Spatial modelling of rainfall trends using satellite datasets and geographic information system     

Sanjay Kumar  Deepesh Machiwal  Devi Dayal 《水文科学杂志》2017,62(10):1636-1653

This study developed a standard methodology for identifying spatial trends using satellite-based raster datasets. It involves the novelty of exploring the capabilities of a geographic information system in implementing the procedures of three trend tests, the Spearman rank order correlation (SROC) test, the Kendall rank correlation (KRC) test and the Mann-Kendall (MK) test, on raster datasets of the Tropical Rainfall Measuring Mission at 0.25° × 0.25° resolution. Comparative evaluation of the three tests revealed fair agreement of a major part of the test results for pre-, post- and non-monsoon and one-day maximum rainfall. Also, similar results from KRC and MK tests were obtained over a considerable area for annual, monsoon and monthly maximum rainfall. These findings suggest the importance of selecting the appropriate test depending on rainfall magnitudes at the chosen time scale and emphasize the robustness of the KRC and MK tests.  相似文献   

Assessing Carbon Stock and Sequestration of the Tropical Seagrass Meadows in Indonesia     

Wahyudi  A’an J.  Rahmawati  Susi  Irawan  Andri  Hadiyanto  Hadiyanto  Prayudha  Bayu  Hafizt  Muhammad  Afdal  Afdal  Adi  Novi S.  Rustam  Agustin  Hernawan  Udhi. E.  Rahayu  Yusmiana P.  Iswari  Marindah Y.  Supriyadi  Indarto H.  Solihudin  Tubagus  Ati  Restu Nur Afi  Kepel  Terry L.  Kusumaningtyas  Mariska A.  Daulat  August  Salim  Hadiwijaya L.  Sudirman  Nasir  Suryono  Devi D.  Kiswara  Wawan 《Ocean Science Journal》2020,55(1):85-97

Ocean Science Journal - Seagrass meadows provide critical ecosystem services for coastal areas, e.g., as nursery habitats for various fish species, help with water filtration of suspended sediment,...  相似文献   

Recent snow cover variation in the Upper Indus Basin of Gilgit Baltistan,Hindukush Karakoram Himalaya     

Hazrat BILAL  CHAMHURI Siwar  MAZLIN Bin Mokhtar  KASTURI Devi Kanniah 《山地科学学报》2019,(2)

Mountainous basins like the Upper Indus Basin(UIB) of Gilgit Baltistan(GB) are dependent on seasonal snowmelt and glacier melt. Monitoring of the snow-covered area(SCA) is not only vital for the overall hydrology of the Indus basin but also important to the sustainable agriculture and hydropower system. The snow-covered area in the UIB of GB was investigated for changes over the last 18 years using the Moderate Resolution Imaging Spectroradiometer(MODIS) snow product. The study area was divided into five elevation zones ranging from 877-8564 meters above sea level(m ASL). In contrast to the global cryosphere related studies, SCA in the UIB is slightly increasing. Elevation based SCA analysis also indicated that SCA is slightly increasing in each elevation zone. However, a significant amount of snow is concentrated in areas above 5000 m ASL. Due to the strong correlation between SCA and precipitation, the precipitation data also follow a similar trend. Analysis of the climatic data suggests a statistically significant increase in total monthly precipitation and relative humidity, a slight decrease in mean monthly temperature and a significant upward tendency in monthly solar irradiance data. All these trends in combination with the increasing trend in global precipitation, winter westerly disturbances and orographic precipitation are the important factors behind the slightly increasing SCA in the study area. Our results though constrained by short observation period mainly contribute to the understanding of advancing snow cover and glaciers in Hindukush Karakoram.  相似文献   

Optical and radar remote sensing data for forest cover mapping in Peninsular Malaysia     

Nazarin Ezzaty Mohd Najib  Kasturi Devi Kanniah 《Singapore journal of tropical geography》2019,40(2):272-290

This study aims to map forest cover in Peninsular Malaysia using satellite images as deforestation is of concern in the recent decades, and is an important environmental issue for the future too. The Carnegie Landsat Analysis System‐Lite (CLASlite) program was used in this study to detect forest cover in Peninsular Malaysia using Landsat satellite data. The results of the study show that CLASlite algorithm misclassified some oil palm, rubber and urban areas as forest vegetation. A reliable forest cover map was produced by first combining Landsat and ALOS PALSAR images to identify oil palm, rubber and urban areas, and then subsequently removing them. The HH and HV polarization data of ALOS PALSAR (threshold method) could detect oil palm plantations with 85.26 per cent of overall accuracy. For urban area detection, Enhance Build up Index (EBBI) using spectral bands from Landsat provided higher overall accuracy of 94 per cent. These methods produced a forest cover reading of 5 914 421 ha with an overall classification accuracy of 94.5 per cent. The forest cover (including rubber areas) detected in this study is 0.38 per cent higher than the percentage of 2010 forest cover detected by the Forestry Department of Peninsular Malaysia. The technique described in this paper presents an alternative and viable approach for updating forest cover maps in Malaysia.  相似文献