Reuben Sebego

Spectral Discrimination of Insect Defoliation Levels in Mopane Woodland Using Hyperspectral Data

Mopane woodland are a source of valuable resources that contribute substantially to rural economies and nutrition across Southern Africa. However, a number of factors have, of late, brought the sustainability of the mopane woodland resources into question. One of such factors is the difficulty in monitoring of defoliation process within the woodland. In this study we set out to discriminate the levels of change in forest canopy cover detectable after insect defoliation using ground based hyperspectral measurements in mopane woodland. Canopy spectral measurements were taken from three levels of defoliation: Undefoliated (UD), Partly defoliated (PD) and Refoliating plants (R) using ASD FieldSpec HandHeld 2. A pre-filtering approach (ANOVA) was compared with random forest independent variable selector in selecting the significant wavelengths for classification. Furthermore, a backward feature elimination method was used to select optimal wavelengths for discriminating the different levels of defoliation in mopane woodland. Results show that optimal wavelengths located at 707 nm, 710 nm, 711 nm, 712 nm, 713 nm, 714 nm, 727 nm, and 1066 nm were able to discriminate between the three levels of defoliation. The results further show that there was no significant difference in the overall accuracy of classification when random forest variable selector was used 82.42% (Kappa = 0.64) and the pre-filtering approach (ANOVA) 81.21% (Kappa = 0.68) used before building the classification. Overall, the study clearly demonstrated that the dynamic process of defoliation in mopane woodland can be assessed and detected using hyperspectral dataset and effective algorithm for discrimination.

Interpretation of mopane woodlands using air photos with implications on satellite image classification

Abstract Delineation of stands of Colophospermum mopane is carried out on aerial photographs for the area around Palapye, Botswana. The purpose of this study was to evaluate aerial photos as ground truth material for satellite image classification, and to assess the quality of an existing vegetation map around the study area. Colophospermum mopane can be accurately mapped using colour infrared (CIR) photographs. The study shows that CIR photography can be used for accurately mapping the distribution of mopane. This material can therefore, be used as a reliable tool for ground truthing vegetation classification of satellite images, as well as for monitoring the distribution of the species. The only pre-existing vegetation map over the study area is checked against a visually interpreted map for consistency of the level of detail. A close-up view of pictures of scanned CIR air photos are used to study tree shadow characteristics of Savannah vegetation. Results from this investigation are used to explain the concept of the darkening effect, prevalent on Savannah environments. A model is presented to show the effect of tree shadows on brightness values and on NDVI measured by satellites.

Mapping of Colophospermum mopane using Landsat Tm in eastern Botswana

ABSTRACT The spatial distribution of a tree species, Colophospermum mopane is mapped at its southern limits in eastern Botswana. Its relationship with soil type distribution is also investigated. Methods applied in the exercise used the possibilities of integrated applications of geographic information systems and remote sensing to detect and delineate spectral classes of C. mopane and of soils. Landsat TM data for the wet and dry seasons were analysed and interpreted for soil and vegetation classification. Supervised classification of the wet season (19/04/93) image was carried out using land use/cover classes derived from Colour infrared (CIR) aerial photographs, flown during the wet season (April, 1996) over the study area. Classification of the dry season (19/10/84) image on the other hand was based on the existing Food and Agricultural Organisation (FAO) soil maps of the same area. Results show that CIR photographs can be reliably used in selecting training areas for the classification of Landsat TM imagery. Secondly, results also indicate that Landsat TM can be used to map the distribution pattern of mopane. The methods applied in this study and the tools used prove that the much needed inventorying of vegetation in Botswana can be carried out using remote sensing. Lastly, the study shows that spectral classes of soil and vegetation have a positive relationship.

Modeling the Spatio-temporal dynamics and evolution of land use and land cover (1984–2015) using remote sensing and GIS in Raya, Northern Ethiopia

This study models the spatio-temporal dynamics, patterns, and evolution of land use and land cover (LULC) (1984–2015) using remote sensing and GIS supported by in-suit measurements in Raya, Northern Ethiopia. Landsat thematic mapper (TM), and operational land imager (OLI) path 168/169 and row 051/52 were acquired from the United States Geological Survey Landsat archive. All necessary image pre-processing techniques were applied to remove the distortions due to sensors. Eight major LULC types based on a supervised image classification and maximum likelihood decision rule were identified. Post-classification change detection method was also applied to detect the dynamics in LULC. Significant change in forestland, shrub/bush land, built-up area, grassland, cropland, barren land, and floodplain areas were observed over the period 1984–2015. Considerable losses were observed in grasslands (36.9%), water body (8.7%), and floodplain areas (74.4%), while other LULC types increased. This explains why the study area is frequently affected by drought and other related disasters. An overall accuracy of 88.5, 86.5 and 90.5% were observed for the 1984, 1995 and 2015 LULC, respectively. The overall Kappa coefficient of 0.87, 0.85, and 0.90 were also observed for the same periods. Besides, the Pearson pairwise correlation matrix among the 1984–1995, 1995–2015 and 1984–2015 LULC shows positive and strong correlation (r = 0.916, r = 0.908, r = 0.914) at p < 0.005 significance level. Therefore, there is no much difference in identifying LULC types using TM and OLI products. This study is crucial to implement scientific land use policies and strategies in the study area.

A spatio-temporal analysis of peri-urbanisation in sub-Saharan Africa: a case study from Lobatse, Botswana

This paper aims at delineating and rationalising the spatial processes that characterise peri-urbanisation in sub-Saharan Africa, using Lobatse, Botswana, as a case study. The research techniques employed included the sourcing of: archival documents; available and simulated time series data; social survey data; field observations as well as spatial data derived from aerial photographs for 1966–2006 and integrated in a geographical information systems framework. The exercise resulted in: (1) the production of temporal-spatial model maps, (2) the systematic description and explanation of the spatial growth patterns of the study area, (3) the modelling of its rationalised growth pattern, and (4) an analysis of the environmental and socioeconomic implications of this spatial growth pattern. The study further confirmed the relevance of certain underlying principles of urban morphology and morphogenesis. Among the key recommendations, we suggest that, to move towards sustainable development, the national Environmental Impact Assessment Act should guide all future development.

Clear the Mind of Pre-conceived Ideas and Get Your Hands Dirty! An Approach to Field-based Courses: The SLUSE-southern Africa Experience

This paper explores an approach to problem-oriented, interdisciplinary field-based courses devised by university consortia in southern Africa and Denmark. The SLUSE (Sustainable Land Use and Natural Resource Management) model has been applied on six three-week field courses within southern Africa and trained over 200 students. Student groups composed of individuals from different academic disciplines that investigated problems specifically devised to integrate social and natural science approaches set the stage for an interdisciplinary approach. The field locations are in rural areas that have a legacy of marginalization, poverty and reliance on natural resources for at least part of their livelihoods thus allowing for environmental and natural resource issues to be investigated. Course evaluations show that students feel they gain invaluable exposure to the innovative field-based learning environment created by the SLUSE approach. The main benefit perceived by hosting local communities was an increase in their self-esteem and to harness the knowledge and experience gained from the courses to further enrich their own communities. On reflection, the students value the opportunity to work cross-culturally, and trying new techniques on ‘real’ issues. To many students the personal challenges they face adjusting to the demands of the field course are as important as the academic outputs.

Cellular automata and Markov Chain (CA_Markov) model-based predictions of future land use and land cover scenarios (2015–2033) in Raya, northern Ethiopia

Little is known about the future land use and land cover (LULC) type in some parts of Ethiopia, but not in the study area. This study aims to predict and analyze the future scenarios of LULC (2015–2033) using cellular automata and Markov Chain model (CA_Markov) by taking into consideration the physical and socio-economic drivers of LULC dynamics. The historical LULC change data of 1984–1995, 1995–2015, and 1984–2015 were used as a baseline. Both transition rules and transition area matrix for the period 1984–1995, 1995–2015, and 1984–2015 were produced quantitatively using the Markov chain model. After that, the physical and socio-economic factors were standardized using fuzzy and then Multi-Criteria Evaluation (MCE) was used to produce the transition suitability image. The CA_Markov model was then applied as a standard contiguity filter of 5 × 5 to predict the 2033 LULC condition using the TerrSet Geospatial Modeling and Monitoring System software. The result indicated that forestland are predicted to increase by 108 sq km (44.5%), shrub/bush lands 710 sq km (20%), built-up area 286.2 sq km (48.3%), and grasslands 31 sq km (15%), respectively. However, significant reductions (losses) in a water body (Wb) 5.2 sq km (11.2%), croplands (Cl) 78.9 sq km (1.3%), barren lands (Bl) 800 sq km (27.4%), and floodplain area (Fp) 251.68 sq km (33.7%), respectively. Furthermore, the Pearson correlation result between the historical and predicted LULC type indicated that there are positive, strongly correlated, and are statistically significant relationships (r = 0.981, p = 0.000). The increase in forest land and reduction in barren and flood plain may benefit the study area. However, the decrease in the water body may contribute to the severity of drought in the area. This study may help to use as useful information to foster better decisions and improve policies in land use within the framework of sustainable land use planning system.

Land use intensification and implications on land degradation in the Boteti area: Botswana

Abstract Arid and semi-arid areas worldwide face challenges of over utilization of rangelands, with a possibility of declining into degraded lands. Overgrazing by livestock and persistent deforestation of woodlands has been reported in the rangelands of Boteti Sub- District of Botswana. This study focuses on depicting changing patterns of land use that have come about as a result of a forcing from natural phenomenon. Periodic droughts and the drying up of the Boteti river which has been a source of livelihood for a long time has manifested on land utilization trends around the villages of Boteti District. New patterns of land use have since emerged as an adaptation strategy against the drier environment. The study mapped land use and land cover around two ‘river village settlements’. Land degradation indicators were identified within the various land cover categories. Results show that communities have shifted from flood recession farming to dry-land farming with emphasis on livestock. The latter are ironically privileged by government policies that are skewed toward livestock production, especially the introduction of fenced private ranches and conservation areas. As a result, they have relentlessly exerted more pressure on the communal land, manifesting itself through moderate to severe incidents of land degradation.