Detecting Zimbabwe's Decadal Economic Decline Using Nighttime Light Imagery

Zimbabwe’s economy declined between 2000 and 2009. This study detects the economic decline in different regions of Zimbabwe using nighttime light imagery from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS). We found a good correlation (coefficient = 0.7361) between Zimbabwe’s total nighttime light (TNL) and Gross Domestic Product (GDP) for the period 1992 to 2009. Therefore, TNL was used as an indicator of regional economic conditions in Zimbabwe. Nighttime light imagery from 2000 and 2008 was compared at both national and regional scales for four types of regions. At the national scale, we found that nighttime light in more than half of the lit area decreased between 2000 and 2008. Moreover, within the four region types (inland mining towns, inland agricultural towns, border towns and cities) we determined that the mining and agricultural sectors experienced the most severe economic decline. Some of these findings were validated by economic survey data, proving that the nighttime light data is a potential data source for detecting the economic decline in Zimbabwe.

[1]  K. Seto,et al.  Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data , 2011 .

[2]  Naizhuo Zhao,et al.  Estimation of virtual water contained in international trade products using nighttime imagery , 2012, Int. J. Appl. Earth Obs. Geoinformation.

[3]  Blessing Chiripanhura Sneaking up and stumbling back: Textiles sector performance under crisis conditions in Zimbabwe , 2008 .

[4]  E. H. Erwin,et al.  A global inventory of coral reef stressors based on satellite observed nighttime lights , 2008 .

[5]  J. Henderson,et al.  A Bright Idea for Measuring Economic Growth. , 2011, The American economic review.

[6]  Zhifeng Liu,et al.  Spatiotemporal dynamics of electric power consumption in Chinese Mainland from 1995 to 2008 modeled using DMSP/OLS stable nighttime lights data , 2012, Journal of Geographical Sciences.

[7]  Mikhail Zhizhin,et al.  A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data , 2009 .

[8]  Amon Murwira,et al.  The use of multi-temporal MODIS images with ground data to distinguish cotton from maize and sorghum fields in smallholder agricultural landscapes of Southern Africa , 2012 .

[9]  Christopher D. Elvidge,et al.  Quantifying light-fishing for Dosidicus gigas in the eastern Pacific using satellite remote sensing , 2004 .

[10]  Zhifeng Liu,et al.  Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008 , 2012 .

[11]  Baghdad Nights: Evaluating the US Military ‘Surge’ Using Nighttime Light Signatures , 2008 .

[12]  K. Giller,et al.  Comparative performance of conservation agriculture and current smallholder farming practices in semi-arid Zimbabwe , 2012 .

[13]  Godwin Masuka,et al.  Contests and struggle: Cotton farmers and COTTCO in Rushinga district, Zimbabwe, 1999–2006 , 2012 .

[14]  B. Cousins,et al.  An overview of Fast Track Land Reform in Zimbabwe: editorial introduction , 2011 .

[15]  Masamu Aniya,et al.  Hybrid classification of Landsat data and GIS for land use/cover change analysis of the Bindura district, Zimbabwe , 2009 .

[16]  W. Nordhaus,et al.  Using luminosity data as a proxy for economic statistics , 2011, Proceedings of the National Academy of Sciences.

[17]  C. Elvidge,et al.  Spatial characterization of electrical power consumption patterns over India using temporal DMSP‐OLS night‐time satellite data , 2009 .

[18]  Nhamo Anthony Mhiripiri,et al.  The production of stardom and the survival dynamics of the Zimbabwean music industry in the post-2000 crisis period , 2010 .

[19]  Christopher D. Elvidge,et al.  Estimation of Mexico's Informal Economy and Remittances Using Nighttime Imagery , 2009, Remote. Sens..

[20]  Xi Li,et al.  Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China , 2013, Remote. Sens..

[21]  Rekopantswe Mate,et al.  Making Ends Meet at the Margins?: Grappling with Economic Crisis and Belonging in Beitbridge Town , Zimbabwe , 2005 .

[22]  Jin Chen,et al.  Modelling the population density of China at the pixel level based on DMSP/OLS non‐radiance‐calibrated night‐time light images , 2009 .

[23]  Macleans Mzumara Was Zimbabwe competitive in international trade 2000-2009 , 2011 .

[24]  Christopher D. Elvidge,et al.  Biomass burning and related trace gas emissions from tropical dry deciduous forests of India: A study using DMSP-OLS data and ground-based measurements , 2002 .

[25]  Ajuruchukwu Obi,et al.  Performance of Smallholder Agriculture Under Limited Mechanization and the Fast Track Land Reform Program in Zimbabwe , 2011 .

[26]  I. W. Nyakudya,et al.  Maize yield forecasting for Zimbabwe farming sectors using satellite rainfall estimates , 2011 .

[27]  C. Elvidge,et al.  National Trends in Satellite-Observed Lighting: 1992–2012 , 2011 .

[28]  Cyrus Samimi,et al.  Deforestation in the Miombo woodlands: a pixel-based semi-automated change detection method , 2011 .

[29]  J. Muller,et al.  Mapping regional economic activity from night-time light satellite imagery , 2006 .

[30]  C. Elvidge,et al.  Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption , 1997 .

[31]  Budhendra L. Bhaduri,et al.  A global poverty map derived from satellite data , 2009, Comput. Geosci..

[32]  Shumirai Nyota,et al.  Digging for Diamonds, Wielding New Words: A Linguistic Perspective on Zimbabwe's ‘Blood Diamonds’ , 2012 .

[33]  W. Gumindoga,et al.  Estimation of actual evapotranspiration using the Surface Energy Balance System (SEBS) algorithm in the Upper Manyame catchment in Zimbabwe , 2011 .

[34]  Patience Mudimu,et al.  Developing an informal settlement upgrading protocol in Zimbabwe – the Epworth story , 2012 .

[35]  C. Elvidge,et al.  Spatial analysis of global urban extent from DMSP-OLS night lights , 2005 .

[36]  Qian Zhang,et al.  Can Night-Time Light Data Identify Typologies of Urbanization? A Global Assessment of Successes and Failures , 2013, Remote. Sens..

[37]  R. F. Grais,et al.  Explaining Seasonal Fluctuations of Measles in Niger Using Nighttime Lights Imagery , 2011, Science.

[38]  T. Pei,et al.  Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: A comparative case study from China's cities , 2012 .