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Featured researches published by Mamat Sawut.


Remote Sensing | 2015

Monitoring Soil Salinization in Keriya River Basin, Northwestern China Using Passive Reflective and Active Microwave Remote Sensing Data

Ilyas Nurmemet; Abduwasit Ghulam; Tashpolat Tiyip; Racha Elkadiri; Jianli Ding; Matthew Maimaitiyiming; Abdulla Abliz; Mamat Sawut; Fei Zhang; Abdugheni Abliz; Qian Sun

Soil salinization is one of the most widespread soil degradation processes on Earth, especially in arid and semi-arid areas. The salinized soil in arid to semi-arid Xinjiang Uyghur Autonomous Region in China accounts for 31% of the area of cultivated land, and thus it is pivotal for the sustainable agricultural development of the area to identify reliable and cost-effective methodologies to monitor the spatial and temporal variations in soil salinity. This objective was accomplished over the study area (Keriya River Basin, northwestern China) by adopting technologies that heavily rely on, and integrate information contained in, a readily available suite of remote sensing datasets. The following procedures were conducted: (1) a selective principle component analysis (S-PCA) fusion image was generated using Phased Array Type L-band SAR (PALSAR) backscattering coefficient (σ°) and Landsat Enhanced Thematic Mapper Plus (ETM+) multispectral image of Keriya River Basin; and (2) a support vector machines (SVM) classification method was employed to classify land cover types with a focus on mapping salinized soils; (3) a cross-validation method was adopted to identify the optimum classification parameters, and obtain an optimal SVM classification model; (4) Radarsat-2 (C band) and PALSAR polarimetric images were used to analyze polarimetric backscattering behaviors in relation to the variation in soil salinization; (5) a decision tree (DT) scheme for multi-source optical and polarimetric SAR data integration was proposed to improve the estimation and monitoring accuracies of soil salinization; and (6) detailed field observations and ground truthing were used for validation of the adopted methodology, and quantity and allocation disagreement measures were applied to assess classification outcome. Results showed that the fusion of passive reflective and active microwave remote sensing data provided an effective tool in detecting soil salinization. Overall accuracy of the adopted SVM classifier with optimal parameters for fused image of ETM+ and PALSAR data was 91.25% with a Kappa coefficient of 0.89, which was further improved by the DT data integration and classification method yielding an accuracy of 93.01% with a Kappa coefficient of 0.92 and lower disagreement of quantity and allocation.


International Journal of Applied Earth Observation and Geoinformation | 2014

Estimating soil sand content using thermal infrared spectra in arid lands

Mamat Sawut; Abduwasit Ghulam; Tashpolat Tiyip; Yan-jun Zhang; Jianli Ding; Fei Zhang; Matthew Maimaitiyiming

a b s t r a c t Sand content is a textural property of soils closely related to soil quality. A fast determination of sand content at large scales is paramount importance for monitoring soil degradation to improve agricultural practices. The main objective of this study is to evaluate the ability of the thermal infrared region (TIR) to estimate sand content of soils. Thermal infrared spectra obtained in the field from a Fourier Transform Spectrometer are used to develop a partial least square regression model (PLSR) that translates thermal emittance to soil texture properties. Our results show that the 9.435-9.473 m wavelength regions hold a great promise for prediction of sand content. Coefficient of determination R2 is 0.87 and standard error (SE) is 2.79. We also show that second derivative of thermal spectral profiles is very useful to detect kaolinite in sand dominated soils. The results of this study provide further insights for developing future thermal sensors aimed at predicting soil quality as indicated by the sand content and other textural properties.


Journal of Arid Land | 2013

Vegetation fractional coverage change in a typical oasis region in Tarim River Watershed based on remote sensing

Fei Zhang; Tashpolat Tiyip; Jianli Ding; Mamat Sawut; Verner Carl Johnson; Nigara Tashpolat; Dongwei Gui

Vegetation fractional coverage (VFC) is an important index to describe and evaluate the ecological system. The vegetation index is widely used to monitor vegetation coverage in the field of remote sensing (RS). In this paper, the author conducted a case study of the delta oasis of Weigan and Kuqa rivers, which is a typical saline area in the Tarim River Watershed. The current study was based on the TM/ETM+ images of 1989, 2001, and 2006, and supported by Geographic Information System (GIS) spatial analysis, vegetation index, and dimidiate pixel model. In addition, VBSI (vegetation, bare soil and shadow indices) suitable for TM/ETM+ images, constructed with FCD (forest canopy density) model principle and put forward by ITTO (International Tropical Timber Organization), was used, and it was applied to estimate the VFC. The estimation accuracy was later proven to be up to 83.52%. Further, the study analyzed and appraised the changes in vegetation patterns and revealed a pattern of spatial change in the vegetation coverage of the study area by producing the map of VFC levels in the delta oasis. Forest, grassland, and farmland were the three main land-use types with high and extremely-high coverage, and they played an important role in maintaining the vegetation. The forest area determined the changes of the coverage area, whereas the other two land types affected the directions of change. Therefore, planting trees, protecting grasslands, reclaiming farmlands, and controlling unused lands should be included in a long-term program because of their importance in keeping regional vegetation coverage. Finally, the dynamic variation of VFC in the study area was evaluated according to the quantity and spatial distribution rendered by plant cover digital images to deeply analyze the reason behind the variation.


Environmental Earth Sciences | 2013

Studies on the reflectance spectral features of saline soil along the middle reaches of Tarim River: a case study in Xinjiang Autonomous Region, China

Fei Zhang; Tashpolat Tiyip; Jianli Ding; Hsiang-te Kung; Verner Carl Johnson; Mamat Sawut; Nigara Tashpolat; Dongwei Gui

There has been growing interest in the use of reflectance spectroscopy as a rapid and inexpensive tool for soil characterization. In this study, 53 soil samples were collected from the oasis in the Weigan and Kuqa River delta along the middle reaches of Tarim River to investigate the level of soil chemical components in relation to soil spectral. An approach combining spectral technology and multi-variant statistical analysis was used to determine the reflectance spectral features of saline soil. The spectral data was first pretreated to remove noises and absorption bands from water, which eliminated influence from instrument errors and other external background factors. Several spectral absorption features were calculated for several saline soil samples to confirm that soil at the same salinity level had similar absorption spectral properties. Secondly, a correlation relationship between reflectance spectra and salinity factors was estimated by bivariate correlation method. Fourteen salinity factors including eight major ions and soil electrical conductivity (EC), soil salt content (SSC), pH, and total dissolved solid (TDS) in the saline soil were evaluated. Datasets of the salinity factors that correlated significantly with field data measurements of reflectance rate and the corresponding spectrum data were used to construct quantitative regression models. According to the multiple linear regression analysis, SSC, SO42−, TDS, and EC had a correlation coefficient at 0.746, 0.908, 0.798, and 0.933 with the raw spectral data, respectively, which confirmed strong correlation between salinity factors and soil reflectance spectrum. Findings from this study will have significant impact on characterization of spectral features of saline soil in oasis in arid land.


Environmental Monitoring and Assessment | 2012

Spectral reflectance properties of major objects in desert oasis: a case study of the Weigan–Kuqa river delta oasis in Xinjiang, China

Fei Zhang; Tashpolat Tiyip; Jianli Ding; Mamat Sawut; Nigara Tashpolat; Hsiang-te Kung; Guihong Han; Dongwei Gui

Aiming at the remote sensing application has been increasingly relying on ground object spectral characteristics. In order to further research the spectral reflectance characteristics in arid area, this study was performed in the typical delta oasis of Weigan and Kuqa rivers located north of Tarim Basin. Data were collected from geo-targets at multiple sites in various field conditions. The spectra data were collected for different soil types including saline–alkaline soil, silt sandy soil, cotton field, and others; vegetations of Alhagi sparsifolia, Phragmites australis, Tamarix, Halostachys caspica, etc., and water bodies. Next, the data were processed to remove high-frequency noise, and the spectral curves were smoothed with the moving average method. The derivative spectrum was generated after eliminating environmental background noise so that to distinguish the original overlap spectra. After continuum removal of the undesirable absorbance, the spectrum curves were able to highlight features for both optical absorbance and reflectance. The spectrum information of each ground object is essential for fully utilizing the multispectrum data generated by remote sensing, which will need a representative spectral library. In this study using ENVI 4.5 software, a preliminary spectral library of surface features was constructed using the data surveyed in the study area. This library can support remote sensing activities such as feature investigation, vegetation classification, and environmental monitoring in the delta oasis region. Future plan will focus on sharing and standardizing the criteria of professional spectral library and to expand and promote the utilization of the spectral databases.


Isprs Journal of Photogrammetry and Remote Sensing | 2014

Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation

Matthew Maimaitiyiming; Abduwasit Ghulam; Tashpolat Tiyip; Filiberto Pla; Pedro Latorre-Carmona; Ümüt Halik; Mamat Sawut; Mario Caetano


Environmental Earth Sciences | 2016

Effects of shallow groundwater table and salinity on soil salt dynamics in the Keriya Oasis, Northwestern China

Abdulla Abliz; Tashpolat Tiyip; Abduwasit Ghulam; Ümüt Halik; Jianli Ding; Mamat Sawut; Fei Zhang; Ilyas Nurmemet; Abdugheni Abliz


Agricultural Science and Technology Hunan | 2011

A method of soil salinization information extraction with SVM classification based on ICA and texture features.

Zhang Fei; Tashpolat Tiyip; Kung HsiangTe; Ding Jian-li; Mamat Sawut; J. Verner; Han Guihong; Gui Dongwei


Sustainability | 2018

Model Prediction of Secondary Soil Salinization in the Keriya Oasis, Northwest China

Jumeniyaz Seydehmet; Guang Hui Lv; Ilyas Nurmemet; Tayierjiang Aishan; Abdulla Abliz; Mamat Sawut; Abdugheni Abliz; Mamattursun Eziz


Progress in geography | 2011

Assessment of Soil Salinization Sensitivity for Different Types of Land Use in the Ebinur Lake Region in Xinjiang

Mamat Sawut

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Dongwei Gui

Chinese Academy of Sciences

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