Mining and Agricultural Productivity
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1 Mining and Agricultural Productivity - A presentation of preliminary results for Ghana The World Bank, Washington D.C., USA, 29 May 214 MAGNUS ANDERSSON, Senior Lecturer in Human Geography, Lund University, OLA HALL, Senior Lecturer in Human Geography, Lund University, NIKLAS OLÉN, PhD candidate at Department of Physical Geography and Ecosystem Science, Lund University NDVI, MODIS 213
2 Task The objective of the assignment is to use remote sensing data to estimate level and growth (or decline) of production in four case studies in Africa (Ghana, Mali, Tanzania, and Burkina Faso). Compare the estimated levels and changes in agricultural and non-agricultural production in mining and non-mining localities, where the distinction is defined by a distance metric. Define a radius around the mining areas, and then define larger radius in order to estimate the level and composition of production agricultural and nonagricultural as a function of distance from the mining areas.
3 Output A background paper (co-authored with the World Bank team in charge of the project), motivating question, the empirical methodology, discussion of results and policy conclusions will be the main output. Prepared and documented spatial database with NDVI and Nighlight for use by World Bank team.
4 A Satellite Based Method We decide spatial and temporal resolution Strength are detail and overview in observation Field studies or remote sensing? A combination is necessary Temporal Resolution (days) Temporal scaling MODIS EVI Ikonos QuickBird DMSP OLS Spatial scaling Spatial Resolution (m)
5 Data Production data from 15 mines in Ghana provided by World Bank team MODIS NDVI Aqua & Terra Duration: Spatial: 25x25m Temporal: 23x2 obs./year Hansen (213) Forest Cover Duration: 2 21 Spatial: 3x3m Temporal: Annual DMSP-OLS Nighttime Lights Duration: Spatial: 1x1km Temporal: Annual
6 Normalized Difference Vegetation Index (NDVI) NDVI and variations thereof can be used to study economic development Can be linked to Leaf area, biomass, NPP, land-use changes, etc. NDVI = NIR - Red NIR + Red Vegetation
7 Normalized Difference Vegetation Index (NDVI) Provides an estimate of vegetation Health Changes over time Water Barren areas Shrub/Grassland Tropical rainforest
8 TIMESAT program used to process NDVI Display data Filter data Extract information from vegetation time-series Start/End of Season (a,b) Amplitude (c) Maximum (d) Integrals d * c a b Eklundh & Jönsson (211), Jönsson & Eklundh (22;24)
9 Link between night light and economic activies
10 Light & Agriculture Model Ghana (I) Growth ~NNNNNNNNNNNNNNNNNN + AAAAAAAAAAAAAAAAAAAAAA
11 Light & Agriculture Model Ghana (II) An extension of the model: Growth ~NNNNNNNNNNNNNNNNNN + NNNNNNNN + FFFFFFFFFFFF llllllll 8E+1 7E+1 6E+1 5E+1 GDP (current LCU) 4E+1 3E+1 modelgdp 2E+1 1E
12 Preliminary results Ghana - Working process Maps and spatial analysis - Reference and land cover maps Classification of mines - large and small based on production data Descriptive analysis - night light trends and buffer - forest loss trends and buffer - NDVI trends and buffer Growth model for districts - local economic growth - spatial analysis of growth trends
13 Large expanding mines production figures 25 TARKWA MINE AHAFO / SUBIKA - NTOTOROSO
14 Large expanding mines Night-light trends Sum of Lights/Area TARKWA MINE AHAFO / SUBIKA - NTOTOROSO Sum of Lights/Area
15 Large expanding mines Night-light yearly buffer AHAFO / SUBIKA - NTOTOROSO Buffer distance (km) AHAFO / SUBIKA - 14 NTOTOROSO Buffer distance (km) AHAFO / SUBIKA - NTOTOROSO Buffer distance (km) TARKWA MINE Buffer distance (km) TARKWA MINE Buffer distance (km) TARKWA MINE Buffer distance (km) TARKWA MINE Buffer distance (km) TARKWA MINE Buffer distance (km)
16 Small mines production figures (provided by World Bank) Axis Title WASSA IDUAPRIEM
17 Small mines Night-light trends Wassa Sum of Lights/Area Obotan Sum of Lights/Area
18 Small mines Night-light yerly buffer OBOTAN Buffer distance (km) OBOTAN Buffer distance (km) OBOTAN Buffer distance (km) OBOTAN Buffer distance (km) WASSA WASSA WASSA - 28 WASSA Buffer distance (km) Buffer distance (km) Buffer distance (km) Buffer distance (km)
19 Night light - districts average change
20 3 Categories Night light average change , Average of Ave %Change (%) , 6, 5, 4, 3, Category-1 Category-2 Category-3 Category (1+2) Whole (1+2+3) 2, 1,, Category-1 Category-2 Category-3 Category (1+2) Whole (1+2+3)
21 Large expanding mines Forest cover loss yearly buffer AHAFO / SUBIKA - NTOTOROSO AHAFO / SUBIKA - NTOTOROSO AHAFO / SUBIKA - NTOTOROSO AHAFO / SUBIKA - NTOTOROSO AHAFO / SUBIKA - NTOTOROSO TARKWA MINE TARKWA MINE TARKWA MINE TARKWA MINE TARKWA MINE
22 Sum of Forest Decrease / Area Large expanding mines Forest cover loss trends , 12, 1, 8, 6, 4, 2,, TARKWA MINE Sum of Forest Decrease / Area 9, 8, 7, 6, 5, 4, 3, 2, 1,, AHAFO / SUBIKA - NTOTOROSO
23 Small mines Forest loss trends Wassa 2, 18, 16, 14, 12, 1, 8, 6, 4, 2,, Sum of Forest Decrease / Area Obotan Sum of Forest Decrease / Area 12, 1, 8, 6, 4, 2,,
24 Small mines Forest loss yearly buffer WASSA - 21 WASSA - 25 WASSA OBOTAN - 21 OBOTAN - 25 OBOTAN - 29 OBOTAN
25 Forest loss- districts average change
26 3 Categories Forest loss average change Average of Ave %Change (%) , 3, 25, 2, 15, 1, 5,, Category-1 Category-2 Category-3 Category (1+2) Whole (1+2+3) Category-1 Category-2 Category-3 Category (1+2) Whole (1+2+3)
27 Intensity of NDVI / Area Large expanding mines NDVI trends TARKWA MINE Intensity of NDVI / Area AHAFO / SUBIKA - NTOTOROSO
28 Large expanding mines NDVI buffer AHAFO / SUBIKA - NTOTOROSO - 21 AHAFO / SUBIKA - NTOTOROSO - 25 AHAFO / SUBIKA - NTOTOROSO - 29 AHAFO / SUBIKA - NTOTOROSO TARKWA MINE - 21 TARKWA MINE - 25 TARKWA MINE - 29 TARKWA MINE
29 Small mines NDVI trends Intensity of NDVI / Area Wassa Obotan 16 Intensity of NDVI / Area
30 Small mines NDVI buffer WASSA - 21 WASSA - 25 WASSA - 29 WASSA OBOTAN OBOTAN OBOTAN OBOTAN
31 NDVI change districts average change
32 3 Categories NDVI change average change ,7 Average of Ave %Change (%),6,5,4,3,2,1 Category-1 Category-2 Category-3 Category (1+2) Whole (1+2+3), Category-1 Category-2 Category-3 Category (1+2) Whole (1+2+3) -,1 -,2
33 Results estimation of economic growth in districts An extension of the national model on district level: Growth ~NNNNNNNNNNNNNNNNNN + NNNNNNNN + FFFFFFFFFFFF llllllll lm(formula = GDP ~ + ndvi + forest + light, data = data) Residuals: Min 1Q Median 3Q Max e e e e e+1 Coefficients: Estimate Std. Error t value Pr(> t ) ndvi * forest light ** --- Signif. codes: ***.1 **.1 * Residual standard error: 1.463e+1 on 9 degrees of freedom Multiple R-squared:.8665, Adjusted R-squared:.822 F-statistic: on 3 and 9 DF, p-value:.2836
34 Results estimation of districts scattered growth 14 Ave Change/1 by District
35 Results estimation of district growth
36 Spatial analysis of district growth Average of Ave of Change/1 Category-1 Category-2 Category-3 Category (1+2) Whole (1+2+3) Category-1 Category-2 Category-3 Category (1+2) Whole (1+2+3)
37 Conclusions Remote sensing data reflects production data from mines Large variation between years in both forest loss and nightlight change District with mine small change in forest loss Bottleneck in processing large datasets o MODIS: One tile 46 observations (images)* 12 years * 2MB= 11 GB Ghana consists of 4 tiles (44GB)
38 The way forward June 2-6 running the local growth model for MLI, TNZ, BF June 7-15 drafting paper (Lund) June 16-2 comments WB team June submit paper (Lund)
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