Smos based High Resolution Soil Moisture Estimates for Desert Locust Preventive Management

This paper presents the the first attempt to include soil moisture information from remote sensing in the tools available to desert locust managers. The soil moisture requirements were first assessed with the users. The main objectives of this paper are: i) to describe and validate the algorithms used to produce a soil moisture dataset at 1 km resolution relevant to desert locust management based on DisPATCh methodology applied to SMOS and ii) the development of an innovative approach to derive high (100 m) resolution soil moisture products from Sentinel-1 in synergy with SMOS data. For the purpose of soil moisture validation, 4 soil moisture stations where installed in desert areas (one in each user country). The soil moisture 1km product was thoroughly validated and its accuracy is amongst the best available soil moisture products. Current comparison with in-situ soil moisture stations shows good values of correlation (R > 0.7) and low RMSE (below 0.04 m3m−3). The low number of acquisitions on wet dates has limited the development of the soil moisture 100m product over the Users Areas. The Soil Moisture product at 1km will be integrated into the national and global Desert Locust early warning systems in national locust centres and at DLIS-FAO, respectively.

[1]  W. Wagner,et al.  A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data , 1999 .

[2]  Yann Kerr,et al.  Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission , 2001, IEEE Trans. Geosci. Remote. Sens..

[3]  Keith Cressman,et al.  Role of remote sensing in desert locust early warning , 2013 .

[4]  K. Cressman,et al.  Surveillance, information sharing and early warning systems for transboundary plant pests diseases: the FAO experience. , 2009 .

[5]  M. Lecoq,et al.  Preventive control and desert locust plagues , 2008 .

[6]  Stephen J. Simpson,et al.  Locust Phase Polyphenism: An Update , 2009 .

[7]  Olivier Merlin,et al.  Consistency between In Situ, Model-Derived and High-Resolution-Image-Based Soil Temperature Endmembers: Towards a Robust Data-Based Model for Multi-Resolution Monitoring of Crop Evapotranspiration , 2015, Remote. Sens..

[8]  Pere Quintana-Seguí,et al.  Comparison of remote sensing and simulated soil moisture datasets in Mediterranean landscapes , 2016 .

[9]  Pierre Defourny,et al.  A Dynamic Vegetation Senescence Indicator for Near-Real-Time Desert Locust Habitat Monitoring with MODIS , 2015, Remote. Sens..

[10]  Ahmad Al Bitar,et al.  SMOS disaggregated soil moisture product at 1 km resolution: Processor overview and first validation results , 2016, Remote Sensing of Environment.

[11]  A. Chehbouni,et al.  Soil surface moisture estimation over a semi-arid region using ENVISAT ASAR radar data for soil evaporation evaluation , 2011 .

[12]  R. Lacaze,et al.  A Global Database of Land Surface Parameters at 1-km Resolution in Meteorological and Climate Models , 2003 .

[13]  Arnaud Mialon,et al.  The SMOS Soil Moisture Retrieval Algorithm , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Syukuro Manabe,et al.  THE ATMOSPHERIC CIRCULATION AND THE HYDROLOGY OF THE EARTH ’ S SURFACE , 1969 .

[15]  P. Snoeij,et al.  GMES SENTINEL-1 MISSION AND SYSTEM , 2009 .

[16]  A. Al Bitar,et al.  SMOS soil moisture product evaluation over West-Africa from local to regional scale , 2015 .

[17]  Michel Lecoq,et al.  Phase polyphenism and preventative locust management. , 2010, Journal of insect physiology.

[18]  J. Eitzinger,et al.  The ASCAT Soil Moisture Product: A Review of its Specifications, Validation Results, and Emerging Applications , 2013 .

[19]  Pierre Defourny,et al.  Operational Monitoring of the Desert Locust Habitat with Earth Observation: An Assessment , 2015, ISPRS Int. J. Geo Inf..

[20]  Richard K. Moore,et al.  Microwave Remote Sensing, Active and Passive , 1982 .

[21]  Christoph Rüdiger,et al.  DisPATCh as a tool to evaluate coarse-scale remotely sensed soil moisture using localized in situ measurements: Application to SMOS and AMSR-E data in Southeastern Australia , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[22]  Jiancheng Shi,et al.  The Soil Moisture Active Passive (SMAP) Mission , 2010, Proceedings of the IEEE.

[23]  B. P. Uvarov,et al.  A revision of the genus Locusta, L. (= Pachytylus, Fieb.), with a new theory as to the periodicity and migrations of locusts , 1921 .

[24]  Pietro Ceccato,et al.  Evaluating Detection Skills of Satellite Rainfall Estimates over Desert Locust Recession Regions , 2010 .

[25]  Philippe Richaume,et al.  Disaggregation of SMOS Soil Moisture in Southeastern Australia , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[26]  Ahmad Al Bitar,et al.  Self-calibrated evaporation-based disaggregation of SMOS soil moisture: An evaluation study at 3 km and 100 m resolution in Catalunya, Spain , 2013 .

[27]  Christelle Vancutsem,et al.  Development and Application of Multi-Temporal Colorimetric Transformation to Monitor Vegetation in the Desert Locust Habitat , 2011, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[28]  M. S. Moran,et al.  Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index , 1994 .

[29]  P. Hunter-Jones.  Egg development in the Desert Locust (Schistocerca gregaria Forsk.) in relation to the availability of water , 2009 .

[30]  Mehrez Zribi,et al.  SMOS based high resolution soil moisture estimates for desert locust preventive management , 2018, Remote Sensing Applications: Society and Environment.

[31]  Malcolm Davidson,et al.  C-Band SAR Data for Mapping Crops Dominated by Surface or Volume Scattering , 2014, IEEE Geoscience and Remote Sensing Letters.

[32]  Yoann Malbéteau,et al.  Performance Metrics for Soil Moisture Downscaling Methods: Application to DISPATCH Data in Central Morocco , 2015, Remote. Sens..

[33]  Anna Balenzano,et al.  On the use of temporal series of L-and X-band SAR data for soil moisture retrieval. Capitanata plain case study , 2013 .

[34]  S. M. Jong,et al.  Observation uncertainty of satellite soil moisture products determined with physically-based modeling , 2012 .

[35]  Thomas J. Jackson,et al.  Soil moisture retrieval from AMSR-E , 2003, IEEE Trans. Geosci. Remote. Sens..

[36]  Kamal Sarabandi,et al.  Full-wave analysis of microwave scattering from short vegetation: an investigation on the effect of multiple scattering , 2002, IEEE Trans. Geosci. Remote. Sens..

[37]  C. Piou,et al.  Importance of solitarious desert locust population dynamics: lessons from historical survey data in Algeria , 2016 .

[38]  J. B. Williams,et al.  Satellite Environmental Monitoring for Migrant Pest Forecasting by FAO: The ARTEMIS System [and Discussion] , 1990 .

[39]  Thierry Pellarin,et al.  Hydrological modelling and associated microwave emission of a semi-arid region in South-western Niger , 2009 .

[40]  Z. Wan,et al.  Using MODIS Land Surface Temperature and Normalized Difference Vegetation Index products for monitoring drought in the southern Great Plains, USA , 2004 .

[41]  A. Latchininsky,et al.  Applications of remote sensing to locust management , 2016 .

[42]  P. Rosnay,et al.  Multi-scale soil moisture measurements at the Gourma meso-scale site in Mali , 2009 .