Spatial Evolution of Prosopis Invasion and its Effects on LULC and Livelihoods in Baringo, Kenya
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Assessment of Land-Use and Land-Cover Changes
2.2.1. Field Reference Data
2.2.2. Satellite Data Selection and Pre-processing
2.2.3. Classification of Satellite Data
2.2.4. Accuracy Assessment
2.3. Land-Use and Land-Cover Change Analysis
3. Results
3.1. Invasion History of Prosopis from 1988 to 2016
3.2. Land-Use and Land-Cover Changes between 1988 and 2016
3.3. Prosopis-Specific Induced Changes on other LULC
4. Discussion
4.1. Spatial Evolution of Prosopis Invasion
4.2. Spatial Changes in Prosopis Coverage
4.3. LULC Changes in the Study Area
5. Conclusions
- Freely available Landsat data analyzed with the implementation of Random Forest machine learning algorithm in the open source R software are useful in assessing spatial temporal LULC changes, especially in regions where commercial data and software is economically inaccessible. The RF algorithm has the ability to separate various landscape components with reliable accuracies.
- The use of bi-seasonal (dry and wet) multispectral data combinations and the Random Forest algorithm allowed us to spatially and quantitatively investigate the evolution of Prosopis invasion, its current extent, and the changes in LULC in the semi-arid environment. The use of dry season images enhanced the ability to differentiate the evergreen Prosopis from deciduous native Vachellia species on the medium-resolution Landsat imagery.
- Prosopis has rapidly increased in the study area since its introduction in 1982. It currently stands at approximately 18,792 ha, invading at a rate of 640 ha per annum. This rapid spread was facilitated by effective seed dispersal agents such as livestock and wildlife, a lack of natural enemies, and favorable climate, among other factors. Our findings indicate that Prosopis has been a key driver of LULC changes in the semi-arid lowlands of Baringo, directly accounting for over a third of the LULC changes observed over the last three decades.
- The LULC classes most vulnerable to Prosopis invasion are grasslands, V. tortilis-dominated zones, and fallow irrigated agricultural fields. Their vulnerability is enhanced by their ecological niche also favoring Prosopis growth and the presence of Prosopis seed dispersal vectors such as livestock, wildlife, water, and humans.
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Class ID | LULC | Classification Description |
---|---|---|
1 | Prosopis | Refers to P. juliflora, which is an evergreen woody alien shrub predominating the lowland areas around Lake Baringo |
2 | Vachellia tortilis | An indigenous tree species predominantly found within the tropical arid and semi-arid lands (ASALs) |
3 | Mixed Vegetation | A combination of natural trees and shrubs that exist as a mix of single stands or as small patches and water weeds |
4 | Grassland | Areas predominantly under grass cover |
5 | Bareland | Degraded areas usually with little or no vegetation (uncovered soils) |
6 | Rainfed cropland | Areas for farming that depend on rainfall for water |
7 | Irrigated cropland | Areas for farming equipped to provide water |
8 | Water | Rivers, lakes, and dams |
Sensor | Acquisition Date | Year Assigned to Classification | |
---|---|---|---|
Dry Season | Wet Season | ||
Landsat 5 TM | Mar, 1989 | July, 1987 | 1988 |
Landsat 5 TM | Jan, 1995 | Mar,1995 | 1995 |
Landsat 5 TM | Feb, 2002 | July, 2002 | 2002 |
Landsat 5 TM | Jan, 2010 | June, 2008 | 2009 |
Landsat 8 OLI | Feb, 2016 | July, 2015 | 2016 |
LULC Classes | 1988 | 1995 | 2002 | 2009 | 2016 | |||||
---|---|---|---|---|---|---|---|---|---|---|
ha | % Share | ha | % Share | ha | % Share | ha | % Share | ha | % Share | |
Prosopis | 882 | 0.5 | 3345 | 1.9 | 8375 | 4.7 | 13,568 | 7.5 | 18,792 | 10.4 |
Vachellia tortilis | 8517 | 4.7 | 6809 | 3.8 | 3158 | 1.8 | 3718 | 2.1 | 4915 | 2.7 |
Mixed vegetation | 128,727 | 71.5 | 130,385 | 72.4 | 132,969 | 73.9 | 124,392 | 69.1 | 123,310 | 68.5 |
Grassland | 7229 | 4.0 | 5652 | 3.1 | 1194 | 0.7 | 691 | 0.4 | 977 | 0.5 |
Bareland | 15,001 | 8.3 | 16,904 | 9.4 | 14,130 | 7.9 | 13,420 | 7.5 | 8503 | 4.7 |
Rainfed cropland | 3840 | 2.1 | 3189 | 1.8 | 5531 | 3.1 | 5453 | 3.0 | 2408 | 1.3 |
Irrigated cropland | 1501 | 0.8 | 473 | 0.3 | 1463 | 0.8 | 3708 | 2.1 | 652 | 0.4 |
Water | 14,325 | 8.0 | 13,264 | 7.4 | 13,204 | 7.3 | 15,071 | 8.4 | 20,464 | 11.4 |
Net Changes | 1988–1995 | 1995–2002 | 2002–2009 | 2009–2016 | 1988–2016 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
LULC | ha | % Total Area | % of Class Area in 1988 | ha | % Total Area | % of Class Area in 1988 | ha | % Total Area | % of Class Area in 1988 | ha | % Total Area | % of Class Area in 1988 | ha | % Total Area | % of Class Area in 1988 |
Prosopis | 2463 | 1.4 | 279.4 | 5030 | 2.8 | 570.4 | 5193 | 2.9 | 589.0 | 5224 | 2.9 | 592.5 | 17910 | 10.0 | 2031.3 |
Vachellia tortilis | −1708 | −1.0 | −20.1 | −3651 | −2.0 | −42.9 | 560 | 0.3 | 6.6 | 1197 | 0.7 | 14.1 | −3602 | −2.0 | −42.3 |
Mixed vegetation | 1658 | 0.9 | 1.3 | 2583 | 1.4 | 2.0 | −8576 | −4.8 | −6.7 | −1082 | −0.6 | −0.8 | −5417 | −3.0 | −4.2 |
Grassland | −1577 | −0.9 | −21.8 | −4458 | −2.5 | −61.7 | −503 | −0.3 | −7.0 | 286 | 0.2 | 4.0 | −6252 | −3.5 | −86.5 |
Bareland | 1903 | 1.1 | 12.7 | −2774 | −1.5 | −18.5 | −709 | −0.4 | −4.7 | −4917 | −2.7 | −32.8 | −6498 | −3.6 | −43.3 |
Rainfed cropland | −651 | −0.4 | −17.0 | 2342 | 1.3 | 61.0 | −78 | −0.0 | −2.0 | −3045 | −1.7 | −79.3 | −1432 | −0.8 | −37.3 |
Irrigated cropland | −1027 | −0.6 | −68.5 | 989 | 0.6 | 66.0 | 2246 | 1.3 | 149.7 | −3056 | −1.7 | −203.7 | −849 | −0.5 | −56.6 |
Water | −1061 | −0.6 | −7.4 | −61 | −0.0 | −0.4 | 1868 | 1.0 | 13.0 | 5393 | 3.0 | 37.6 | 6139 | 3.4 | 42.9 |
Time Period | Losses to P (ha) | Gains from P (ha) | Net Change (ha) | % of Class Area in 1988 |
---|---|---|---|---|
V88-P95 | 984 | 235 | −750 | −8.8 |
V95-P02 | 2146 | 237 | −1909 | −22.4 |
V02-P09 | 789 | 409 | −381 | −4.5 |
V09-P16 | 913 | 281 | −633 | −7.4 |
V88-P16 | 3478 | 26 | −3453 | −40.5 |
M88-P95 | 651 | 227 | −424 | −0.3 |
M95-P02 | 2183 | 725 | −1458 | −1.1 |
M02-P09 | 3837 | 1340 | −2498 | −1.9 |
M09-P16 | 4247 | 1753 | −2494 | −1.9 |
M88-P16 | 6308 | 93 | −6215 | −4.8 |
G88-P95 | 510 | 82 | −428 | −5.9 |
G95-P02 | 1042 | 163 | −879 | −12.2 |
G02-P09 | 341 | 170 | −171 | −2.4 |
G09-P16 | 126 | 285 | 159 | 2.2 |
G88-P16 | 2688 | 13 | −2675 | −37 |
B88-P95 | 50 | 5 | −44 | −0.3 |
B95-P02 | 1009 | 124 | −885 | −5.9 |
B02-P09 | 2977 | 856 | −2121 | −14.1 |
B09-P16 | 3644 | 974 | −2670 | −17.8 |
B88-P16 | 5361 | 10 | −5351 | −35.7 |
R88-P95 | 17 | 0.7 | −17 | −0.4 |
R95-P02 | 5 | 16 | 11 | 0.3 |
R02-P09 | 709 | 139 | −571 | −14.9 |
R09-P16 | 423 | 136 | −287 | −7.5 |
R88-P16 | 131 | 3 | −129 | −3.4 |
I88-P95 | 44 | 0 | −44 | −2.9 |
I95-P02 | 7 | 58 | 51 | 3.4 |
I02-P09 | 456 | 368 | −89 | −5.9 |
I09-P16 | 1287 | 173 | −1115 | −74.3 |
I88-P16 | 378 | 5 | −373 | −24.9 |
W88-P95 | 758 | 1 | −757 | −5.3 |
W95-P02 | 44 | 84 | 40 | 0.3 |
W02-P09 | 0.1 | 637 | 636 | 4.4 |
W09-P16 | 7 | 1822 | 1814 | 12.7 |
W88-P16 | 10 | 295 | 285 | 2 |
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Mbaabu, P.R.; Ng, W.-T.; Schaffner, U.; Gichaba, M.; Olago, D.; Choge, S.; Oriaso, S.; Eckert, S. Spatial Evolution of Prosopis Invasion and its Effects on LULC and Livelihoods in Baringo, Kenya. Remote Sens. 2019, 11, 1217. https://doi.org/10.3390/rs11101217
Mbaabu PR, Ng W-T, Schaffner U, Gichaba M, Olago D, Choge S, Oriaso S, Eckert S. Spatial Evolution of Prosopis Invasion and its Effects on LULC and Livelihoods in Baringo, Kenya. Remote Sensing. 2019; 11(10):1217. https://doi.org/10.3390/rs11101217
Chicago/Turabian StyleMbaabu, Purity Rima, Wai-Tim Ng, Urs Schaffner, Maina Gichaba, Daniel Olago, Simon Choge, Silas Oriaso, and Sandra Eckert. 2019. "Spatial Evolution of Prosopis Invasion and its Effects on LULC and Livelihoods in Baringo, Kenya" Remote Sensing 11, no. 10: 1217. https://doi.org/10.3390/rs11101217