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During the late Neoproterozoic, the Salt Range in Pakistan was one of the regions where the Tethys truncated and marine strata developed. The numerous transgressions and regressions that occurred during that period provided enough initial material for the development of marine evaporites. The geology of the Salt Range is characterized by the presence of dense salt layers and the existence of four regional and local scale unconformities. These thick salt deposits geologically favor potash formation. Here we coupled chloride isotope geochemistry and classical chemistry of local halite samples to assess the extent of brine evaporation that ultimately formed the salt deposits. Our results indicate that evaporites in the Salt Range area are Br-rich and precipitated from seawater under arid climate conditions. The corresponding δ37Cl values vary from –1.04‰ to 1.07‰, with an average of –0.25‰ ± 0.52‰, consistent with the isotope range values reported for other evaporites worldwide. The positive δ37Cl values we obtained indicate the addition of nonmarine Cl, possibly from reworking of older evaporites, the influx of dilute seawater, the mixing of meteoric and seawater, and the influence of gypsum-dehydration water. The negative Cl isotope compositions (δ37Cl < –1‰) indicate that brines reached the last stages of salt deposition during the late Neoproterozoic. We conclude that the Salt Range Formation could be promising for K-Mg salts.

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This study documented the field relationship and integrated provenance of a clastic sequence exposed at the Mesozoic–Cenozoic boundary located in Changla Gali section, Lesser Himalaya, Pakistan, to provide an insight into Cretaceous tectonics of the northern Indian margin. This boundary sequence is represented by the Early Palaeocene Hangu Formation, which consists of shales in the lower part and sandstone in the upper part. The contact relationship of the Early Palaeocene Hangu Formation with the underlying Late Cretaceous Kawagarh Formation is marked by an angular unconformity. The detrital zircons extracted from the shale and sandstone samples shows a major age cluster, which varies between ~700 and ~1,100 Ma (45%), ~1,600 and ~1,900 Ma (15%), and ~480 and ~590 Ma. Additionally, two minor age clusters of the detrital zircons are identified, that is, ~2,300–2,500 Ma and ~600–700 Ma. The younger detrital zircon grains have ages of 298 ± 4 Ma, 297 ± 4 Ma and 116 ± 3 Ma. This age pattern reflect the major source area as the Indian Plate. The two younger Permian zircon grains may be derived from the Panjal mafic volcanic rocks exposed in the vicinity of the study area. However, a single Cretaceous grain may be attributed to ophiolites, as well as Tethyan Himalayan (TH) volcanic rocks. Similarly, the sandstone petrographic results show that the sandstones are quartz‐rich, which show derivation from the craton interior provenance, which is likely the Indian Plate. However, the trace element data suggest a mixed source consisting of felsic and mafic rocks. The contribution of the mafic source is likely associated with the Panjal mafic rocks exposed along the northern Indian margin. The field relationship shows that the underlying Mesozoic sequence is folded prior to the deposition of the Hangu Formation. This folding suggests that the northern Indian margin experienced a regional compression during the Late Cretaceous time, which folded the Mesozoic sequence before the resumption of sedimentation during the Palaeocene. Furthermore, the detrital zircon provenance suggests that the sediments were mainly derived from the Indian Plate. Combining the results, it can be concluded that the compressional event is likely associated with the Late Cretaceous ophiolite obduction onto the leading edge of the Indian Plate. However, the absence of the major ophiolitic age component in the detrital record may suggest that the ophiolites were emplaced over the northern Indian margin but remained submerged during Early Palaeocene time.

This study was undertaken to enumerate the medicinal plants of the area, find out the conservation status, and record the folk knowledge from the inhabitants of Turmic Valley during 2011-2013. The valley is located in the Rondo division of the District Skardu on the Northeastern side of the Indus River. The detailed information about the local flora regarding medicinal uses was collected from the local herbal healers (Hakeems) and other knowledgeable people. Locally used herbs of the area prevent and cure the people from various diseases such as joint pains, bronchitis, flu and fever, lowering blood pressure, constipation, liver disorders, stomach and abdominal problems, etc. The most common medicinal herbs found in the region belong to the families Gentianaceae, Berberidaceae, Umbelliferae, Labiatae, Rosaceae, Compositae, Urticaceae, and Ranunculaceae. The inhabitants of the valley mostly use the 42 plant species for the treatment of different health problems. Forty-two species of plants (including 4 Gymnosperms, 1 monocotyledon, and 37 dicotyledons) and 35 types of diseases have been identified during the current study. Thymus linearis, Rosa webbiana, Urtica dioca, Pleurospermum candollei, Berberis spp., Delphinium brononianum, and Mentha angustifolia were the commonly used plant species in the valley. The collected baseline data of this study will be helpfulfor young researchers in the fieldof taxonomy, ethnobotany, pharmacology, organic chemistry, and particularly for biodiversity conservation. Over exploitation, habitat destruction, and over grazing are the major threats for the loss of the important flora of the area.

A landslide inventory is indispensable for determination of landslide susceptibility, hazard, risk assessment and disaster mitigation strategies. These inventories were traditionally developed using manual digitization of remote sensing images and aerial photographs, and pixel-based image classification. Recently, Object-Based Image Analysis (OBIA) supersedes visual interpretation and pixel-based methods. OBIA utilizes spectral, textural, contextual, morphological and topographical information in remote sensing images. However, OBIA-based landslide detection methods are often designed for specific areas and remote sensing dataset. The aim of this study is to evaluate the transferability of three published OBIA landslide detection methods for semi-automated landslide detection in the Himalaya mountainous region of northern Pakistan. A SPOT-6 multispectral image with Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) Digital Elevation Model (DEM) derivatives, i.e. slope, aspect, hillshade, relief, elevation and stream network are used for landslide detection using eCognition developer software. The three published methods scale parameters for image segmentation and parameter thresholds are evaluated first. It is observed that the aforementioned methods are not directly applicable to our study area and remote sensing datasets. Therefore, an alternate (proposed) method is developed for semi-automated landslide detection. Accuracy assessment of the selected methods and proposed method is assessed by Precision, Recall and F1 measures. Using the proposed method, a total of 357 landslides are detected with 91.46% Precision, 93.31% Recall and 92.38% F1 measure accuracy.

The Pakistani Gilgit-Baltistan are recognised as being one of the most beautiful and interesting places in the world due to the presence of the longest glaciers and the highest reliefs. This area remained remote and inaccessible before 1965, after which began the construction of the first roads (Karakoram Highway – KKH). In 1992, the Pakistani Government delegated the responsibility for initiating a preliminary survey to outline the borders of the Central Karakoram National Park (CKNP). These surveys resulted in the preliminary outline of the CKNP area (about 3.000 km2), in which the major mountain massifs (as Mt. K2), watersheds, and glaciers were included. Since then, several proposals followed. With the aim of preserving this natural beauty for future generations as well as providing the CKNP of a Management Plan, a 5-year multidisciplinary project called SEED (Social, Economic, Environmental Development) started. One of the project’s objectives was the analysis of the landslide geohazards aiming at the implementation of a landslide inventory and the realization of a susceptibility map. The Arandu village, which is part of Shigar valley, where the Chogolungma glacier is, was chosen as test area. During the summer survey had in 2012, part of the landslide-prone areas, previously identified through DEM analysis (derived from ASTER and Remote Sensing (RS) images) and GIS techniques were identified validating the obtained maps. The Analytical Hierarchy Process (AHP) was used to extract the factor weights in a pairwise comparison matrix. Frequency ratio (FR) method was adopted to drive each class weight. The Weighted linear combination was used in the end to determine the landslide susceptibility index value (LSI)