scholarly journals Ecological Monitoring with Spy Satellite Images—The Case of Red Wood Ants in Romania

2021 ◽  
Vol 13 (3) ◽  
pp. 520
Author(s):  
Dietrich Klimetzek ◽  
Petru Tudor Stăncioiu ◽  
Marius Paraschiv ◽  
Mihai Daniel Niță
Keyword(s):  
Satellite Images ◽  
Vegetation Index ◽  
Satellite Image ◽  
Canopy Cover ◽  
Ecological Monitoring ◽  
Google Earth ◽  
Ecosystem Dynamics ◽  
Small Scale ◽  
Habitat Conditions ◽  
Sources Of Information

Dynamics of habitat conditions drive important changes in distribution and abundance of animal species making monitoring an important but also a challenging task when data from the past are scarce. We compared the distribution of ant mounds in the 1960s with recent inventories (2018), looking at changes in canopy cover over time, in a managed forest. Both historical and recent sources of information were used. Habitat suitability at present was determined using a Normalized Difference Vegetation Index (NDVI) image as a proxy for stand canopy cover. The NDVI product was obtained using Google Earth Engine and Sentinel 2 repository. For past conditions (no spectral information available), presence of edges and more open canopies was assessed on a Corona spy-satellite image and based on information from old forest management plans. A threshold distance of 30 m was used to assess location of ant nests compared to favorable habitats. Both old and new information sources showed that ants prefer intermediate canopy cover conditions in their vicinity. Nests remained clustered because of the heterogeneous habitat conditions, but spatial distribution has changed due to canopy alteration along time. The analysis on the NDVI was effective for 82% of cases (i.e., nests occurred within 30 m from favorable habitats). For all the remaining nests (18%), the Google Earth high resolution satellite image revealed in their vicinity the presence of small canopy gaps (undetected by the NDVI). These results show that historical satellite images are very useful for explaining the long-term dynamics of ant colonies. In addition, the use of modern remote sensing techniques provides a reliable and expedite method in determining the presence of favorable small-scale habitat, offering a very useful tool for ecological monitoring across large landscapes and in very different areas, especially in the context of ecosystem dynamics driven and exacerbated by climate change.

scholarly journals Monitoring Olive Oil Mill Wastewater Disposal Sites Using Sentinel-2 and PlanetScopeSatellite Images: Case Studies in Tunisia and Greece

Agronomy ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 90
Author(s):  
Wissal Issaoui ◽  
Dimitrios D. Alexakis ◽  
Imen Hamdi Nasr ◽  
Athanasios V. Argyriou ◽  
Evangelos Alevizos ◽  
...  
Keyword(s):  
Olive Oil ◽  
Satellite Images ◽  
Vegetation Index ◽  
Satellite Image ◽  
Olive Mill Wastewater ◽  
Support Vector ◽  
Inorganic Particles ◽  
Mediterranean Countries ◽  
Sentinel 2 ◽  
Olive Mill

Mediterranean countries are known worldwide for their significant contribution to olive oil production, which generates large amounts of olive mill wastewater (OMW) that degrades land and water environments near the disposal sites. OMW consists of organic substances with high concentrations of phenolic compounds along with inorganic particles. The aim of this study is to assess the effectiveness of satellite image analysis techniques using multispectral satellite data with high (PlanetScope, 3 × 3 m) and medium (Sentinel-2, 10 × 10 m) spatial resolution to detect Olive Mill Wastewater (OMW) disposal sites, both in the SidiBouzid region (Tunisia) and in the broader Rethymno region on the island of Crete, (Greece). Documentation of the sites was carried out by collecting spectral signatures of OMW at temporal periods. The study integrates the application of a variety of spectral vegetation indices (VIs), such as the Normalized Difference Vegetation Index (NDVI), in order to evaluate their efficiency in detecting OMW disposal areas. Furthermore, a set of image-processing methods was applied on satellite images to improve the monitoring of OMW ponds including the false-color composites (FCC), the Principal Component Analysis (PCA), and image fusion. Finally, different classification algorithms, such as the ISODATA, the maximum likelihood (ML), and the Support Vector Machine (SVM) were applied to both satellite images in order to assist in the overall approach to effectively detect the sites. The results obtained from different approaches were compared, evaluating the efficiency of Sentinel-2 and PlanetScope images to detect and monitor OMW disposal areas under different morphological environments.

Satellite Radar Imagery for Detection and Monitoring of Geohazards

2020 ◽  
Vol 2674 (3) ◽  
pp. 283-292
Author(s):  
Sumanth V. Byrraju ◽  
Dimitris C. Rizos ◽  
Yu Qian
Keyword(s):  
Moisture Content ◽  
Synthetic Aperture Radar ◽  
Satellite Images ◽  
Satellite Image ◽  
Synthetic Aperture ◽  
Small Scale ◽  
Interferometric Synthetic Aperture Radar ◽  
Right Of Way ◽  
The Right ◽  
Aperture Radar

This paper presents three case studies that were part of a 1-year study that explores the feasibility of using commercially available satellite and other aerial imagery to monitor the right of way of railroads for effects and conditions that could potentially trigger landslides and other geohazards. Two satellite image processing techniques in the Interferometric Synthetic Aperture Radar (InSAR) family have been studied and employed, that is, the Differential Interferometric Synthetic Aperture Radar (DInSAR) and the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR). All satellite images used in this work are in the public domain and the software is open source. Showcase studies have demonstrated that the current satellite technology makes it feasible to monitor the railway right of way for large- and small-scale deformations and changes in the ground moisture content in adequate resolution. The frequency of acquisition of satellite images is adequate for the long-term monitoring of the infrastructure. The satellite analysis results can be superimposed to visual imagery for ease of visual inspection and evaluation. Future work for the development of a monitoring system of the railway right of way needs to focus on verifying the accuracy of the techniques with in situ measurements through conventional means and quantifying the changes of the moisture content.

scholarly journals Mapping and Area Estimation of Mango Orchards of Lucknow Region by Applying Knowledge Based Decision Tree to Landsat 8 OLI Satellite Images

2020 ◽  
Vol 9 (3) ◽  
pp. 3627-3635
Keyword(s):  
Decision Tree ◽  
Satellite Images ◽  
Vegetation Index ◽  
Accuracy Assessment ◽  
Satellite Image ◽  
Accurate Information ◽  
Landsat 8 ◽  
Atmospheric Conditions ◽  
Area Estimation ◽  
Knowledge Based

Mango is a very important fruit which is liked by majority of the population due to its nutritional value and excellent taste. India is the largest producer of mango in the world. Accurate information is required for policy decision making in terms of providing subsidy, area expansion, and crop insurance planning. Hence, this type of information may be retrieve through satellite images by using the image classification techniques, which are playing a crucial role in crop cover classification, yield prediction and crop monitoring etc. Classification of optical satellite images is still a challenging task due to effect of changing atmospheric conditions such as cloud, snow, haze, dust, fog, and rain etc. In this paper, knowledge based decision tree classification (DTC) has been proposed to classify the mango orchards of Lucknow district using multi-temporal Landsat 8 operational land imager (OLI) images from year 2015 to 2017 and further mango orchard area were also estimated. In order to develop the DTC, separability analysis for various land cover classes was carried out on different vegetation indices namely, normalized difference vegetation index (NDVI), modified normalized difference water index (MNDWI), and soil adjusted vegetation index (SAVI). In order to analyze the performance of DTC, most commonly used satellite image classifiers such as unsupervised classifier (i.e. ISODATA) and supervised classifier (i.e. Maximum Likelihood) have been used and it is observed that the proposed DTC outperformed these traditional classifiers. Also, accuracy assessment has been carried out to measure the performance of proposed DTC and it is observed that all of the three images from 2015 to 2017 are classified with high overall accuracy, which is ranging from 70.66% to 86.69%. Kappa Coefficient (KC) for all the three images ranged from 0.65 to 0.83, which indicates that classified images are highly acceptable for area estimation.

scholarly journals PERKEMBANGAN MANGROVE DAN PRODUKSI IKAN LAUT DI PATI UTARA

2017 ◽  
Vol 13 (2) ◽  
pp. 93-104
Author(s):  
Hermain Teguh Prayitno
Keyword(s):  
Marine Fish ◽  
Mangrove Forest ◽  
Satellite Images ◽  
Satellite Image ◽  
Google Earth ◽  
Landsat 8 ◽  
Fish Production ◽  
Growth Data ◽  
Google Maps ◽  
The Impact

ENGLISHThe fishing activities along the coastal area in Northern Pati potentially cause mangrove destruction. The objectives of this study were: (1) to discuss the growth of mangrove area in Northern Pati and (2) to describe the impact of the mangrove forest on marine fish production. This study used quantitative-descriptive research design. The study locations were Dukuhseti and Tayu subdistrict. It was conducted from August to September 2017. It used raster data obtained from Google Earth and Google Maps, formed Landsat 8 satellite images. The other was data of mangrove forest area in Pati Regency. The data analysis was conducted using the satellite images in 2011, 2013, 2015, and 2017. Then, the mangrove growth data were weighted and classified using scores. Validation was done by comparing the mangrove data from Statistic Agency of Pati Regency and those of the satellite image measuring results. The study concluded: (1) The mangrove forest in Northern Pati was in a poor condition. (2) The growth of mangrove forest fluctuated, which the lowest growth happened in 2013, while the highest was found in 2017. (3) The growth of mangrove forest was followed by the increase of marine fish production. INDONESIAKabupaten Pati berada di bagian utara Pulau Jawa memiliki aktivitas masyarakat sebagai pertambak dan nelayan. Penambahan tambak ke arah laut menyebabkan kerusakan mangrove. Tujuan penelitian ini adalah : (1) untuk mengetahui pertumbuhan mangrove di pesisir Pati utara dan (2) untuk menggambarkan dampak hutan mangrove terhadap produktivitas ikan laut. Penelitian ini merupakan penelitian deskriptif kuantitatif. Lokasi penelitian yaitu Kecamatan Dukuhseti dan Kecamatan Tayu. Waktu Penelitian Agustus sampai dengan September 2017. Sumber data berasal dari data raster dari Google Earth dan Google Maps berupa image satelit Landsat 8. Data lain yaitu data luas hutan mangrove di Kabupaten Pati. Analisis data dengan pengukuran image satelit tahun 2011, 2013, 2015 dan 2017. Selanjutnya data perkembangan mangrove dilakukan pembobotan dan diklasifikasikan berdasarkan skor. Verifikasi hasil dilakukan dengan cara membandingkan data perkembangan mangrove dari BPS Kabupaten Pati dengan hasil pengukuran image satelit. Hasil penelitian yaitu (1) hutan mangrove di Pati utara dalam kondisi berkembang buruk. (2) Perkembangan hutan mangrove fluktuatif, dimana perkembangan terendah terjadi pada 2013, sedangkan perkembangan tertinggi pada 2017; 2) perkembangan mangrove di Pati utara mengalami penurunan pada tahun 2013 dan meningkat kembali pada tahun 2015 dan 2017. (3) Perkembangan mangrove diiringi dengan peningkatan produksi ikan segar di Pati Utara.

scholarly journals SISTEM PENDETEKSI PERUBAHAN LAHAN HIJAU DI JABODETABEK

2018 ◽  
Vol 2 (1) ◽  
pp. 91
Author(s):  
Andree Phanderson ◽  
Dyah Erny Herwindiati ◽  
Bagus Mulyawan
Keyword(s):  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Correction Method ◽  
Google Earth ◽  
Linear Regression Method ◽  
Landsat 8 ◽  
Index Method ◽  
Radiometric Correction ◽  
Green Area

Change of green area in Jakarta, Bogor, Depok, Tangerang and Bekasi (Jabodetabek) has been something very important. Classification of green area aims to do classification in Jabodetabek using Landsat 8 satellite images, band 1, 2, 3, 4 and 5. Before classification was done, the satellite images will be corrected using Radiometric Correction method called Mini-max algorithm. After doing radiometric correction, the classification will use the NDVI (Normalized Difference Vegetation Index) and SAVI (Soil Adjusted Vegetation Index) method. The selected area will be classified as green when NDVI values similar or has more than 0.3. After perform two categories, Y1 and Y2 are selected by NDVI values using dummy dependent variable. Linear regression method use that dummy dependent variable to classify the selected area in Jabodetabek. To see how can we trust the result, the classified area will be compared with the appearance of selected area in Google Earth. The highest degradation of green area is in Bogor, May 2015, 325.7368 Km2.

scholarly journals Monitoring of Forty Years of Agricultural Expansion in the Oum Er Rbia Valley (Morocco). The Use of Google Earth Engine Compared to Sentinel Application Platform

2021 ◽  
Author(s):  
María Adell ◽  
José Antonio Domínguez-Gómez ◽  
Juan Soria
Keyword(s):  
Satellite Images ◽  
Vegetation Index ◽  
Plant Cover ◽  
Vegetation Indices ◽  
Google Earth ◽  
Arid Zones ◽  
Us Government ◽  
Google Earth Engine ◽  
The Moment ◽  
Landsat Satellite

Agriculture in Morocco has been extensive until the middle of the 20th century due to the distribution of rainfall and the availability of water. In the middle of the last century hydraulic works were built that allowed the transition to intensive agriculture by the increase of irrigated areas, allowing that in the territories where there is water for irrigation and the climate allows it, the crops adapt to the demands of the market. The objective of the study is to assess by satellite images the land cover between 1985 and 2020, analyzing the changes in cultivation areas, as well as the changes in desert, sub-desert and forest areas of the Oum Er Rbia hydrological basin in Morocco. Landsat satellite images have been used since 1984 by the US government (Aerospace and Geological Agencies). A series of vegetation indices (NDVI, RVI, TNDVI and EVI) have been used; among which TNDVI (Transformed Normalized Vegetation Index) stands out for its better accuracy, which has allowed us to distinguish vegetation in cultivated and forest areas, as well as arid zones. In addition, the study has compared the use of two methodologies to calculate changes in the coverage of the Earth’s surface, has used local image processing from the Sentinel Application Platform tool and has also used the Google Earth Engine tool. The latter being the most optimal, although at the moment it has great limitations. In both methodologies and in the different indices it has been possible to observe during these 35 years as the cultivated area has increased (related to the availability of water by the construction of reservoirs and canals), how plant cover has improved in forest areas, and a range of variations in arid areas.

scholarly journals Assessing Burned Areas in Wildfires and Prescribed Fires with Spectral Indices and SAR Images in the Margalla Hills of Pakistan

Forests ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1371
Author(s):  
Aqil Tariq ◽  
Hong Shu ◽  
Alexandre S. Gagnon ◽  
Qingting Li ◽  
Faisal Mumtaz ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Satellite Image ◽  
Google Earth ◽  
Burned Area ◽  
Prescribed Fires ◽  
Spectral Indices ◽  
Sar Images ◽  
Suitable Alternative ◽  
Burn Scar ◽  
Regeneration Time

The extent of wildfires cannot be easily mapped using field-based methods in areas with complex topography, and in those areas the use of remote sensing is an alternative. This study first obtained images from the Sentinel-2 satellites for the period 2015–2020 with the objective of applying multi-temporal spectral indices to assess areas burned in wildfires and prescribed fires in the Margalla Hills of Pakistan using the Google Earth Engine (GEE). Using those images, the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR), which are often used to assess the severity of fires, were calculated for wildfires and prescribed fires. For each satellite image, spectral indices values were extracted for the 5th, 20th, 40th, 60th, 80th and 95th percentiles of pixels of each burned area. Then, boxplots representing the distribution of these values were plotted for each satellite image to identify whether the regeneration time subsequent to a fire, also known as the burn scar, and the severity of the fire differed between the autumn and summer wildfires, and with prescribed fires. A statistical test revealed no differences for the regeneration time amongst the three categories of fires, but that the severity of summer wildfires was significantly different from that of prescribed fire, and this, for both indices. Second, SAR images were obtained from the Sentinel-1 mission for the same period as that of the optical imagery. A comparison of the response of 34 SAR variables with official data on wildfires and prescribed fires from the Capital Development Authority revealed that the 95th percentile of the Normalized Signal Ratio (NSR p_95) was found to be the best variable to detect fire events, although only 50% of the fires were correctly detected. Nonetheless, when the occurrence of fire events according to the SAR variable NSR p_95 was compared to that from the two spectral indices, the SAR variable was found to correctly identify 95% of fire events. The SAR variable NSR p_95 is thus a suitable alternative to spectral indices to monitor the progress of wildfires and assess their severity when there are limitations to the use of optical images due to cloud coverage or smoke, for instance.

scholarly journals Time-Series Assessment of Camp-Type Artisanal and Small-Scale Gold Mining Sectors with Large Influxes of Miners Using LANDSAT Imagery

2021 ◽  
Vol 18 (18) ◽  
pp. 9441
Author(s):  
Satomi Kimijima ◽  
Masayuki Sakakibara ◽  
Masahiko Nagai ◽  
Nurfitri Gafur
Keyword(s):  
Time Series ◽  
Gold Mining ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat Imagery ◽  
Market Price ◽  
Fold Increase ◽  
Google Earth ◽  
Small Scale ◽  
Field Investigations

Mining sites development have had a significant impact on local socioeconomic conditions, the environment, and sustainability. However, the transformation of camp-type artisanal and small-scale gold mining (ASGM) sites with large influxes of miners from different regions has not been properly evaluated, owing to the closed nature of the ASGM sector. Here, we use remote sensing imagery and field investigations to assess ASGM sites with large influxes of miners living in mining camps in Bone Bolango Regency, Gorontalo Province, Indonesia, in 1995–2020. Built-up areas were identified as indicators of transformation of camp-type ASGM sites, using the Normalized Difference Vegetation Index, from the time series of images obtained using Google Earth Engine, then correlated with the prevalent gold market price. An 18.6-fold increase in built-up areas in mining camps was observed in 2020 compared with 1995, which correlated with increases in local gold prices. Field investigations showed that miner influx also increased after increases in gold prices. These findings extend our understanding of the rate and scale of development in the closed ASGM sector and the driving factors behind these changes. Our results provide significant insight into the potential rates and levels of socio-environmental pollution at local and community levels.

scholarly journals CRESCIMENTO DA AGRICULTURA IRRIGADA POR PIVÔ CENTRAL NA BACIA HIDROGRÁFICA DO ALTO RIO DAS MORTES - MT

Irriga ◽  
2021 ◽  
Vol 1 (4) ◽  
pp. 661-670
Author(s):  
Juan Vicente Liendro Moncada ◽  
Jefferson Vieira José ◽  
Jéfferson de Oliveira Costa ◽  
Carlos Alberto Quiloango-Chimarro ◽  
Niclene Ponce Rodrigues de Oliveira ◽  
...  
Keyword(s):  
River Basin ◽  
Satellite Images ◽  
Vegetation Index ◽  
Sao Paulo ◽  
Google Earth ◽  
São Paulo ◽  
Mato Grosso ◽  
Center Pivot ◽  
Google Earth Engine ◽  
E Mail

CRESCIMENTO DA AGRICULTURA IRRIGADA POR PIVÔ CENTRAL NA BACIA HIDROGRÁFICA DO ALTO RIO DAS MORTES - MT     JUAN VICENTE LIENDRO MONCADA1; JEFFERSON VIEIRA JOSÉ2; JÉFFERSON DE OLIVEIRA COSTA3; CARLOS ALBERTO QUILOANGO-CHIMARRO4; NICLENE PONCE RODRIGUES DE OLIVEIRA5 E TONNY JOSÉ DE ARAÚJO DA SILVA6   1 Instituto de Ciências Agrárias e Tecnológicas, Universidade Federal de Mato Grosso (UFMT), Avenida dos Estudantes, 5055, Cidade Universitária, 78736-900, Rondonópolis, MT, Brasil. E-mail: [email protected]. 2 Centro Multidisciplinar Campus Floresta, Universidade Federal do Acre (UFA), Estrada do Canela Fina, Km 12, Colônia São Francisco, 69980-000, Cruzeiro do Sul, AC, Brasil. E-mail: [email protected]. 3 Departamento de Engenharia de Biossistemas, Universidade de São Paulo (USP/ESALQ), Avenida Pádua Dias, 235, Agronomia, 13418-900, Piracicaba, SP, Brasil. E-mail: [email protected]. 4 Departamento de Engenharia de Biossistemas, Universidade de São Paulo (USP/ESALQ), Avenida Pádua Dias, 235, Agronomia, 13418-900, Piracicaba, SP, Brasil. E-mail: [email protected]. 5 Instituto de Ciências Agrárias e Tecnológicas, Universidade Federal de Mato Grosso (UFMT), Avenida dos Estudantes, 5055, Cidade Universitária, 78736-900, Rondonópolis, MT, Brasil. E-mail: [email protected]. 6 Instituto de Ciências Agrárias e Tecnológicas, Universidade Federal de Mato Grosso (UFMT), Avenida dos Estudantes, 5055, Cidade Universitária, 78736-900, Rondonópolis, MT, Brasil. E-mail: [email protected].     1 RESUMO   O uso do solo e o seu tipo de cobertura tem sofrido modificações significativas nos últimos anos com o crescimento populacional e desenvolvimento da agricultura. Para obtenção de incrementos de produtividade agrícola uma das tecnologias mais empregadas no Brasil e no mundo é a irrigação. O objetivo dessa pesquisa foi identificar o número de equipamentos e as áreas equipadas com pivôs centrais na bacia hidrográfica do Alto Rio das Mortes no Estado de Mato Grosso, utilizando imagens de satélite de média resolução espacial. A bacia hidrográfica do Rio das Mortes está localizada no Centro-Oeste do Brasil, a qual está inserida na bacia do Rio Araguaia-Tocantins. Foram utilizadas imagens de satélite Landsat e a plataforma do Google Earth Engine (GEE). Foram construídas camadas de Índice de Vegetação por Diferença Normalizada (NDVI) e a partir desses dados procedeu-se a identificação e quantificação das áreas irrigadas por pivô central no local de estudo. Verificamos que a maior concentração de pivôs ocorre nas sub-bacias de Primavera do Leste (213 pivôs, 28 mil hectares) e Poxoréu (31 pivôs, 5 mil hectares). A bacia do Alto Rio das Mortes no ano de 2018 apresentava 271 pivôs centrais, ocupando uma área irrigada de aproximadamente 36,5 mil hectares.   Keywords: geotecnologias, índice de vegetação, irrigação, sensoriamento remoto.     MONCADA, J. V. L.; JOSÉ, J. V.; COSTA, J. O.; QUILOANGO-CHIMARRO, C. A.; OLIVEIRA, N. P. R.; SILVA, T. J. A. INCREASE IN CENTER PIVOT-IRRIGATED AGRICULTURE IN THE RIO DAS MORTES-MT RIVER BASIN     2 ABSTRACT   Land use and land cover have changed significantly in recent years with population growth and the development of agriculture. To obtain increases in agricultural productivity, one of the most used technologies in Brazil and around the world is irrigation. This research identified the amount of equipment and areas equipped by center pivots in the Rio das Mortes River basin in the State of Mato Grosso, using satellite images of medium spatial resolution. The Rio das Mortes River basin is located in center-western Brazil, which is inserted in the Araguaia-Tocantins River basin. Landsat satellite images and the Google Earth Engine (GEE) platform were used. Normalized Difference Vegetation Index (NDVI) layers were constructed, and then the identification and quantification of the areas irrigated by center pivot in the study area were performed. The highest concentration of pivots in the Rio das Mortes River basin is in the sub-basins of Primavera do Leste (213 pivots, 28 thousand hectares) and Poxoréu (31 pivots, 5 thousand hectares). The Rio das Mortes River basin in 2018 had 271 center pivots, occupying an irrigated area of approximately 36.5 thousand hectares.   Keywords: geotechnologies, vegetation index, irrigation, remote sensing.

scholarly journals Differentials in Metropolitanisation Trends in Lagos Peri-Urban Settlements

2017 ◽  
Vol 10 (6) ◽  
pp. 14 ◽  
Author(s):  
Funmilayo Mokunfayo Adedire
Keyword(s):  
Satellite Images ◽  
Satellite Image ◽  
Secondary Data ◽  
Google Earth ◽  
Regional Government ◽  
Metropolitan Regions ◽  
Digital Format ◽  
Locational Quality ◽  
Urban Settlements ◽  
Household Heads

This paper examines the differential in the metropolitanisation of Lagos peri-urban settlements and the policy implication on locational quality of the emerging settlements. Two case studies of Ibeju-Lekki and Ikorodu were selected to represent the peri-urban settlements outside Lagos metropolitan regions. Using purposive sampling, thirty four settlements were selected which comprise sixteen and eighteen in Ibeju-Lekki and Ikorodu respectively. Data was sourced primarily through administration of 370 and 384 questionnaires to household heads in the selected settlements in Ibeju-Lekki and Ikorodu. Secondary data was sourced by conversion of analogue spatial images, the land use maps and satellite images of the study area to digital format. Spatial images from 1980 through 2016 were acquired for this study. Acquired satellite images from Google Earth archive were brought into ArcGIS environment for geo-referencing. Quantitative data was analysed using descriptive statistics while qualitative data was analysed using time series and satellite image analysis. Findings show a differential in transformation of the two cases due to varying demographic characteristics of residents, the locational convenience, level of linkages and the regional government housing policy. It is recommended that the regional planning should create a balance between the pace of development and infrastructural provision in the peri-urban to limit the disparity in development in Lagos peri-urban settlements.

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