Identification of Agricultural Drought Vulnerable Areas of Tamil Nadu, India – Using GIS Based Multi Criteria Analysis

Drought being an insidious hazard, is considered to have one of the most complex phenomenons. The proposed study identifies remote sensing-based indices that could act as a proxy indicator in monitoring agricultural drought over Tamil Nadu's region India. The satellite data products were downloaded from 2000 to 2013 from MODIS, GLDAS – NOAH, and TRMM. The intensity of agricultural drought was studied using indices viz., NDVI, NDWI, NMDI, and NDDI. The satellite-derived spectral indices include raw, scaled, and combined indices. Comparing satellite-derived indices with in-situ rainfall data and 1-month SPI data was performed to identify exceptional drought to no drought conditions for September month. The additive combination of NDDI showed a positive correlation of 0.25 with rainfall and 0.23 with SPI, while the scaled NDDI and raw NDDI were negatively correlated with rainfall and SPI. Similar cases were noticed with raw LST and raw NMDI. Indices viz., LST, NDVI, and NDWI performed well; however, it was clear that NDWI performed better than NDVI while LST was crucial in deciding NDVI coverage over the study area. These results showed that no single index could be put forward to detect agricultural drought accurately; however, an additive combination of indices could be a successful proxy to vegetation stress identification.

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Remote sensing based agricultural drought assessment in Palar basin of Tamil Nadu state, India

Journal of the Indian Society of Remote Sensing ◽

10.1007/s12524-009-0008-8 ◽

2009 ◽

Vol 37 (1) ◽

pp. 9-20 ◽

Cited By ~ 7

Author(s):

T. Murali Krishna ◽

G. Ravikumar ◽

M. Krishnaveni

Keyword(s):

Remote Sensing ◽

Tamil Nadu ◽

Agricultural Drought ◽

Drought Assessment ◽

Palar Basin ◽

Tamil Nadu State

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GOOGLE EARTH ENGINE BASED AGRICULTURAL DROUGHT MONITORING IN KODAVANAR WATERSHED, PART OF AMARAVATHI BASIN, TAMIL NADU, INDIA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b5-2021-43-2021 ◽

2021 ◽

Vol XLIII-B5-2021 ◽

pp. 43-49

Author(s):

P. Thilagaraj ◽

P. Masilamani ◽

R. Venkatesh ◽

J. Killivalavan

Keyword(s):

Tamil Nadu ◽

Water Resource Management ◽

Standardized Precipitation Index ◽

Condition Index ◽

Google Earth ◽

Agricultural Drought ◽

Drought Assessment ◽

Vegetation Stress ◽

Prime Concern ◽

Google Earth Engine

Abstract. The agricultural drought assessment and monitoring has become a prime concern in recent times as it impedes land capability and causes food scarcity. Therefore, the present study constructed a methodological framework through the Google Earth Engine (GEE) platform, which offers advanced and effective monitoring in a timely concern of the drought occurrences. The study has been carried out in the Kodavanar watershed, a part of the Amaravathi basin is noted with signs of drought such as insufficient rainfall and vegetation stress in the current situation. The remote sensing indices are utilised for the agriculture drought assessment including Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Temperature Condition Index (TCI), Vegetation Condition Index (VCI) and Vegetation Health Index (VHI). In particular, the VHI results show that the area of healthy vegetation and no drought category is rapidly decreased from 934.29 to 107.83 sq.km across the years and have been reached threatening condition as extreme drought category with extremely low vegetation cover has been increasing in a exponential proportion of over 5% in the year 2019 and 2020. However, the agriculture drought results compared through the meteorological drought indicator of Standardized Precipitation Index (SPI) reflects that the SPI and VHI are reflecting similar signs and indicating the dry condition of precipitation with moderate vegetation over the highlighted regions of northern tip and central eastern portions. This present work illustrates the effective use of the GEE platform in monitoring the agriculture drought and the highlighted portions of the study should be implemented with proper water resource management by the researchers, planners and policymakers in the Kodavanar watershed for reducing the vegetation stress.

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ASSESSMENT OF AGRICULTURAL DROUGHT USING REMOTE SENSING BASED ON MODIS NDVI FOR DIFFERENT AGRO-CLIMATIC ZONES OF TAMIL NADU, INDIA

10.1130/abs/2020am-355725 ◽

2020 ◽

Author(s):

Venkadesh Samykannu ◽

◽

S. Pazhanivelan ◽

P.J. Prajesh ◽

K.P. Ragunath ◽

...

Keyword(s):

Remote Sensing ◽

Tamil Nadu ◽

Agricultural Drought ◽

Climatic Zones ◽

Modis Ndvi

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MONITORING OF AGRICULTURAL DROUGHT USING FORTNIGHTLY VARIATION OF VEGETATION CONDITION INDEX (VCI) FOR THE STATE OF TAMIL NADU, INDIA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-w9-159-2018 ◽

2018 ◽

Vol XLII-4/W9 ◽

pp. 159-164 ◽

Cited By ~ 1

Author(s):

N. Vaani ◽

P. Porchelvan

Keyword(s):

Tamil Nadu ◽

Agricultural Productivity ◽

Condition Index ◽

The State ◽

Regional Level ◽

Agricultural Drought ◽

Drought Intensity ◽

Vegetation Condition Index ◽

Drought Conditions

<p><strong>Abstract.</strong> India being an agrarian nation widely depends upon rainfall for its agricultural productivity. The failure of rainfall and hence shortfall of productivity badly affects national economy. With an intricate nature of drought, the planning and management requires rigid monitoring for better understanding. The occurrence of drought and its severity varies in a regional level. The process of monitoring agricultural drought in a regional level requires long term analysis of vegetation. In this present work, the attempt has been carried out to study and monitor the spatial and temporal variation of agricultural drought for the state of Tamilnadu, India which is more prone to drought especially due to monsoon failure or change in monsoon. The long term Normalized differenced vegetation index (NDVI) of Global Inventory Modelling and Mapping Studies (GIMMS) for the period of 20 years (1984&ndash;2003) was used to compute the most popular index called vegetation condition index (VCI) to identify the vegetation vigour. The fortnightly variation of VCI during major crop growing period of Kharif season (June to September) was used to monitor the spatio-temporal drought conditions of Tamil Nadu. The results proved that there is wide variation of drought intensity among the districts within the state. The keen observation of fortnightly variation of long term agricultural drought helps finding the onset, period and spatial extent of drought in various districts of the state. The districts which are most often prone to moderate to severe drought conditions during the analysis period were recognized in order to develop various strategies to improve the agricultural productivity in that region. The persistent drought in the state necessitates the government to take appropriate preventive measures to evade drought in future. Based on the severity of the drought level observed from the agricultural drought intensity maps prepared using VCI, the action plans could be prioritized by identifying the high risk zones.</p>

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