Ionospheric climatology derived from gps occultation observations made by the ionospheric occultation experiment

The ionospheric occultation experiment (IOX) is a GPS occultation sensor with an ionospheric mission focus. IOX measurements of GPS L1 and L2 carrier phase during Earth limb views of setting GPS satellites are used together with the Abel transform to determine vertical profiles of electron density from which F-region peak parameters are determined. Data from a four and a half month period beginning in November 2001 are statistically binned and compared with a climatological model. To account for potential errors in interpretation that could arise from violation of the Abel transform assertion of spherical symmetry, the data are compared to both the climatology and to statistics of simulated ionospheric inversions using the climatological model. General characteristics of the climatology are reproduced by the occultation data. However, several significant discrepancies between the model and the data are observed during this near-solar maximum time period. In particular, average mid-latitude daytime densities are shown to be higher than the climatological prediction and the height of F2 layer in the post-sunset equatorial region is underestimated by up to 150 km.

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Forest cover mapping of East district,Sikkim using IRS-1A LISS II satellite data

Remote sensing techniques have been applied to classify tour density classes within each of the forest type along with other major landuse/landcover classes in the East district, Sikkim using IRS-1A LISS II satellite data pertaining to the period of November, 1988. The shadow problem in rugged terrain and difficulty in acquiring cloud free data for different seasons pose problems to achieve considerable mapping accuracy. In the present study, the forests of the district were delineated through supervised classification techniques using maximum likelihood algorithm into five forest types as sal forests, subtropical broad-leaved forests, Himalayan wet temperate forests, Rhododendron forests and alpine forests. The alpine forests were further stratified into two categories as moist alpine scrub and dry alpine scrub. The statistical data obtained from the present study shows that 55.47 percent of the total geographical area of the East district was under forest cover. An overall accuracy of more than 85 percent in correctly delineating forest classes was achieved.     

Analyzing multi-year rice-fallow dynamics in Odisha using multi-temporal Landsat-8 OLI and Sentinel-1 Data

ABSTRACT

Sustainable intensification of existing cropland is one of the most viable options for meeting the escalating food demands of the ever-increasing population in the world. Accurate geospatial data about the potential single-crop (rice-fallows) areas is vital for policymakers to target the agro-technologies for enhancing crop productivity and intensification. Therefore, the study aimed to evaluate and understand the dynamics of rice-fallows in the Odisha state of India, using SAR (Sentinel-1) and Optical (Landsat OLI) datasets. This study utilized a decision-tree approach and Principal component analysis (PCA) for the segmentation and separation of different vegetation classes. The estimated overall accuracy of extracted rice-fallow maps was in the range of 84 to 85 percent. The study identified about 2.2, 2.0 and 2.1mha of Rice-Fallows in the years 2015–16, 2016–17, and 2017–18, respectively. The combined analysis (all three years) of rice-fallow maps identified about 1.34mha of permanent rice-fallows, whereas the remaining 0.6–0.8mha area was under the current-fallow category. About 50% of the total permanent rice-fallows were detected in the rainfed areas of Mayurbhanj, Bhadrak, Bolangir, Sundargarh, Keonjhar, Baleswar, Nawarangpur and Bargarh districts. The study also illustrated the time-series profiles of SMAP (soil moisture) datasets for the ten agroclimatic zones of the Odisha, which can be utilized (along with rice-fallow maps) for the selection of crop and cultivars (e.g. short or medium duration pulses or oilseeds) to target the rice fallows. The approach utilized in the current study can be scaled up in similar areas of South and South-east Asia and Africa to identify single-crop areas for targeting improved technologies for enhanced crop productivity and intensification.     

AnnGIS: Integration of GIS and a Continuous Simulation Model for Non-Point Source Pollution Assessment

Non-Point Source (NPS) models and monitoring data are often used to evaluate management practices and develop NPS pollution control plans. Application of a dynamic NPS model requires efficient input data acquisition, storage, organization, reduction, and analysis accompanied by manipulation, interpretation, reporting, and display of model outputs. A Geographic Information System (GIS) helps extract, store, and organize input data as well as manipulate and display model outputs. This paper illustrates the development of an integrated GIS system for a continuous simulation, pollutant-loading model, AnnAGNPS ( Ann ualized AG ricultural N on- P oint S ource Pollution). The integrated system, called AnnGIS, was developed using the ArcView GIS and related program extensions. Using AnnGIS, modeling studies and management plans can be efficiently and easily developed. AnnGIS helps store, organize, and manipulate spatial and tabular data, extract spatial input parameters, develop analysis scenarios, and visualize input and output data in spatial, tabular, and graphical forms. AnnGIS is generic in nature (not limited to a particular geographic location) and can be successfully used in regions for which AnnAGNPS is designed. AnnGIS's powerful graphical user interface and reference data sets facilitate efficient and informed decision-making concerning agricultural non-point pollution control and management.     

Lineaments and seismicity of Kerala — a remote sensing based analysis

Seismically active lineaments of Kerala State were identified by correlating the lineaments mapped using IRS LISS-I data with the earthquake occurrences. There are 31 earthquake incidences in Kerala since 1821, out of which 22 are falling on/close to 9 major lineaments/faults (length more than 20 km) indicating the possible correlation between lineaments/faults and earthquakes. It was observed that the earthquake occurrences are mostly associated with the NNW-SSE to NW-SE trending lineaments (6 out of 9 lineaments), which are considered to be formed sympathetic to the West Coast Fault. Hence, there is a need to monitor these seismically active lineaments using advanced techniques such as GPS, SAR Interferometry etc. for better understanding of the influence of these lineaments on the seismic activities of Kerala.