| Globally,coastal areas suffer from increased human activities and hence becoming ecologically vulnerable.Numerous scientific researchers have revealed that changes on the coastal land use and land cover（LULC）at both the regional and global scales are as a result of multiple social,cultural and economic factors.There is an overall concern on the land use practices,such as shifting cultivation and extraction of forest materials as agents of forest losses,which are threatening coastal estuaries.These concerns were initiated several decades ago（since 1970’s）in order to address issues concerning global environmental changes on the land-use and land-cover dynamics,driving forces,and impacts on the environmental and social aspects towards sustainable development.The report from the census data indicated that Tanzania’s population increased from 12.3 million in 1967 to 44.9 million people in 2012.By the end of 2020,population grew up to 59.7 million people.Based on the United Nations data estimates,it is projected that the population will rise up to 282.67 million by the end of the century.Over population or population density has implications for land resources as the need to produce enough food for people,housing requirements and fuel wood increase in response to growing population needs.This is aligned with the questionnaire survey that revealed that 90% of the total respondents believed that population growth was attributed to land use change in their area.These implications have yet needed to be proved quantitatively in Tanzania because there have been rare LULCC studies taking the coast Tanzania as a whole since 2000.The coastal area of Tanzania is economically and environmentally important and rich in biodiversity.It is on the eastern part of Tanzania mainland,and it consists of five administrative regions which are Tanga,Pwani,Dar es Salaam,Lindi and Mtwara.These regions cover approximately 15% of the total country’s land area,and about 25% of the overall Tanzania population live on the coast.The area is located between latitudes 5°20’S-10°20’S and longitudes 38°0’E-40°20’E,situated along the Indian Ocean coastal belt.Tanzania coastline extends from the north to south on the mainland,bordering Kenya in the north and Ruvuma River in the south.The area faces poor management of land-based resources,tied with a growing interest and reliance on various products and services which poses a challenge for managing the natural resources in this area.Also,the conversion of forestlands and wetlands for other uses such as settlement and agriculture to satisfy a growing population has not helped much.It is a problem facing not only the coastal but many parts of the country.The coastal ecosystems in Tanzania have been experiencing major land use and land cover changes（LULCC）and remarkable deterioration in the nature of their environment through destruction of natural habitats and biodiversity loss.These changes were driven by the natural and anthropogenic factors.But,the changes are mostly due to anthropogenic activities as Tanzania coast is among the areas with high population growth compared to other places in Tanzania due to their economic potential in terms of agriculture and trade.The changes on land associated with inadequate planning brings along adverse impacts such as soil erosion,flooding which in the long-run substitute into the climate change.Understanding of the long-term development and driving forces of coastal changes are needed,especially at local levels where many decisions on land utilization policies are formulated.However,in Tanzania especially the coastal zone,there is insufficient scientific researches that shows the general pattern and trend of the changes despite the noticeable increasing population growth.The overall objective of this study was to examine the magnitude of the LULCC in the coast of Tanzania from 2000 to 2020,associated with the drivers and impacts to the coastal ecosystem for sustainable coastal management.More specifically,it was in attempts to determine the status and extent of LULCC with respect to human and climatic factors in the Tanzanian coast between 2000 and 2010;2010 and 2020;to assess the driving factors contributing LULCC in the coast of Tanzania;to determine the impacts of LULCC to the Tanzania coastal ecosystem;and to predict future LULC for 2030 with CA-Markov model.The key focus was on the implications of biophysical and anthropogenic factors on the future prospects of coastal Tanzania.Furthermore,by analyzing the LULCC process of the Msimbazi Basin near the center of Dar es Salaam,it was intended to reveal the damage to the ecosystem in the region by disordered land use to adapt a rapid settlement expansion.Multiple sources of data were used in this study.The Landsat TM and land cover data of 2000,2010 and 2020 time-period were from Globeland30,the 30-meter resolution global land cover data product,launched and maintained by National Geomatics Center of China.Eight classes of land cover data were used which are cultivated land,built-up land,forest,shrub land,grassland,wetland,bare land,and water.Landsat TM for 1990,2000 and 2010 and Landsat-8 OLI data for 2019 from United States Geological Survey（USGS）Global Visualization Viewer（Glo Vis）were used for Msimbazi river basin so as to study the spatial-temporal changes.All of these images have a spatial resolution of 30 m,with multispectral coverage from the visible to the middle infrared radiation fields of the electromagnetic spectrum.The MOD13Q1 NDVI（Terra Vegetation Indices 16-day Global 250 m）dataset was used in studying the vegetation dynamics along the coast of Tanzania.The dataset spanning between 2000 and 2018 was downloaded from the Google Earth Engine（GEE）.The assessment of large-scale vegetation dynamics was evaluated from the inter-annual time-series MODIS NDVI data during 2000-2018,through developing code in the GEE editor.The MOD13Q1 has 250 m spatial resolution and 16 days of temporal resolution.The study also made use of the meteorological datasets consisting of precipitation and land surface temperature obtained from the GEE platform.Remotely-sensed precipitation was calculated using the recently available CHIRPS（Climate Hazard Group Infrared Precipitation with Station）datasets for the period 2000 to 2018.The dataset offers global coverage,delivers daily precipitation values at 0.05° spatial resolution.The annual temperature data were retrieved from the MOD11A2（Terra Land Surface Temperature and Emissivity 8-Day Global 1km）dataset,which has an average of 8-days per-pixel,a spatial resolution of 1km in a 1200x1200 km grid;the LSTDay1km band,was used to evaluate the temperature trend from 2000 to 2018.The population data makes part and parcel of the significant information in this study.Census data of 1988,2002 and 2012 was obtained from the National Bureau of Statistics（NBS）in Tanzania.Due to the lack of the recent population census,the 2019 population data were obtained through projection of the 2012 population data by an arithmetical method.As a cloud-computing geospatial processing tool,in this study,GEE platform was not only used for open accessible satellite imageries and their products retrieval,and it was used for analysis and visualization purposes as well.Land cover data for the coast Tanzania was from Globeland30 and used directly for analysis.Image processing and land cover classification methods were applied for TM and OLI images over Msimbazi river basin.In consideration of seasonality and cloud cover effects,images were selected from the dry season（June to October）in order to acquire images with less atmospheric haze,more vegetation visibility and also no differences due to seasons.In that aspect,atmospheric correction and image enhancement were not carried out due to the good image quality.Pre-processing of these images only involves image stacking.After image stacking where different images having different bands were stacked into a single multilayer image.These images were projected using the Universal Transverse Mercator（UTM）coordinate system of the WGS 1984,zone 37 S and Arc 1960 datum.The process was carried out using ERDAS Imagine version 9.1.The pre-processed image was then classified to generate the land-cover types and determine changes that have taken place in Msimbazi basin between 1990-2000,2000-2010 and 2010-2019 time periods.Supervised classification technique with maximum likelihood algorithm was applied.This was performed using Arc GIS 10.5 software.Land use/cover data from Institute of Resource Assessment（IRA）and Surveys and Mapping Division（SMD）were used as reference data during digitization in order to assist in image interpretation and classification.During fieldwork,location coordinates（ground-truth）data collected using a hand-held Global Positioning System（GPS）device are used as training samples during classification and reference data when assessing the classification accuracy.The area was classified into seven land classes: agriculture,built-up land,forest,bushland,grassland,water and wetland vegetation.The more accurate Sentinel-2 image of 2016 having 10 m spatial resolution was used as a base layer in comparison of the pixel-based information from the classified images.The assessment was achieved by comparing the pixel values from the Sentinel image to the pixel values of the classified images.In this case,1000 points were specified and randomly distributed in the Sentinel image.The Mann-Kendall（M-K）test and Pearson correlation were used to determine the trend of vegetation cover and climatological data and relationship between them respectively.The trends of LULC changes in 2030 were simulated in Terr Set using the Land Change Modeler（LCM）that has been mainly used for monitoring and evaluating ecological sustainability in different parts of the world,including Tanzania.The simulation process was done in two main sessions.The first session involved the classified 2000 and 2010 imagery used to predict the 2020 LULC and validate its accuracy based on its real LULC classified using the same approach as for the 2000 and 2010 imagery.The next session for the 2010 and 2020 LULC maps was used to predict the 2030 LULC patterns.In both sessions,the predictions of LULC maps were done using the Markovian chain model after training the variables of elevation and slope using MLP（Multilayer perceptron）neural network.Specifically,the steps followed in each session aimed to 1)harmonize essential prediction parameters such as spatial extent and resolution of the imagery and 2)compute and evaluate change maps to determine a significant threshold for creating transition potentials used for predicting future LULCs.Land surface temperature（LST）and precipitation are typically considered to be the most important climatic factors influencing vegetation and can either enhance or constrain greenness.The analysis of this study used temperature and precipitation as indicators of climate change that have influenced the NDVI indicating vegetation cover which imply also changes in land use and cover change.Using the NDVI,the analysis indicates that,mean maximum temperature of 31.2℃ occurred in 2017 and minimum of 27.4℃ in 2002,with a mean value of 29.3℃.The Mann-Kendall temperature trend analysis estimated values of Z = 2.87 and β = 0.152.This threshold |Z| value is > 1.96,thus rejecting the null hypothesis and implying that the trend in temperature over the period is both positive and statistically significant.Places with high temperatures especially in coastal areas have high evaporation rates.In these areas,photosynthesis of a plant increases as the temperature rises.Given that increased temperatures are associated with higher evapotranspiration,it is expected that this would impact soil water availability and,in turn,reduce vegetation greenness.Understanding precipitation-vegetation interaction is of great importance to implementing adaptation and mitigation measures for terrestrial ecosystems.In this study,the results indicate maximum annual precipitation occurred in 2006（1344 mm）and minimum（650 mm）in 2003,with a mean of 997 mm.It is observed that NDVI changes seasonally,with the wet season showing higher NDVI than the dry season,together with higher rainfall.Lag effects are evident in the time series.For example,it is perhaps surprising that,in Tanga and Mtwara,NDVI increased regardless of lower annual precipitation values between 2006 and 2007.However,higher rainfall values in the previous two years（2005–2006）appear to have been able to support vegetation growth through the drier years.The precipitation trend analysis produces values of Z = 1.68 which,being below 1.96,means that the null hypothesis is accepted and that the trend,while positive,is not statistically significant.Pearson correlation analysis was used to assess the nature of the response of NDVI to the temperature and precipitation.The results revealed that vegetation growth has a positive relationship with precipitation but is negatively correlated with temperature.This is consistent with the fact that soil moisture availability strongly influences vegetation growth and productivity.Results confirmed that precipitation and temperature are the prominent controlling factors and have a strong influence on vegetation cover.Coastal Tanzania has therefore experienced increased temperatures and variable moisture conditions which threaten natural vegetation and ecosystems at large.Classified land cover maps taken from Globe Land30 were analyzed to discover the nature and scale of anthropogenic effects on the coastal land.The results obtained in the studied area between 2000 and 2010 showed the increase in cultivated land,built-up land and bare land by 432,758 ha,4,459 ha,and 7,551 ha,which are 46.87%,5.00% and 539.36%,respectively,while forests,wetland and water decreased by 1,145,823 ha,2,270 ha,and 1,918 ha,which are 12.64%,1.79% and 3.49%,respectively.In the latter period i.e.between 2010 and 2020,cultivated land,built-up land,and bare land increased by 428,632 ha,67,818 ha,and 2,788 ha,which are 31.61%,72.47% and 31.15%,respectively,while forests,and water decreased by 320,289 ha and 12,773 ha,which are 4.05% and 24.12%,respectively.The noted increase in cultivated land is simply a result of the need for food to feed the growing population.The increase in bare land is the result of cutting down trees for forestry and leaving the land barren.The built-up land increased rapidly is directly linked to population increase and urban growth.The impacts of intense urbanization and associated urban land-use change along coastlines is vast and unprecedented.The decline of forest cover was mainly due to forest exploitation for resources such as fuel wood,charcoal,timber,and herbs which are sold in urban areas to generate income.Additionally,forest is also cleared frequently for agriculture and settlement in order to sustain increasing population demands.The consequences are continuous habitat loss and degradation,and the space remaining for the endemic species is shrinking in coastal Tanzania.Likewise,in predicting future trend,the CA-Markov model using Land Change Modeller in the Terr Set was used to simulate land cover pattern for the year 2030.The trend of LULCC simulated by the CA-Markov model reveals that the main land-use of cultivated land,forest and built-up land conform with the existed land-use change observed in the previous year.The results showed that the area covered by the cultivated land is expected to increase between 2020 and 2030 by 430,234 ha,i.e.,24.66%.While forest and grassland are expected to decrease by 294,890 ha and 143,837 ha,which are 3.88% and 3.06%,respectively.This was due to the huge demand of land,and hence caused extreme land use changes and conversion into cultivated land and built-up land.Moreover,the land occupied wetland,water and bare land has shown more or less similar area percentage in the year 2020 and in 2030.This might be due to the increase on the level of awareness by the society on the importance of natural resources for the coastal areas.Msimbazi basin comprising rivers and wetlands is the largest catchment in Dar es Salaam having an area coverage of approximately 162 km2 equivalent to 11% of the total region.The basin has been selected to understand the influence of population growth on the land use and cover changes.The results revealed that the dominant area is built‐up land that occupied 39.3% of the total in 1990 and gradually increased to 42.6% in 2000,54.1% in 2010 and 65.7% in 2019.Moreover,forest and agriculture that in 1990 had been the second and third largest in size,respectively,had been decreasing rapidly throughout the entire period.The proportion of forest area decreased from 26.9% in 1990 to 11.9% in 2019,and the agricultural land decreased from 15.2% in 1990 to 3.1% in 2019.Census data has shown that Msimbazi had a total population of 1.1 million in the year 1988,and this proportion was projected to rise to approximately 3.7 million in 2019.More importantly,the unprecedented population growth associated with informal settlements and inadequate planning result in urbanization with poor infrastructure development.The change in this area is thus obviously driven by rapid population growth and poor planned fast urbanization.In summary,this study provides a solid data foundation and scientific support for the Tanzanian government to plan and utilize coastal land.It is manifested in the following three aspects.1.Despite the continuous population growth and dramatic land use and cover changes in the Tanzania coast,there are few national studies in the entire Tanzania coast.This study quantifies the status,pattern and their trends in the Tanzania’s coastal regions from 2000 to 2020,and provides an analysis of the drivers of climate change and anthropogenic activities.The data and analysis provided by this study are critical to government planners,policy makers and other environmental stakeholders,and will provide critical assistance in managing and optimizing the use of land resources to reduce poverty and achieve sustainable development.2.The results of a study of land use and cover change processes in the Msimbazi Basin in the central coastal city of Dar es Salaam show that,from 1990 to 2019,the proportion of built-up land,agricultural land and forest area in the basin has remained unchanged,which is at about 80% of the basin.However,agricultural land and forest land decreased from 42.1% in 1990 to 35.4%,24.1%,and 15.0% in 2000,2010,and 2019,respectively,corresponding to the increase in construction land,proving the rapid population growth.Driven by the sharp increase in land demand for build-up land,the natural ecosystem in the area has been fatally damaged.In view of this,in November 2020,the Tanzanian government proposed a project to redesign the Msimbazi Basin as an urban park to mitigate flood hazards and protect residents and infrastructure.3.The findings of this study provide an alarm for developing countries,similar to Tanzania,that are highly dependent on agricultural economies.Most people in Tanzania are engaged in agricultural activities,and while the agriculture supports their livelihoods and boosts the national economy,overreliance on this sector is bound to lead to extreme changes in land use and land cover.Therefore,the national economic structure needs to be adjusted to ensure sustainable economic and social development. |
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