“…9 ), showing recurring seasonal flooding during episodes of extreme rainfall such as in 1804, 1805, and 1871 ( 105 ). However, previous RS-based attempts to identify the former channel network across Cholistan have suggested several potential interconnected waterflows ( 106 – 109 ), but little is known about their chronology. Moreover, the detected relict network of fluvial environments across the region has several characteristics that differ from a major Ghaggar-Hakra course, specifically 1) these paleochannels form multiple courses with roughly similar orientation, 2) their morphology is relatively straight, at least by comparison with those documented to the north of the study area, where they tend to be very sinuous given the low slope of the alluvial plain (see refs.…”
This paper presents an innovative multisensor, multitemporal machine-learning approach using remote sensing big data for the detection of archaeological mounds in Cholistan (Pakistan). The Cholistan Desert presents one of the largest concentrations of Indus Civilization sites (from ca. 3300 to 1500 BC). Cholistan has figured prominently in theories about changes in water availability, the rise and decline of the Indus Civilization, and the transformation of fertile monsoonal alluvial plains into an extremely arid margin. This paper implements a multisensor, multitemporal machine-learning approach for the remote detection of archaeological mounds. A classifier algorithm that employs a large-scale collection of synthetic-aperture radar and multispectral images has been implemented in Google Earth Engine, resulting in an accurate probability map for mound-like signatures across an area that covers ca. 36,000 km2. The results show that the area presents many more archaeological mounds than previously recorded, extending south and east into the desert, which has major implications for understanding the archaeological significance of the region. The detection of small (<5 ha) to large mounds (>30 ha) suggests that there were continuous shifts in settlement location. These shifts are likely to reflect responses to a dynamic and changing hydrological network and the influence of the progressive northward advance of the desert in a long-term process that culminated in the abandonment of much of the settled area during the Late Harappan period.
“…9 ), showing recurring seasonal flooding during episodes of extreme rainfall such as in 1804, 1805, and 1871 ( 105 ). However, previous RS-based attempts to identify the former channel network across Cholistan have suggested several potential interconnected waterflows ( 106 – 109 ), but little is known about their chronology. Moreover, the detected relict network of fluvial environments across the region has several characteristics that differ from a major Ghaggar-Hakra course, specifically 1) these paleochannels form multiple courses with roughly similar orientation, 2) their morphology is relatively straight, at least by comparison with those documented to the north of the study area, where they tend to be very sinuous given the low slope of the alluvial plain (see refs.…”
This paper presents an innovative multisensor, multitemporal machine-learning approach using remote sensing big data for the detection of archaeological mounds in Cholistan (Pakistan). The Cholistan Desert presents one of the largest concentrations of Indus Civilization sites (from ca. 3300 to 1500 BC). Cholistan has figured prominently in theories about changes in water availability, the rise and decline of the Indus Civilization, and the transformation of fertile monsoonal alluvial plains into an extremely arid margin. This paper implements a multisensor, multitemporal machine-learning approach for the remote detection of archaeological mounds. A classifier algorithm that employs a large-scale collection of synthetic-aperture radar and multispectral images has been implemented in Google Earth Engine, resulting in an accurate probability map for mound-like signatures across an area that covers ca. 36,000 km2. The results show that the area presents many more archaeological mounds than previously recorded, extending south and east into the desert, which has major implications for understanding the archaeological significance of the region. The detection of small (<5 ha) to large mounds (>30 ha) suggests that there were continuous shifts in settlement location. These shifts are likely to reflect responses to a dynamic and changing hydrological network and the influence of the progressive northward advance of the desert in a long-term process that culminated in the abandonment of much of the settled area during the Late Harappan period.
“…It extends to the Thar desert in Sindh between longitudes 69°52′ to 73°24′ E and latitudes 28°42′ to 29°25′N (Fig. 1), present at an altitude of 89 m above sea level [1]. With reference to the climate, it is categorized as harsh, sub-tropical region with scarcity of precipitation and long dearth season, low relative humidity, with high rate of evaporation [2, 3].…”
Section: Introductionmentioning
confidence: 99%
“…These are abundantly present in soil of different types, but the arid habitats like deserts are now becoming the target ecosystems for their search because of the uniqueness of environmental conditions.Fig. 1GIS Location map of Cholistan desert Pakistan, Islam et al [1], (Map used with permission)…”
Background
Actinobacteria are famous for the production of unique secondary metabolites that help in controlling the continuously emerging drug resistance all over the globe. This study aimed at the investigation of an extreme environment the Cholistan desert, located in southern Punjab, Pakistan, for actinobacterial diversity and their activity against methicillin resistant
Staphylococcus aureus
(MRSA). The Cholistan desert is a sub-tropical and arid ecosystem with harsh environment, limited rainfall and low humidity. The 20 soil and sand samples were collected from different locations in the desert and the actinobacterial strains were selectively isolated. The isolated strains were identified using a polyphasic taxonomic approach including morphological, biochemical, physiological characterization, scanning electron microscopy (SEM) and by 16S rRNA gene sequencing.
Results
A total of 110 desert actinobacterial strains were recovered, which were found to be belonging to 3 different families of the order
Actinomycetales
, including the family
Streptomycetaceae
, family
Pseudonocardiaceae
and the family
Micrococcaceae
. The most frequently isolated genus was
Streptomyces
along with the genera
Pseudonocardia
and
Arthrobacter
. The isolated strains exhibited promising antimicrobial activity against methicillin resistant
Staphylococcus aureus
(MRSA) with zone of inhibition in the range of 9–32 mm in antimicrobial screening assays. The chemical profiling by thin layer chromatography, HPLC-UV/Vis and LC-MS analysis depicted the presence of different structural classes of antibiotics.
Conclusion
The study revealed that Cholistan desert harbors immense actinobacterial diversity and most of the strains produce structurally diverse bioactive secondary metabolites, which are a promising source of novel antimicrobial drug candidates.
Electronic supplementary material
The online version of this article (10.1186/s12866-019-1414-x) contains supplementary material, which is available to authorized users.
“…Fradelizio et al (2008) used 3D seismic imaging to identify the margins and the bottom of a paleochannel inserted between 10 and 15 meters deep in a layer of clay. Islam et al (2016) used vertical electrical survey and electrical conductivity (electromagnetic survey) to map a paleochannel in the Cholistan desert of Pakistan and evaluate the quality of groundwater present in it.…”
This paper presents the results of a survey of electric resistivity along a stretch of the Sucuru River, in the vicinity of the Sumé city, in the Northeast region of Brazil. The goal is to map the occurrence of sediments saturated with water whose main paleochannel is a suitable feature for drilling water-producer wells. Two manual Auger coring surveys were made with pick up of sediment samples for petrophysical tests and record of six 2D lines of electric resistivity, applying multiple vertical electric soundings, which were interpolated to generate a 3D electrical resistivity model of that part of the river. The results show that the fine sediments tend to have low values of electrical resistivity (lower than 50 ohm.m), except on non-saturated region, while intervals with lithotypes of high grain sizes tend to present resistivity values between 50 and 200 ohm.m, except in regions of high porosity and high water saturation. In general, it is seen that there is an area with resistivity higher than 200 ohm.m at the top, which corresponds to the non-saturated sediments zone, and another at the base, which corresponds to the crystalline basement. The model allows someone to view, in addition to the main paleochannel, secondary channels, which hardly would be completely identified through a regular core drilling program.
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