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Mir A. Matin
International Centre for Integrated Mountain Development

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Chapter
Published: 15 August 2021 in Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region
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Geospatial information, defined as information that refers to a location on Earth, is becoming a critical tool in governance (Chantillon et al. in ISPRS Int J Geo-Inf 6, 2017). Over the last decade, such information has become part of mainstream information management, thereby creating a massive demand for geospatial content and solutions among individuals, private companies, and government agencies.

ACS Style

Mir A. Matin; Sheikh Tawhidul Islam. Geospatial Applications in the HKH Region: Country Needs and Priorities. Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region 2021, 41 -57.

AMA Style

Mir A. Matin, Sheikh Tawhidul Islam. Geospatial Applications in the HKH Region: Country Needs and Priorities. Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region. 2021; ():41-57.

Chicago/Turabian Style

Mir A. Matin; Sheikh Tawhidul Islam. 2021. "Geospatial Applications in the HKH Region: Country Needs and Priorities." Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region , no. : 41-57.

Chapter
Published: 15 August 2021 in Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region
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During the last decade, SERVIR has been striving for realizing its vision of “Space to Village” by implementing services that provide innovative solutions to improve livelihoods and foster self-reliance with the help of EO and geospatial technologies. Over these years, there has been significant development in the field of EO and geospatial technology. However, the capacity of the key agencies to utilize these advancements to produce, disseminate, and use information has not been able to catch up with these developments. As cited in the previous chapters, SERVIR-HKH has been working with various partners and stakeholders in co-developing and implementing applied, user-driven EO and geospatial information services in the HKH region. SERVIR-HKH recognizes that the sustainability of information products and applications and their use requires an understanding of users and their needs. Understanding the user’s needs and organizational context is the key to delivering effective services. As illustrated in Chaps. 10.1007/978-3-030-73569-2_2 and 10.1007/978-3-030-73569-2_3, the needs assessment study revealed that the use of geospatial data in the region started in the early 1990s, but there are still gaps in the institutionalization and sharing of that information. Often, individual agencies produce geospatial information for their own purpose and do not share it due to lack of policies. Besides, in most cases, the information would have been generated through specific projects funded by external agencies without proper sustainability planning. And as has happened in many cases, those services could not be continued due to lack of resources and capacity.

ACS Style

Mir A. Matin; Birendra Bajracharya; Rajesh Bahadur Thapa. Lessons and Future Perspectives of Earth Observation and GIT in the HKH. Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region 2021, 363 -375.

AMA Style

Mir A. Matin, Birendra Bajracharya, Rajesh Bahadur Thapa. Lessons and Future Perspectives of Earth Observation and GIT in the HKH. Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region. 2021; ():363-375.

Chicago/Turabian Style

Mir A. Matin; Birendra Bajracharya; Rajesh Bahadur Thapa. 2021. "Lessons and Future Perspectives of Earth Observation and GIT in the HKH." Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region , no. : 363-375.

Journal article
Published: 18 June 2021 in Progress in Disaster Science
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Low-lying Bangladesh is known as one of the most flood-prone countries in the world. During the last few decades, the frequency, intensity, and duration of floods have increased. To ensure safety and save lives when people's homes submerge because of flooding, it is urgent to relocate them to safe shelters during the flooding. In Bangladesh, the number of designated flood shelters is very less. To plan and prioritise the building of shelters, flood hazard zonation and the identification of suitable locations for shelters are vital for disaster risk mitigation. This study attempted the first and most extensive national flood inundation database and flood dynamics of Bangladesh developed between 2017 and 2020 using public domain Sentinel-1 Synthetic Aperture Radar (SAR) images were processed in the Google Earth Engine (GEE) and replicable methodology. Using a set of analytic hierarchy process (AHP) criteria associated with flood disasters (e.g., floods recurrence areas), elevation, land cover, landform, population density, accessibility, distance to road, and distance to settlement layers were used to identify the hazard zones and the safest locations for building flood shelters. The study assessed that 7.11% of the area was inundated by overflow water in June 2017 and 8.99% in August 2017. Similarly, in June, July, and August 2018; June, July and August 2019, and July 2020, with inundation covering 7.26%, 10.87%, 11.07%, 9.50%, 10.56%, 5.01% and 11.14% of the country, respectively. The results show that extremely-high flood prone areas cover about 13% of Bangladesh. Analysis of the suitability of flood shelters shows that about 8% is extremely-high suitable, 16% is very-high suitable, and 7% is very-low suitability for flood shelters. The flood suitability and flood hazard maps would be helpful to support the local government, national and international organisations for flood disaster risk minimisation and the planning and construction of flood shelters.

ACS Style

Kabir Uddin; Mir A. Matin. Potential flood hazard zonation and flood shelter suitability mapping for disaster risk mitigation in Bangladesh using geospatial technology. Progress in Disaster Science 2021, 11, 100185 .

AMA Style

Kabir Uddin, Mir A. Matin. Potential flood hazard zonation and flood shelter suitability mapping for disaster risk mitigation in Bangladesh using geospatial technology. Progress in Disaster Science. 2021; 11 ():100185.

Chicago/Turabian Style

Kabir Uddin; Mir A. Matin. 2021. "Potential flood hazard zonation and flood shelter suitability mapping for disaster risk mitigation in Bangladesh using geospatial technology." Progress in Disaster Science 11, no. : 100185.

Journal article
Published: 04 January 2021 in Hydrology and Earth System Sciences
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South and Southeast Asia is subject to significant hydrometeorological extremes, including drought. Under rising temperatures, growing populations, and an apparent weakening of the South Asian monsoon in recent decades, concerns regarding drought and its potential impacts on water and food security are on the rise. Reliable sub-seasonal to seasonal (S2S) hydrological forecasts could, in principle, help governments and international organizations to better assess risk and act in the face of an oncoming drought. Here, we leverage recent improvements in S2S meteorological forecasts and the growing power of Earth observations to provide more accurate monitoring of hydrological states for forecast initialization. Information from both sources is merged in a South and Southeast Asia sub-seasonal to seasonal hydrological forecasting system (SAHFS-S2S), developed collaboratively with the NASA SERVIR program and end users across the region. This system applies the Noah-Multiparameterization (NoahMP) Land Surface Model (LSM) in the NASA Land Information System (LIS), driven by downscaled meteorological fields from the Global Data Assimilation System (GDAS) and Climate Hazards InfraRed Precipitation products (CHIRP and CHIRPS) to optimize initial conditions. The NASA Goddard Earth Observing System Model sub-seasonal to seasonal (GEOS-S2S) forecasts, downscaled using the National Center for Atmospheric Research (NCAR) General Analog Regression Downscaling (GARD) tool and quantile mapping, are then applied to drive 5 km resolution hydrological forecasts to a 9-month forecast time horizon. Results show that the skillful predictions of root zone soil moisture can be made 1 to 2 months in advance for forecasts initialized in rainy seasons and up to 8 months when initialized in dry seasons. The memory of accurate initial conditions can positively contribute to forecast skills throughout the entire 9-month prediction period in areas with limited precipitation. This SAHFS-S2S has been operationalized at the International Centre for Integrated Mountain Development (ICIMOD) to support drought monitoring and warning needs in the region.

ACS Style

Yifan Zhou; Benjamin F. Zaitchik; Sujay V. Kumar; Kristi R. Arsenault; Mir A. Matin; Faisal M. Qamer; Ryan A. Zamora; Kiran Shakya. Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins. Hydrology and Earth System Sciences 2021, 25, 41 -61.

AMA Style

Yifan Zhou, Benjamin F. Zaitchik, Sujay V. Kumar, Kristi R. Arsenault, Mir A. Matin, Faisal M. Qamer, Ryan A. Zamora, Kiran Shakya. Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins. Hydrology and Earth System Sciences. 2021; 25 (1):41-61.

Chicago/Turabian Style

Yifan Zhou; Benjamin F. Zaitchik; Sujay V. Kumar; Kristi R. Arsenault; Mir A. Matin; Faisal M. Qamer; Ryan A. Zamora; Kiran Shakya. 2021. "Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins." Hydrology and Earth System Sciences 25, no. 1: 41-61.

Journal article
Published: 06 September 2020 in Remote Sensing
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Time series land cover data statistics often fluctuate abruptly due to seasonal impact and other noise in the input image. Temporal smoothing techniques are used to reduce the noise in time series data used in land cover mapping. The effects of smoothing may vary based on the smoothing method and land cover category. In this study, we compared the performance of Fourier transformation smoothing, Whittaker smoother and Linear-Fit averaging smoother on Landsat 5, 7 and 8 based yearly composites to classify land cover in Province No. 1 of Nepal. The performance of each smoother was tested based on whether it was applied on image composites or on land cover primitives generated using the random forest machine learning method. The land cover data used in the study was from the years 2000 to 2018. Probability distribution was examined to check the quality of primitives and accuracy of the final land cover maps were accessed. The best results were found for the Whittaker smoothing for stable classes and Fourier smoothing for other classes. The results also show that classification using a properly selected smoothing algorithm outperforms a classification based on its unsmoothed data set. The final land cover generated by combining the best results obtained from different smoothing approaches increased our overall land cover map accuracy from 79.18% to 83.44%. This study shows that smoothing can result in a substantial increase in the quality of the results and that the smoothing approach should be carefully considered for each land cover class.

ACS Style

Nishanta Khanal; Mir Matin; Kabir Uddin; Ate Poortinga; Farrukh Chishtie; Karis Tenneson; David Saah. A Comparison of Three Temporal Smoothing Algorithms to Improve Land Cover Classification: A Case Study from NEPAL. Remote Sensing 2020, 12, 2888 .

AMA Style

Nishanta Khanal, Mir Matin, Kabir Uddin, Ate Poortinga, Farrukh Chishtie, Karis Tenneson, David Saah. A Comparison of Three Temporal Smoothing Algorithms to Improve Land Cover Classification: A Case Study from NEPAL. Remote Sensing. 2020; 12 (18):2888.

Chicago/Turabian Style

Nishanta Khanal; Mir Matin; Kabir Uddin; Ate Poortinga; Farrukh Chishtie; Karis Tenneson; David Saah. 2020. "A Comparison of Three Temporal Smoothing Algorithms to Improve Land Cover Classification: A Case Study from NEPAL." Remote Sensing 12, no. 18: 2888.

Preprint content
Published: 27 July 2020
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South and Southeast Asia is subject to significant hydrometeorological extremes, including drought. Under rising temperatures, growing populations, and an apparent weakening of the South Asian monsoon in recent decades, concerns regarding drought and its potential impacts on water and food security are on the rise. Reliable sub-seasonal to seasonal (S2S) hydrological forecasts could, in principle, help governments and international organizations to better assess risk and act in the face of an oncoming drought. Here, we leverage recent improvements in S2S meteorological forecasts and the growing power of Earth Observations to provide more accurate monitoring of hydrological states for forecast initialization. Information from both sources is merged in a South and Southeast Asia sub-seasonal to seasonal hydrological forecasting system (SAHFS-S2S), developed collaboratively with the NASA SERVIR program and end-users across the region. This system applies the Noah-MultiParameterization (NoahMP) Land Surface Model (LSM) in the NASA Land Information System (LIS), driven by downscaled meteorological fields from the Global Data Assimilation System (GDAS) and Climate Hazards InfraRed Precipitation products (CHIRP and CHIRPS) to optimize initial conditions. The NASA Goddard Earth Observing System Model - sub-seasonal to seasonal (GEOS-S2S) forecasts, downscaled using the National Center for Atmospheric Research (NCAR) General Analog Regression Downscaling (GARD) tool and quantile mapping, are then applied to drive 5-km resolution hydrological forecasts to a 9-month forecast time horizon. Results show that the skillful predictions of root zone soil moisture can be made one to two months in advance for forecasts initialized in rainy seasons and up to 8 months when initialized in dry seasons. The memory of accurate initial conditions can positively contribute to forecast skills throughout the entire 9-month prediction period in areas with limited precipitation. This SAHFS-S2S has been operationalized at the International Centre for Integrated Mountain Development (ICIMOD) to support drought monitoring and warning needs in the region.

ACS Style

Yifan Zhou; Benjamin F. Zaitchik; Sujay V. Kumar; Kristi R. Arsenault; Mir A. Matin; Faisal M. Qamer; Ryan A. Zamora; Kiran Shakya. Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins. 2020, 2020, 1 -36.

AMA Style

Yifan Zhou, Benjamin F. Zaitchik, Sujay V. Kumar, Kristi R. Arsenault, Mir A. Matin, Faisal M. Qamer, Ryan A. Zamora, Kiran Shakya. Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins. . 2020; 2020 ():1-36.

Chicago/Turabian Style

Yifan Zhou; Benjamin F. Zaitchik; Sujay V. Kumar; Kristi R. Arsenault; Mir A. Matin; Faisal M. Qamer; Ryan A. Zamora; Kiran Shakya. 2020. "Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins." 2020, no. : 1-36.

Preprint content
Published: 27 July 2020
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ACS Style

Yifan Zhou; Benjamin F. Zaitchik; Sujay V. Kumar; Kristi R. Arsenault; Mir A. Matin; Faisal M. Qamer; Ryan A. Zamora; Kiran Shakya. Supplementary material to "Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins". 2020, 1 .

AMA Style

Yifan Zhou, Benjamin F. Zaitchik, Sujay V. Kumar, Kristi R. Arsenault, Mir A. Matin, Faisal M. Qamer, Ryan A. Zamora, Kiran Shakya. Supplementary material to "Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins". . 2020; ():1.

Chicago/Turabian Style

Yifan Zhou; Benjamin F. Zaitchik; Sujay V. Kumar; Kristi R. Arsenault; Mir A. Matin; Faisal M. Qamer; Ryan A. Zamora; Kiran Shakya. 2020. "Supplementary material to "Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins"." , no. : 1.

Original research article
Published: 19 June 2020 in Frontiers in Environmental Science
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Wheat is cultivated on more than 2.7 million hectares in Afghanistan annually, yet the country is dependent on imports to meet domestic demand. The timely estimation of domestic wheat production is highly critical to address any potential food security issues and has been identified as a priority by the Ministry of Agriculture Irrigation and Livestock (MAIL). In this study, we developed a system for in-season mapping of wheat crop area based on both optical (Sentinel-2) and synthetic aperture radar (SAR, Sentinel-1) data to support estimation of wheat cultivated area for management and food security planning. Utilizing a 2010 Food and Agriculture Organization (FAO) cropland mask, wheat sown area for 2017 was mapped integrating decision trees and machine learning algorithms in the Google Earth Engine cloud platform. Information from provincial crop calendars in addition to training and validation data from field-based surveys, and high-resolution Digitalglobe and Airbus Pleiades images were used for classification and validation. The total irrigated and rainfed wheat area were estimated as 912,525 and 562,611 ha, respectively for 2017. Province-wise accuracy assessments show the maximum accuracy of irrigated (IR) and rainfed (RF) wheat across provinces was 98.76 and 99%, respectively, whereas the minimum accuracy was found to be 48% (IR) and 73% (RF). The lower accuracy is attributed to the unavailability of reference data, cloud cover in the satellite images and overlap of spectral reflectance of wheat with other crops, especially in the opium poppy growing provinces. While the method is designed to provide estimation at different stages of the growing season, the best accuracy is achieved at the end of harvest using time-series satellite data for the whole season. The approach followed in the study can be used to generate wheat area maps for other years to aid in food security planning and policy decisions.

ACS Style

Varun Tiwari; Mir A. Matin; Faisal M. Qamer; Walter Lee Ellenburg; Birendra Bajracharya; Krishna Vadrevu; Begum Rabeya Rushi; Waheedullah Yusafi. Wheat Area Mapping in Afghanistan Based on Optical and SAR Time-Series Images in Google Earth Engine Cloud Environment. Frontiers in Environmental Science 2020, 8, 1 .

AMA Style

Varun Tiwari, Mir A. Matin, Faisal M. Qamer, Walter Lee Ellenburg, Birendra Bajracharya, Krishna Vadrevu, Begum Rabeya Rushi, Waheedullah Yusafi. Wheat Area Mapping in Afghanistan Based on Optical and SAR Time-Series Images in Google Earth Engine Cloud Environment. Frontiers in Environmental Science. 2020; 8 ():1.

Chicago/Turabian Style

Varun Tiwari; Mir A. Matin; Faisal M. Qamer; Walter Lee Ellenburg; Birendra Bajracharya; Krishna Vadrevu; Begum Rabeya Rushi; Waheedullah Yusafi. 2020. "Wheat Area Mapping in Afghanistan Based on Optical and SAR Time-Series Images in Google Earth Engine Cloud Environment." Frontiers in Environmental Science 8, no. : 1.

Journal article
Published: 02 October 2019 in Remote Sensing
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During the last few decades, a large number of people have migrated to Kathmandu city from all parts of Nepal, resulting in rapid expansion of the city. The unplanned and accelerated growth is causing many environmental and population management issues. To manage urban growth efficiently, the city authorities need a means to be able to monitor urban expansion regularly. In this study, we introduced a novel approach to automatically detect urban expansion by leveraging state-of-the-art cloud computing technologies using the Google Earth Engine (GEE) platform. We proposed a new index named Normalized Difference and Distance Built-up Index (NDDBI) for identifying built-up areas by combining the LandSat-derived vegetation index with distances from the nearest roads and buildings analysed from OpenStreetMap (OSM). We also focused on logical consistencies of land-cover change to remove unreasonable transitions supported by the repeat photography. Our analysis of the historical urban growth patterns between 2000 and 2018 shows that the settlement areas were increased from 63.68 sq km in 2000 to 148.53 sq km in 2018. The overall accuracy of mapping the newly-built areas of urban expansion was 94.33%. We have demonstrated that the methodology and data generated in the study can be replicated to easily map built-up areas and support quicker and more efficient land management and land-use planning in rapidly growing cities worldwide.

ACS Style

Nishanta Khanal; Kabir Uddin; Mir A. Matin; Karis Tenneson. Automatic Detection of Spatiotemporal Urban Expansion Patterns by Fusing OSM and Landsat Data in Kathmandu. Remote Sensing 2019, 11, 2296 .

AMA Style

Nishanta Khanal, Kabir Uddin, Mir A. Matin, Karis Tenneson. Automatic Detection of Spatiotemporal Urban Expansion Patterns by Fusing OSM and Landsat Data in Kathmandu. Remote Sensing. 2019; 11 (19):2296.

Chicago/Turabian Style

Nishanta Khanal; Kabir Uddin; Mir A. Matin; Karis Tenneson. 2019. "Automatic Detection of Spatiotemporal Urban Expansion Patterns by Fusing OSM and Landsat Data in Kathmandu." Remote Sensing 11, no. 19: 2296.

Journal article
Published: 26 August 2019 in Agronomy
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Large Cardamom (Amomum subulatum Roxb.) is one of the most valuable cash crop of the Himalayan mountain region including Nepal, India, and Bhutan. Nepal is the world’s largest producer of the crop while the Taplejung district contributes a 30%–40% share in Nepal’s total production. Large cardamom is an herbaceous perennial crop usually grown under the shade of the Uttis tree in very specialized bioclimatic conditions. In recent years, a decline in cardamom production has been observed which is being attributed to climate-related indicators. To understand the current dynamics of this under-canopy herbaceous crop distribution and its future potential under climate change, a combination of modelling, remote sensing, and expert knowledge is applied for the assessment. The results suggest that currently, Uttis tree cover is 10,735 ha in the district, while 50% (5198 ha) of this cover has a large cardamom crop underneath. When existing cultivation is compared with modelled suitable areas, it is observed that the cultivatable area has not yet reached its full potential. In a future climate scenario, the current habitat will be negatively affected, where mid elevations will remain stable while lower and higher elevation will become infeasible for the crop. Future changes are closely related to temperature and precipitation which are steadily changing in Nepal over time.

ACS Style

Sajana Maharjan; Faisal Mueen Qamer; Mir Matin; Govinda Joshi; Sanjeev Bhuchar. Integrating Modelling and Expert Knowledge for Evaluating Current and Future Scenario of Large Cardamom Crop in Eastern Nepal. Agronomy 2019, 9, 481 .

AMA Style

Sajana Maharjan, Faisal Mueen Qamer, Mir Matin, Govinda Joshi, Sanjeev Bhuchar. Integrating Modelling and Expert Knowledge for Evaluating Current and Future Scenario of Large Cardamom Crop in Eastern Nepal. Agronomy. 2019; 9 (9):481.

Chicago/Turabian Style

Sajana Maharjan; Faisal Mueen Qamer; Mir Matin; Govinda Joshi; Sanjeev Bhuchar. 2019. "Integrating Modelling and Expert Knowledge for Evaluating Current and Future Scenario of Large Cardamom Crop in Eastern Nepal." Agronomy 9, no. 9: 481.

Journal article
Published: 03 July 2019 in Remote Sensing
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Bangladesh is one of the most flood-affected countries in the world. In the last few decades, flood frequency, intensity, duration, and devastation have increased in Bangladesh. Identifying flood-damaged areas is highly essential for an effective flood response. This study aimed at developing an operational methodology for rapid flood inundation and potential flood damaged area mapping to support a quick and effective event response. Sentinel-1 images from March, April, June, and August 2017 were used to generate inundation extents of the corresponding months. The 2017 pre-flood land cover maps were prepared using Landsat-8 images to identify major land cover on the ground before flooding. The overall accuracy of flood inundation mapping was 96.44% and the accuracy of the land cover map was 87.51%. The total flood inundated area corresponded to 2.01%, 4.53%, and 7.01% for the months April, June, and August 2017, respectively. Based on the Landsat-8 derived land cover information, the study determined that cropland damaged by floods was 1.51% in April, 3.46% in June, 5.30% in August, located mostly in the Sylhet and Rangpur divisions. Finally, flood inundation maps were distributed to the broader user community to aid in hazard response. The data and methodology of the study can be replicated for every year to map flooding in Bangladesh.

ACS Style

Kabir Uddin; Mir A. Matin; Franz J. Meyer. Operational Flood Mapping Using Multi-Temporal Sentinel-1 SAR Images: A Case Study from Bangladesh. Remote Sensing 2019, 11, 1581 .

AMA Style

Kabir Uddin, Mir A. Matin, Franz J. Meyer. Operational Flood Mapping Using Multi-Temporal Sentinel-1 SAR Images: A Case Study from Bangladesh. Remote Sensing. 2019; 11 (13):1581.

Chicago/Turabian Style

Kabir Uddin; Mir A. Matin; Franz J. Meyer. 2019. "Operational Flood Mapping Using Multi-Temporal Sentinel-1 SAR Images: A Case Study from Bangladesh." Remote Sensing 11, no. 13: 1581.

Journal article
Published: 11 December 2018 in Sustainability
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Land cover change is a critical driver for enhancing the soil erosion risk in Nepal. Loss of the topsoil has a direct and indirect effect on human life and livelihoods. The present study provides an assessment of the decadal land use and land cover (LULC) change and consequent changes in the distribution of soil erosion risk for the years, 1990, 2000, and 2010, for the entire country of Nepal. The study attempted to understand how different land cover types change over the three decades and how it has changed the distribution of soil erosion risks in Nepal that would help in the development of soil conservation priority. The land cover maps were produced using geographic object-based image analysis (GEOBIA) using Landsat images. Soil erosion patterns were assessed using the revised universal soil loss equation (RUSLE) with the land cover as the input. The study shows that the forest cover is the most dominant land cover in Nepal that comprises about 6,200,000 ha forest cover. The estimated annual erosion was 129.30 million tons in 1990 and 110.53 million tons in 2010. The assessment of soil erosion dynamics was presented at the national, provincial, and district level. District wise analysis revealed that Gulmi, Parbat, Syangja, and the Tanahu district require priority for soil conservation.

ACS Style

Kabir Uddin; Mir Abdul Matin; Sajana Maharjan. Assessment of Land Cover Change and Its Impact on Changes in Soil Erosion Risk in Nepal. Sustainability 2018, 10, 4715 .

AMA Style

Kabir Uddin, Mir Abdul Matin, Sajana Maharjan. Assessment of Land Cover Change and Its Impact on Changes in Soil Erosion Risk in Nepal. Sustainability. 2018; 10 (12):4715.

Chicago/Turabian Style

Kabir Uddin; Mir Abdul Matin; Sajana Maharjan. 2018. "Assessment of Land Cover Change and Its Impact on Changes in Soil Erosion Risk in Nepal." Sustainability 10, no. 12: 4715.

Journal article
Published: 23 October 2018 in Resources
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For many decades, non-timber forest products (NTFPs) have been an important livelihood commodity in Nepal as a traditional source of food, fiber, and medicines. However, the importance of NTFPs have been recognized only recently. NTFPs form more than 5% of Nepal’s national gross domestic product and are facing threat due to anthropogenic drivers and changing climate. Understanding of the current distribution and future dynamics of NTFPs is essential for effective conservation planning and management. In the maiden attempt, we used the Maxent model to understand the current and predict the future distribution by 2050 of 10 major NTFPs in Chitwan Annapurna Landscape, Nepal. The prediction accuracy of the models calculated based on the area under curve was high (>90%) and the prediction by 2050 highlights potential increase in distribution range of seven NTFPs and potential decrease in that of three NTFPs in the study area. The results from our study could play an important role in planning and management of these NTFPs considering their high economic and ecological significance and sensitivity to predicted climate change.

ACS Style

Vishwas Chitale; Ramesh Silwal; Mir Matin. Assessing the Impacts of Climate Change on Distribution of Major Non-Timber Forest Plants in Chitwan Annapurna Landscape, Nepal. Resources 2018, 7, 66 .

AMA Style

Vishwas Chitale, Ramesh Silwal, Mir Matin. Assessing the Impacts of Climate Change on Distribution of Major Non-Timber Forest Plants in Chitwan Annapurna Landscape, Nepal. Resources. 2018; 7 (4):66.

Chicago/Turabian Style

Vishwas Chitale; Ramesh Silwal; Mir Matin. 2018. "Assessing the Impacts of Climate Change on Distribution of Major Non-Timber Forest Plants in Chitwan Annapurna Landscape, Nepal." Resources 7, no. 4: 66.

Journal article
Published: 10 October 2018 in Hydrology
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: Accurate meteorological estimates are critical for process-based hydrological simulation and prediction. This presents a significant challenge in mountainous Asia where in situ meteorological stations are limited and major river basins cross international borders. In this context, remotely sensed and model-derived meteorological estimates are often necessary inputs for distributed hydrological analysis. However, these datasets are difficult to evaluate on account of limited access to ground data. In this case, the implications of uncertainty associated with precipitation forcing for hydrological simulations is explored by driving the South Asia Land Data Assimilation System (South Asia LDAS) using a range of meteorological forcing products. MERRA2, GDAS, and CHIRPS produce a wide range of estimates for rainfall, which causes a widespread simulated streamflow and evapotranspiration. A combination of satellite-derived and limited in situ data are applied to evaluate model simulations and, by extension, to constrain the estimates of precipitation. The results show that available gridded precipitation estimates based on in situ data may systematically underestimate precipitation in mountainous regions and that performance of gridded satellite-derived or modeled precipitation estimates varies systematically across the region. Since no station-based data or product including station data is satisfactory everywhere, our results suggest that the evaluation of the hydrological simulation of streamflow and ET can be used as an indirect evaluation of precipitation forcing based on ground-based products or in-situ data. South Asia LDAS produces reasonable evapotranspiration and streamflow when forced with appropriate meteorological forcing and the choice of meteorological forcing should be made based on the geographical location as well as on the purpose of the simulations.

ACS Style

Debjani Ghatak; Benjamin Zaitchik; Sujay Kumar; Mir A. Matin; Birendra Bajracharya; Christopher Hain; Martha Anderson. Influence of Precipitation Forcing Uncertainty on Hydrological Simulations with the NASA South Asia Land Data Assimilation System. Hydrology 2018, 5, 57 .

AMA Style

Debjani Ghatak, Benjamin Zaitchik, Sujay Kumar, Mir A. Matin, Birendra Bajracharya, Christopher Hain, Martha Anderson. Influence of Precipitation Forcing Uncertainty on Hydrological Simulations with the NASA South Asia Land Data Assimilation System. Hydrology. 2018; 5 (4):57.

Chicago/Turabian Style

Debjani Ghatak; Benjamin Zaitchik; Sujay Kumar; Mir A. Matin; Birendra Bajracharya; Christopher Hain; Martha Anderson. 2018. "Influence of Precipitation Forcing Uncertainty on Hydrological Simulations with the NASA South Asia Land Data Assimilation System." Hydrology 5, no. 4: 57.

Research article
Published: 01 January 2017 in International Journal of Wildland Fire
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Forest fire is one of the key drivers of forest degradation in Nepal. Most of the forest fires are human-induced and occur during the dry season, with ~89% occurring in March, April and May. The inaccessible mountainous terrain and narrow time window of occurrence complicate suppression efforts. In this paper, forest fire patterns are analysed based on historical fire incidence data to explore the spatial and temporal patterns of forest fires in Nepal. Three main factors are involved in the ignition and spread of forest fires, namely fuel availability, temperature and ignition potential. Using these factors a spatially distributed fire risk index was calculated for Nepal based on a linear model using weights and ratings. The input parameters for the risk assessment model were generated using remote sensing based land cover, temperature and active fire data, and topographic data. A relative risk ranking was also calculated for districts and village development committees (VDCs). In total, 18 out of 75 districts were found with high risk of forest fires. The district and VDC level fire risk ranking could be utilised by the Department of Forest for prioritisation, preparedness and resource allocation for fire control and mitigation.

ACS Style

Mir A. Matin; Vishwas Sudhir Chitale; Manchiraju S. R. Murthy; Kabir Uddin; Birendra Bajracharya; Sudip Pradhan. Understanding forest fire patterns and risk in Nepal using remote sensing, geographic information system and historical fire data. International Journal of Wildland Fire 2017, 26, 276 -286.

AMA Style

Mir A. Matin, Vishwas Sudhir Chitale, Manchiraju S. R. Murthy, Kabir Uddin, Birendra Bajracharya, Sudip Pradhan. Understanding forest fire patterns and risk in Nepal using remote sensing, geographic information system and historical fire data. International Journal of Wildland Fire. 2017; 26 (4):276-286.

Chicago/Turabian Style

Mir A. Matin; Vishwas Sudhir Chitale; Manchiraju S. R. Murthy; Kabir Uddin; Birendra Bajracharya; Sudip Pradhan. 2017. "Understanding forest fire patterns and risk in Nepal using remote sensing, geographic information system and historical fire data." International Journal of Wildland Fire 26, no. 4: 276-286.

Journal article
Published: 01 November 2015 in Journal of Arid Environments
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Mir A. Matin; Charles P.-A. Bourque. Mountain-river runoff components and their role in the seasonal development of desert-oases in northwest China. Journal of Arid Environments 2015, 122, 1 -15.

AMA Style

Mir A. Matin, Charles P.-A. Bourque. Mountain-river runoff components and their role in the seasonal development of desert-oases in northwest China. Journal of Arid Environments. 2015; 122 ():1-15.

Chicago/Turabian Style

Mir A. Matin; Charles P.-A. Bourque. 2015. "Mountain-river runoff components and their role in the seasonal development of desert-oases in northwest China." Journal of Arid Environments 122, no. : 1-15.

Journal article
Published: 03 August 2015 in Hydrology and Earth System Sciences
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This study associates the dynamics of enhanced vegetation index in lowland desert oases to the recycling of water in two endorheic (hydrologically closed) river basins in Gansu Province, north-west China, along a gradient of elevation zones and land cover types. Each river basin was subdivided into four elevation zones representative of (i) oasis plains and foothills, and (ii) low-, (iii) mid-, and (iv) high-mountain elevations. Comparison of monthly vegetation phenology with precipitation and snowmelt dynamics within the same basins over a 10-year period (2000–2009) suggested that the onset of the precipitation season (cumulative % precipitation > 7–8 %) in the mountains, typically in late April to early May, was triggered by the greening of vegetation and increased production of water vapour at the base of the mountains. Seasonal evolution of in-mountain precipitation correlated fairly well with the temporal variation in oasis-vegetation coverage and phenology characterised by monthly enhanced vegetation index, yielding coefficients of determination of 0.65 and 0.85 for the two basins. Convergent cross-mapping of related time series indicated bi-directional causality (feedback) between the two variables. Comparisons between same-zone monthly precipitation amounts and enhanced vegetation index provided weaker correlations. Start of the growing season in the oases was shown to coincide with favourable spring warming and discharge of meltwater from low- to mid-elevations of the Qilian Mountains (zones 1 and 2) in mid-to-late March. In terms of plant requirement for water, mid-seasonal development of oasis vegetation was seen to be controlled to a greater extent by the production of rain in the mountains. Comparison of water volumes associated with in-basin production of rainfall and snowmelt with that associated with evaporation seemed to suggest that about 90 % of the available liquid water (i.e. mostly in the form of direct rainfall and snowmelt in the mountains) was recycled locally.

ACS Style

M. A. Matin; C. P.-A. Bourque. Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China. Hydrology and Earth System Sciences 2015, 19, 3387 -3403.

AMA Style

M. A. Matin, C. P.-A. Bourque. Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China. Hydrology and Earth System Sciences. 2015; 19 (8):3387-3403.

Chicago/Turabian Style

M. A. Matin; C. P.-A. Bourque. 2015. "Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China." Hydrology and Earth System Sciences 19, no. 8: 3387-3403.

Preprint content
Published: 26 January 2015 in Hydrology and Earth System Sciences Discussions
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In this study, we analysed the role of vegetation in the recycling of water in two endorheic watersheds in northwest China, namely within the Shiyang and Hei River watersheds (Gansu Province), along a gradient of elevation zones and within-zone landcover types. Each watershed was subdivided into four elevation zones representative of (i) oasis plains and foothills, and (ii) low-, (iii) mid-, and (iv) high-mountain elevations. By means of monthly summaries of enhanced vegetation index (EVI), DEM-height values, terrain orientation, and a decision-tree classifier, landcover in the study area (consisting of oases, deserts, and adjoining Qilian Mountains) was classified into 11 unique landcover types. Comparison of monthly vegetation phenology with precipitation and snowmelt dynamics within the same watersheds over a ten-year period (2000–2009) suggested that the onset of the precipitation season in the mountains (in May) was triggered by the greening of vegetation and increased production of water vapour at the base of the mountains. Seasonal evolution of in-mountain precipitation correlated fairy well with the temporal variation in oasis-vegetation coverage and phenology (of crops and grasses) characterised by monthly EVI, giving r2 values of 0.65 and 0.85 for the Shiyang and Hei River watersheds, respectively. Generally, comparisons between same-zone monthly precipitation volumes and EVI provided weaker correlations. Start of the growing season in the oases was shown to coincide with the discharge of meltwater from the low- to mid-elevations of the Qilian Mountains in mid-to-late March. Comparison of water volumes associated with in-mountain production of rainfall and snowmelt with that associated with actual evapotranspiration revealed that about 90% of the water flowing downslope to the oases was eventually returned to the Qilian Mountains as water vapour generated in the lowlands.

ACS Style

M. A. Matin; C. P.-A. Bourque. Role of vegetation and landcover dynamics on the recycling of water in two endorheic watersheds of NW China (Gansu Province). Hydrology and Earth System Sciences Discussions 2015, 1 .

AMA Style

M. A. Matin, C. P.-A. Bourque. Role of vegetation and landcover dynamics on the recycling of water in two endorheic watersheds of NW China (Gansu Province). Hydrology and Earth System Sciences Discussions. 2015; ():1.

Chicago/Turabian Style

M. A. Matin; C. P.-A. Bourque. 2015. "Role of vegetation and landcover dynamics on the recycling of water in two endorheic watersheds of NW China (Gansu Province)." Hydrology and Earth System Sciences Discussions , no. : 1.

Journal article
Published: 01 December 2013 in Remote Sensing of Environment
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Mir A. Matin; Charles P.-A. Bourque. Intra- and inter-annual variations in snow–water storage in data sparse desert–mountain regions assessed from remote sensing. Remote Sensing of Environment 2013, 139, 18 -34.

AMA Style

Mir A. Matin, Charles P.-A. Bourque. Intra- and inter-annual variations in snow–water storage in data sparse desert–mountain regions assessed from remote sensing. Remote Sensing of Environment. 2013; 139 ():18-34.

Chicago/Turabian Style

Mir A. Matin; Charles P.-A. Bourque. 2013. "Intra- and inter-annual variations in snow–water storage in data sparse desert–mountain regions assessed from remote sensing." Remote Sensing of Environment 139, no. : 18-34.

Journal article
Published: 01 April 2013 in Journal of Hydrology
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Mir Matin; Charles P.-A. Bourque. Assessing spatiotemporal variation in actual evapotranspiration for semi-arid watersheds in northwest China: Evaluation of two complementary-based methods. Journal of Hydrology 2013, 486, 455 -465.

AMA Style

Mir Matin, Charles P.-A. Bourque. Assessing spatiotemporal variation in actual evapotranspiration for semi-arid watersheds in northwest China: Evaluation of two complementary-based methods. Journal of Hydrology. 2013; 486 ():455-465.

Chicago/Turabian Style

Mir Matin; Charles P.-A. Bourque. 2013. "Assessing spatiotemporal variation in actual evapotranspiration for semi-arid watersheds in northwest China: Evaluation of two complementary-based methods." Journal of Hydrology 486, no. : 455-465.