Quantitative Multi-Year Assessment of Flood Impact on Land Use and Land Cover in Sylhet Region, Bangladesh: Insights from Sentinel Imageries

Abstract. The terms ‘land use’ and ‘land cover’ typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cover tracts. We believe this is misleading, and feel we need to reiterate the well-established symbiosis of land uses as amalgams of land covers; in other words land covers are subsets of land use. Our paper addresses this spatially complex, and frequently ambiguous relationship, and posits that bivariate cartographic techniques are an ideal vehicle for representing both land use and land cover simultaneously. In more specific terms, we explore the use of nested symbology as ways to represent graphically land use and land cover, where land cover are circles nested with land use squares. We also investigate bivariate legends for representing statistical covariance as a means for visualizing the combinations of land use and cover. Lastly, we apply Sankey flow diagrams to further illustrate the complex, multifaceted relationships between land use and land cover. Our work is demonstrated on data representing land use and cover data for the US state of Florida.

The study aimed to assess the changes that have occurred in land use and land cover within the Maasai Mara landscape using remote sensed data from 1997 to 2017; examine the elephant distribution in relation to land use and land cover changes within the Mara landscape and to determine changes in elephant home ranges in relation to Land use and cover changes in the Mara landscape. In examining the land use and land cover changes on the elephant ranges and distribution, an integrated methodological approach was employed in which the changes that have taken place within the study area over a period of 20 years was determined by analysis involving a 10-year changes in land use and land cover using three epochs from 1997, 2007 and 2017 to generate six land use classes. The Maasai Mara Landscape (MML) supports one of the richest wildlife populations remaining on earth but over the last century, has experienced transformation notably through conversion of former rangelands into croplands. Elephants have both temporal and spatial requirements, which if not provided, render them vulnerable to the land-use practices. The study assessed land use and vegetation cover changes that have occurred and their effects on the elephant movements and distribution within the MML using an integrated methodological approach. The analysis revealed changes in land use and land cover classes over a period of 20 years for the three epochs, from 1997, 2007 and 2017. Elephant’s distribution has been restricted to areas of high vegetation densities within specific habitats hence accelerating the rate of habitat destruction and degradation due to their high densities. These changes have drastically reduced forage for elephants necessitating them to travel longer distances out of their home range in search for food. Human beings have caused land use and cover changes which have detrimental impacts on the ecosystem and ecosystem services. The Maasai Mara landscape supports one of the richest wildlife populations remaining on earth but over the last century, it has experienced land transformation notably through conversion of former rangelands used mainly for tourism and production of grains such as wheat. Land outside the national parks and the reserve is important to the future of elephant existence in Kenya. Little is known about how human occupation on these landscapes negatively affects elephants (Loxodonta africana) habitats, movement and ranges. This has been confirmed by the current continuous demarcation/fencing of land in most areas in Narok County. Elephants like other landscape species, have both temporal and spatial requirements, which if not provided, will render them vulnerable to the land use practices of people. The study aimed to assess the changes that have occurred in land use and land cover within the Maasai Mara landscape using remote sensed data from 1997 to 2017; examine the elephant distribution in relation to land use and land cover changes within the Mara landscape and to determine changes in elephant home ranges in relation to Land use and cover changes in the Mara landscape. The paper describes the different changes that have taken place within the MML and how these changes have affected elephant populations, their trend and distribution within the MML. In examining the land use and land cover changes on the elephant ranges and distribution, an integrated methodological approach was employed in which the changes that have taken place within the study area over a period of 20 years was determined by analysis involving a 10-year changes in land use and land cover using three epochs from 1997, 2007 and 2017 to generate six land use classes. The study found out that there were significant changes of various classes across the years. Forest, water and open shrubs coverages decreased from 1997 to 2017. Classification noted a serious problem within the study area of continuous increase of bare ground coverage across the study years. Elephant populations have been increasing within the area .at an annual rate of 2.69%. The animals are distributed all over the landscape. Distribution of elephants has been restricted to high densities within a specific habitat hence accelerating rate of habitat destruction and degradation due to their high densities within a specific habitat. These changes have reduced drastically foliage for elephants thus necessitating them to travel longer distances in search and as a result increases elephant home ranges.

In recent years, land use and land cover plays a pivotal role in global environmental change. Under these circumstances,the need of a new dimension for detecting land use and cover is getting more imperative for conservation and effectivemanagement of land use and cover types. Importantly, the use of information technology to support decision making indetecting land use and cover is essential and recent. One of the technologies used is Airborne Remote Sensing. Theobjective of this study is to identify, quantify, classify and map land use and land cover mapping in Setiu, Terengganuusing UPM-APSB’s AISA airborne hyperspectral remote sensing. Detection of land use and cover was performed usingairborne hyperspectral imaging data taken on 20 April 2006 with the support of existing land use and cover maps. Thesize of the study area is 100 ha. The image was displayed in ENVI 4.0 Software using bands 202217 (RGB)combination. The data were then enhanced and classified for different land use and cover classes. From the dataanalysis, the image can be classified into eight classes. The classes are 2-3 years old oil palm plantation, 4-5 years oldoil palm plantation, young (3-4 years old) rubber plantation, matured (15-17 years old) rubber plantation, vegetationcrops, open area, road and river. The land use and land cover classes area distribution of the plots under study in Setiu,Terengganu were 4.18 ha, 8.58 ha, 6.26 ha, 70.43 ha, 2.98 ha, 2.31 ha, 2.78 ha, and 2.48 ha. Overall, the classificationaccuracy of interpretation of the airborne imagery for land use and cover in Setiu, Terengganu is 89.51 and kappacoefficient is 0.86. This study shows that, airborne hyperspectral remote sensing technique is capable in identifying,quantifying, classifying and mapping land use and cover in Setiu, Terengganu, hence a good decision support tool inland use and cover planning and management.

Land cover and use are critical for climate change, water quality and use, biodiversity and soil conservation as well as important drivers of rural economic activity and the evolution of rural communities. The Land Use in Rural New Zealand (LURNZ) model is a simulation model that predicts overall shifts in land use at a national scale and then allocates those changes spatially. We create a new dataset that allows us to consider fine scale land cover and use on private rural land and land characteristics associated with those land covers and uses. Second, we produce some summary statistics on the land cover transitions that were observed from 1996 to 2002. We find some evidence that supports our simple model of the relationship between land use changes and observable land quality, and the use of Land Use Capability and slope in rules to simulate the location of changes in land use and cover and also identify some directions for future work.

Land cover and use are critical for climate change, water quality and use, biodiversity and soil conservation as well as important drivers of rural economic activity and the evolution of rural communities. The Land Use in Rural New Zealand (LURNZ) model is a simulation model that predicts overall shifts in land use at a national scale and then allocates those changes spatially. We create a new dataset that allows us to consider fine scale land cover and use on private rural land and land characteristics associated with those land covers and uses. Second, we produce some summary statistics on the land cover transitions that were observed from 1996 to 2002. We find some evidence that supports our simple model of the relationship between land use changes and observable land quality, and the use of Land Use Capability and slope in rules to simulate the location of changes in land use and cover and also identify some directions for future work.

The Tibetan Plateau (TP) is an important ecological security barrier for China and, indeed, for all Asia. Land use and land cover changes in the plateau not only affect the ecological environment and regional development of the plateau itself but also affect the stability and economic development of ecosystems in eastern China and other parts of Asia. This paper is based on an examination of the achievements of land use and cover change in the TP and a reanalysis of data including that of Climate Change Initiative Land Cover from 1992 to 2015; land use data provided by the Resource and Environmental Science Data Center of the Chinese Academy of Sciences for 1995, 2000, 2010 and 2015; and statistical data from Qinghai and Tibet. The paper analyzes the overall characteristics of land use and land cover changes in the TP and the spatial and temporal processes and their driving forces of land use and land cover change in typical regions and land types. This research is important not only for land change science and global change research but also for the promotion of the plateau and its adjacent areas. In recent decades, research has shown that the land use and land cover structure of the TP is stable, and the proportion of first-level land use type change was less than 7% from 1992 to 2015. Most of these changes are single time changes, with multiple land change occurring only in 1.85% of the total change area. The quality of land cover has been improved in areas where no land type change occurred. The Normalized Difference Vegetation Index (NDVI) showed an increasing trend in 24.45% of the area and a decreasing trend in only 1.31% of the area. The area of cultivated land, forest, grassland, wetland, and construction land on the plateau has increased, whereas bare land, glacier, and snow cover area has decreased. In most parts of the TP, the quality of alpine grassland has improved; however, in some areas, it has degraded at a local scale. Most of the woodland has recovered well after phased changes. Prior to 1980, there was a rapid increase in cultivated land area, but this has since become stable with only minor increases. However, the utilization intensity of cultivated land has increased significantly in recent years. Construction land has expanded significantly, and the recent growth rate has accelerated since 2010. Both the increasing speed of change and the construction land area in Qinghai Province are higher than in Tibet. There has been a general trend of a slight decrease in bare land change. In densely populated areas in the Yellow River-Huangshui River Valley and the One-River-Two-Tributaries area, land types that are closely related to human utilization such as construction land, cultivated land, and artificial woodland have undergone obvious changes. In pastoral areas, such as the Northern Tibetan Plateau and the Source Regions of The Three Rivers, overgrazing and ecological construction have significantly affected land cover. In the Qomolangma National Nature Preserve, land use types are diverse; changes are complex; and land cover is more sensitive to both climate change and human activity. There are limitations to the study of land change in the plateau, such as the difficulty of meeting the needs of ecological construction with existing data and the lack of in-depth understanding of the process of land use change and its environmental effects. Field monitoring and remote sensing techniques must be strengthened in order to clarify the process of land use intensity change and its impact on the ecological environment of the TP. These improvements will better serve the construction of an ecological security barrier and the sustainable development of the region.

Introduction: Landscape changes can be monitored using geotechnologies through land use and land cover management over time, which helps identify and understand transformations in the landscape and supports decision-making processes. This study aims to analyze land use and cover change in the Portal do Sertão Identity Territory, Bahia, and to relate the possible causes that have currently induced such changes. This territory, located in the Caatinga biome, has its economic activities mainly concentrated in the primary and tertiary sectors. Remote Sensing (RS) and Geographic Information Systems (GIS) were employed to monitor changes in land use and cover in this territory from 1985 to 2022, using images from the MapBiomas Collection 8.0. During the study period, there was a reduction in the area used for agriculture and livestock and a significant increase in urbanization, with an urban area growth of more than 380%. Additionally, water bodies also expanded, mainly due to the construction of the Pedra do Cavalo Hydroelectric Plant in 1985, which resulted in a larger flooded area. Forest formations, although fluctuating over the years, were negatively impacted by agricultural expansion and urbanization. Therefore, the use of geotechnologies such as RS and GIS proves to be an effective tool for environmental monitoring, enabling the identification and management of land use changes and contributing to the mitigation of environmental impacts. Objective: The aim of this study is to investigate land use and land cover changes in the Portal do Sertão Identity Territory, in order to identify the possible causes currently driving these transformations. . Theoretical Framework: Remote Sensing (RS) is a science that maps Earth’s surface targets using sensors without direct contact. It is an essential tool for understanding and monitoring land use and land cover changes, providing critical information for decision-making from multiple perspectives. Its integration with Geographic Information Systems (GIS) enhances the spatiotemporal analysis of processes such as environmental and territorial degradation. The concept of "Identity Territory," developed by SEPLAN-BA, considers sociocultural, economic, and geographic factors for territorial organization. Institutionalized by state decrees, it divides Bahia into 27 territories to promote regional public policies. The articulation of RS, GIS, and the Identity Territory framework offers an effective approach to understanding and managing land use changes in the Portal do Sertão. Method: This study analyzed land use and land cover changes in the Portal do Sertão Identity Territory, composed of 27 municipalities in Bahia, aiming to understand the possible driving forces behind these changes. Satellite images from the MapBiomas Brazil Collection 8.0 were used for the years 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, and 2022. A GIS environment was used to reclassify the images into four classes based on the MapBiomas classification: Forest Formation, Agriculture, Urban Area, and Water Bodies. The total area per class was quantified for each year, and land use transition maps were generated for spatial analysis. Results and Discussion: The analysis revealed that between 1985 and 2022, the Portal do Sertão Identity Territory experienced significant transformations in land use and cover. There was a notable reduction in agricultural and livestock areas and a sharp increase in urban development, particularly in Feira de Santana and neighboring municipalities, driven by industrialization, public policies, and real estate expansion. Forest cover fluctuated, while water bodies increased following the construction of the Pedra do Cavalo Hydroelectric Plant in 1985. These changes reflect processes of urbanization, rural exodus, and territorial reconfiguration influenced by economic, social, and infrastructural factors. Research Implications: This research provides essential technical and spatial support for territorial planning in the region, assisting local governments and institutions in making more informed decisions based on historical land use patterns. The findings highlight the importance of integrated public policies focused on territorial planning, environmental preservation, and housing, especially in light of rapid population growth. Originality/Value: This study contributes to the literature by analyzing the drivers of land use change using open-access data from MapBiomas. Its significance lies in the integration of Remote Sensing and GIS to investigate land use trends in the Portal do Sertão over the past decades, providing strategic insights to support public policy development and more effective territorial planning.

<i>Abstract.</i>—Surrounding land use and cover can have profound effects on the physical, chemical, and biological properties of stream ecosystems. For this reason, changes in land use and cover throughout catchments often have strong effects on stream ecosystems that are particularly interesting to researchers. Additionally, natural physical and climatic, or physiographic, characteristics are important for determining natural land cover and constraining human land use and are also strongly related to stream habitat and biota. Because the physiographic template differs among catchments and is an important mediator of catchment processes, it is important to account for natural physiographic differences among catchments to understand the relationship between land use/cover and stream biota. In this paper, we develop and assess the usefulness of a regional framework, land use/cover distinguished physiographic regions (LDPRs), which is designed for understanding relationships between land use/cover and stream biota while accounting for the physiographic template. We classified hydrologic units into LDPRs based on physiographic predictors of land use and cover for the eastern and western United States through the use of multivariate regression tree analysis. Next, we used case study data to assess the usefulness of LDPRs by determining if the relationships between fish assemblage function and land use/cover varied among classes using hierarchical logistic regression models. Eight physiographic characteristics determined land cover patterns for both the eastern and western United States and were used to classify hydrologic units into LDPR classes. Five commonly used biotic metrics describing trophic, reproductive, and taxonomic groupings of fish species responded in varying ways to agriculture and urban land use across LDPRs in the upper Mississippi River basin. Our findings suggest that physiographic differences among hydrologic units result in different pathways by which land use and cover affects stream fish assemblages and that LDPRs are useful for stratifying hydrologic units to investigate those different processes. Unlike other commonly used regional frameworks, the rationale and methods used to develop LDPRs properly account for the often-confounded relationship between physiography and land use/cover when relating land cover to stream biota. Therefore, we recommend the use and refinement of LDPRs or similarly developed regional frameworks so that the varying processes by which human land use results in stream degradation can be better understood.

Abstract. An attempt has been made to explore, evaluate and identify the sensitive parameter(s) of Cellular Automata Markov chain modeling to monitor and predict the future land use land cover pattern scenario in a part of Brahmaputra River Basin, India. For this purpose, land use land cover maps derived from satellite images of Landsat MSS image of 1987 and Landsat TM image of 1997 were used to predict future land use land cover of 2007 using Cellular Automata Markov model. Sensitivity analysis has been carried out to identify the land use land cover parameter(s), which have the highest, lowest or intermediate influence on predicted results. The validity of the Cellular Automata Markov process for projecting future land use and cover changes in the study area calculates various Kappa Indices of Agreement (Kstandard) which indicate how well the comparison map agrees and disagrees with the reference map (land use land cover map derived from IRS-P6 LISS III image of 2007). The results shows that the land with or without scrub appeared to be most sensitive parameter as it has highest influences on predicted results of land use land cover of 2007. The second most sensitive parameter was lakes / reservoirs / ponds to predict land use land cover of 2007, followed by river, agricultural crop land, plantation, open land, marshy / swampy, sandy area, aquatic vegetation, built up land, dense forest, degraded forest, waterlogged area and agricultural fallow land. The least sensitive parameter is agricultural fallow land, which has minimum influence on predicted results of land use land cover of 2007. The validation of CA Markov land use land cover prediction results shows Kstandard is 0.7928.

Current estimates of land cover and land use are important aspects in understanding the flux of material and energy from terrestrial ecosystems into hydrological and atmospheric components of the earth system. These land use characteristics define the various dimensions of human impacts on ecosystem processes and resource use. The recent availability of global remote sensing data and agricultural census data from various regions of the world, including portions of Asia such as China and Mongolia, now makes it feasible to evaluate differences in the physical environment and land use patterns affecting land cover and land use changes. In addition, recent research involving transects studies along gradients of climate, soil, and land use intensity has been carried out during the past decade to allow more careful regional comparisons. Using the analysis of the Mongolian-North East China Transect (NECT), we can estimate the effect of land cover differences on ecosystem dynamics. The 30 m-Thematic Mapper data provides a way to identify fine scale features of the regional landscape patterns which are not captured by the 1-km AVHRR data. The focus of this paper is to evaluate the scale of land use and cover changes in the Asian region and the biogeochemical implications of these changes. The estimates of land cover and land use can vary depending on the spatial scale of the features represented across the land surface. Both physical and social factors influence the spatial extent these features represent. Therefore, the scale of land use intensification can affect the accuracy of land use area estimations. In particular, those regions of the world where land use practices are implemented via small individual holdings may be underestimated when using coarse scale remote sensing data such as AVHRR, where as the Thematic Mapper satellite data at 30 to 50 m resolution can provide a better estimate of land cover and land use area. The accuracy of the extrapolated fluxes of ecosystem dynamics and biogeochemical cycles are directly proportional to the accuracy associated with the land estimates. We will evaluate the land cover estimates in this region of Asia using these data sources. This region encompasses a broad set of precipitation and temperature regimes and includes characteristics of regional land cover and land use related to grazing systems and grain cultivation.

The Victorian Land Use Information System (VLUIS) dataset has been created by the Spatial Information Sciences Group of the Agriculture Research Division in the Department of Economic Development, Jobs, Transport, and Resources. The method used to create VLUIS is significantly different to traditional methods used to create land use information and has been designed to create regular and consistent data over time. It covers the entire landmass of Victoria and separately describes the land tenure, land use and land cover for each cadastral parcel across the state, biennially for land tenure and use and annually for land cover; for each year from 2006 to 2015. The data can be provided as a spatial dataset or in tabular format. To use the VLUIS data correctly it is important to understand the difference between the three components of VLUIS. The Guidelines for land use mapping in Australia: principles, procedures and definitions, Edition 3 published in 2006 by the Commonwealth of Australia, defines them as follows: Land tenure is the ownership and leasehold interests in land (VLUIS only reports ownership). Land use means the purpose to which the land cover is committed or the property type. Land cover refers to the physical surface of the earth, including various combinations of vegetation types, soils, exposed rocks and water bodies as well as anthropogenic elements, such as agriculture and built environments. The Victorian Land Use Information System (VLUIS) is an ongoing project designed to maintain and manage the Victorian land use mapping dataset. The methodology is still being refined and as such the dataset is subject to improvements and the release of later versions. It is important you speak to the custodian to be advised of the technical details of the dataset and its utility for your desired use. Land Cover 2014: Land cover classification accuracy statements for the entire state may not be representative of land cover classification accuracy levels in the north-west of the state due to a paucity of ground truth data in this area (particularly west of Swan Hill and north of Sea Lake). Users are advised to use this land cover information with discretion and contact the data custodians for further information if required. Land cover classification accuracy varies between classes and the overall classification accuracy may be misleading in terms of the accuracy of an individual class. Users are asked to contact the data custodians for detailed class accuracy information if required for their purposes. A metadata statement, for the VLUIS 2014/15 product, and ESRI symbology files for the data can be freely downloaded from the VLUIS project page on the Victorian Resources Online website: http://vro.agriculture.vic.gov.au/dpi/vro/vrosite.nsf/pages/vluis

Abstract. In this study, attempts has been made to find out cellular automata (CA) contiguity filters impacts on Land use land cover change predictions results. Cellular Automata (CA) Markov chain model used to monitor and predict the future land use land cover pattern scenario in a part of Brahmaputra River Basin, India, using land use land cover map derived from multi-temporal satellite images. Land use land cover maps derived from satellite images of Landsat MSS image of 1987 and Landsat TM image of 1997 were used to predict future land use land cover of 2007 using Cellular Automata Markov model. The validity of the Cellular Automata Markov process for projecting future land use and cover changes calculates using various Kappa Indices of Agreement (Kstandard) predicted (results) maps with the reference map (land use land cover map derived from IRS-P6 LISS III image of 2007). The validation shows Kstandard is 0.7928. 3x3, 5x5 and 7x7 CA contiguity filters are evaluated to predict LULC in 2007 using 1987 and 1997 LULC maps. Regression analysis have been carried out for both predicted quantity as well as prediction location to established the cellular automata (CA) contiguity filters impacts on predictions results. Correlation established that predicted LULC of 2007 and LULC derived from LISS III Image of 2007 are strongly correlated and they are slightly different to each-other but the quantitative prediction results are same for when 3x3, 5x5 and 7x7 CA contiguity filters are evaluated to predict land use land cover. When we look at the quantity of predicted land use land cover of 2007 area statistics are derived by using 3x3, 5x5 and 7x7 CA contiguity filters, the predicted area statistics are the same. Other hands, the spatial difference between predicted LULC of 2007 and LULC derived from LISS III images of 2007 is evaluated and they are found to be slightly different. Correlation coefficient (r) between predicted LULC classes and LULC derived from LISS III image of 2007 using 3x3, 5x5, 7x7 are 0.7906, 0.7929, 0.7927, respectively. Therefore, the correlation coefficient (r) for 5x5 contiguity filters is highest among 3x3, 5x5, and 7x7 filters and established/produced most geographically / spatially distributed effective results, although the differences between them are very small.

As one of the last agricultural frontiers of the humid tropics, Amazonia is the largest area of the world currently undergoing frontier settlement. Although the earliest intrusions of foreign populations into Amazonia date from pre-Hispanic times, the large-scale entrance of peasant colonists into the vast region is a recent phenomenon. Much of this movement represents the spontaneous migration of peoples, but governments in the region have also become increasingly interested in opening up and integrating Amazonia to national and international economies. These actions are frequently seen as potential solutions to a number of national problems, including the need to increase agricultural production, correct spatial imbalances in the distribution of population, exploit frontier lands for reasons of national security, and defuse potentially serious political problems resulting from the existing agrarian structure, landlessness, and unemployment. The upper basin of the Amazon in Ecuador, bordering on the eastern slopes of the Andes, is one such area of frontier settlement. Recent decades have witnessed the rapid conversion of these Amazonian forests to agricultural uses through a series of schemes bearing such labels as land development and colonization. Most forest intervention in the region has come at the hands of colonist farmers attempting to establish land claims along transport routes originally constructed to aid in petroleum exploration and exploitation. These are farmers who formerly have made a living in long-established farmlands and who, for various reasons (population pressures, pervasive poverty, maldistribution of farmland, lack of inputs for intensive cultivation, lack of nonagrarian livelihood opportunities, and generally inadequate rural development) have been increasingly squeezed out of their homelands. A marginal person by virtue of his low socioeconomic and political status, the farmer often perceives

Land use and cover changes trigger multi-factorial responses with tangible and intangible effects. Driving forces governing changes are scale-, place- and time-dependent; because of their complexity, a multi-scalar analysis is required to determine conjoint causation. Studies using multi-scalar approach in semiarid scrubland ecosystems are scanty. This paper investigates land use changes on the largest semiarid scrubland ecosystem of Mexico, the Baja California Peninsula, using a multi-scalar analysis approach. It further provides insight into the likely underlying causes for land use trends. Multi-temporal databases were compiled for 1978, 1990, 2000 and 2003 from various sources; population was projected for the same years. Land cover processes were validated through intensive fieldwork. Map overlapping with the aid of geographic information systems allowed computation of land cover transformation rates. New algorithms were developed to better understand land cover trends. Multi-variate analysis was also performed to provide a synthetic statistical overview. Results showed that land cover change occurred at different times, at variable scales, due to distinct drivers. As a consequence, the current regional scenario has been shaped by distinguishable socio-economic changes. The semiarid scrubland ecosystems in the Baja California Peninsula experienced contrasting trends detectable only at site and local scales. Regionally, the replacement of original vegetation (scrubland) for other land cover category is following trends similar to those in the rest of Mexico and most semiarid ecosystems worldwide. These findings support the hypothesis that land use and cover changes must be analyzed at different times and scales to deeply understand underlying forces.

Forest and wood land ecosystems in Tanzania occupy more than 45% of the land area, more than two thirds of which made up of the Miombo woodland. The main form of land use in the Miombo region has long been shifting and small-scale sedentary cultivation. The lack of infrastructure and prevalence of deadly diseases such as malaria and trypanosiomiasis have long limited extensive clearance for cultivation, livestock farming and settlements. However, due to positives changes in the socio-economical, political and technological setup in miombo region, the types and intensity of land use are now changing. This paper discusses preliminary results from a study conducted with the aim of contributing to the understanding of dynamics of land cover and use changes in miombo woodlands of eastern Tanzania. The study area comprises four villages around the “Kitulangalo Forest Reserve”, 140 km west of Dar es Salaam on either side of the Morogoro-Dar es Salaam highway. Landsat MSS satellite images of July 1975, Landsat TM satellite images of July 2000 were used to assess land cover changes between 1975 and 2000. Participatory Rural Appraisal (PRA), questionnaire survey and checklists for key informants were the major methods used for collecting socio-economic data. The land cover/use class of woodland with scattered cultivation has recorded the highest percentage of change between July 1975 and July 2000. While all other classes have registered positive changes, only the closed woodland class has had negative change meaning that this class has been decreasing in favour of other land cover/use classes. Recent land cover and use changes are drastic in the study area. These changes have been triggered largely by varied factors including mainly increased population density and subsequent economic activities. Economic activities including charcoal business, shifting cultivation, opening up of improved highway and pastoralism in the study area have greatly contributed to deforestation and woodland degradation. In light of these findings, there is need for: (1) Adequate land use planning and survey of village lands so as to avoid exacerbation of land use conflict and environmental degradation in the study area. (2) Agrarian reforms to eliminate open access regimes to natural resources. (3) Enforcement of fiscal policies related to the extraction of natural resource products such as timber and charcoal so as to reduce pressure on woodlands. Keywords: land use – cover change – Kitulangalo – miombo woodlands