Assessing Agricultural Drought in Natural Rubber Plantations Using MODIS/Terra Satellite Data

Transcription

1 Scientist C Agronomy/Soils Assessing Agricultural Drought in Natural Rubber Plantations Using MODIS/Terra Satellite Data *Meti S., Shebin S.M., James Jacob., Pradeep B., and Jessy, M.D. Rubber Research Institute of India, Rubber Board, Ministry of Commerce & Industry Govt. of India, Kerala meti@rubberboard.org.in International Rubber Conference October 2012 Introduction to Drought Drought is the consequence of natural reduction in amount of precipitation over extended period of time (WMO, 1997). 1

2 Characteristics of Drought It is slow creeping natural disaster Varies spatially and temporally Drought monitoring methods 1. Conventional ground based 2. Monitoring vegetation using satellite images Drought monitoring by its very nature, require reliable and timely time series data at same location and satellite data is the obvious choice Drought Assessment Globally NOAA and MODIS are the widely used satellite data for drought assessment and monitoring. IWMI drought assessment for south-west Asia and NADAMS project of NRSC Hyderabad are the good examples of operational use of satellite data for drought monitoring and assessment. 2

3 Satellite based drought assessment Reflectance in visible region Reflectance in Infra red region Two vital inputs used for satellite based drought assessment Normalized Difference Vegetation Index (NDVI) derived from reflectance in visible region indicate vegetation health. Higher NDVI- more vegetation cover and better health of vegetation Reflectance in Infra red region- is the land surface temperature Surface Energy Balance Land surface Temperature (LST) is the skin temperature of ground derived from reflectance in IR region. It indicate the earth s surface energy balance and hence is used as a proxy for assessing the surface ET 3

4 Relation between LST and NDVI No Evaporation LST NDVImax -LST NDVI i LST NDVImax -LST NDVImin Max Evaporation Max transpiration Bare soil Full vegetation cover Using this relation Wan (2001) developed an index called Vegetation Temperature Condition Index (VTCI). VTCI = LST NDVImax - LST NDVI i LST NDVImax - LST NDVImin where, LST NDVImax = a + b NDVIi LST NDVImin = a' + b' NDVIi LST NDVI i denotes LST of a pixel The value of VTCI ranges from 0 to 1; the lower VTCI associated with dry area and higher value with wetter area. 4

5 The need for Drought assessment in NR growing area In India, natural rubber is grown in varied agro-climatic condition and soil type. In the context of climate change, there is a need to monitor and delineate the rubber areas, prone to drought and adopt suitable mitigation strategies. Objective To identify the spatial extent of agricultural drought stress in natural rubber plantations of Kerala and Kanyakumari district of Tamil Nadu using satellite based remote sensing data and GIS. 5

6 Study Area Longitude: 74 o 48' to 77 o 38' E Latitude: 7 o 58' to 12 o 53' N Geographical area: 40, Sq. km. Elevation: m Slope: 0-84 o Rubber Area: 5,19, ha (12.28% of the geographical area). Materials and Methods Details of satellite data used Satellite Data Used MODIS 11 A2 LST Satellite Data Acquisition Period 01/01/2010 to 08/01/ /02/2010 to 09/02/ /03/2010 to 13/03/2010 MODIS 13 A2 06/03/2010 to 21/03/2010 NDVI website ( Administrative boundaries : SOI toposheet of scale 1:2, 50,000 Software : ArcGIS v. 10 and Rolta Geomatica v Kasargod Kannur Kozhikkode Malappuram Rubber Distribution map Wynad Trissur Ernakulam Alapuzha Kottayam Palakkad Idukki Kollam Trivandrum KmKannyakumari 6

7 Preprocessing The following preprocessing steps were followed for the MODIS data 1. Conversion of file format from HDF to Geotif 2. Layer stacking 3. Reprojection to UTM WGS Multiplication with scaling factor 5. Subsetting of study area Results 7

8 Land Surface Temperature January February Land Surface Temperature February March 8

9 NDVI image 9

10 Area under different NDVI ranges NDVI of March % Area (ha) % 21.17% % 0.35% 4.51% 0.002% 0 < >0.9 Series1 Area Relation between LST and NDVI Uisng the LST_NDVI max and LST_NDVI min, calculated the VTCI value for all pixels 10

11 VTCI of March 2010 Geographical Area under different VTCI ranges during March Area (ha) VTCI March % 27.78% 19.20% 7.23% 2.34% 1.72% 1.32% 0 < >0.9 Area

12 Overlay Analysis in GIS Rubber Distribution map VTCI map Overlay analysis Rubber area under moisture stress Overlaid administrative boundary Districtwise rubber area under moisture stress Distribution of rubber area with moisture stress 12

13 64.70% 25.25% 8.36% 1.58% 0.11% 0.002% 0 VTCI 13

14 Conclusion Study showed the utility of Geospatial technology in assessing and delineating NR growing areas experiencing moisture stress. For any drought planner, monitoring drought at regional scale without much expenditure is possible using MODIS satellite data. 14