Time-series analysis of MODIS (LST and NDVI) and TRMM rainfall for drought assessment over India

IF 2.3 Q2 REMOTE SENSING Applied Geomatics Pub Date : 2023-04-25 DOI:10.1007/s12518-023-00505-y

P. Thanabalan, R. Vidhya, R. S. Kankara, R. Manonmani

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引用次数: 1

Abstract

In this study, an attempt has been made using rainfall, LST, and NDVI combination of LSNR model which is used to infer drought condition in different monsoon period and to predict the seasonal changes of drought condition. The Indian monsoon pattern with different seasonal changes has been studied for the year 2009 to 2013 using optical and passive remote sensing data, and cross correlation with different time lag is carried out. The cross correlation between LST and NDVI time-lag deviation responses describe that May month LST having influence with September NDVI (90 days before onset) in other words 2–3 months. The correlation performed with a combination of rainfall and NDVI are not at significant level. The passive Advanced Microwave Scanning Radiometer (AMSR-E) derived soil moisture data also clearly examined the drought and normal years, as the soil moisture is highly sensitive to rainfall and temperature to assess drought condition. The relationship between Tropical Rainfall Meteorological Mission (TRMM) rainfall records is compared with observed Indian Meteorological Department (IMD) datasets for the same time period to confirm the drought severity. This will help in being prepared for the drought condition well before it actually sets in and is useful for planner in agricultural operations.

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印度干旱评估的MODIS (LST和NDVI)和TRMM降雨时序分析

摘要本研究尝试将LSNR模型与降雨、LST和NDVI相结合，用于推断不同季风期的干旱状况，并预测干旱状况的季节变化。利用光学和被动遥感数据研究了2009-2013年不同季节变化的印度季风模式，并进行了不同时滞的互相关。LST和NDVI时间滞后偏差响应之间的交叉相关性描述了5月LST对9月NDVI（发病前90天）的影响，换句话说是2-3个月。降雨和NDVI的组合相关性不显著。被动高级微波扫描辐射仪（AMSR-E）获得的土壤水分数据也清楚地检查了干旱和正常年份，因为土壤水分对降雨量和温度高度敏感，可以评估干旱状况。将热带降雨气象任务（TRMM）降雨记录与印度气象部门（IMD）同期观测数据集之间的关系进行比较，以确认干旱的严重程度。这将有助于在干旱发生之前做好准备，对农业运营的规划者也很有用。

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来源期刊

Applied Geomatics REMOTE SENSING-

CiteScore

5.40

自引率

3.70%

发文量

期刊介绍： Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences. The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology. Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements