Rapid Land Cover Changes Research Articles

Spatial and spectral remote sensing features to detect deforestation in Brazilian Savannas

The Brazilian Savannas have been under increasing anthropic pressure for many years, and land-use/land-cover changes (LULCC) have been largely neglected. Remote sensing provides useful tools to detect changes, but previous studies have not attempted to separate the effects of phenology from deforestation, clearing or fires to improve the accuracy of change detection without a dense time series. The scientific questions addressed in this study were: how well can we differentiate seasonal changes from deforestation processes combining the spatial and spectral information of bi-temporal (normalized difference vegetation index) NDVI images? Which feature best contribute to increase the separability on classification assessment? We applied an object-based remote sensing method that is able to separate seasonal changes due to phenology effects from LULCC by combining spectral and the spatial context using traditional spectral features and semivariogram indices, exploring the full capability of NDVI image difference to train random forest (RF) algorithm. We found that the spatial variability of NDVI values is not affect by vegetation seasonality and, therefore, the combination of spectral features and semivariogram indices provided high global accuracy (97.73%) to separate seasonal changes and deforestation or fires. From the total of 13 features, 6 provided the best combination to increase the separability on classification assessment (4 spatial and 2 spectral features). How to accurately extract LULCC while disregarding the ones caused by phenological differences in Brazilian seasonal biomes undergoing rapid land-cover changes can be achieved by adding semivariogram indices in combination with spectral features as input data to train RF algorithm.

Micro level analyses of environmentally disastrous urbanization in Bangalore.

Indian metropolitan (tier I) cities have been undergoing rapid urbanization during the post-globalization era with the unprecedented market interventions, which have led to the rapid land cover changes affecting the ecology, climate, hydrology, and local environment. The unplanned urbanization has given way to the dispersed, haphazard growth at the city outskirts with the lack of basic amenities and infrastructure as the planners lack advance information of sprawl regions. This has necessitated understanding and visualization of urbanization patterns for planning towards sustainable cities. The analyses of urban dynamics during 1973-2017 using temporal remote sensing data reveal 1028% increase in urban area with the decline of 88% vegetation and 79% of water bodies. Consequences of the unplanned urbanization are the increase in greenhouse gas emissions, decline in vegetation cover, loss of groundwater table (from 28 to 300m), contamination of water sources, increase in land surface temperature, increase in disease vectors, etc. An attempt is made to understand the implications of unplanned growth at the micro level by considering the prime growth poles such as Peenya Industrial Estate (PIE), Whitefield (WF), Bangalore South Region (BSR). The spatial analyses reveal the decline of vegetation and open spaces with intense urbanization of 86.35% (in BSR), 87.39% (PIE) and 81.61% (WF) in 2017. WF witnessed the drastic transformation from agrarian ecosystem to a concrete jungle during the past four decades. Spatial patterns of urbanization were assessed through the landscape metrics and rule-based modeling which confirms intense urbanization with single class dominance. Specifically, NP metrics depicts PIE region had sprawl growth till 2003 with numerous patches and is transformed by 2017 it has become to a single dense urban patch. This necessitates appropriate planning strategies to mitigate further erosion of environmental resources and ensure clean air, water, and environment to all residents.

Numerical modelling and remote sensing based approaches for investigating groundwater dynamics under changing land-use and climate in the agricultural region of Pakistan

The shrinking groundwater resource is a major cause of ecosystem imbalance, which is further intensified by rapid changes in land use and land cover (LULC) and climate in the lower Chenab canal (LCC) of Pakistan. Present study aims to investigate groundwater dynamics using a novel approach by incorporating remote sensing data in combination with actual patterns of LULC, while statistical approach is employed for downscaling of climatic data under two emission scenarios including H3A2 and H3B2. A 3-D numerical groundwater flow model is used for evaluating current patterns of groundwater use and its dynamics. The results of water budget show a total horizontal groundwater inflow of 2844 Mm3 and an outflow of 2720.2 Mm3. The groundwater abstraction through pumping is about 17374.43 Mm3 as compared to groundwater recharge of 19933.20 Mm3, yields a surplus of 2682.87 Mm3, which raises groundwater levels in major parts of LCC. Change in rice cultivation has the highest impact on groundwater levels in upper regions of LCC, whereas higher negative changes are observed for lower parts under decreased fodder area in place of rice, cotton and sugarcane. For climate scenarios, a rise in groundwater level is observed for 2011 to 2025, whereas, its drop is expected for the periods 2026–2035 and 2036–2045 under H3A2 scenario. Due to no imminent threats to groundwater, there is an opportunity for groundwater development through water re-allocation. Groundwater status under H3B2 emission regime is rather complex during 2011–2025. Water management under such situation requires revisiting of cropping patterns and augmenting water supply through additional surface water resources. Considering the limitations of the current study, it is recommended to update model with river flow under changing climate, and to extend investigations for combined effects of LULC and climate change.

Spatial patterns in dissolved organic matter composition controlled by watershed characteristics in a coastal river network: The Neuse River Basin, USA

The effect of watershed characteristics (land use land cover and morphology) on spatial variability in dissolved organic matter (DOM) composition, and concentrations of dissolved organic carbon [DOC] and nitrogen [DON] was assessed in a coastal river basin draining into Pamlico Sound in eastern North Carolina, USA. Understanding the factors that influence DOM concentration and composition i.e., structurally complex molecules with high molecular weight versus low molecular weight, simple molecules can provide insights on DOM cycling and water composition implications. Such information is imperative for large coastal river networks undergoing rapid and intense land use and land cover (LULC) changes. DOM composition was estimated using optical indices calculated from DOM absorbance and fluorescence measurements. DOM was derived from terrestrial sources, and ordination analysis indicated that LULC, in particular, % wetland area was the most significant control on DOM composition and concentration. Wetland and agricultural coastal streams were abundant in humic and complex DOM, whereas forested and urban streams were least abundant in humic DOM. We speculate that greater availability of mobilizable DOM in wetland and agricultural watersheds contributed to this observation. In comparison, mixed urbanized and forested streams in North Carolina’s Piedmont region were abundant in [DOC], less complex, low molecular weight DOM, as well as greater amounts [DON] due to higher urban runoff and elevated DOM production in these streams. Our results indicated that physiographic transition from Piedmont to coastal plain and varying LULC influenced the spatial variability in DOM composition and concentration. Our findings highlight that increasing anthropogenic alterations might increase the abundance of reactive DOM in coastal rivers and estuaries resulting in severe water quality issues. This information is important for monitoring and developing land use policies.

Analyzing Land Cover Change Using Remote Sensing and GIS: A Case Study of Gilgit River Basin, North Pakistan

Mountainous areas of northern Pakistan are rich in biodiversity, glaciers and key watershed of Indus Riversystem which provide ecosystem services for their inhabitants. These regions have experienced extensive deforestationand are presently vulnerable by rapid land cover changes, therefore an effective assessment and monitoring is essentialto capture such changes. The aim of this study is to analyze the observed changes in land cover over a period of thirtynine years, divided into three stages (1976-1999, 1999-2008 and 2008-2015). Four images from Landsat 2Multispectral Scanner System (MSS), Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper andLandsat 8 Operation Land Imager data were obtained to detect land cover change. This study used supervisedclassification-maximum likelihood algorithm in ERDAS imagine to identify land cover changes perceived in GilgitRiver Basin, Pakistan. The result showed that the range land, glaciers, water bodies, built-up/agricultural cover are themajor categories that have been altered by the natural and anthropogenic actions. In 1976, built up/agriculture, rangeland, water bodies and glacier cover was 1.13%, 45.3%, 0.66% and 13.2%, respectively. Whereas in 2015, builtup/agriculture, range land, water bodies and glacier cover was 3.25%, 12.7%, 0.91% and 8.2%, respectively. Thesesland cover shifts posed acute threat to watershed resources. Therefore, a comprehensive watershed resourcemanagement is essential or otherwise, these resources will deplete rapidly and no longer be capable of playing their rolein socioeconomic and sustainable environmental development of the area

Analyzing Land Cover Change Using Remote Sensing and GIS: A Case Study of Gilgit River Basin, North Pakistan

Mountainous areas of northern Pakistan are rich in biodiversity, glaciers and key watershed of Indus Riversystem which provide ecosystem services for their inhabitants. These regions have experienced extensive deforestationand are presently vulnerable by rapid land cover changes, therefore an effective assessment and monitoring is essentialto capture such changes. The aim of this study is to analyze the observed changes in land cover over a period of thirtynine years, divided into three stages (1976-1999, 1999-2008 and 2008-2015). Four images from Landsat 2Multispectral Scanner System (MSS), Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper andLandsat 8 Operation Land Imager data were obtained to detect land cover change. This study used supervisedclassification-maximum likelihood algorithm in ERDAS imagine to identify land cover changes perceived in GilgitRiver Basin, Pakistan. The result showed that the range land, glaciers, water bodies, built-up/agricultural cover are themajor categories that have been altered by the natural and anthropogenic actions. In 1976, built up/agriculture, rangeland, water bodies and glacier cover was 1.13%, 45.3%, 0.66% and 13.2%, respectively. Whereas in 2015, builtup/agriculture, range land, water bodies and glacier cover was 3.25%, 12.7%, 0.91% and 8.2%, respectively. Thesesland cover shifts posed acute threat to watershed resources. Therefore, a comprehensive watershed resourcemanagement is essential or otherwise, these resources will deplete rapidly and no longer be capable of playing their rolein socioeconomic and sustainable environmental development of the area

Drought and Human Impacts on Land Use and Land Cover Change in a Vietnamese Coastal Area

Drought is a dry-weather event characterized by a deficit of water resources in a period of year due to less rainfall than normal or overexploitation. This insidious hazard tends to occur frequently and more intensively in sub-humid regions resulting in changes in the landscape, transitions in agricultural practices and other environmental-social issues. The study area is in the sub-humid region of the northern coastal zone of Binh Thuan province, Vietnam—Tuy Phong district. This area is indicated as a subject of prolonged droughts during 6-month dry seasons, which have occurred more frequently in recent years. Associated with economic transitions in agricultural practicing, urbanization, and industrialization, prolonged droughts have resulted in rapid changes in land use and land cover (LULC) in Tuy Phong, especially in three coastal communes: Binh Thanh, Lien Huong, and Phuoc The. A bi-temporal analysis using high-resolution data, the 2011 WorldView2 and the 2016 GeoEye1, was examined to assess LULC changes from observed severe droughts in those three communes. Results showed a dramatic reduction in the extent of hydrological systems (about 20%), and significant increases of tree canopies in urban areas and near the coastal areas (approximately 76.8%). Paddy fields declined by 51% in 2016; such areas transitioned to inactive status or were alternated for growing drought-tolerant plants. Shrimp farming experienced a recognizable decrease by approximately 44%. The 2014 map and field observations during summer 2016 provide references for object-based classification and validation. Overall agreement of results is about 85%.

Historical aerial and terrestrial photographs for the investigation of mass movement dynamics in the Ethiopian Highlands

AbstractThe edges of the Ethiopian Plateau are affected by frequent landslides predisposed by pronounced seasonality in precipitation, thick weathering mantle of volcanic material, and rough relief. We analyzed the three‐dimensional dynamics of three large landslides in Dessie using digital elevation models and ortho‐images derived from a time‐series of aerial photographs reaching back to 1936. Furthermore, we utilized repeated photography based on terrestrial photographs from the 1930s and 1940s to analyze landscape changes. It was revealed that the large sliding zone (25.4 ha) in lacustrine sediments at Kerra locality existed approximately in the present extent already before 1936. The volume of depleted material of the 1986–1994 rock slide at Doro Mezleya locality was assessed as 1.82 106 m3 with mean vertical thickness of 48 m. Additionally, we described the nowadays inactive Hot Spring landslide (12.9 ha). We documented a large scale reforestation of the area carried out as a remediation measure and rapid changes in land cover and settlement structure. We conclude that two out of three studied large landslides existed before 1936 and thus are not induced by the increased human pressure on the landscape of the last decades. Additionally, we provide an overview about collections of historical aerial photographs of Ethiopia, and we discuss their potential and drawbacks for mass wasting studies.

Waterfowl Spring Migratory Behavior and Avian Influenza Transmission Risk in the Changing Landscape of the East Asian-Australasian Flyway

Avian influenza has advanced from a regional concern to a global health issue with significant economic, trade, and public health implications. Wild birds, particularly waterfowl (Anseriformes), are known reservoirs for low-pathogenic avian influenza viruses (AIV) and recent studies have shown their potential in the spread of highly pathogenic forms of virus. East Asia remains an epicenter for the emergence of novel strains of AIV, however, information on movement ecology of waterfowl, and subsequently a clearer understanding of disease transmission risks in this region has been greatly lacking. To address this, we marked two species of wild waterfowl, northern pintail (Anas acuta) and Eurasian wigeon (Anas penelope), with satellite transmitters on their wintering grounds in Hong Kong, China to study the northward spring migration in the East Asian-Australasian Flyway in relation to disease transmission factors. Northern pintail were found to initiate migration 42 days earlier, travel 2150 km farther, and perform 4.4 more stopovers than Eurasian wigeon. We found both species used similar stopover locations including areas along the Yangtze River near Shanghai, Bohai Bay and Korea Bay in rapidly developing regions of the Yellow Sea, and the Sea of Okhotsk where the species appeared to funnel through a migratory bottleneck. Both species appeared to exhibit strong habitat selection for rice paddies during migration stopovers, a habitat preference which has the potential to influence risks of AIV outbreaks as rapid land use and land cover changes occur throughout China. Both species had greatest association with H5N1 outbreaks during the early stages of migration when they were at lower latitudes. While Eurasian wigeon were not associated with outbreaks after the mean date of wintering ground departures, northern pintail were associated with outbreaks until the majority of individuals departed from the Yellow Sea, a migratory stopover location. Our results show species-level differences in migration timing and behavior for these common and widespread species, demonstrating the need to consider their unique temporal and spatial movement ecology when incorporating wild birds into AIV risk modeling and management.

Predicting the Potential Impact of Climate Change on Carbon Stock in Semi-Arid West African Savannas

West African savannas are experiencing rapid land cover change that threatens biodiversity and affects ecosystem productivity through the loss of habitat and biomass, and carbon emissions into the atmosphere exacerbating climate change effects. Therefore, reducing carbon emissions from deforestation and forest degradation in these areas is critical in the efforts to combat climate change. For such restorative actions to be successful, they must be grounded on a clear knowledge of the extent to which climate change affects carbon storage in soil and biomass according to different land uses. The current study was undertaken in semi-arid savannas in Dano, southwestern Burkina Faso, with the threefold objective of: (i) identifying the main land use and land cover categories (LULCc) in a watershed; (ii) assessing the carbon stocks (biomass and soil) in the selected LULCc; and (iii) predicting the effects of climate change on the spatial distribution of the carbon stock. Dendrometric data (Diameter at Breast Height (DBH) and height) of woody species and soil samples were measured and collected, respectively, in 43 plots, each measuring 50 × 20 m. Tree biomass carbon stocks were calculated using allometric equations while soil organic carbon (SOC) stocks were measured at two depths (0–20 and 20–50 cm). To assess the impact of climate change on carbon stocks, geographical location records of carbon stocks, remote sensing spectral bands, topographic data, and bioclimatic variables were used. For projections of future climatic conditions, predictions from two climate models (MPI-ESM-MR and HadGEM2-ES) of CMIP5 were used under Representative Concentration Pathway (RCP) 8.5 and modeling was performed using random forest regression. Results showed that the most dominant LULCc are cropland (37.2%) and tree savannas (35.51%). Carbon stocks in woody biomass were higher in woodland (10.2 ± 6.4 Mg·ha−1) and gallery forests (7.75 ± 4.05 Mg·ha−1), while the lowest values were recorded in shrub savannas (0.9 ± 1.2 Mg·ha−1) and tree savannas (1.6 ± 0.6 Mg·ha−1). The highest SOC stock was recorded in gallery forests (30.2 ± 15.6 Mg·ha−1) and the lowest in the cropland (14.9 ± 5.7 Mg·ha−1). Based on modeling results, it appears clearly that climate change might have an impact on carbon stock at horizon 2070 by decreasing the storage capacity of various land units which are currently suitable. The decrease was more important under HadGEM2-ES (90.0%) and less under MPI-ESM-MR (89.4%). These findings call for smart and sustainable land use management practices in the study area to unlock the potential of these landscapes to sequestering carbon.

Linking land use changes to variation in soil properties in a Mediterranean mountain agroecosystem

Several decades of intensive rainfed farming in Mediterranean mountains and later land abandonment has led to rapid land use and land cover changes. During recent centuries, the conversion of rangelands into croplands has increased the surfaces prone to erosion. In the southern Pre-Pyrenees, the process was reversed during the middle of the twentieth century, allowing the recovery of vegetation and subsequent variation in land cover. This work aims to assess how land use changes after generalised land abandonment affect some major soil properties related to soil quality. For this purpose, 98 replicate bulk soil samples were collected in a 23 km2 catchment that was mostly cultivated at the beginning of the last century. Soil samples were distributed over areas representing the main land uses (agricultural land, natural forest, pine afforestation and scrubland). Bulk density, stoniness, grain size, pH, carbonates, electrical conductivity, soil organic carbon (SOC), total nitrogen (TN), water retention capacity and magnetic properties (low frequency magnetic susceptibility (LF) and frequency dependence (FD)) were analysed in the samples from different land use areas. A past scenario was recreated using estimated data from the SPEROS-C model in order to evaluate changes in SOC over time. Furthermore, a multitemporal analysis of the Normalised Difference Vegetation Index of Landsat images was performed between 1972 and the present in order to assess the dynamics of revegetation. After land abandonment, 16.5% of the area remained as croplands, but afforestation and natural revegetation occupied 83.5% of the catchment. The highest mean value for SOC was found in the pine afforested area and the highest TN mean value was found in the natural forest. The lowest mean values for SOC and TN were recorded on the agricultural land. These results show the impact of soil changes produced by land use changes in fragile Mediterranean mountain agroecosystems.

New Derivation Method of Region Specific Curve Number for Urban Runoff Prediction at Melana Watershed in Johor, Malaysia

The Soil Conservation Services (SCS) rainfall-runoff model has been incorporated into many types of software and adopted by Malaysian government agencies for design use. However, hydrologists argue the accuracy of the predicted runoff results from this model in recent decades. Malaysia does not have a regional specific curve numbers available for the use in rainfall-runoff modelling, and therefore SCS-CN practitioner has no option but to adopt its guideline and handbook values which are specific to US region. Unlike the conventional SCS-CN technique, the proposed calibration methodology in this paper discarded the use of CN as input to the SCS model, rearranged the model equation and derived statistically significant CN value(s) of a specific region through rainfall-runoff events directly through the use of inferential statistics. The SCS rainfall-runoff framework can now be calibrated quickly to address urban runoff prediction challenge under rapid land use and land cover or climate changes with the proposed methodology. Between July and October of 2004, the derived λ was 0.0005 while λ = 0.20 was found to be statistically insignificant at alpha = 0.01 level at Melana watershed in Johor, Malaysia. Optimum CN of 90.45 was derived to represent the rainfall-runoff characteristic of Melana watershed. Runoff prediction error was reduced by 90% and achieved the Nash-Sutcliffe (NS) index of 0.86. The new method can provide CN adjustment guidelines for SCS practitioners and any software which incorporated the model to predict urban runoff.

Impacts of Land Use and Cover Changes on Transhumant Pastoralism in Sudanian Zones of Burkina Faso, West Africa

This research aimed to investigate how the rapid land use and cover changes is affecting pastoral resources and practices within Kompienga province in Sudanian zone of Burkina Faso. To achieve this aim, Landsat images data of years 1989, 2001, 2013 and 2015 were retrieved and analysed. Images were acquired following the path 193 and row 52, from Landsat-5 Thematic Mapper (TM), Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI). Images processing were done using 350 training sample for both; the purpose of supervised classification and accuracy assessment. Random Forest Algorithm (RFA) procedures in R-Software (version 3.3.2) were used for images classification. Furthermore, survey data were collected through group discussions and individual interviews with a 271 head of household respondents (pastoralists and agro-pastoralists) to investigate respondents’ perceptions on land uses and covers changes and its impacts on their pastoral and agro pastoral resources and animal husbandry practices. Results showed that Land use dynamics was characterized by an increase in croplands at an average rate of 46.7 % per year, between 1989 and 2015. On the contrary a decline of pasture lands was observed since 2001 at an average rate of 6.0 % per year. Similar trends in land uses changes were observed by interviewed respondents who depicted an increase in cropping lands (98.5 % of respondents) to the detriment of pasture lands (97.8 % of respondents). To overcome these land use/land cover changes and it subsequent consequences, respondent pastoralists and agro pastoralists have developed local adaptations strategies. Thus, some measures are still needed at government level to sustain local pastoralist and agro-pastoralist efforts and strengthen their adaptive capacity.

Past role and future outlook of the Conservation Reserve Program for supporting honey bees in the Great Plains

Human dependence on insect pollinators continues to grow even as pollinators face global declines. The Northern Great Plains (NGP), a region often referred to as America's last honey bee (Apis mellifera) refuge, has undergone rapid land-cover change due to cropland expansion and weakened land conservation programs. We conducted a trend analysis and estimated conversion rates of Conservation Reserve Program (CRP) enrollments around bee apiaries from 2006 to 2016 and developed models to identify areas of habitat loss. Our analysis revealed that NGP apiaries lost over 53% of lands enrolled in the CRP, and the rate of loss was highest in areas of high apiary density. We estimated over 163,000 ha of CRP lands in 2006 within 1.6 km of apiaries was converted to row crops by 2012. We also evaluated how alternative scenarios of future CRP acreage caps may affect habitat suitability for supporting honey bee colonies. Our scenario revealed that a further reduction in CRP lands to 7.7 million ha nationally would reduce the number of apiaries in the NGP that meet defined forage criteria by 28% on average. Alternatively, increasing the national cap to 15 million ha would increase the number of NGP apiaries that meet defined forage criteria by 155%. Our scenarios also show that strategic placement of CRP lands near existing apiaries increased the number of apiaries that meet forage criteria by 182%. Our research will be useful for informing the potential consequences of future US farm bill policy and land management in the epicenter of the US beekeeping industry.

Land-Cover Change Analysis and Simulation in Conakry (Guinea), Using Hybrid Cellular-Automata and Markov Model

In this study, land-cover change in the capital Conakry of Guinea was simulated using the integrated Cellular Automata and Markov model (CA-Markov) in the Geographic Information System (GIS) and Remote Sensing (RS). Historical land-cover change information was derived from 1986, 2000 and 2016 Landsat data. Using the land-cover change maps of 1986 and 2000, the land-cover change map for 2016 was simulated based on the Markov model in IDRISSI software (Clark University, Worcester, MA, USA). The simulated result was compared with the 2016 land-cover map for validation using the Relative Operating Characteristic (ROC). The ROC result showed a very strong agreement between the two maps. From this result, the land-cover change map for 2025 was simulated using CA-Markov model. The result has indicated that the proportion of the urban area was 49% in 2016, and it is expected to increase to 52% by 2025, while vegetation will decrease from 35% in 2016 to 32% in 2025. This study suggests that the rapid land-cover change has been led by both rapid population growth and extreme poverty in rural areas, which will result in migration into Conakry. The results of this study will provide bases for assessing the sustainability and the management of the urban area and for taking actions to mitigate the degradation of the urban environment.

Environmental Monitoring of Spatio-Temporal Changes in Northern Istanbul using Remote Sensing and GIS

This study aims to evaluate the landscape transformation and the effect of the third Bosphorus Bridge construction works on the natural ecosystem over seven years’ time in two districts, Beykoz and Sariyer, located at the northern part of Asian and European Istanbul. The study applied supervised classification-maximum likelihood algorithm to monitor land cover changes using multi-temporal satellite data of Landsat covering study area for the years of 2009 and 2016. The overall classification accuracies are 92.36% with Kappa statistic of 0.89 for 2009 and 91.25% with Kappa statistic of 0.89 for the year 2016. The current study resulted with a rapid land cover change at the study area with approximately 4% and %1 decrease in forest and green area, 2% increase in both agricultural and urban/build up areas. Additionally, the destroyed area increased with approximately 1% of the study area in the 7 years period.

Agricultural land use and cover change in the Cerrado/Amazon ecotone: A case study of the upper Teles Pires River basin

ABSTRACT The upper Teles Pires River basin is a key hydrological resource for the state of Mato Grosso, but has suffered rapid land use and cover change. The basin includes areas of Cerrado biome, as well as transitional areas between the Amazon and Cerrado vegetation types, with intensive large-scale agriculture widely-spread throughout the region. The objective of this study was to explore the spatial and temporal dynamics of land use and cover change from 1986 to 2014 in the upper Teles Pires basin using remote sensing and GIS techniques. TM (Thematic Mapper) and TIRS (Thermal Infrared Sensor) sensor images aboard the Landsat 5 and Landsat 8, respectively, were employed for supervised classification using the “Classification Workflow” in ENVI 5.0. To evaluate classification accuracy, an error matrix was generated, and the Kappa, overall accuracy, errors of omission and commission, user accuracy and producer accuracy indexes calculated. The classes showing greatest variation across the study period were “Agriculture” and “Rainforest”. Results indicated that deforested areas are often replaced by pasture and then by agriculture, while direct conversion of forest to agriculture occured less frequently. The indices with satisfactory accuracy levels included the Kappa and Global indices, which showed accuracy levels above 80% for all study years. In addition, the producer and user accuracy indices ranged from 59-100% and 68-100%, while the errors of omission and commission ranged from 0-32% and 0-40.6%, respectively.

The potential use of natural resources in urban informal settlements as substitutes for financial capital during flooding emergencies

Rapid and widespread land cover change and the subsequent loss of the buffering capacity provided by healthy ecosystems against natural hazards has resulted in increased vulnerability to natural hazards. There is an insufficient understanding of the natural resources contribution to the resilience of poor urban communities living in informal settlements and the financial implications thereof. Thus, household strategies used to recover from the October 2012 flood shock were investigated within the informal settlements of three small South African towns using questionnaires. Within the vulnerability paradigm and the sustainable livelihood framework, the study also quantified and evaluated the relative contribution of natural resources to recovery strategies and the impacts on household financial capital. We found that natural resources contributed up to 70% to recovery of households from the flood shock, most of this being to reconstruct housing structures after the flood. Factors such as household head education level, household income, kinship level, the extent of property damage and the cost associated with property rehabilitation significantly influenced the uptake of natural resources in recovery from floods, and this was variable among settlements and towns. The main findings showed that natural resources reduced household vulnerability of urban informal settlements by providing an emergency-net function that substitutes financial capital. Their inclusion in disaster management plans and responses has the potential to contribute to the sustainable livelihoods of the urban poor in the Eastern Cape, South Africa.

Spatiotemporal monitoring of land surface temperature and estimated radiation using remote sensing: human health implications for East London, South Africa

Increase in land surface temperature (LST) and area radiation (R) has serious health implications on human life. Therefore, investigating LST and R changes is fundamental in providing crucial information for human survival. Remote sensing was used to assess the LST and estimated radiation of East London city in Eastern Cape Province of South Africa from Landsat thematic mapper images for 1986, 1996, 2006, and operational land imager, thermal infrared sensor for 2016 spanning a period of 30 years. Rapid urbanization and land cover changes in this area have contributed significantly to this drastic change in the natural surface characteristics (increased land surface temperature and surface solar radiation). For instance, vegetation cover declined by about 358.812 km2 and built-up increased built-up area by 175.473 km2 during this period, which correlates with the area thermal characteristics changes. Also, the radiation increased over the years with values exceeding the global solar radiation index. Exposure to increased ultraviolet radiation possesses risks of heat stroke, skin cancer, and heart disease to the local population. Consequently, this study provides pertinent information for human health sustainability and epidemiological cases management. Further investigation is needed in established case-specific causes. This study also epitomises the significance of remote sensing climate variability studies.

Impact of Abrupt Land Cover Changes by Tropical Deforestation on Southeast Asian Climate and Agriculture

Southeast Asia (SE Asia) undergoes major and rapid land cover changes as a result of agricultural expansion. Landscape conversion results in alterations to surface fluxes of moisture, heat, and momentum and sequentially impact the boundary layer structure, cloud-cover regime, and all other aspects of local and regional weather and climate occurring also in regimes remote from the original landscape disturbance. The extent and magnitude of the anthropogenic modification effect is still uncertain. This study investigates the biogeophysical effects of large-scale deforestation on monsoon regions using an idealized deforestation simulation. The simulations are performed using the regional climate model COSMO-CLM forced with ERA-Interim data during the period 1984–2004. In the deforestation experiment, grasses in SE Asia, between 20°S and 20°N, replace areas covered by trees. Using principal component analysis, it is found that abrupt conversion from forest to grassland cover leads to major climate variability in the year of disturbance, which is 1990, over SE Asia. The persistent land modification leads to a decline in evapotranspiration and precipitation and a significant warming due to reduced latent heat flux during 1990–2004. The strongest effects are seen in the lowlands of SE Asia. Daily precipitation extremes increase during the monsoon period and ENSO, differing from the result of mean precipitation changes. Maximum temperature also increases by 2°C. The impacts of land cover change are more intense than the effects of El Niño and La Niña. In addition, results show that these land clearings can amplify the impact of the natural mode ENSO, which has a strong impact on climate conditions in SE Asia. This will likely have consequences for the agricultural output.