Indian Space Research Organisation

The search for water on the surface of the anhydrous Moon had remained an unfulfilled quest for 40 years. However, the Moon Mineralogy Mapper (M3) on Chandrayaan-1 has recently detected absorption features near 2.8 to 3.0 micrometers on the surface of the Moon. For silicate bodies, such features are typically attributed to hydroxyl- and/or water-bearing materials. On the Moon, the feature is seen as a widely distributed absorption that appears strongest at cooler high latitudes and at several fresh feldspathic craters. The general lack of correlation of this feature in sunlit M3 data with neutron spectrometer hydrogen abundance data suggests that the formation and retention of hydroxyl and water are ongoing surficial processes. Hydroxyl/water production processes may feed polar cold traps and make the lunar regolith a candidate source of volatiles for human exploration.

Crop diseases are a noteworthy risk to sustenance security, however their quick distinguishing proof stays troublesome in numerous parts of the world because of the non attendance of the important foundation. Emergence of accurate techniques in the field of leaf-based image classification has shown impressive results. This paper makes use of Random Forest in identifying between healthy and diseased leaf from the data sets created. Our proposed paper includes various phases of implementation namely dataset creation, feature extraction, training the classifier and classification. The created datasets of diseased and healthy leaves are collectively trained under Random Forest to classify the diseased and healthy images. For extracting features of an image we use Histogram of an Oriented Gradient (HOG). Overall, using machine learning to train the large data sets available publicly gives us a clear way to detect the disease present in plants in a colossal scale.

A new 1 km global IIASA-IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo-Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA-IFPRI cropland product has been validated using very high-resolution satellite imagery via Geo-Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo-Wiki. The first ever global field size map was produced at the same resolution as the IIASA-IFPRI cropland map based on interpolation of field size data collected via a Geo-Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website.

The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOTST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" shortterm tracking in RGB, (iii) VOT-LT2019 focused on longterm tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard shortterm, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website.

This paper presents a constructive solution to the problem of designing a reduced-order Luenberger observer for linear systems subject to arbitrary unknown inputs.

The explosive growth and uneven distribution of population, poor irrigation practices, rapid urbanization/industrialization, large-scale deforestation and improper land use practices have induced the depletion and pollution of both the surface and groundwater resources in India. In addition, recurrent drought further aggravates the problem of water even for drinking, especially in rural areas. In order to ensure 'Health for All', the Government of India has launched many programmes to provide potable drinking water to every settlement in the country within the next five years. In order to accomplish these tasks, the systematic planning of groundwater exploitation using modern technologies is essential for the proper utilization of this precious natural resource. On this basis, we extracted information on lithology, geological structures, landforms, land use/land cover from remotely sensed data and drainage networks, soil characteristics and slope of the terrain using conventional methods and then integrated in a Geographical Information System (GIS) environment to depict village-wise groundwater prospect zones. Thus, a GIS-based model which takes account of local condition/variations has been developed specifically for mapping groundwater prospects. A pilot study was carried out for the Gorna sub-basin, a part of the Son watershed, Madhya Pradesh, India. Information from this study could be used for effective identification of suitable locations for extraction of potable water for rural populations.

Land use is central to addressing sustainability issues, including biodiversity conservation, climate change, food security, poverty alleviation, and sustainable energy. In this paper, we synthesize knowledge accumulated in land system science, the integrated study of terrestrial social-ecological systems, into 10 hard truths that have strong, general, empirical support. These facts help to explain the challenges of achieving sustainability in land use and thus also point toward solutions. The 10 facts are as follows: 1) Meanings and values of land are socially constructed and contested; 2) land systems exhibit complex behaviors with abrupt, hard-to-predict changes; 3) irreversible changes and path dependence are common features of land systems; 4) some land uses have a small footprint but very large impacts; 5) drivers and impacts of land-use change are globally interconnected and spill over to distant locations; 6) humanity lives on a used planet where all land provides benefits to societies; 7) land-use change usually entails trade-offs between different benefits-"win-wins" are thus rare; 8) land tenure and land-use claims are often unclear, overlapping, and contested; 9) the benefits and burdens from land are unequally distributed; and 10) land users have multiple, sometimes conflicting, ideas of what social and environmental justice entails. The facts have implications for governance, but do not provide fixed answers. Instead they constitute a set of core principles which can guide scientists, policy makers, and practitioners toward meeting sustainability challenges in land use.

Inspiration is useful for exploration and discovery of new solution spaces. Systems in natural and artificial worlds and their functionality are seen as rich sources of inspiration for idea generation. However, unlike in the artificial domain where existing systems are often used for inspiration, those from the natural domain are rarely used in a systematic way for this purpose. Analogy is long regarded as a powerful means for inspiring novel idea generation. One aim of the work reported here is to initiate similar work in the area of systematic biomimetics for product development, so that inspiration from both natural and artificial worlds can be used systematically to help develop novel, analogical ideas for solving design problems. A generic model for representing causality of natural and artificial systems has been developed, and used to structure information in a database of systems from both the domains. These are implemented in a piece of software for automated analogical search of relevant ideas from the databases to solve a given problem. Preliminary experiments at validating the software indicate substantial potential for the approach.

Abstract In order to demarcate the ground water potential zones of Marudaiyar basin different thematic maps such as, lithology, landforms, lineaments and surface water bodies at a 1: 50000 scale were prepared, using remotely-sensed data as well as drainage density and slope classes from Survey of India topographical sheets. In addition, a soil map at 1:50000 scale covering the study area was generated from a 1:250000 scale soil map prepared by the Soil Survey and Landuse Organization by regrouping the soil types based on their hydrological characteristics. All the thematic layers were integrated and analysed using a model developed with logical conditions in the geographical information system (GIS). The ground water potential zones map generated through this model was verified with the yield data to ascertain the validity of the model developed. The verification showed that the ground water potential zones demarcated through the model are in agreement with the bore well yield data collected in the field. Since the present approach was built with logical conditions and reasoning, this approach can be successfully used elsewhere with appropriate modifications. Thus, the above study has clearly demonstrated the capabilities of remote sensing technique and GIS in demarcation of the different ground water potential zones, particularly in such a diverse geological set up.

The Indo‐Gangetic Plain (IGP) encompasses a vast area, (accounting for ∼21% of the land area of India), which is densely populated (accommodating ∼40% of the Indian population). Highly growing economy and population over this region results in a wide range of anthropogenic activities. A large number of thermal power plants (most of them coal fed) are clustered along this region. Despite its importance, detailed investigation of aerosols over this region is sparse. During an intense field campaign of winter 2004, extensive aerosol and atmospheric boundary layer measurements were made from three locations: Kharagpur (KGP), Allahabad (ALB), and Kanpur (KNP), within the IGP. These data are used (1) to understand the regional features of aerosols and BC over the IGP and their interdependencies, (2) to compare it with features at locations lying at far away from the IGP where the conditions are totally different, (3) to delineate the effects of mesoscale processes associated with changes in the local atmospheric boundary layer (ABL), (4) to investigate the effects of long‐range transport or moving weather phenomena in modulating the aerosol properties as well as the ABL characteristics, and (5) to examine the changes as the season changes over to spring and summer. Our investigations have revealed very high concentrations of aerosols along the IGP, the average mass concentrations ( M T ) of total aerosols being in the range 260 to 300 μ g m −3 and BC mass concentrations ( M B ) in the range 20 to 30 μ g m −3 (both ∼5 to 8 times higher than the values observed at off‐IGP stations) during December 2004. Despite, BC constituted about 10% to the total aerosol mass concentration, a value quite comparable to those observed elsewhere over India for this season. The dynamics of the local atmospheric boundary layer (ABL) as well as changes in local emissions strongly influence the diurnal variations of M T and M B , both being inversely correlated with the mixed layer height ( Z i ) and the ventilation coefficient ( V c ). The share of BC to total aerosols is highest (∼12%) during early night and lowest (∼4%) in the early morning hours. While an increase in the V c results in a reduction in the concentration almost simultaneously, an increase in Z imax has its most impact on the concentration after ∼1 day. Accumulation mode aerosols contributed ∼90% to the aerosol concentration at ALB, ∼77 % at KGP and 74% at KNP. The BC mass mixing ratio was ∼10% over all three locations and is comparable to the value reported for Trivandrum, a tropical coastal location in southern India. This indicates presence of submicron aerosols species other than BC (such as sulfate) over KGP and KNP. A cross‐correlation analysis showed that the changes in M B at KGP is significantly correlated with those at KNP, located ∼850 km upwind, and ALB after a delay of ∼7 days, while no such delay was seen between ALB and KNP. Back trajectory analyses show an enhancement in M B associated with trajectories arriving from west, the farther from to the west they arrive, the more is the increase. This, along with the ABL characteristics, indicate two possibilities: (1) advection of aerosols from the west Asia and northwest India and (2) movement of a weather phenomena (such as cold air mass) conducive for build up of aerosols from the west to east. As the winter gives way to summer, the change in the wind direction and increased convective mixing lead to a rapid decrease in M B .

Errors encountered in digital transmission over most real communication channels are not independent but appear in clusters. Such channels are said to exhibit memory, i.e., statistical dependence in the occurrence of errors; and thus cannot be adequately represented by the classical memoryless binary symmetric channel. The existence of memory implies additional capacity. To exploit this through efficient coding schemes, it is necessary to describe and model the underlying statistical structure of the error process. This paper reviews various channel models, noting the interaction between channel modeling and error control.

Abstract We assess the urbanization impacts on the heavy rainfall climatology during the Indian summer monsoon. While a number of studies have identified the impact of urbanization on local precipitation, a large‐scale assessment has been lacking. This relation between urbanization and Indian monsoon rainfall changes is investigated by analyzing in situ and satellite‐based precipitation and population datasets. Using a long‐term daily rainfall dataset and high‐resolution gridded analysis of human population, this study showed a significantly increasing trend in the frequency of heavy rainfall climatology over urban regions of India during the monsoon season. Urban regions experience less occurrences of light rainfall and significantly higher occurrences of intense precipitation compared to nonurban regions. Very heavy and extreme rainfall events showed increased trends over both urban and rural areas, but the trends over urban areas were larger and statistically more significant. Our analysis suggests that there is adequate statistical basis to conclude that the observed increasing trend in the frequency of heavy rainfall events over Indian monsoon region is more likely to be over regions where the pace of urbanization is faster. Moreover, rainfall measurements from satellites also indicate that urban areas are more (less) likely to experience heavier (lighter) precipitation rates compared to those in nonurban areas. While the mechanisms causing this enhancement in rainfall remain to be studied, the results provide the evidence that the increase in the heavy rainfall climatology over the Indian monsoon region is a signature of urban‐induced rainfall anomaly. Copyright © 2009 Royal Meteorological Society

SUMMARY Block diagonalization of binary matrices is a primary step in the design of cellular production systems. ‘Grouping efficiency’ which is a weighted average of two measures that consider the voids in the diagonal blocks and exceptional elements in the off-diagonal blocks was the only criterion available to measure the goodness of block diagonal forms. The present work critically analyses this function and brings out its shortcomings, the most severe of them being its low discriminating power. A simple and elegant function has been derived in its place. The new function called grouping efficacy obviates all the defects of the earlier function while retaining the requisite properties. The mathematical properties of the function have been analysed and the function values compared with those of grouping efficiency in the case of well-structured and ill-structured data sets.

Himalayas possess one of the largest resources of snow and ice, which act as a huge freshwater reservoir. Monitoring the glaciers is important to assess the overall reservoir health. In this investigation glacial retreat was estimated for 466 glaciers in Chenab, Parbati and Baspa basins from 1962. Expeditions to Chhota Shigri, Patsio and Samudra Tapu glaciers in Chenab basin, Parbati glacier in Parbati basin and Shaune Garang glacier in Baspa basin were organized to identify and map glacial terminus. The investigation has shown, an overall reduction in glacier area from 2077 sq km to 1628 sq km from 1962, an overall deglaciation of 21 percent. However, number of glaciers is increased due to fragmentation. Mean of glacial extent was reduced from 1.4 to 0.32 km² between 1962 and 2001. In addition, number of glaciers with higher areal extent is reduced and lower areal extent has been increased between the periods. Small glaciarates and ice fields have shown extensive deglaciation. For example, 127 glaciarates and ice fields less than 1 km² have shown retreat of 38 percent from 1962, possibly due to small response time. This means combination glacial fragmentation, higher retreat of small glaciers and climate change are influencing sustainability of Himalayan glaciers.

[1] The NASA Discovery Moon Mineralogy Mapper imaging spectrometer was selected to pursue a wide range of science objectives requiring measurement of composition at fine spatial scales over the full lunar surface. To pursue these objectives, a broad spectral range imaging spectrometer with high uniformity and high signal-to-noise ratio capable of measuring compositionally diagnostic spectral absorption features from a wide variety of known and possible lunar materials was required. For this purpose the Moon Mineralogy Mapper imaging spectrometer was designed and developed that measures the spectral range from 430 to 3000 nm with 10 nm spectral sampling through a 24 degree field of view with 0.7 milliradian spatial sampling. The instrument has a signal-to-noise ratio of greater than 400 for the specified equatorial reference radiance and greater than 100 for the polar reference radiance. The spectral cross-track uniformity is >90% and spectral instantaneous field-of-view uniformity is >90%. The Moon Mineralogy Mapper was launched on Chandrayaan-1 on the 22nd of October. On the 18th of November 2008 the Moon Mineralogy Mapper was turned on and collected a first light data set within 24 h. During this early checkout period and throughout the mission the spacecraft thermal environment and orbital parameters varied more than expected and placed operational and data quality constraints on the measurements. On the 29th of August 2009, spacecraft communication was lost. Over the course of the flight mission 1542 downlinked data sets were acquired that provide coverage of more than 95% of the lunar surface. An end-to-end science data calibration system was developed and all measurements have been passed through this system and delivered to the Planetary Data System (PDS.NASA.GOV). An extensive effort has been undertaken by the science team to validate the Moon Mineralogy Mapper science measurements in the context of the mission objectives. A focused spectral, radiometric, spatial, and uniformity validation effort has been pursued with selected data sets including an Earth-view data set. With this effort an initial validation of the on-orbit performance of the imaging spectrometer has been achieved, including validation of the cross-track spectral uniformity and spectral instantaneous field of view uniformity. The Moon Mineralogy Mapper is the first imaging spectrometer to measure a data set of this kind at the Moon. These calibrated science measurements are being used to address the full set of science goals and objectives for this mission.

For more than 20 years the Normalized Difference Vegetation Index (NDVI) has been widely used to monitor vegetation stress. It takes advantage of the differential reflection of green vegetation in the visible and near-infrared (NIR) portions of the spectrum and provides information on the vegetation condition. The Land Surface Water Index (LSWI) uses the shortwave infrared (SWIR) and the NIR regions of the electromagnetic spectrum. There is strong light absorption by liquid water in the SWIR, and the LSWI is known to be sensitive to the total amount of liquid water in vegetation and its soil background. In this study we investigated the LSWI characteristics relative to conventional NDVI-based drought assessment, particularly in the early crop season. The area chosen for the study was the state of Andhra Pradesh located in the Indian peninsular. The Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Index (VI) product from the Aqua satellite was used in the study. The analysis was carried out for the years 2002 (deficit year) and 2005 (normal year) using the NDVI from the MODIS VI product and deriving the LSWI using the NIR and SWIR reflectance available with the MODIS VI product. The response of LSWI to rainfall, observed in the rate of increase in LSWI in the subsequent fortnights, shows that this index could be used to monitor the increase in soil and vegetation liquid water content, especially during the early part of the season. The relationship between the cumulative rainfall and the current fortnight LSWI is stronger in the low rainfall region (<500 mm), while the one-fortnight lagged LSWI had a stronger relationship in the high rainfall region (>500 mm). The relationship between LSWI and the cumulative rainfall for the entire state was mixed in 2002 and 2005. The strength of the relationship was weak in the high rainfall region. When LSWI was regressed directly with NDVI for three LSWI ranges, it was observed that the NDVI with the one-fortnight lag had a strong relationship with the LSWI in most of the categories.

This study explores the scope for achieving enhanced recognition system performance through deployment of a composite classifier system consisting of two or more component classifiers which belong to different categories. The domains of deployment of these individual components (classifiers) are determined by optimal partitioning of the problem space. The criterion for such optimal partitioning is determined in each case by the characteristics of the classifier components. An example, in terms of partitioning the feature space for optimal deployment of a composite system consisting of the linear and nearest neighbor (NN) classifiers as its components, is presented to illustrate the concepts, the associated methodology, and the possible benefits one could expect through such composite classifier system design. Here, the optimality of the partitioning is dictated by the linear class separability limitation of the linear classifier and the computational demand characteristics of the NN classifier. Accordingly, the criterion for the optimal feature space partitioning is set to be the minimization of the domain of application of the NN classifier, subject to the constraint that the linear classifier is to be deployed only in regions satisfying the underlying assumption of linear separability of classes. While many alternatives are available for the solution of the resulting constrained optimization problem, a specific technique-Sequential Weight Increasing Factor Technique (SWIFT)- was employed here for convenience in view of previous successful experience with this technique in other application areas. Numerical results derived using the well-known IRIS data set are furnished to demonstrate the effectiveness of the new concepts and methodology.

To detect landslides by object-based image analysis using criteria based on shape, color, texture, and, in particular, contextual information and process knowledge, candidate segments must be delineated properly. This has proved challenging in the past, since segments are mainly created using spectral and size criteria that are not consistent for landslides. This paper presents an approach to select objectively parameters for a region growing segmentation technique to outline landslides as individual segments and also addresses the scale dependence of landslides and false positives occurring in a natural landscape. Multiple scale parameters were determined using a plateau objective function derived from the spatial autocorrelation and intrasegment variance analysis, allowing for differently sized features to be identified. While a high-resolution Resourcesat-1 Linear Imaging and Self Scanning Sensor IV (5.8 m) multispectral image was used to create segments for landslide recognition, terrain curvature derived from a digital terrain model based on Cartosat-1 (2.5 m) data was used to create segments for subsequent landslide classification. Here, optimal segments were used in a knowledge-based classification approach with the thresholds of diagnostic parameters derived from If-means cluster analysis, to detect landslides of five different types, with an overall recognition accuracy of 76.9%. The approach, when tested in a geomorphologically dissimilar area, recognized landslides with an overall accuracy of 77.7%, without modification to the methodology. The multiscale classification-based segment optimization procedure was also able to reduce the error of commission significantly in comparison to a single-optimal-scale approach.

Abstract A radar-based climatology of 91 unique summertime (May 2000–August 2009) thunderstorm cases was examined over the Indianapolis, Indiana, urban area. The study hypothesis is that urban regions alter the intensity and composition/structure of approaching thunderstorms because of land surface heterogeneity. Storm characteristics were studied over the Indianapolis region and four peripheral rural counties approximately 120 km away from the urban center. Using radar imagery, the time of event, changes in storm structure (splitting, initiation, intensification, and dissipation), synoptic setting, orientation, and motion were studied. It was found that more than 60% of storms changed structure over the Indianapolis area as compared with only 25% over the rural regions. Furthermore, daytime convection was most likely to be affected, with 71% of storms changing structure as compared with only 42% at night. Analysis of radar imagery indicated that storms split closer to the upwind urban region and merge again downwind. Thus, a larger portion of small storms (50–200 km 2 ) and large storms (&gt;1500 km 2 ) were found downwind of the urban region, whereas midsized storms (200–1500 km) dominated the upwind region. A case study of a typical storm on 13 June 2005 was examined using available observations and the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5), version 3.7.2. Two simulations were performed with and without the urban land use/Indianapolis region in the fourth domain (1.33-km resolution). The storm of interest could not be simulated without the urban area. Results indicate that removing the Indianapolis urban region caused distinct differences in the regional convergence and convection as well as in simulated base reflectivity, surface energy balance (through sensible heat flux, latent heat flux, and virtual potential temperature changes), and boundary layer structure. Study results indicate that the urban area has a strong climatological influence on regional thunderstorms.

In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion.