35 research outputs found

    Comparing the spatio-temporal variability of remotely sensed oceanographic parameters between the Arabian Sea and Bay of Bengal throughout a decade

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    The spatio-temporal variability of sea-surface temperature (SST), photosynthetically active radiation (PAR), chlorophyll-a (Chl-a), particulate organic carbon (POC) and particulate inorganic carbon (PIC) was evaluated in the Arabian Sea (ABS) and Bay of Bengal (BoB), from July 2002 to November 2014 by means of remotely sensed monthly composite Aqua MODIS level-3 data having a spatial resolution of 4.63 km. Throughout the time period under consideration, the surface waters of ABS (27.76 ± 1.12°C) were slightly cooler than BoB (28.93 ± 0.76°C); this was observed during all the seasons. On the contrary, the availability of PAR was higher in ABS (45.76 ± 3.41 mol m-2 d-1) compared to BoB (41.75 ± 3.75 mol m-2 d-1), and its spatial dynamics in the two basins was mainly regulated by cloud cover and turbidity of the water column. The magnitude and variability of Chl-a concentration were substantially higher in ABS (0.487 ± 0.984 mg m-3), compared to BoB (0.187 ± 0.243 mg m-3), and spatially higher values were observed near the coastal waters. Both POC and PIC exhibited higher magnitudes in ABS compared to BoB; however, the difference was substantially high in case of POC. None of the parameters showed any significant temporal trend during the 12-year span, except PIC, which exhibited a significant decreasing trend in ABS

    Analysis of parcel-based image classification methods for monitoring the activities of the Land Bank of Galicia (Spain)

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    [EN] The abandonment of agricultural plots entails a low economic productivity of the land and a higher vulnerability to wildfires and degradation of affected areas. In this sense, the local government of Galicia is promoting new methodologies based on high-resolution images in order to classify the territory in basic and generic land uses. This procedure will be used to control the sustainable management of plots belonging to the Land Bank. This paper presents an application study for maintaining and updating land use/land cover geospatial databases using parcel-oriented classification. The test is performed over two geographic areas of Galicia, in the northwest of Spain. In this region, forest and shrublands in mountain environments are very heterogeneous with many private unproductive plots, some of which are in a high state of abandonment. The dataset is made of high spatial resolution multispectral imagery, cadastral cartography employed to define the image objects (plots), and field samples used to define evaluation and training samples. A set of descriptive features is computed quantifying different properties of the objects, i.e. spectral, texture, structural, and geometrical. Additionally, the effect on the classification and updating processes of the historical land use as a descriptive feature is tested. Three different classification methodologies are analyzed: linear discriminant analysis, decision trees, and support vector machine. The overall accuracies of the classifications obtained are always above 90 % and support vector machine method is proved to provide the best performance. Forest and shrublands areas are especially undefined, so the discrimination between these two classes is low. The results enable to conclude that the use of automatic parcel-oriented classification techniques for updating tasks of land use/land cover geospatial databases, is effective in the areas tested, particularly when broad and well defined classes are required.The authors appreciate the collaboration and support provided by Xunta de Galicia, Sociedade para o Desenvolvemento Comarcal de Galícia, and Banco de Terras de Galicia. The financial support provided by the Spanish Ministerio de Ciencia e Innovación in the framework of the projects CGL2010-19591/BTE and CGL2009-14220 is also acknowledged.Hermosilla, T.; Díaz Manso, J.; Ruiz Fernández, LÁ.; Recio Recio, JA.; Fernández-Sarría, A.; Ferradáns Nogueira, P. (2012). Analysis of parcel-based image classification methods for monitoring the activities of the Land Bank of Galicia (Spain). Applied Geomatics. 4(4):245-255. https://doi.org/10.1007/s12518-012-0087-zS24525544Arikan M (2004) Parcel-based crop mapping through multi-temporal masking classification of landsat 7 images in Karacabey, Turkey. Int Arch Photogramm Remote Sens Spat Inf Sci 35:1085–1090Balaguer A, Ruiz LA, Hermosilla T, Recio JA (2010) Definition of a comprehensive set of texture semivariogram features and their evaluation for object-oriented image classification. Comput Geosci 36(2):231–240Balaguer-Besser A, Hermosilla T, Recio JA, Ruiz LA (2011) Semivariogram calculation optimization for object-oriented image classification. Model Sci Educ Learn 4(7):91–104Blaschke T (2010) Object based image analysis for remote sensing. ISPRS J Photogramm 65(1):2–16Cohen Y, Shoshany M (2000) Integration of remote sensing, GIS and expert knowledge in national knowledge-based crop recognition in Mediterranean environment. Int Arch Photogramm Remote Sens 33(Part B7):280–286Congalton R (1991) A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens Environ 37(1):35–46Dadhwal VK, Singh RP, Dutta S, Parihar JS (2002) Remote sensing based crop inventory: a review of Indian experience. Trop Ecol 43(1):107–122De Wit AJW, Clevers JGPW (2004) Efficiency and accuracy of per-field classification for operational crop mapping. Int J Remote Sens 25:4091–4112Del Frate F, Pacifici F, Solimini D (2008) Monitoring urban land cover in Rome, Italy, and its changes by single-polarization multitemporal SAR images. IEEE J Sel Top Appl Earth Obs Remote Sens 1:87–97Díaz-Manso JM, Ferradáns-Nogueira P (2011) Modelo de uso actual da terra. In: Cobelle-Rico EJ, Diaz-Manso JM, Crecente-Maseda R, Martínez-Rivas EM (eds) Mercado e Mobilidade de Terras en Galícia, 1st edn. Servizo de Publicacións e Intercambio Científico, Santiago de Compostela, Spain, pp 31–44Dupas CA (2000) SAR and LANDSAT TM image fusion for land cover classification in the Brazilian Atlantic Forest Domain. Int Arch Photogramm Remote Sens XXXIII(Part B1):96–103El Kady M, Mack CB (1992) Remote sensing for crop inventory of Egypt’s old agricultural lands. Int Arch Photogramm Remote Sens 29:176–185Everitt BS, Dunn G (2001) Applied multivariate data analysis, 2nd edn. Edward Arnold, LondonHaralick RM, Shanmugam K, Dinstein I (1973) Texture features for image classification. IEEE Transact Syst Man Cybern 3(6):610–622Hermosilla T, Almonacid J, Fernández-Sarría A, Ruiz LA, Recio JA (2010) Combining features extracted from imagery and lidar data for object-oriented classification of forest areas. Int Arch Photogramm Remote Sens Spat Inf Sci 38(4/C7)Hernández Orallo J, Ramírez Quintana MJ, Ferri Ramírez C (2004) Introducción a la minería de datos. Pearson Educación S.A, MadridHomer C, Huang C, Yang L, Wylie B, Coan M (2004) Development of a 2001 National Land-Cover Database for the United States. Photogramm Eng Remote Sens 70:829–840Huberty CJ (1994) Applied discriminant analysis. Wiley, New YorkLaws KI (1985) Goal-directed texture image segmentation. Appl Artif Intel II, SPIE 548:19–26Ormeci C, Alganci U, Sertel E (2010) Identification of crop areas using SPOT-5 data, FIG Congress 2010 Facing the Challenges—building the capacity. Sydney, Australia, pp 11–16Peled A, Gilichinsky M (2004) GIS-driven analyses of remotely sensed data for quality assessment of existing land cover classification. Int Arch Photogramm Remote Sens Spat Inf Sci 35Peled A, Gilichinsky M (2010) Knowledge-based classification of land cover for the quality assessment of GIS database. Int Arch Photogramm Remote Sens Spat Inf Sci 38:217–222Perveen F, Nagasawa R, Ali S, Husnain (2008) Evaluation of ASTER spectral bands for agricultural land cover mapping using pixel-based and object-based classification approaches. Int Arch Photogramm Remote Sens Spat Inf Sci 37(4-C1)Petit CC, Lambin EF (2002) Impact of data integration technique on historical land-use/land-cover change: comparing historical maps with remote sensing data in the Belgian Ardennes. Landsc Ecol 17:117–132Quinlan JR (1993) C4.5: Programs for machine learning. Kaufmann, San FranciscoRabe A, van der Linden S, Hostert P (2010) imageSVM, Version 2.1. www.hu-geomatics.deRecio JA, Hermosilla T, Ruiz LA, Fernández-Sarría A (2011) Historical land use as a feature for image classification. Photogramm Eng Remote Sens 77(4):377–387Ruiz LA, Fernández-Sarría A, Recio JA (2004) Texture feature extraction for classification of remote sensing data using wavelet decomposition: a comparative study. Int Arch Photogramm Remote Sens Spat Inf Sci 35(B4):1109–1115Ruiz LA, Recio JA, Hermosilla T, Fdez. Sarriá A (2009) Identification of agricultural and land cover database changes using object-oriented classification techniques. 33rd International Symposium on Remote Sensing of Environment, May 4–8, Stresa (Italy)Ruiz LA, Recio JA, Fernández-Sarría A, Hermosilla T (2011) A feature extraction software tool for agricultural object-based image analysis. Comput Electron Agric 76(4):284–296Tansey K, Chambers I, Anstee A, Denniss A, Lamb A (2009) Object-oriented classification of very high resolution airborne imagery for the extraction of hedgerows and field margin cover in agricultural areas. Appl Geogr 29(2):145–157van der Linden S, Rabe A, Wirth F, Suess S, Okujeni A, Hostert P (2010) imageSVM regression, application manual: imageSVM version 2.1. Humboldt-Universität zu Berlin, GermanyVapnik VN (1998) Statistical learning theory. Wiley, New YorkWalsh SJ, McCleary AL, Mena CF, Shao Y, Tuttle JP, Gonzalez A, Atkinson R (2008) QuickBird and Hyperion data analysis of an invasive plant species in the Galapagos Islands of Ecuador: implications for control and land use management. Remote Sens Environ 112(5):1927–1941Walter V (2004) Object-based classification of remote sensing data for change detection. ISPRS J Photogramm Remote Sens 58:225–238Walter V (2005) Object-based evaluation of lidar and multiespectral data for automatic change detection in GIS databases. Geo-Inf Syst 18:10–15Zaragozí, B, Rabasa, A, Rodríguez-Sala, JJ, Navarro, JT, Belda, A, Ramón, A (2012) Modelling farmland abandonment: A study combining GIS and data mining techniques. Agric Ecosys Environ 155:124–132Zhang S, Liu X (2005) Realization of data mining model for expert classification using multi-scale spatial data. Int Arch Photogramm Remote Sens Spat Inf Sci 26(4/W6):107–11

    Forest carbon stocks and fluxes in physiographic zones of India

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    <p>Abstract</p> <p>Background</p> <p>Reducing carbon Emissions from Deforestation and Degradation (REDD+) is of central importance to combat climate change. Foremost among the challenges is quantifying nation's carbon emissions from deforestation and degradation, which requires information on forest carbon storage. Here we estimated carbon storage in India's forest biomass for the years 2003, 2005 and 2007 and the net flux caused by deforestation and degradation, between two assessment periods i.e., Assessment Period first (ASP I), 2003-2005 and Assessment Period second (ASP II), 2005-2007.</p> <p>Results</p> <p>The total estimated carbon stock in India's forest biomass varied from 3325 to 3161 Mt during the years 2003 to 2007 respectively. There was a net flux of 372 Mt of CO<sub>2 </sub>in ASP I and 288 Mt of CO<sub>2 </sub>in ASP II, with an annual emission of 186 and 114 Mt of CO<sub>2 </sub>respectively. The carbon stock in India's forest biomass decreased continuously from 2003 onwards, despite slight increase in forest cover. The rate of carbon loss from the forest biomass in ASP II has dropped by 38.27% compared to ASP I.</p> <p>Conclusion</p> <p>With the Copenhagen Accord, India along with other BASIC countries China, Brazil and South Africa is voluntarily going to cut emissions. India will voluntary reduce the emission intensity of its GDP by 20-25% by 2020 in comparison to 2005 level, activities like REDD+ can provide a relatively cost-effective way of offsetting emissions, either by increasing the removals of greenhouse gases from the atmosphere by afforestation programmes, managing forests, or by reducing emissions through deforestation and degradation.</p

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    Not AvailableAN ATTEMPT HAS BEEN MADE TO DOCUMENT THE INFORMATION ON THE CHARACTERISTICS OF LIMESTONE DEGRADED MINED LANDS IN THE WESTERN HIMALAYAS. WHILE DOING SO- GEO- CHARACTERISTICS, PHYSICO- CHEMICAL PROPERTIES , MINED SPOIL/DEBRIS FLOW AND RAINFALL VOLUME RELATIONSHIP AND EFFECT OF REHABILITATION MEASURES IN IMPROVING THE QUALITY OF WATER DETERIORATED DUE TO MINING AND SOME OTHER TOPICS HAVE BEEN DEALT WITH.Not Availabl

    Optimization of spectral bands for ocean colour remote sensing of aquatic environments

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    Selection of central wavelengths, bandwidths and the number of spectral bands of any sensor to be flown on a remote sensing satellite is important to ensure discriminability of targets and adequate signal-to-noise ratio for the retrieval of parameters. In recent years, a large number of spectral measurements over a wide variety of water types in the Arabian Sea and the Bay of Bengal have been carried out through various ship cruises. It was felt pertinent to use this precious data set to arrive at meaningful selection of spectral bands and their bandwidths of the ocean colour sensor to be flown on the forthcoming Oceansat-3 of ISRO. According to IOOCG reports and studies by Lee and Carder (2002) it is better for a sensor to have ~15 bands in the 400-800 nm range for adequate derivation of major properties (phytoplankton biomass, colored dissolved organic matter, suspended sediments, and bottom properties) in both oceanic and coastal environments from observation of water colo

    Tidal Circulation in the Hooghly Estuary and Adjacent Coastal Oceans

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    A terrain-following ocean general circulation model is implemented for simulating tidal and residual circulation patterns in the Hooghly Estuary and its adjacent coastal oceans (HECO) on the east coast of India. The model is forced with time-varying tidal levels and momentum fluxes at the eastern and southern open boundaries, and winds at the air�sea interface. Simulated tidal levels and currents are compared well with the observations. Based on model solutions, spatial patterns of semi-diurnal and diurnal tides and circulation are described. The residual circulation shows prevalence of ocean-ward along channel flow from north to south with distinct differential circulation patterns on its right and left flanks of the outer estuary. A mesoscale eddy associated with residual circulation has been occurring in the southwestern flank of the HECO, adjacent to the Digha coast. This is associated with enriched chlorophylla concentration (Chla), causing the region as the suitable place for the fishing activity. The residual currents in the left of the channel (toward the Sunderban) in the southeastern flank of the HECO are eastward and diverging in nature and are associated with reduced Chla. © 2019, Indian Society of Remote Sensing

    Coupling geomorphology parameters with lithology for micro-level groundwater resource assessment: a case study from semi-arid hard rock terrain in Tamil Nadu, India

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    The standard procedure of groundwater resource estimation in India till date is based on the specific yield parameters of each rock type (lithology) derived through pumping test analysis. Using the change in groundwater level, specific yield, and area of influence, groundwater storage change could be estimated. However, terrain conditions in the form of geomorphological variations have an important bearing on the net groundwater recharge. In this study, an attempt was made to use both lithology and geomorphology as input variables to estimate the recharge from different sources in each lithology unit influenced by the geomorphic conditions (lith-geom), season wise separately. The study provided a methodological approach for an evaluation of groundwater in a semi-arid hard rock terrain in Tirunelveli, Tamil Nadu, India. While characterizing the gneissic rock, it was found that the geomorphologic variations in the gneissic rock due to weathering and deposition behaved differently with respect to aquifer recharge. The three different geomorphic units identified in gneissic rock (pediplain shallow weathered (PPS), pediplain moderate weathered (PPM), and buried pediplain moderate (BPM)) showed a significant variation in recharge conditions among themselves. It was found from the study that Peninsular gneiss gives a net recharge value of 0.13 m/year/unit area when considered as a single unit w.r.t. lithology, whereas the same area considered with lith-geom classes gives recharge values between 0.1 and 0.41 m/year presenting a different assessment. It is also found from this study that the stage of development (SOD) for each lith-geom unit in Peninsular gneiss varies from 168 to 230 %, whereas the SOD is 223 % for the lithology as a single unit

    Tidal and Residual Circulation in the Gulf of Khambhat and its Surrounding on the West Coast of India

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    A terrain-following ocean model is implemented for simulating three-dimensional tidal and residual circulations in the Gulf of Khambhat and its adjacent oceans on the west coast of India. The model is forced with time varying tidal levels and momentum fluxes at the western and southern boundaries. Simulated tidal levels and currents compare well with the observation at tide gauge and current-meter stations. Estimated residual circulation in the region has several notable features that include strong southward along channel flow inside the gulf, northwestward propagating coastal boundary jet currents parallel the 60 m isobaths, southward slope currents, alongshore coastal currents on the southeastern flank of the shelf and a number of meso-scale eddies. All these features of residual circulation are captured well by the satellite imagery of Chlorophyll concentration mapped in the month of March, the period when tide plays dominant role on the control of net circulation in the region

    Phytomass carbon pool of trees and forests in India

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    The study reports estimates of above ground phytomass carbon pools in Indian forests for 1992 and 2002 using two different methodologies. The first estimate was derived from remote sensing based forest area and crown density estimates, and growing stock data for 1992 and 2002 and the estimated pool size was in the range 2,626–3,071 Tg C (41 to 48 Mg C ha-1) and 2,660–3,180 Tg C (39 to 47 Mg C ha-1) for 1992 and 2002, respectively. The second methodology followed IPCC 2006 guidelines and using an initial 1992 pool of carbon, the carbon pool for 2002 was estimated to be in the range of 2,668–3,112 Tg C (39 to 46 Mg C ha-1), accounting for biomass increment and removals for the period concerned. The estimated total biomass increment was about 458 Tg over the period 1992–2002. Removals from forests include mainly timber and fuel wood, whereby the latter includes large uncertainty as reported extraction is lower than actual consumption. For the purpose of this study, the annual extraction values of 23 million m3 for timber and 126 million m3 for fuel wood were used. Out of the total area, 10 million ha are plantation forests with an average productivity (3.2 Mg ha-1 year-1) that is higher than natural forests, a correction of 408 Tg C for the 10 year period was incorporated in total estimated phytomass carbon pool of Indian forests. This results in an estimate for the net sink of 4 Tg C year-1. Both approaches indicate Indian forests to be sequestering carbon and both the estimates are in agreement with recent studies. A major uncertainty in Indian phytomass carbon pool dynamics is associated with trees outside forests and with soil organic carbon dynamics. Using recent remote-sensing based estimates o

    Characterization of the Seasonal Circulation Patterns and Its Application on Oil Spill Transport in the Northwestern Continental Shelf of India

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    We implemented the Princeton Ocean Model to study the seasonal circulation patterns in the Gulf of Khambhat and surrounding oceans on the northwestern continental shelf of India. Simulated currents are used in General NOAA Operational Modeling Environment to track a past oil spill event in this region. The model's performance is evaluated against the Synthetic Aperture Radar (SAR) and in situ measurements. Mean currents, computed by subtracting tidal components from the simulated currents, are used together with satellite images of Chlorophyll-a to describe spatial patterns of the circulation. Mean-flow patterns inside the gulf are characterized with strong along-channel flow during southwest monsoon and spring seasons, which are weak during winter and autumn seasons. On the proximity of the gulf mouth currents are northwestward throughout the year except the southwest monsoon when the circulations are southwestward. Coastal boundary currents parallel to the 60Â m isobath are prominent during the inter-monsoon and weak during the monsoon periods. Slope currents, near the shelf-break, are strong during southwest monsoon and spring periods. Numerical experiments suggest that ocean current is the main driver of the net transport of spilled oil in this region and other factors such as direct wind drift play negligible role
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