Academic literature on the topic 'Land settlement patterns – Nigeria'

Climate variation largely impacts migration in with the capacity to worsen conflict and security situations in parts of Africa, Nigeria in particularly, already facing security threats from the activities of sedentary and nomadic pastoral farmer’s interaction. Increasing variations in rainfall patterns significantly impact the migration patterns of vulnerable households and constitute a risk factor to their livelihoods. For effective adaptation plan and sustainable livelihood decision that has climate resilient future, there is need for better understanding of the conflict and security implications of climate variation. This paper, therefore, interrogates the nexus between climate variation and migration, as well as the impact of this nexus on conflicts and security of lives and properties in Nigeria. Using critical analysis and qualitative methodology, the study establishes that migration settlement policies that fail to define the rights and duties of settlers and those of indigenes of any particular community, create loopholes for the reification of identities and identity-induced crisis. The conclusion of the paper is that migration issues resulting from climate variation have not been adequately addressed to involve all stakeholders. There is the need to harvest environmental impact assessment data of climate variation to guide the provision of alternative options to climate-related emergencies across Nigeria.

Urban forests are an essential component of urban areas as they provide many environmental and social services that contribute to the quality of life in cities. Urban forests in most cities of Nigeria are gradually becoming bitty as a result of urbanization activities, thereby posing adverse effects. In this study, we assessed the changes in the urban forests cover under the influence of different human settlement (HS) extents across the urban area of Ibadan city using remotely sensed data. The pattern of change(s) in the urban forests cover over 20 years were examined by analysing and manipulating Landsat and Sentinel-2 datasets using Google Earth Engine, ArcGIS 10.1, and Erdas 2014 software. The extents of human settlement (for the year 2000, 2005, 2010, 2015, and 2020) were extracted (from Landsat datasets), analysed, and mapped to evaluate the status of the urban forests cover under different human settlement extents. The result reveals a substantial land cover changes within the urban area of Ibadan. The urban forest cover decreased from 24.14% to 7.99%. Also, there is a significant decrease in the urban forests cover as a result of a substantial increase in human settlement extent (102,806 to 122,572 pixels). The study provides an opportunity to map the status of urban forest cover and extents of HS in a developing city using remotely sensed data and applications of GIS tools.

The land use land cover change and its modeling approach has recently been considered by the scientific community to observe environmental changes. Remote Sensing and Geographical Information System (GIS) give major techniques which can be useful in the analysis at the town locale as well as the city levels. RS data from Thematic Mapper sensor of 1998, 2002, 2010, 2014, and 2018, Operational Land Imager of 2018 were used for the analysis. The study used a supervised classification technique for classification, and Cellular Automata Markovian (CA-Markov) Model analysis was used for future projection of 2038. The result shows that the projected the year 2038 with 0.9079 K-standard value of stimulation, the study further uses Maximum likelihood classifier (MLC) a supervised classification method to classify the images. The study reveals a continuous pattern of urban growth from 3.96 km2 in 2018 to 4.73 in 2038 in terms of settlement growth, dense vegetation has decreased from 11.73 in 2018 to 8.55 in 2038 also shrubland has decreased from 44.82 to 36.30, the last bare land has increased more than all the classes from 162.69 to 173.69. The findings of the present study are useful for planners and decision-makers in sustainable natural resource management.

Abstract Studies have shown that information on landscape transformation is an important benchmark data set because of its value as an environmental change indicator. Therefore, dynamism of landscape transformation over a 34-year period are analysed for a case study in Ibiono-Ibom, Akwa-Ibom State, Nigeria. The study adopted a mixed method consisting of remote sensing and GIS-based analysis, and semi-structured interviews covering 400 households while factors contributing to landscape structures and changes are studied. The results point out three main driving factors responsible for the landscape transformation in the study area: agricultural practices which lead to intensification of forest resources, riparian vegetation, vegetated wetlands and non-vegetated wetlands; urbanization which modifies the structure and morphology of the landscape, and finally, population growth directly related to massive infrastructural development which encroached on all other land spaces. GIS-based analysis of remotely-sensed data showed that built-up area had increased by 7535.2 ha between 1986 and 2020; shrub and arable land by 1343.9 ha and light forest decreased by 4998.3 ha. While bare-land reduced by 1522.1 ha; vegetated wetland reduced by 1092 ha; water body coverage reduced by 168 ha and non-vegetated wetland size also reduced by 2029.4 ha. Analysis of household survey results revealed that the perceptions of respondents validate the observed patterns during the remotely-sensed data analysis phase of the research, with 54 % (n=400) of respondents reporting a decline in agricultural land use, and 19.3 % (n=400) observing a decline in forest areas in the study area. Furthermore, agricultural intensification, urban development, timber exploitation, firewood collection and increase in settlements were identified as the proximate drivers of these observed landscape transformation dynamics in the study area. The study concluded that the variation in landscape transformation of the study area are clear indication of the extent of biodiversity loss and ecosystem degradation in the study area.

In its determination to provide food and jobs for Nigerians, and appeal to educated young men to set the pattern for farming, many state governments have re-introduced Farm Settlement Scheme (FSS)/Graduate Employment Scheme once abandoned. One major challenge leading to programme failure in Nigeria is the inability to know the influence of the factors on the participation and constraints of such programmes. This study analysed the determinants of crop farmers? participation in FSS in Lagos State with the aim of drawing some lessons for future rural development programmes. One hundred and thirty (130) farmers were sampled through two-stage sampling procedures. Data were collected with the aid of a questionnaire and were analysed using both descriptive and inferential statistics such as the logit regression model. Results show that about 67% of the respondents were male and 72% were married. The major constraining factors to participation in FSS were administrative bottlenecks, inadequate capital, and government interference. The logit regression showed that educational level, farming experience, extension contacts and security of land under FSS were the significant variables (P<0.5) that directly influenced the probability of participation of the farmers in FSS in Lagos State, Nigeria. Farming experience is very crucial for the survival of FSS. Therefore, it is recommended that the determinants of participation and constraints to the participation of the farmers be assessed in any rural development programme to know the necessary action against failure. The effort at increasing extension contacts about FSS will further encourage farmers to participate in FSS.

Background: In Nigeria, medicinal plants are now being threatened due to increased urbanization, land clearing for farming and over-harvesting from their natural habitats. As such, if such trends continue, some of these medicinal plants might increasingly become not available and in the extreme circumstance be faced with extinction. Methods: An epidemiological descriptive field survey that employed a carefully-structured, closed-ended, interviewer-administered, paper-based questionnaire designed to capture information on the use of medicinal plants as antimalarial and for management of other associated illnesses. We also employed Global Positioning System (Garmin etrex 75) to captures the geo-coordinates of previously identified medicinal plants across the footpath transect at 20 m intervals. A total of twenty-one (21) medicinal plant species were surveyed across five communities with varying numbers per locations. Results: Out of the nine (9) identified traditional healers across the communities, all claimed to have used at least one or combinations of these plants for treatment of malaria. An image classification performed through land cover land use map of the study area revealed six classes: swamp /water bodies, river valley, savanna woodland, degraded woodland, grassland and settlements cluster. Most threatened species such as Aristolochia ringes, Mucuna prurins, Azadirachta indica, Kigelia africana, Citrus limon, Ludwigia suffruticosa, Parkia biglobosa, and Picralima nitida are those found in Malete KWASU campus axis in the degraded woodland and settlement cluster classes. This is due to the high level of forest destruction in the area as a result of growing student population and massive constructions of students’ hostel. We reported that about 60% of original plant cover has been lost between 2005 and 2015. It was observed that availability of surface water bodies played a crucial role in influencing the distribution of identified medicinal plants. The nearest neighbour analysis gave a nearest neighbour index of 0.695 at p=0.000003 and z-score of -4.70314. This shows that the observed random distribution of medicinal plants in the study area was statistically significant. It has been observed that random patterns are usually associated with natural occurrences. The random spatial pattern confirms that these plants have not yet been affected by anthropogenic activities and hence need to be conserved there in the wild. Conclusion: There is need to leverage on conservation of medicinal plants for treating malaria in their natural habitats. Also, the need to ensure sustainable harvesting and other socio-ecological process to ensure these are not threatened to the extreme case of extinction in these communities. In the view of the above, we recommend that KWASU-Malete campus axis be monitored, proper urban planning initiatives implemented and ensure cultivation and preservation of these plants are incorporated into the greening efforts of the Kwara state government in this area.

Globally there are concerns about outdoor air pollution and its effects on the environment and human health. Researchers are concerned with the negative effects of and best mitigation strategies for air pollution. Climate change and human health are a common phenomenon associated with air pollution, as carbon dioxide (CO2) is absorbed and emitted naturally as part of the carbon cycle. This study was aimed at assessing the emission level of CO2 in Kuje Area Council in the Federal Capital Territory, Nigeria and its effect on the environment and human health. Fifty specific residential and commercial locations were considered, and over 1200 observations of CO2 field data were collected and analysed during two seasons–dry and wet. The land-use settlement pattern was taken into consideration. The data were collected weekly at different time bands (2-, 4-, 6-, and 8-hour time intervals) using the AMPROBE CO2-100, CO2 meter gas detection instrument with self-calibration capability of ±30 parts per million (ppm), ±5% reading (0–5000) accuracy. A Garmin CX60 global positioning system was used to obtain the point locations Universal Transvers Mercator coordinates. The results showed higher mean CO2 emission values of >541 ppm and <713 ppm during the dry and wet seasons, respectively. It was also observed that these values were contrary to and exceeded the American Society of Heating, Refrigerating and Air-Conditioning Engineers and Occupational Safety and Health Administration normal outdoor level standards of 350–450 ppm. These higher CO2 values were found in the residential and commercial districts, and if not monitored and controlled they will have adverse effects on human health and climate change effects. Quick interventions would be to plant trees to sequestrate the CO2 and to regulate the transportation system within the area due to continuous carbon emission.

Rapid urbanization rates impact significantly on the nature of Land Cover patterns of the environment, which has been evident in the depletion of vegetal reserves and in general modifying the human climatic systems (Henderson, et al., 2017; Kumar, Masago, Mishra, & Fukushi, 2018; Luo and Lau, 2017). This study explores remote sensing classification technique and other auxiliary data to determine LULCC for a period of 50 years (1967-2016). The LULCC types identified were quantitatively evaluated using the change detection approach from results of maximum likelihood classification algorithm in GIS. Accuracy assessment results were evaluated and found to be between 56 to 98 percent of the LULC classification. The change detection analysis revealed change in the LULC types in Minna from 1976 to 2016. Built-up area increases from 74.82ha in 1976 to 116.58ha in 2016. Farmlands increased from 2.23 ha to 46.45ha and bared surface increases from 120.00ha to 161.31ha between 1976 to 2016 resulting to decline in vegetation, water body, and wetlands. The Decade of rapid urbanization was found to coincide with the period of increased Public Private Partnership Agreement (PPPA). Increase in farmlands was due to the adoption of urban agriculture which has influence on food security and the environmental sustainability. The observed increase in built up areas, farmlands and bare surfaces has substantially led to reduction in vegetation and water bodies. The oscillatory nature of water bodies LULCC which was not particularly consistent with the rates of urbanization also suggests that beyond the urbanization process, other factors may influence the LULCC of water bodies in urban settlements. Keywords: Minna, Niger State, Remote Sensing, Land Surface Characteristics References Akinrinmade, A., Ibrahim, K., & Abdurrahman, A. (2012). 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Monitoring and prediction of land-use and land-cover (LULC) change Dhaka megacity (pp. 75-97): Springer. Coutts, A. M., Harris, R. J., Phan, T., Livesley, S. J., Williams, N. S., & Tapper, N. J. (2016). Thermal infrared remote sensing of urban heat: Hotspots, vegetation, and an assessment of techniques for use in urban planning. Remote Sensing of Environment, 186, pp. 637-651. Debnath, A., Debnath, J., Ahmed, I., & Pan, N. D. (2017). Change detection in Land use/cover of a hilly area by Remote Sensing and GIS technique: A study on Tropical forest hill range, Baramura, Tripura, Northeast India. International journal of geomatics and geosciences, 7(3), pp. 293-309. Desheng, L., & Xia, F. (2010). Assessing object-based classification: advantages and limitations. Remote Sensing Letters, 1(4), pp. 187-194. Dewan, A. M., & Yamaguchi, Y. (2009). Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization. Applied Geography, 29(3), pp. 390-401. Dronova, I., Gong, P., Wang, L., & Zhong, L. (2015). Mapping dynamic cover types in a large seasonally flooded wetland using extended principal component analysis and object-based classification. Remote Sensing of Environment, 158, pp. 193-206. Duro, D. C., Franklin, S. E., & Dubé, M. G. (2012). A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery. Remote Sensing of Environment, 118, pp. 259-272. Elmhagen, B., Destouni, G., Angerbjörn, A., Borgström, S., Boyd, E., Cousins, S., . . . Hambäck, P. (2015). Interacting effects of change in climate, human population, land use, and water use on biodiversity and ecosystem services. Ecology and Society, 20(1) Farhani, S., & Ozturk, I. (2015). Causal relationship between CO 2 emissions, real GDP, energy consumption, financial development, trade openness, and urbanization in Tunisia. Environmental Science and Pollution Research, 22(20), pp. 15663-15676. Feng, L., Chen, B., Hayat, T., Alsaedi, A., & Ahmad, B. (2017). The driving force of water footprint under the rapid urbanization process: a structural decomposition analysis for Zhangye city in China. Journal of Cleaner Production, 163, pp. S322-S328. Fensham, R., & Fairfax, R. (2002). Aerial photography for assessing vegetation change: a review of applications and the relevance of findings for Australian vegetation history. Australian Journal of Botany, 50(4), pp. 415-429. Ferreira, N., Lage, M., Doraiswamy, H., Vo, H., Wilson, L., Werner, H., . . . Silva, C. (2015). Urbane: A 3d framework to support data driven decision making in urban development. Visual Analytics Science and Technology (VAST), 2015 IEEE Conference on. Garschagen, M., & Romero-Lankao, P. (2015). Exploring the relationships between urbanization trends and climate change vulnerability. Climatic Change, 133(1), pp. 37-52. Gokturk, S. B., Sumengen, B., Vu, D., Dalal, N., Yang, D., Lin, X., . . . Torresani, L. (2015). System and method for search portions of objects in images and features thereof: Google Patents. Government, N. S. (2007). Niger state (The Power State). Retrieved from http://nigerstate.blogspot.com.ng/ Green, K., Kempka, D., & Lackey, L. (1994). Using remote sensing to detect and monitor land-cover and land-use change. Photogrammetric engineering and remote sensing, 60(3), pp. 331-337. Gu, W., Lv, Z., & Hao, M. (2017). Change detection method for remote sensing images based on an improved Markov random field. Multimedia Tools and Applications, 76(17), pp. 17719-17734. Guo, Y., & Shen, Y. (2015). Quantifying water and energy budgets and the impacts of climatic and human factors in the Haihe River Basin, China: 2. Trends and implications to water resources. Journal of Hydrology, 527, pp. 251-261. Hadi, F., Thapa, R. B., Helmi, M., Hazarika, M. K., Madawalagama, S., Deshapriya, L. N., & Center, G. (2016). Urban growth and land use/land cover modeling in Semarang, Central Java, Indonesia: Colombo-Srilanka, ACRS2016. Hagolle, O., Huc, M., Villa Pascual, D., & Dedieu, G. (2015). A multi-temporal and multi-spectral method to estimate aerosol optical thickness over land, for the atmospheric correction of FormoSat-2, LandSat, VENμS and Sentinel-2 images. Remote Sensing, 7(3), pp. 2668-2691. Hegazy, I. R., & Kaloop, M. R. (2015). Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. International Journal of Sustainable Built Environment, 4(1), pp. 117-124. Henderson, J. V., Storeygard, A., & Deichmann, U. (2017). Has climate change driven urbanization in Africa? Journal of development economics, 124, pp. 60-82. Hu, L., & Brunsell, N. A. (2015). A new perspective to assess the urban heat island through remotely sensed atmospheric profiles. Remote Sensing of Environment, 158, pp. 393-406. Hughes, S. J., Cabral, J. A., Bastos, R., Cortes, R., Vicente, J., Eitelberg, D., . . . Santos, M. (2016). A stochastic dynamic model to assess land use change scenarios on the ecological status of fluvial water bodies under the Water Framework Directive. Science of the Total Environment, 565, pp. 427-439. Hussain, M., Chen, D., Cheng, A., Wei, H., & Stanley, D. (2013). Change detection from remotely sensed images: From pixel-based to object-based approaches. ISPRS Journal of Photogrammetry and Remote Sensing, 80, pp. 91-106. Hyyppä, J., Hyyppä, H., Inkinen, M., Engdahl, M., Linko, S., & Zhu, Y.-H. (2000). Accuracy comparison of various remote sensing data sources in the retrieval of forest stand attributes. Forest Ecology and Management, 128(1-2), pp. 109-120. Jiang, L., Wu, F., Liu, Y., & Deng, X. (2014). Modeling the impacts of urbanization and industrial transformation on water resources in China: an integrated hydro-economic CGE analysis. Sustainability, 6(11), pp. 7586-7600. Jin, S., Yang, L., Zhu, Z., & Homer, C. (2017). A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011. Remote Sensing of Environment, 195, pp. 44-55. Joshi, N., Baumann, M., Ehammer, A., Fensholt, R., Grogan, K., Hostert, P., . . . Mitchard, E. T. (2016). A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring. Remote Sensing, 8(1), p 70. Kaliraj, S., Chandrasekar, N., & Magesh, N. (2015). Evaluation of multiple environmental factors for site-specific groundwater recharge structures in the Vaigai River upper basin, Tamil Nadu, India, using GIS-based weighted overlay analysis. Environmental earth sciences, 74(5), pp. 4355-4380. Koop, S. H., & van Leeuwen, C. J. (2015). Assessment of the sustainability of water resources management: A critical review of the City Blueprint approach. Water Resources Management, 29(15), pp. 5649-5670. Kumar, P., Masago, Y., Mishra, B. K., & Fukushi, K. (2018). Evaluating future stress due to combined effect of climate change and rapid urbanization for Pasig-Marikina River, Manila. Groundwater for Sustainable Development, 6, pp. 227-234. Lang, S. (2008). Object-based image analysis for remote sensing applications: modeling reality–dealing with complexity Object-based image analysis (pp. 3-27): Springer. Li, M., Zang, S., Zhang, B., Li, S., & Wu, C. (2014). A review of remote sensing image classification techniques: The role of spatio-contextual information. European Journal of Remote Sensing, 47(1), pp. 389-411. Liddle, B. (2014). Impact of population, age structure, and urbanization on carbon emissions/energy consumption: evidence from macro-level, cross-country analyses. Population and Environment, 35(3), pp. 286-304. Lillesand, T., Kiefer, R. W., & Chipman, J. (2014). Remote sensing and image interpretation: John Wiley & Sons. Liu, Y., Wang, Y., Peng, J., Du, Y., Liu, X., Li, S., & Zhang, D. (2015). Correlations between urbanization and vegetation degradation across the world’s metropolises using DMSP/OLS nighttime light data. Remote Sensing, 7(2), pp. 2067-2088. López, E., Bocco, G., Mendoza, M., & Duhau, E. (2001). Predicting land-cover and land-use change in the urban fringe: a case in Morelia city, Mexico. Landscape and urban planning, 55(4), pp. 271-285. Luo, M., & Lau, N.-C. (2017). Heat waves in southern China: Synoptic behavior, long-term change, and urbanization effects. Journal of Climate, 30(2), pp. 703-720. Mahboob, M. A., Atif, I., & Iqbal, J. (2015). Remote sensing and GIS applications for assessment of urban sprawl in Karachi, Pakistan. Science, Technology and Development, 34(3), pp. 179-188. Mallinis, G., Koutsias, N., Tsakiri-Strati, M., & Karteris, M. (2008). Object-based classification using Quickbird imagery for delineating forest vegetation polygons in a Mediterranean test site. ISPRS Journal of Photogrammetry and Remote Sensing, 63(2), pp. 237-250. 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Towards better exploiting convolutional neural networks for remote sensing scene classification. Pattern Recognition, 61, pp. 539-556. Oguz, H., & Zengin, M. (2011). Analyzing land use/land cover change using remote sensing data and landscape structure metrics: a case study of Erzurum, Turkey. Fresenius Environmental Bulletin, 20(12), pp. 3258-3269. Pohl, C., & Van Genderen, J. L. (1998). Review article multisensor image fusion in remote sensing: concepts, methods and applications. International journal of remote sensing, 19(5), pp. 823-854. Price, O., & Bradstock, R. (2014). Countervailing effects of urbanization and vegetation extent on fire frequency on the Wildland Urban Interface: Disentangling fuel and ignition effects. Landscape and urban planning, 130, pp. 81-88. Prosdocimi, I., Kjeldsen, T., & Miller, J. (2015). Detection and attribution of urbanization effect on flood extremes using nonstationary flood‐frequency models. Water resources research, 51(6), pp. 4244-4262. Rawat, J., & Kumar, M. (2015). Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science, 18(1), pp. 77-84. Rokni, K., Ahmad, A., Solaimani, K., & Hazini, S. (2015). A new approach for surface water change detection: Integration of pixel level image fusion and image classification techniques. International Journal of Applied Earth Observation and Geoinformation, 34, pp. 226-234. Sakieh, Y., Amiri, B. J., Danekar, A., Feghhi, J., & Dezhkam, S. (2015). Simulating urban expansion and scenario prediction using a cellular automata urban growth model, SLEUTH, through a case study of Karaj City, Iran. Journal of Housing and the Built Environment, 30(4), pp. 591-611. Santra, A. (2016). Land Surface Temperature Estimation and Urban Heat Island Detection: A Remote Sensing Perspective. Remote Sensing Techniques and GIS Applications in Earth and Environmental Studies, p 16. Shrivastava, L., & Nag, S. (2017). MONITORING OF LAND USE/LAND COVER CHANGE USING GIS AND REMOTE SENSING TECHNIQUES: A CASE STUDY OF SAGAR RIVER WATERSHED, TRIBUTARY OF WAINGANGA RIVER OF MADHYA PRADESH, INDIA. Shuaibu, M., & Sulaiman, I. (2012). Application of remote sensing and GIS in land cover change detection in Mubi, Adamawa State, Nigeria. J Technol Educ Res, 5, pp. 43-55. Song, B., Li, J., Dalla Mura, M., Li, P., Plaza, A., Bioucas-Dias, J. M., . . . Chanussot, J. (2014). Remotely sensed image classification using sparse representations of morphological attribute profiles. IEEE transactions on geoscience and remote sensing, 52(8), pp. 5122-5136. Song, X.-P., Sexton, J. O., Huang, C., Channan, S., & Townshend, J. R. (2016). Characterizing the magnitude, timing and duration of urban growth from time series of Landsat-based estimates of impervious cover. Remote Sensing of Environment, 175, pp. 1-13. Tayyebi, A., Shafizadeh-Moghadam, H., & Tayyebi, A. H. (2018). Analyzing long-term spatio-temporal patterns of land surface temperature in response to rapid urbanization in the mega-city of Tehran. Land Use Policy, 71, pp. 459-469. Teodoro, A. C., Gutierres, F., Gomes, P., & Rocha, J. (2018). Remote Sensing Data and Image Classification Algorithms in the Identification of Beach Patterns Beach Management Tools-Concepts, Methodologies and Case Studies (pp. 579-587): Springer. Toth, C., & Jóźków, G. (2016). Remote sensing platforms and sensors: A survey. ISPRS Journal of Photogrammetry and Remote Sensing, 115, pp. 22-36. Tuholske, C., Tane, Z., López-Carr, D., Roberts, D., & Cassels, S. (2017). Thirty years of land use/cover change in the Caribbean: Assessing the relationship between urbanization and mangrove loss in Roatán, Honduras. Applied Geography, 88, pp. 84-93. Tuia, D., Flamary, R., & Courty, N. (2015). 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Lidar: range-resolved optical remote sensing of the atmosphere: Springer Science & Business. Wellmann, T., Haase, D., Knapp, S., Salbach, C., Selsam, P., & Lausch, A. (2018). Urban land use intensity assessment: The potential of spatio-temporal spectral traits with remote sensing. Ecological Indicators, 85, pp. 190-203. Whiteside, T. G., Boggs, G. S., & Maier, S. W. (2011). Comparing object-based and pixel-based classifications for mapping savannas. International Journal of Applied Earth Observation and Geoinformation, 13(6), pp. 884-893. Willhauck, G., Schneider, T., De Kok, R., & Ammer, U. (2000). Comparison of object oriented classification techniques and standard image analysis for the use of change detection between SPOT multispectral satellite images and aerial photos. Proceedings of XIX ISPRS congress. Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., . . . Young, S. A. (2009). Overview of the CALIPSO mission and CALIOP data processing algorithms. Journal of Atmospheric and Oceanic Technology, 26(11), pp. 2310-2323. Yengoh, G. T., Dent, D., Olsson, L., Tengberg, A. E., & Tucker III, C. J. (2015). Use of the Normalized Difference Vegetation Index (NDVI) to Assess Land Degradation at Multiple Scales: Current Status, Future Trends, and Practical Considerations: Springer. Yu, Q., Gong, P., Clinton, N., Biging, G., Kelly, M., & Schirokauer, D. (2006). Object-based detailed vegetation classification with airborne high spatial resolution remote sensing imagery. Photogrammetric Engineering & Remote Sensing, 72(7), pp. 799-811. Zhou, D., Zhao, S., Zhang, L., & Liu, S. (2016). Remotely sensed assessment of urbanization effects on vegetation phenology in China's 32 major cities. Remote Sensing of Environment, 176, pp. 272-281. Zhu, Z., Fu, Y., Woodcock, C. E., Olofsson, P., Vogelmann, J. E., Holden, C., . . . Yu, Y. (2016). 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Debt collateral is often unacceptable to the execution of debt collateral because there is coercion and leads to court so that many debts are not collected. In Minangkabau customary law, there is no compulsion to pay off debts. This research answers how people make debt-receivables agreements and must be repaid by the debtors in the Minangkabau customary law arrangement in Sungai Dareh village, West Sumatra. This research method is through observation and interviews of local customary leaders. The implementation of the pattern of execution of debt collateral settlement in Minangkabau is motivated by the legal relationship between the creditor and the collateral in the form of land. The creditor only has the right to cultivate or take the proceeds from the land given by the debt recipient until the debt is paid off or redeemed by the debt recipient, so that debt settlement will never transfer ownership rights to the land. In an urgent situation, the creditor can transfer the debt to the new lender, which stops the legal relationship between the first creditor and the debt recipient and creates a new legal relationship between the second creditor and the debt recipient. Creditors' rights remain a priority, and there is no time limit in paying off debts. This debt settlement is very different from debt settlement in positive law in Indonesia. The creditor has the right to sell the land as collateral for the debt if the debt cannot be settled after a certain period, which results in the loss of ownership of the debt recipient over the land that is used as debt collateral. There is a need for positive legal reform in Indonesia regarding the execution of debt guarantees.

This study aim to attempt mapping out the Land Use or Land Cover (LULC) status of Regional Project Coordination Committee (RPCC) between 2009-2019 with a view of detecting the land consumption rate and the changes that has taken place using RS and GIS techniques; serving as a precursor to the further study on urban induced variations or change in weather pattern of the cityn Rangpur City Corporation(RCC) is the main administrative functional area for both of Rangpur City and Rangpur division and experiencing a rapid changes in the field of urban sprawl, cultural and physical landscape,city growth. These agents of Land use or Land cover (LULC) varieties are responsible for multi-dimensional problems such as traffic congestion, waterlogging, and solid waste disposal, loss of agricultural land. In this regard, this study fulfills LULC changes by using Geographical Information Systems (GIS) and Remote Sensing (RS) as well as field survey was conducted for the measurement of change detection. The sources of data were Landsat 7 ETM and landsat 8 OLI/TIRS of both C1 level 1. Then after correcting the data, geometrically and radiometrically change detection and combined classification (supervised & unsupervised) were used. The study finds LULC changes built-up area, water source, agricultural land, bare soil in a change of percentage is 17.23, 2.58, -9.94, -10.19 respectively between 2009 and 2019. Among these changes, bare soil is changed to a great extent, which indicates the expansion of urban areas is utilizing the land to a proper extent. Keywords: Urban expansion; land use; land cover; remote sensing; geographic information system (GIS); Rangpur City Corporation(RCC). References Al Rifat, S. A., & Liu, W. (2019). Quantifying spatiotemporal patterns and major explanatory factors of urban expansion in miami metropolitan area during 1992-2016. Remote Sensing, 11(21) doi:10.3390/rs11212493 Arimoro AO, Fagbeja MA, Eedy W. (2002). The Need and Use of Geographic Information Systems for Environmental Impact Assessment in Africa: With Example from Ten Years Experience in Nigeria. AJEAM/RAGEE, 4(2), 16-27. Belal, A.A. and Moghanm, F.S. (2011).Detecting Urban Growth Using Remote Sensing and GIS Techniques in Al Gharbiya Governorate, Egypt.The Egyptian Journal of Remote Sensing and Space Science, 14, 73-79. http://dx.doi.org/10.1016/j.ejrs.2011.09.001 Dewan, A.M. and Yamaguchi, Y. (2009). Using Remote Sensing and GIS to Detect and Monitor and Use and Land Cover Change in Dhaka Metropolitan of Bangladesh during 1960-2005. Environmental Monitor Assessment, 150, 237- 249. Retrieved from http://dx.doi.org/10.1007/s10661-008-0226-5 Djimadoumngar, K.-N., & Adegoke, J. (2018). Satellite-Based Assessment of Land Use and Land Cover (LULC) Changes around Lake Fitri, Republic of Chad. Journal of Sustainable Development, 11(5), 71. doi:10.5539/jsd.v11n5p71 Edwards, B., Frasch, T., & Jeyacheya, J. (2019). Evaluating the effectiveness of land-use zoning for the protection of built heritage in the bagan archaeological zone, Myanmar—A satellite remote-sensing approach. Land use Policy, 88 doi:10.1016/j.landusepol.2019.104174 Fallati, L., Savini, A., Sterlacchini, S., & Galli, P. (2017). Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data. Environmental Monitoring and Assessment, 189(8). doi:10.1007/s10661-017-6120-2 Fučík, P., Novák, P., & Žížala, D. (2014). A combined statistical approach for evaluation of the effects of land use, agricultural and urban activities on stream water chemistry in small tile-drained catchments of south bohemia, czech republic. Environmental Earth Sciences, 72(6), 2195-2216. doi:10.1007/s12665-014-3131-y Elbeih, S. F., & El-Zeiny, A. M. (2018). Qualitative assessment of groundwater quality based on land use spectral retrieved indices: Case study sohag governorate, egypt. Remote Sensing Applications: Society and Environment, 10, 82-92. doi:10.1016/j.rsase.2018.03.001 Fasal, S. (2000). Urban expansion and loss of agricultural land – A GIS based study of Saharanpur City, India. Environment and Urbanization, 12(2), 133 – 149 He, S., Wang, X., Dong, J., Wei, B., Duan, H., Jiao, J., & Xie, Y. (2019). Three-dimensional urban expansion analysis of valley-type cities: A case study of chengguan district, lanzhou, china. Sustainability (Switzerland), 11(20) doi:10.3390/su11205663 Heimlich, R.E and W.D. Anderson. (2001). Development at the Urban Fringe and Beyond: Impacts on Agriculture and Rural Land. 803, Economic Research Service, U.S. Department of Agriculture, Washington D.C., pg 80 Im, N., Kawamura, K., Suwandana, E., & Sakuno, Y. (2014). Monitoring land use and land cover effects on water quality in cheung ek lake using ASTER images. American Journal of Environmental Sciences, 11(1), 1-12. doi:10.3844/ajessp.2015.1.12 Kalnay, E., & Cai, M. (2003). Impact of urbanization and land-use change on climate. Nature, 423(6939), 528-531. doi:10.1038/nature01675 Matlhodi, B., Kenabatho, P. K., Parida, B. P., & Maphanyane, J. G. (2019). Evaluating land use and land cover change in the gaborone dam catchment, botswana, from 1984-2015 using GIS and remote sensing. Sustainability (Switzerland), 11(19) doi:10.3390/su11195174 Uddin, M. M. M. (2015). Causal relationship between agriculture, industry and services sector for GDP growth in Bangladesh: An econometric investigation. Journal of Poverty, Investment and Development, 8. Mondal, I., Srivastava, V. K., Roy, P. S., & Talukdar, G. (2014). Using logit model to identify the drivers of landuse landcover change in the lower gangetic basin, india. Paper presented at the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, , XL-8(1) 853-859. doi:10.5194/isprsarchives-XL-8-853-2014 Navale, V. B., & Mhaske, S. Y. (2019). Land use/land cover changes in sangamner city by using remote sensing and GIS. International Journal of Recent Technology and Engineering, 8(2), 4614-4621. doi:10.35940/ijrte.B3386.078219 Nicolson, L.D. (1987). The Greening of the cities; Routledge and Kegan Paul, London Nong, D., Fox, J., Miura, T., & Saksena, S. (2015). Built-up Area Change Analysis in Hanoi Using Support Vector Machine Classification of Landsat Multi-Temporal Image Stacks and Population Data. Land, 4(4), 1213–1231. doi:10.3390/land4041213 Park, H., Fan, P., John, R., Ouyang, Z., & Chen, J. (2019). Spatiotemporal changes of informal settlements: Ger districts in ulaanbaatar, mongolia. Landscape and Urban Planning, 191 doi:10.1016/j.landurbplan.2019.103630 Rajeshwari D. (2006). Management of the Urban Environment Using Remote Sensing and Geographic Information Systems.J. Hum. Ecol., 20(4), 269-277. Retrieved from http://www.krepublishers.com/02_journals/JHE/ Rasul, A., Balzter, H., Ibrahim, G., Hameed, H., Wheeler, J., Adamu, B., … Najmaddin, P. (2018). Applying Built-Up and Bare-Soil Indices from Landsat 8 to Cities in Dry Climates. Land, 7(3), 81. doi:10.3390/land7030081 Risma, Zubair, H., & Paharuddin. (2019). Prediction of land use and land cover (LULC) changes using CA-Markov model in Mamuju Subdistrict. Journal of Physics: Conference Series, 1341, 082033. doi:10.1088/1742-6596/1341/8/082033 Schilling, K. E., Jha, M. K., Zhang, Y.-K., Gassman, P. W., & Wolter, C. F. (2008). Impact of land use and land cover change on the water balance of a large agricultural watershed: Historical effects and future directions. Water Resources Research, 44(7). doi:10.1029/2007wr006644 Copyright (c) 2019 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

Although settlement patterns are a central topic of archaeological research, there is a paucity of general theory on the determinants of agrarian settlement. What passes for a theory of agrarian settlement in archaeology is a borrowed model which does not recognize the relationship between population density and agricultural intensity. This dissertation argues that the rules determining where farmers settle are inextricable from how they farm. Ethnohistoric and ethnoarchaeological data are used to investigate the relationship between agricultural change and the determinants of settlement location in the case of the Kofyar, a population of farmers colonizing a frontier area in the central Nigerian savanna. As they moved into an area with a low ratio of population to productive land, Kofyar agriculture was extensified in accord with the Boserup (1965) model. With potentially greater travel costs associated with domestic water than with farm plots, streams exerted a strong attraction to early settlements. With increasing land pressure, the attraction value of farmland eclipsed the attraction to water. Contrary to Boserup's theory that agricultural responses to land pressure cross-cut environments, analysis of settlement histories of over 1000 households shows that responses vary with soil type. Farmers on high-quality sandstone-derived soils tend to intensify cultivation, while farmers on inferior shale-derived and igneous-derived soils tend to abandon their farms when yields begin to decline. The location of Kofyar compounds with respect to each other is closely related to the labor demands of agricultural production. The restricted range of distances between residential compounds reflects the reliance on inter-household collaboration in agricultural production.

Thesis (Ph. D.)--University of Oregon, 1993.
Typescript. Includes vita and abstract. Includes bibliographical references (leaves 256-275). Also available via Internet as PDF file through Southern Oregon Digital Archives: http://soda.sou.edu. Search First Nations/Tribal Collection.

The Upper Wabash Drainage over the last few years has become an area which has provided archaeologists with vital data concerning prehistoric settlement patterns. One time period which has not been well represented is the Archaic Period. Many questions have been unanswered about Archaic settlement patterns within the region. This study examines data from archaeological survey and presents a model for both Early and Late Archaic settlement within the Upper Wabash drainage. The information generated by this analysis will provide a better understanding of the Archaic period within this region. The study will also prove to be useful as a reference for future research as well as an important mechanism for resource management.
Department of Anthropology

Thesis (M.A.) University of Missouri-Columbia, 2004.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (June 29, 2006) Vita. Includes bibliographical references.

AbstractWithin the several European analyses of spatial patterns, Belgium and Flanders take a specific position. The average ‘settlement area percentage’ (i.e., all land used beyond agriculture, semi-natural areas, forestry, and water bodies) for Europe is 4%, but 32% of the Flemish area is occupied with artificial land. Belgium has the highest score for urban-sprawl indicators, and within the European context, almost the entire area is considered urban. The aim of the research presented in this paper is to expand on the theme of indicators for spatial patterns by analyzing the Flemish area with detailed data across various scales. The results are collected in a report, the ‘Ruimterapport’— ‘RURA’, published in 2018. RURA is a bundling and compilation of research results from very diverse sources, amongst others studies from the Department of Environment and Spatial Development of Flanders and of Espon studies. This article presents the most important results from RURA and further positions them in international comparative literature. New maps and indicators are developed for the urban/peri-urban/rural dimensions of the human settlement area, urban sprawl, and settlement patterns by differentiating amongst others between urban centers, ribbon development, and scattered buildings. The paper gives a quantitative, methodological, and empirical contribution to the field of urban and regional development processes and contributes to conceptualizations of space. The case of Flanders, with its specific sprawl pattern, illustrates the difficulties spatial planning policy makers currently are facing, dealing with the complexity of space and society.

This chapter treats a variety of human interactions with the land that trace their origins more to political and commercial drivers rather than directly to geology, topography, soils and local biota. Examples of land subdivisions are taken mostly from the United States, which illustrates a variety of land-use patterns that result from property surveys. Land hunger and government policies have also contributed to wars, which have altered landscapes. These have characterized the history of most parts of the world, having major repercussions on the environment as well as on people. Examples range over time and space. Industrialization increased the ability of people to travel and thus trade quickly over long distances thus intensifying and extending the impact of humans on the land, especially as industrialization further separated local land use from resource protection. Cities have flourished, often along trade routes, perhaps even before the development of agriculture Some all but disappeared, but all have had both local and regional effects on the land. Examples are discussed of effects both within cities today and resulting from cities that no longer exist.

Although Khulna's actual history is not about more than 200 years, but it has a 2000 years settlement and commercial history. Khulna was a part of Ganaridai, Vanga, Jessore dynasty, Rarh (South Bengal) in different periods. The connection of rivers always made a blessing for Khulna for water transportation to accelerate trade and commerce. According to Ptolemy, the ancient Gangaridai had an ancient port located in greater Jessore [1,557]. Some archaic incidents, verses, and legends of Mani-Rishis (Ancient Indian Scholars) proved the old settlement and commercial style. The chronological evolution of the ancient Period (6th century BC – 1757 AD) described a civilization's development with the incremental commercial approach [2,315]. The colonial regime can relate to the evolution of a commercial and economic center like Barobazar as a whole. All these chronological narrations, consecutive phenomena, and influential factors will depict the trend of retail evolution. The research aims to describe Khulna's commercial development's sequential affairs and find the missing links between eras. Various ancient documents, Blueprints, Greek Periplus, etc. will describe the settlement, commercial mode, and history. It will determine the answer to the questions about the growth and establishment of river port cities and major economic centers' evolution. The paper will describe commercial –spatial progression in 4 Particular eras. GIS surveys and some old maps will illustrate the commercial land-use patterns of Barobazar from the Colonial Period to the present and the river base trade. These will elaborate on the existing conditions as well as the revolutionary changes. The fundamental research will help for the further Urban regeneration of Barobazar as a central economic hub. The historical consequences will help to sort out the development pattern and strategies behind the progression.

With the establishment of the Constitution of 1988, a new approach to urban governance emerged in Brazil. The document brought significant changes regarding the right to the city and adequate housing, in particular, for the urban poor. The recognition of these rights triggered the experimentation with inclusionary policies around the country (Rolnik and Santoro, 2013). As a result, informal settlements started to be acknowledged as part of the formal city and were included in zoning and planning laws. One of the main outcomes of these experiments was the creation of Special Zones of Social Interest (ZEIS), a land and housing policy that linked investments on infrastructure in precarious settlements to land regularisation processes. In 2001, ZEIS was incorporated into the City Statute, a document that established a range of collective rights to guide land use and development. Since then, the instrument has gained popularity in the country as a land regularisation tool. Nevertheless, a considerable share of settlements remains poorly built and addressing informality is still a challenge. Therefore, this paper evaluated the co-relation between the implementation of ZEIS, land regularisation processes and provision of basic infrastructure in precarious settlements. More specifically, it measured the quality of State interventions supported by the zoning. By focusing on quality, this article aimed to evaluate whether ZEIS has encouraged adequate housing conditions for the urban poor or reinforced precarious patterns of development. To explore this relationship, a case study was conducted on the performance of ZEIS in Favela of Sapé, a settlement in the West of São Paulo. As a methodology, case studies have become a common option for performing evaluations and analyse what a program, practice or police has achieved (Yin, 2012). Moreover, this research strategy commonly relies on various sources of field-based information (Yin, 2012). Accordingly, this paper comprised mainly primary qualitative data. It also made broad use of content and secondary analysis, with the goal of ensuring validity and reliability. The performance of ZEIS in Sapé demonstrated that since its implementation, in 2001, tenure security and physical characteristics have enhanced considerably in the area, particularly, when it comes to housing quality and provision of basic infrastructure. Nevertheless, these accomplishments are being compromised by a strong process of reoccupation which is supported by illegal organisations. In addition, there is a delay of the Municipality in meeting the demands for housing in the area because of governance issues and mismanagement of financial resources. This scenario, combined with a weak inspection body, has once again permitted the development of precarious housing and infrastructure in the area. It also has compromised the issuance of freehold land titles to the settlement’s dwellers. In other words, the site is under a vicious circle where neither the provision of housing and infrastructure is enough to meet the demand nor the land regularisation is completed because of the reoccupations. In sum, although the implementation of ZEIS seems to have a share of responsibility in Sapé’s upgrading process, the local authorities do not have the capacity of reinforcement necessary to maintain these improvements. Furthermore, it is fair to assume that the current legal framework provided by ZEIS is not adequate for the context of São Paulo and requires further adjustments. Not only because of the complex character of the city, but also because in practice, urban norms may be interpreted differently according to political and cultural conditions (Rolnik, 1997).

Cartographying the real metropolis: A proposal for a data-based planning beyond the administrative boundaries. Juan R. Selva-Royo¹, Nuño Mardones¹, Alberto Cendoya² ¹University of Navarra, School of Architecture, Department of Theory and Design, University of Navarra Campus, 31080 Pamplona, Spain; ²University of Navarra, ICS, Navarra Center for International Development, University of Navarra Campus, 31080, Pamplona, Spain E-mail: jrselva@unav.es, nmardones@unav.es, cendoya.alberto@gmail.com Keywords (3-5): Data planning, metropolitan areas, big data, urban extent, good governance Conference topics and scale: Cartography and big data Nowadays, there is a great gap between the functional reality of urban agglomerations and their planning, largely because of the traditional linkage of urban management to the administrative limits inherited from the past. It is also true that the regulation of urban activities, including census and statistical information, requires a closer view of its citizens that can only be addressed from the municipal level. In any case, it is clear that the metropolitan delimitation has met useful but often ethereal or exclusionary criteria (economic or labor patterns, functional areas...), which become disfigured by an administrative reality that does not always correspond to the real metropolis. This paper, aware of the new cartographic possibilities linked to the big data - CORINE Land Cover, SIOSE, multi-sector digital atlases (in many cases referred to the urban extent, etc.) and other open system platforms - explores the evidence that might base a new objective methodology for the delimitation and planning of large urban areas. Indeed, what if basic data for cities would arise not from administrative entities but from independent outside approaches such as satellite imagery? What if every single sensing unit (every citizen, company, building or vehicle) directly issued relevant and dynamic information without going through the municipal collection? Finally, the research analyzes the eventual implications of this data-based planning with administrative structures and urban planning competencies in force through some current case studies, with the purpose of achieving a more efficient and clear metropolitan governance for our planet. References (100 words) Aguado, M. (coord.) (2012) Áreas Urbanas +50. Información estadística de las Grandes Áreas Urbanas españolas 2012 (Centro de Publicaciones Secretaría General Técnica Ministerio de Fomento, Madrid). Angel, S. (dir.) (2016) Atlas of Urban Expansion (http://www.atlasofurbanexpansion.org) accessed 29 January 2017. Brenner, N. and Katsikis, N. (2017) Is the World Urban? Towards a Critique of Geospatial Ideology (Actar Publishers, New York). Florczyk, A. J., Ferri, S., Syrris, V., Kemper, T., Halkia, M., Soille, P., and Pesaresi, M. (2016). ‘A New European Settlement Map from Optical Remotely Sensed Data’, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9, 1978-1992.