Informations et ressources scientifiques
sur le développement des zones arides et semi-arides

Accueil du site → Doctorat → Chine → 2020 → Agricultural Drought Monitoring Using Multi-source Remote Sensing Data in China

Northwest A&F University (2020)

Agricultural Drought Monitoring Using Multi-source Remote Sensing Data in China

Tehseen Javed

Titre : Agricultural Drought Monitoring Using Multi-source Remote Sensing Data in China

Auteur : Tehseen Javed;

Grade : Doctoral Dissertation 2020

Université : Northwest A&F University

Résumé partiel
Drought is an insidious hazard of nature,which is considered by many to be the most complex but least,understood of all-natural hazards.For monitoring of drought,large historical datasets are required,which involves complex inter-relationship between the climatological and meteorological data.The extraction of valuable information from such extensive data archives demands an automated and efficient way.Data mining is the answer to the above problem as it has the potential to search for hidden patterns and identify the relationship between the data.China has also been suffered from frequent droughts events,which has brought potential hazards to sustainable crop production.Therefore,the study of spatial-temporal variation characteristics of agricultural drought monitoring plays a vital role in drought relief and agricultural planning.The study analyzes the relationship between the metrological and agricultural drought,the impact of drought on vegetation phenology,and productivity and investigates the drought indices performances for prediction of agriculture drought.Multiple datasets were used in this study,daily precipitation and temperature datasets from 763 stations,between1961-2017 china meteorological bureau,satellite gridded monthly precipitation,land cover,thermal bands,normalized difference vegetation index(NDVI),and soil moisture.For assessment of drought events and there correlation the following drought indices were calculated,standardized precipitation index(SPI),standardized precipitation-evapotranspiration index(SPEI),precipitation anomaly,vegetation condition index(VCI),NDVI anomaly,enhanced vegetation index(EVI),standardized soil moisture index(SSI),multivariate standardized drought index(MSDI),and vegetation health index(VHI).To find the correction and trends of these drought indices,the following statistical analysis was performed ;Pearson correlation coefficient(r),linear regression,coefficient of determination(R2),and root mean square error(RMSE)and modified Mann-Kendall(MMK).The study was divided into four phases.In the first phase of the study,drought was assessed under four different land cover types,cropland,forestland,grassland,and desert-land in China.The modified Mann-Kendall test was used to detect the significance of a trend

Mots clés : agricultural drought; drought indices; land cover type; modified Mann–Kendall test; remote sensing; vegetation phenology; CHIRPS; LST; NDVI; four sub-regions of China;

Présentation (CNKI)

Page publiée le 10 juin 2021