Gis based morphometric analysis of a forest watershed in lower Shivaliks of Punjab using high resolution satellite data

2020 ◽  
Vol 19 (3) ◽  
pp. 292
Author(s):  
Vishnu Prasad ◽  
Abrar Yousuf ◽  
Navneet Sharma
2020 ◽  
Author(s):  
Ahmad Alhourani ◽  
Zaid Aljuboori ◽  
Candice Nguyen ◽  
Heegok Yeo ◽  
Brian Williams ◽  
...  

2011 ◽  
Vol 4 (1) ◽  
pp. 500-502
Author(s):  
Md. Fazlul Haque ◽  
◽  
Md. Mostafizur Rahman Akhand ◽  
Dr. Dewan Abdul Quadir

2013 ◽  
Vol 20 (4) ◽  
pp. 1191-1210 ◽  
Author(s):  
Jonas Jägermeyr ◽  
Dieter Gerten ◽  
Wolfgang Lucht ◽  
Patrick Hostert ◽  
Mirco Migliavacca ◽  
...  

Author(s):  
Sreenivasan G ◽  
Anju Bajpai ◽  
Prakasa Rao D S ◽  
Girish Kumar T P ◽  
Ashish Shrivastava ◽  
...  

Neurosurgery ◽  
2010 ◽  
Vol 66 (1) ◽  
pp. 187-195 ◽  
Author(s):  
Jörg Wellmer ◽  
Yaroslav Parpaley ◽  
Marec von Lehe ◽  
Hans-Jürgen Huppertz

Abstract OBJECTIVE Focal cortical dysplasias (FCDs) are highly epileptogenic lesions. Surgical removal is frequently the best treatment option for pharmacoresistant epilepsy. However, subtle FCDs may remain undetected even after high-resolution magnetic resonance imaging (MRI). Morphometric MRI analysis, which compares the individual brain with a normal database, can facilitate the detection of FCDs. We describe how the results of normal database–based MRI postprocessing can be used to guide stereotactic electrode implantation and subsequent resection of lesions that are suspected to be FCDs. METHODS A presurgical evaluation was conducted on a 19-year-old woman with pharmacoresistant hypermotor seizures. Conventional high-resolution MRI was classified as negative for epileptogenic lesions. However, morphometric analysis of the spatially normalized MRI revealed abnormal gyration and blurring of the gray-white matter junction, which was suggestive of a small and deeply seated FCD in the left frontal lobe. RESULTS The brain region highlighted by morphometric analysis was marked as a region of interest, transferred back to the original dimension of the individual MRI, and imported into a neuronavigation system. This allowed the region of interest–targeted stereotactic implantation of 2 depth electrodes, by which seizure onset was confirmed in the lesion. The electrodes also guided the final resection, which rendered the patient seizure-free. The lesion was histologically classified as FCD Palmini and Lüders IIB. CONCLUSION Transferring normal database–based MRI postprocessing results into a neuronavigation system is a new and worthwhile extension of multimodal neuronavigation. The combination of resulting regions of interest with functional and anatomic data may facilitate planning of electrode implantation for invasive electroencephalographic recordings and the final resection of small or deeply seated FCDs.


2018 ◽  
Vol 18 (8) ◽  
pp. 5483-5497 ◽  
Author(s):  
Jennifer Kaiser ◽  
Daniel J. Jacob ◽  
Lei Zhu ◽  
Katherine R. Travis ◽  
Jenny A. Fisher ◽  
...  

Abstract. Isoprene emissions from vegetation have a large effect on atmospheric chemistry and air quality. “Bottom-up” isoprene emission inventories used in atmospheric models are based on limited vegetation information and uncertain land cover data, leading to potentially large errors. Satellite observations of atmospheric formaldehyde (HCHO), a high-yield isoprene oxidation product, provide “top-down” information to evaluate isoprene emission inventories through inverse analyses. Past inverse analyses have however been hampered by uncertainty in the HCHO satellite data, uncertainty in the time- and NOx-dependent yield of HCHO from isoprene oxidation, and coarse resolution of the atmospheric models used for the inversion. Here we demonstrate the ability to use HCHO satellite data from OMI in a high-resolution inversion to constrain isoprene emissions on ecosystem-relevant scales. The inversion uses the adjoint of the GEOS-Chem chemical transport model at 0.25∘ × 0.3125∘ horizontal resolution to interpret observations over the southeast US in August–September 2013. It takes advantage of concurrent NASA SEAC4RS aircraft observations of isoprene and its oxidation products including HCHO to validate the OMI HCHO data over the region, test the GEOS-Chem isoprene oxidation mechanism and NOx environment, and independently evaluate the inversion. This evaluation shows in particular that local model errors in NOx concentrations propagate to biases in inferring isoprene emissions from HCHO data. It is thus essential to correct model NOx biases, which was done here using SEAC4RS observations but can be done more generally using satellite NO2 data concurrently with HCHO. We find in our inversion that isoprene emissions from the widely used MEGAN v2.1 inventory are biased high over the southeast US by 40 % on average, although the broad-scale distributions are correct including maximum emissions in Arkansas/Louisiana and high base emission factors in the oak-covered Ozarks of southeast Missouri. A particularly large discrepancy is in the Edwards Plateau of central Texas where MEGAN v2.1 is too high by a factor of 3, possibly reflecting errors in land cover. The lower isoprene emissions inferred from our inversion, when implemented into GEOS-Chem, decrease surface ozone over the southeast US by 1–3 ppb and decrease the isoprene contribution to organic aerosol from 40 to 20 %.


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