the latter cannot by themselves sense the gravitational field and thus require appropriate gravity compensation. This compensation is in the form of horizontal gravity components. An analysis of the model errors in upward continuation using derivatives of the standard Pizzetti integral solution (spherical approximation) shows that discretization of the data and truncation of the integral are the major sources of error in the predicted horizontal components of the gravity disturbance. The irregular shape of the data boundary, even the relatively rough topography of a simulated mountainous region, has only secondary effect, except when the data resolution is very high (small discretization error). Other errors due to spherical approximation are even less important. The analysis excluded all measurement errors in the gravity anomaly data in order to quantify just the model errors. Based on a consistent gravity field/topographic surface simulation, upward continuation errors in the derivatives of the Pizzetti integral to mean altitudes of about 3,000 and 1,500 m above the mean surface ranged from less than 1 mGal (standard deviation) to less than 2 mGal (standard deviation), respectively, in the case of 2 arcmin data resolution. Least-squares collocation performs better than this, but may require significantly greater computational resources.