Towards understanding the environmental and climatic changes and its contribution to the spread of wildfires in Ghana using remote sensing tools and machine learning (Google Earth Engine)

Figures & data

Figure 1. Geographic situation of the studies zones and districts.

Table 1. Characteristics of the data used in this research and their references

Parameters	Dataset availability	Dataset resolution	Dataset provider and retrieval platform	References/citations
PR	1981-01-01T00:00:00Z–2022-12-31T00:00:00	0.05° grid monthly and daily temporal resolution and a ∼4 km (1/24th degree) spatial resolution	CHIRPS Daily data University of California, Santa Barbara	Funk et al. (2015)
Tmax, Tmin, PDSI, WS, SM, ETA and ETR	1958-01-01T00:00:00Z–2021-12-01T00:00:00	0.05° grid: monthly and daily temporal resolution and a ∼4 km (1/24th degree) spatial resolution	TerraClimate University of California Merced	Abatzoglou et al. (2018); Wang-Erlandsson et al. (2016); Hegewisch and Abatzoglou (2020);
RH	1982-01-01T00:00:00Z–2022-12-01T00:00:00	0.1 × 0.1 degree (MERRA-2 and CHIRPS)	Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System; NASA GES DISC at NASA Goddard Space Flight Center	Funk et al. (2015) McNally et al. (2017)

Table 2. Drought classification according to the SPI values (McKee, Doesken, and Kleist (1993))

Class of SPI	−1 < SPI < 0	1 < SPI < 2	SPI > 2	0 < SPI < 1	−2 < SPI < −1	SPI < −2
Degree of drought or wetness	Wetness moderate (WM)	Wetness high (WH)	Wetness extreme (HE)	Drought moderate (DM)	Drought high (DH)	Drought extreme (DE)

Table 3. PDSI categorisation of drought severity (Palmer 1965).

PDSI value	Drought category
4.00 or more	Extremely wet
3.00–3.99	Very wet
2.00–2.99	Moderately wet
1.00–1.99	Slightly wet
0.50–0.99	Incipient wet spell
0.49 to −0.49	Near normal
−0.50 to −0.99	Incipient dry spell
−1.00 to −1.99	Mild drought
−2.00 to −2.99	Moderate drought
−3.00 to −3.99	Severe drought
−4.00 or less	Extreme drought

Table 4. Designation of variables used in for computing of RH.

Variables used	Designations
$q$	Specific humidity or the mass mixing ratio of water vapour to total air (dimensionless)
$m_v$	Specific mass of water vapour (kg)
$m_{vs}$	Specific mass of water vapour at equilibrium (kg)
$m_d$	Specific mass of dry air (kg)
$w$	Mass mixing ratio of water vapour to dry air (dimensionless)
$w_s$	Mass mixing ratio of water vapour to dry air at equilibrium (dimensionless)
$e_s\left(T\right)$	Saturation vapour pressure (Pa)
$e_{s0}$	Saturation vapour pressure at T0 (Pa)
$R_d$	Specific gas constant for dry air (J kg^−1 K^−1)
$R_v$	Specific gas constant for water vapour (J kg^−1 K^−1)
$p$	Pressure (Pa)
$L_v\left(T\right)$	Specific enthalpy of vaporisation (J kg^−1)
$T$	Temperature (K)
$T_0$	Reference temperature (typically 273.16 K) (K)

Table 5. Data requirements for application of the SWB model (Finkelstein et al. 2022).

Data type

Gridded (ARC ASCII or Surfer grid)

Land use/land cover

Surface-water flow direction (D8)

Hydrologic soil group

Available water capacity

Tabular

Soil and land use properties lookup table

The climate at a single station

Matrix of soil-water retention for given accumulated potential

water loss

Table 6. Designation of variables used in for computing of ETR (ASCE-EWRI 2005).

Variables used	Designations
$\mathrm{E}\mathrm{T}\mathrm{R}$	Reference evapotranspiration (mm.d^−1 for daily time steps or mm h^-1 for hourly time steps),
$\mathrm{R}\mathrm{n}$	Calculated net radiation at the crop surface (MJ.m^−2.d^−1 for daily time steps or MJ.m^−2.h^−1 for hourly time steps),
$G$	Soil heat flux density at the soil surface (MJ.m^−2.d^−1 for daily time steps or MJ.m^−2.h^−1 for hourly time steps),
$T$	Mean daily or hourly air temperature at 1.5–2.5-m height (°C),
$u_2$	Mean daily or hourly wind speed at 2-m height (m s^−1),
$e^o$	Saturation vapour pressure at 1.5–2.5-m height (kPa), calculated for daily time steps as the average saturation vapour pressure at maximum and minimum air temperature,
$e$	Mean actual vapour pressure at 1.5–2.5-m height (kPa)
$\mathrm{\Delta }$	Slope of the saturation vapour pressure-temperature curve (kPa °C^−1),
$\gamma$	Psychrometric constant (kPa °C^−1),
$C_n$	Numerator constant that changes with reference type and calculation time step (K mm.s^3 Mg^−1.d^−1 or K mm.s^3 Mg^−1 h^−1)
$C_d$	Denominator constant that changes with reference type and calculation time step (s.m^−1).
Units for the 0.408 coefficient are m^2 mm MJ^−1.

Table 7. Rainfall Anomalies Index classification (Freitas 2005).

	RAI range	Classification
Rainfall Anomaly Index (RAI)	Above 4	Extremely humid
	2–4	Very humid
	0–2	Humid
	−2 to 0	Dry
	−4 to −2	Very dry
	Below −4	Extremely dry

Figure 2. Monthly rainfall variation in Guinea-savannah (a) and Forest-savannah mosaic (b) zones.

Figure 3. Annual variation of SPI and PDSI in Guinea-Savannah (a) and Forest-savannah mosaic (b) zones.

Table 8. Variation in climatic (SPI) (a) and hydrological (PDSI) (b) drought in Guinea-Savannah and Forest-savannah mosaic zones.

According to SPI values		EW	HD	HW	ED	MD	MW
Guinea-savannah zone	Years	1991, 1999, 2018, 2019	1992, 1998, 2002, 2005, 2014, 2015	2003, 2009, 2010, 2021	2001, 2013, 2017	1993, 1995, 1996, 2006, 2007, 2008, 2011, 2012	1994, 1997, 2000, 2004, 2016, 2020
	Number of years	4	6	4	3	8	6
	Percentage (%)	12.9	19.4	12.9	9.7	25.8	19.4
Forest-savannah mosaic Zone	Years	1991, 1995, 1999, 2007, 2010, 2011, 2019, 2021	1994, 1998, 2004, 2005, 2014	2008	1992, 2001, 2013, 2015, 2020	1996, 2002, 2006, 2009	1993, 1997, 2000, 2003, 2012, 2016, 2017, 2018
	Number of years	8	5	1	5	4	8
	Percentage (%)	25.8	16.1	3.2	16.1	12.9	25.8
Extreme Wetness (EW); High Drought (HD); High Wet (HW); Extreme Drought (ED); Moderate Drought (MD); moderate Wetness (MW)
According to PDSI values		ED	SD	MD	MiD	IDS	NN	IWS	SW	VW
Guinea-savannah zone	Year	2017, 2016, 2002	2020, 2021	1993, 2019, 2015, 2001, 2006	2018, 2007, 2005, 2003, 2013, 1998, 2014, 1994, 2012	2008, 1999, 1995, 2011, 1992, 2010	2004	2000, 2009	1996, 1997, 1991	0
	Number of years	3	2	5	9	6	1	2	3	0
	Percentage (%)	9.7	6.5	16.1	29.0	19.4	3.2	6.5	9.7	0.0
Forest-savannah mosaic zone	Year	2017, 2016, 2021, 2001, 1993	2002, 2018, 1994	1992, 2015, 2006, 1998	2000, 2020, 1997, 2012, 2003, 2010, 2007, 2013	2004, 2011, 1995, 2005, 2019, 2014, 1999	2009, 1996	0	2008	1991
	Number of years	5	3	4	8	7	2	0	1	1
	Percentage (%)	16.1	9.7	12.9	25.8	22.6	6.5	0.0	3.2	3.2
Extreme Drought (ED); Severe Drought (SD); Moderate Drought (MD); Mild Drought (MiD); Incipient Dry Spell (IDS); Near Normal (NN); Incipient Wet Spell (IWS); Slightly Wet (SW); Very Wet (VW)

Figure 4. Monthly temperature variation in Guinea-Savannah (a) and Forest-savannah mosaic (b) zones.

Figure 5. Monthly variation of relative humidity and wind speed in Guinea-Savannah (a) and Forest-savannah mosaic (b) zones.

Figure 6. Monthly spatial presentation of climatic and environmental parameters in Guinea-Savannah (a) and Forest-Savannah mosaic (b) zones.

Figure 7. Annual rainfall anomaly in Guinea-Savannah (a) and Forest-savannah Mosaic (b) zones.

Figure 8. Annual thermometric anomaly in Guinea-Savannah (a) and Forest-Savannah mosaic (b) zones.

Figure 9. Annual soil moisture anomaly in Guinea-Savannah (a) and Forest-Savannah mosaic (b) zones.

Figure 10. Annual moisture anomaly in Guinea-Savannah (a) and Forest-Savannah mosaic (b) areas.

Figure 11. Annual variation of fire risk indices in Guinea-Savannah (a) and Forest-Savannah mosaic (b) areas.

Table 9. Period of HR and SM breakdown in Guinea-Savannah (a) and Forest-Savannah mosaic (b) areas.

		Pettitt test			Lee-Heghinian test
		Kt (Break year)	Test U	Significant level	Break year	Break Probability	Significant level
Guinea-savannah zone	PR	No break	–	–	2017	0.1484	**
	RH	No break	–	–	2003	0.1523	**
Forest-savannah mosaic zone	PR	No break	–	–	1991	0.387	**
	RH	No break	–	–	2002	0.1227	**

** p < 0,01; Precipitation (PR); Relative Humidity (RH); Soil Moisture (SM).

Table 10. Trend of different variables in Guinea-Savannah (a) and Forest-Savannah mosaic (b) areas.

	Variable	Tau	S	Z	p-value	Sen's lope S
Guinea Savannah zone	ETA	−0.166	−77	−1.292	0.1965^ns	−0.255
	ETR	0.389	181	3.059	2.218 × 10^−3**	0.267
	PR	−0.019	−9	−0.136	0.8918^ns	−0.024
	PDSI	−0.402	−187	−3.161	1.57 × 10^−3***	−0.103
	RH	0.148	69	1.156	0.2478^ns	0.068
	SM	−0.209	−97	−1.632	0.1028**	−0.496
	Tmax	0.557	259	4.385	1.159 × 10^−5***	0.042
	Tmean	0.665	309	5.235	1.651 × 10^−7***	0.036
	Tmin	0.570	265	4.487	7.221 × 10^−6***	0.035
	WS	−0.196	−91	−1.530	0.1261^ns	−0.003
Forest-Savannah mosaic zone	ETA	0.058	27	0.442	0.6586^ns	0.077
	ETR	0.557	259	4.385	1.159 × 10^−5***	0.352
	PR	−0.041	−19	−0.306	0.7597^ns	−0.076
	PDSI	−0.101	−47	−0.782	0.4343^ns	−0.040
	RH	0.075	35	0.578	0.5633^ns	0.025
	SM	−0.196	−91	−1.530	0.1261^ns	−0.389
	Tmax	0.583	271	4.589	4.453 × 10^−6***	0.045
	Tmean	0.695	323	5.473	4.429 × 10^−8***	0.043
	Tmin	0.665	309	5.235	1.651 × 10^−7***	0.041
	WS	−0.286	−133	−2.244	0.02486*	−0.003

ns = non significative; * p < 0,05; ** p < 0,01; *** p < 0,001; Trend (At 95% level); Mann Kendall Statistic (S); Normalised Test Statistic (Z); Sen's slope (S) At 95% level.

Figure 12. Spearman's correlation matrix in Guinea-Savannah (a) and Forest-savannah mosaic (b) areas (Significant at *p < 0.05; ** p < 0.01; and *** p < 0.001).

Table 11. Cross-correlation function between climatic, environmental and burned area variables in Guinea-Savannah (a) and Forest-Savannah mosaic (b) zones.

	Cross-correlation function (Burned area and parameters)
	Guinea-savannah zone		Forest-savannah mosaic zone
	CCFmax*	Lag (month)	CCFmax*	Lag (month)
ETA	−0.59	−1	0.37	19
ETR	0.514	−3	0.514	−3
PR	−0.523	0	−0.523	0
PDSI	−0.094	−7	−0.099	−19
RH	−0.644	12	0.394	6
SM	−0.428	−3	−0.428	−3
Tmax	0.511	10	0.539	−2
Tmean	0.58	10	0.601	−2
Tmin	0.459	9	0.465	−15
WS	−0.452	−9	−0.452	−9
AI	−0.684	−12	−0.702	12
FDI	0.586	−13	0.595	11

Actual Evapotranspiration (ETA); Reference Evapotranspiration (ETR); Precipitation (PR); Palmer Drought Severity Index (PDSI); Relative Humidity (RH); Soil Moisture (SM); Maximum Temperature (T_max); Average Temperature (T_mean); Minimum Temperature (T_min); Wind Speed (WS); Ångström Indice (AI); Lowveld Fire Danger Index (FDI); CCFmax*: Maximum significant value (p < 0.05) of the cross-correlation function.

Table 12. Cross-correlation function between climatic, environmental and active fires variables in Guinea-Savannah (a) and Forest-Savannah mosaic (b) zone.

	Cross-correlation function (Active fires and parameters)
	Guinea-savannah zone		Forest-savannah mosaic zone
	CCFmax*	Lag (month)	CCFmax*	Lag (month)
ETA	−0.602	11	0.408	8
ETR	0.548	−3	0.548	−3
PR	−0.538	−12	−0.553	0
PDSI	−0.122	17	−0.122	17
RH	0.424	18	0.427	6
SM	0.496	−21	−0.431	9
Tmax	0.565	−2	0.565	−2
Tmean	0.63	10	0.649	−2
Tmin	0.519	9	0.519	9
WS	−0.48	15	−0.496	3
AI	0.356	18	0.36	7
FDI	0.639	−1	0.639	−1

Actual Evapotranspiration (ETA); Reference Evapotranspiration (ETR); Precipitation (PR); Palmer Drought Severty Index (PDSI); Ralative Humidity (RH); Soil Moisture (SM); Maximum Temperature (T_max);Average Temperature (T_mean); Minimum Temperature (T_min); Wind Speed (WS); Ångström Indice (AI); Lowveld Fire Danger Index (FDI); CCFmax*: Maximum significant value (p < 0.05) of the cross-correlation function.

Funk, C., P. Peterson, M. Landsfeld, D. Pedreros, J. Verdin, S. Shukla, G. Husak, et al. 2015. “The Climate Hazards Infrared Precipitation with Stations—A new Environmental Record for Monitoring Extremes.” Scientific Data 2 (1): 150066. doi:10.1038/sdata.2015.66.

 PubMed Web of Science ®Google Scholar

Abatzoglou, J. T., S. Z. Dobrowski, S. A. Parks, and K. C. Hegewisch. 2018. “TerraClimate, a High-Resolution Global Dataset of Monthly Climate and Climatic Water Balance from 1958–2015.” Scientific Data 5 (1): 170191. doi:10.1038/sdata.2017.191.

 PubMed Web of Science ®Google Scholar

Wang-Erlandsson, L., W. G. M. Bastiaanssen, H. Gao, J. Jägermeyr, G. B. Senay, A. I. J. M. van Dijk, J. P. Guerschman, P. W. Keys, L. J. Gordon, and H. H. G. Savenije. 2016. “Global Root Zone Storage Capacity from Satellite-Based Evaporation.” Hydrology and Earth System Sciences 20 (4): 1459–1481. doi:10.5194/hess-20-1459-2016.

 Web of Science ®Google Scholar

Hegewisch, K. C., and J. T. Abatzoglou. 2020. “Data Download’ Web Tool”. Climate Toolbox (https://climatetoolbox.org/), version 2020-04-17.

 Google Scholar

Mcnally, A., K. Arsenault, S. Kumar, S. Shukla, P. Peterson, S. Wang, C. Funk, C. D. Peters-Lidard, and J. P. Verdin. 2017. “A land data assimilation system for sub-Saharan Africa food and water security applications.” Scientific Data 4. 170012.

 PubMed Web of Science ®Google Scholar

McKee, T. B., N. J. Doesken, and J. Kleist. 1993. “The Relationship of Drought Frequency and Duration to Time Scale.” In Proceedings of the Eighth Conference on Applied Climatology, Anaheim, California, 17-22 January 1993, 179–184. Boston: American Meteorological Society.

 Google Scholar

Palmer, W. C. 1965. “Meteorological Drought. U. S. Weather Bureau Res. Paper No. 45.

 Google Scholar

Finkelstein, J. S., J. Monti, J. P. Masterson, and D. A. Walter. 2022. “Application of a Soil-Water-Balance Model to Estimate Annual Groundwater Recharge for Long Island”. New York, 1900–2019: U.S. Geological Survey Scientific Investigations Report 2021–5143, 25 p., https://doi.org/10.3133/sir20215143.

 Google Scholar

ASCE-EWRI. 2005. “The ASCE Standardized Reference Evapotranspiration Equation.” In Environmental and Water Resources Institute (EWRI) of the American Society of Civil. Engineers, ASCE, Standardization of Reference Evapotranspiration Task Committee Final Report, 213 pp., edited by R. G. Allen, I. A. Walter, and R. L. Elliot. Reston: American Society of Civil Engineers (ASCE).

 Google Scholar

Freitas, Mas. 2005. “Um sistema de suporte à decisão para o monitoramento de secas meteorológicas em regiões semi- áridas.” Rev. Tecnol 19 (1): 84–95. doi:10.5020/23180730.1998.1175.

 Google Scholar

Data availability statement

Data (climatic and environmental data) used in this paper are respectively available at https://code.earthengine.google.com/fa9846d34c532e5f6d043ad4f7376640; https://code.earthengine.google.com/0eba04b7ded613d5a05e811ea2b5ee36 for Guinea-Savannah zone and Forest-savannah zone and fire data on https://doi.org/10.5281/zenodo.7749206.