Multifrequency algorithms for precise point positioning: MAP3

We present the new MAP3 algorithms to perform static precise point positioning (PPP) from multifrequency and multisystem GNSS observations. MAP3 represents a two-step strategy in which the least squares theory is applied twice to estimate smoothed pseudo-distances, initial phase ambiguities, and slant ionospheric delay first, and the absolute receiver position and its clock offset in a second adjustment. Unlike the classic PPP technique, in our new approach, the ionospheric-free linear combination is not used. The combination of signals from different satellite systems is accomplished by taking into account the receiver inter-system bias. MAP3 has been implemented in MATLAB and integrated within a complete PPP software developed on site and named PCube. We test the MAP3 performance numerically and contrast it with other external PPP programs. In general, MAP3 positioning accuracy with low-noise GPS dual-frequency observations is about 2.5 cm in 2-h observation periods, 1 cm in 10 h, and 7 mm after 1 day. This means an improvement in the accuracy in short observation periods of at least 7 mm with respect to the other PPP programs. The MAP3 convergence time is also analyzed and some results obtained from real triple-frequency GPS and GIOVE observations are presented.     

Use of the L2C signal for inversions of GPS radio occultation data in the neutral atmosphere

Results from processing FORMOSAT-3/COSMIC radio occultations (RO) with the new GPS L2C signal acquired both in phase locked loop (PLL) and open loop (OL) modes are presented. Analysis of L2P, L2C, and L1CA signals acquired in PLL mode shows that in the presence of strong ionospheric scintillation not only L2P tracking, but also L1CA tracking often fails, while L2C tracking is most stable. The use of L2C improves current RO processing in the neutral atmosphere mainly by increasing the number of processed occultations (due to significant reduction in the number of L2 tracking failures) and marginally by a reduction in noise in statistics. The latter is due to the combination of reduced L2C noise (compared to L2P) and increased L1CA noise in those occultations where L2P would have failed. This result suggests application of OL tracking for L1CA and L2C signals throughout an entire occultation to optimally acquire RO data. Two methods of concurrent processing of L1CA and L2C RO signals are considered. Based on testing of individual occultations, these methods allow: (1) reduction in uncertainty of bending angles retrieved by wave optics in the lower troposphere and (2) reduction in small-scale residual errors of the ionospheric correction in the stratosphere.     

Non-linear motions of Australian geodetic stations induced by non-tidal ocean loading and the passage of tropical cyclones

We investigate daily and sub-daily non-tidal oceanic and atmospheric loading (NTOAL) in the Australian region and put an upper bound on potential site motion examining the effects of tropical cyclone Yasi that crossed the Australian coast in January/February 2011. The dynamic nature of the ocean is important, particularly for northern Australia where the long-term scatter due to daily and sub-daily oceanic changes increases by 20–55 % compared to that estimated using the inverted barometer (IB) assumption. Correcting the daily Global Positioning System (GPS) time series for NTOAL employing either a dynamic ocean model or the IB assumption leads to a reduction of up to 52 % in the weighted scatter of daily coordinate estimates. Differences between the approaches are obscured by seasonal variations in the GPS precision along the northern coast. Two compensating signals during the cyclone require modelling at high spatial and temporal resolution: uplift induced by the atmospheric depression, and subsidence induced by storm surge. The latter dominates ( \(>\) 135 %) the combined net effect that reaches a maximum of 14 mm, and 10 mm near the closest GPS site TOW2. Here, 96 % of the displacement is reached within 15 h due to the rapid transit of cyclones and the quasi-linear nature of the coastline. Consequently, estimating sub-daily NTOAL is necessary to properly account for such a signal that can be 3.5 times larger than its daily-averaged value. We were unable to detect the deformation signal in 2-hourly GPS processing and show that seasonal noise in the Austral summer dominates and precludes GPS detection of the cyclone-related subsidence.     

Statewide groundwater‐vulnerability assessment in nebraska using the drastic/GIS model

The paper summarizes a technique for implementing the “DRASTIC” groundwater‐vulnerability model within the context of an automated raster‐based geographic information system. Discussion focuses on a methodological development and a statewide project completed recently in Nebraska. The final products, a comprehensive flow chart illustrating procedures and a map of calculated potential pollution hazard, are presented. The methodology can be executed successfully with minimal training and experience. Areas of Nebraska considered vulnerable to groundwater pollution are identified.     

Determination of turbidity patterns of the Zhujiang estuarine region,South China,using satellite images and a GIS approach

Landsat MSS images and SPOT HRV data were employed to map the changes in turbidity levels in the Zhujiang estuarine region, South China, during the dry season in the period 1973–1987 at low and high tides. Analysis of turbidity trends and changes in the spatial pattern of high turbidity class was carried out with a GIS software—IDRISI. It was concluded that with the use of OVERLAY and RECLASS functions in the GIS approach a large number of turbidity maps could be easily compared and the turbidity trend determined. The GIS approach further permitted evaluation of the importance of such factors as water depths, mean tidal differences, and water salinity to sedimentation in the study region.     

Surface description for urban climate studies: A gis based methodology

In order to understand the nature of the urban climate, predict the effects of urbanization, or attempt to ameliorate some of the negative hydroclimatic effects of urbanization, it is necessary to have a good understanding of the role and significance of the urban surface. This paper presents a methodology which uses GIS to represent the characteristics and morphology of the urban surface, which can be used to describe a site objectively, model fluxes, or ensure spatial consistency between measured and modelled data, all of which can vary through time. The methodology is illustrated with respect to Chicago, Illinois. Surface data collected at three spatial scales were used to construct a georeferenced database which was linked to an objective, dynamic accessing system. Spatial variability of surface cover, derived hydroclimatic attributes, and modelled fluxes associated with changes in the urban environment are used to illustrate potential applications of the approach.     

Crop area monitoring within an advanced agricultural information system

This paper describes a framework for an image processing procedure for operational agricultural crop area estimation. This operational framework has been conceived within the development of an Advanced Agricultural Information System (AAIS) for the “Regione del Veneto “ (RdV ‐ Veneto Region) in northeastern Italy. The objective of this program is to develop the ability to generating timely and accurate area estimates and production information for four major agricultural crops: soybeans, sugar beets, corn, and small grains. AAIS uses state of the art methods in remote sensing and geographic information systems (GIS) technology and integrates a variety of data types including satellite imagery. This paper describes the methodology developed for image and ancillary data processing for the production of crop area statistics. Using a combination of standard unsupervised classification and GIS operations that incorporate knowledge about the agricultural system, a “sequential masking” classification procedure was derived. This sequential masking procedure yielded crop classification accuracies that at the study site level range between 76% and 99% depending on the crop under study. We believe that classification accuracies will improve with full system implementation, along with the incorporation of new and/or improved thematic information and operational experience using AAIS‐based estimation.     

Computerized Database of Salt Affected Soils for Agro‐climatic Regions in the Indo–Gangetic Plain of India Using GIS

Abstract

Indo_Gangetic Plain (IGP) of India that stretched from the foothills of Himalayas near the Punjab State to the Gangetic delta in West Bengal State was known for highly fertile soil and favorable climatic condition for highest production of rice‐wheat. Appearance of soil salinity in large areas of IGP caused a major concern due to loss of productivity. The salt affected soils maps of India (NRSA 1997) showed vast areas of salt affected soils distributed along the Gangetic Plain covering the States of Haryana, Punjab, Uttar Pradesh, Bihar and West Bengal. In the analogue form, these maps contain voluminous data were difficult to handle without messing the whole dataset. An attempt was made to prepare a digitized database of salt affected soils to facilitate easy access, retrieval and map calculations required for reclamation and management of salt affected soil. The salt affected soils maps on 1:250, 000 scale were digitized for the States of Punjab, Haryana, Uttar Pradesh, Bihar and West Bengal using ILWIS. GIS. The Survey of India topomap was used for geo‐referencing and basemap preparation overlaying thematic layers for administrative and political boundaries, infrastructure, irrigation and drainage and settlements. The attribute data on physiography and the soil characteristics were stored in an attribute table and linked with the digitized polygons to prepare a relational database. Combining geo‐referenced (State) maps of Haryana, Punjab, Uttar Pradesh, Bihar and West Bengal using GIS, a composite map for Indo‐Gangetic plain was prepared. Four Agroclimatic regions (ACRs) and seventeen Agroclimatic zones (ACZs) were identified in the Indo‐Gangetic Plain (The Planning Commission of India) for planning and development of natural resources at regional level. The boundaries of ACZs and ACRs were delineated from the primary (master) database of IGP using ILWIS.GIS. The distribution of SAS polygons at regional and zonal level was delineated superimposing digitized boundaries of ACRs and ACZs over the master database of IGP. The state‐wise, region‐wise and zone‐wise extent of SAS was calculated. Soils were essentially saline at Lower‐ and Middle Gangetic Plain regions but highly variable and complex saline‐sodic in the Upper‐ and Trans‐Gangetic Plain regions. The area statistics showed that maximum SAS area occurred in ACR V (Upper Gangetic Plain) in Uttar Pradesh (UP) followed by ACR IV (Middle Gangetic Plain) in UP and Bihar, ACR III (Lower Gangetic Plain) in West Bengal and ACR VI (Trans‐Gangetic Plain) of Haryana and Punjab. Such database in digital format provides geo‐referenced, easy to access and retrievable, relational database comprising of thematic and attribute information of salt affected soils at state, regional and zonal level to facilitate overlay and map calculation of related data such as water quality, climatic, landform etc, useful for planning and decision making in reclamation and management of salt affected soils in IGP and other similar regions.     

Computerized database on salt affected soils in western and central India using GIS

Salt affected soils occupy significant areas in western and central India manifested by the arid and semiarid climate, sandy/clayey soil texture, absence of natural drainage, and inadequate infrastructure and irrigation development. These soils are productive following reclamation and appropriate management. The National Remote Sensing Agency, Hyderabad (India) published state-wise maps of salt affected soils in India on 1:250,000 scale using a legend that includes physiography, soil characteristics, and the aerial extent of the mapping units. In the analogue form, voluminous data contained in such maps were difficult to handle by users of varied backgrounds. An attempt was made to prepare a computerized database of salt affected soils for easy access, retrieval, and manipulation of spatial and attribute data useful for management of salt affected soils. The salt affected soils maps were prepared, for Rajasthan, Gujarat, Madhya Pradesh, and Maharashtra states, overlaying digitized layers of SAS polygons and the Survey of India basemap using the ILWIS (Integrated Land and Water Information System) software. GIS was used to prepare a composite (master) database of western and central India that showed the extent and distribution of salt affected soils. A relational database was prepared combining the digitized polygons with soil characteristics such as nature and degree of salinity (presence of higher concentration of neutral salts and neutral soil reaction), sodicity (presence of higher concentration of basic salts and alkaline reaction) and ground coverage. The regional and zonal databases of salt affected soils were prepared at a suitable scale overlaying agro-climatic regions agro-climatic zones. Spatial relation of salt affected soils with physiography, climate, geology, and agro-eco-sub-regions were evaluated employing map calculations in GIS. Saline soils were prevalent in Gujarat, and Rajasthan while sodic soils were dominant in Maharashtra and Madhya Pradesh. These were distributed primarily in the arid (B) plain of Rajasthan, alluvial (A) and coastal (D) plains of Gujarat, and peninsular plain (F) of Maharashtra and Madhya Pradesh. It occupied 2,596,942 ha (78%) in the western (Rajasthan and Gujarat) and 733,608 ha (22%) in the central (Madhya Pradesh and Maharashtra) regions. The SAS occupied 3.3 million ha in the western and central region constituting 50% of the total salt affected soils in India. The saline and sodic soils occupied 2,069,285 ha (62%) and 1,261,266 ha (38%), respectively.     

Mapping spiny aster infestations with QuickBird imagery

QuickBird satellite imagery acquired in June 2003 and September 2004 was evaluated for detecting the noxious weed spiny aster [Leucosyris spinosa (Benth.) Greene] on a south Texas, USA rangeland area. A subset of each of the satellite images representing a diversity of cover types was extracted and used as a study site. The satellite imagery had a spatial resolution of 2.8 m and contained 11-bit data. Unsupervised and supervised classification techniques were used to classify false colour composite (green, red, and near-infrared bands) images of the study site. Imagery acquired in June was superior to that obtained in September for distinguishing spiny aster infestations. This was attributed to differences in spiny aster phenology between the two dates. An unsupervised classification of the June image showed that spiny aster had producer's and user's accuracies of 90% and 93.1%, respectively, whereas a supervised classification of the June image had producer's and user's accuracies of 90% and 81.8%, respectively. These results indicate that high resolution satellite imagery coupled with image analysis techniques can be used successfully for detecting spiny aster infestations on rangelands.