Change Detection Process and Techniques

Land use / land cover changes studies have become very interesting over the past decades through using remote sensing because of the availability of a suite of sensors operating at various imaging scales and scope of using various techniques as well as considered the good ways for effective monitoring and accurate land use /land cover changes. This paper looks into the following aspects related to the remote sensing technology, change detection process and techniques for land cover changes, and factor affecting change detection techniques and considerations. Keywords: Remote Sensing, Land Use / Land Cover, Change Detectio

Determination of flood extend using OLI data (case study: Dezful 2016 flood)

Among the various natural hazards, floods may be considered as the most devastating factor that inflicts great damage on human societies. Therefore, the importance of estimating flood damage and its scope in planning to reduce damages and determine points with high risk is very important. The aim of this study is to determine the extent of flood hazard using OLI satellite data. For this reason, a window of OLI satellite images of Landsat 8 was acquired before and after the Dezful flood of April 25, 2016. First, preprocessing operations include radiometric and atmospheric corrections of images were done, and the principal component analysis was then used to reduce the correlation of the data. Data processing was performed using a Support Vector Machine algorithm with linear and polynomial kernels. In order to train the Support Vector Machine algorithm, training samples for each class (agricultural land, flood extent, water resources, settlement areas, and recreational areas along the river boundary) were harvested at the user level. In order to evaluate the similarity of the classes and the degree of correlation between the samples, the quantitative assessment method of the Jeffries Matusita was performed. The results showed that the flood area was 11593.26 ha, the highest damage was due to agricultural land with a destruction of 8467.45 ha and recreational and tourist areas along the riverbank with a destruction of 2659.14 ha

DIFFERENCES OF COASTALLINE CHANGES IN THE AREA AFFECTED BY LAND COVER CHANGES AND COASTAL GEOMORPHOLOGICAL SOUTH BALI 1995 - 2021

The South Bali coast is prone to abrasion due to its geographical position facing the Indian Ocean. High sea waves and currents in the south of Bali will erode beaches whose lithology and morphology are prone to abrasion. Land cover conditions that do not support coastal protection will also affect the high abrasion of the southern coast of Bali. This study aims to analyze the shoreline changes in South Bali from 1995-2021. The analytical method used is the Digital shoreline analysis system (DSAS), with data from Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI/TIRS, and Sentinel 2A. The analysis results show that the area directly facing the waves is relatively high, with volcanic rock formations, and there is no mangrove as coastal protection. The lack of good coastal management shows the area with the highest abrasion. It was found in the western part of Tabanan Regency, eastern Gianyar, and southern Badung. Meanwhile, the average coastal accretion was relatively high in the neck of South Bali, in areas where the land cover was mangrove and adjacent to river mouths, which experienced much sedimentation

リモートセンシング ト GIS ニ ヨル トチ リヨウ トチ ヒフク ノ ヘンカ ノ スイテイ ニ ツイテ ：ガボン コク デ ラ モンダ ホゴ リン ノ バアイ

Foret Classee de la Mondah（FCM）ラ・モンダ保護林の土地利用・土地被覆（LULC）の変化について、定性的及び定量的に説明し、主な変動因子を求めた。このため、2000年4月7日にETM+、及び、2014年4月6日にOLIによる2時期の観測データについて、最尤法により分類後にLULCの変化を求めた。この結果、周辺地域の人口増加にともない宅地面積が20倍に急増し、不可逆的な人為的変化が見いだされた。これに加え、森林地域の面積が9.77%減少した。現地調査におけるGPSにより特定した位置情報、Google Earthによる高解像度データをサンプル領域の抽出あるいは分類結果の検証に利用した。LULCの持続的な管理を可能とするための保全政策を検討する段階で、政策立案者に対して、参照データとなる関連情報を見出すことができた。The Land Use / Land Cover (LUCL) changes in Foret Classee de la Mondah (FCM) in Gabon was studied to account for changes occurred in the past as a categorical and numerical changes and to explain their main driving causes. For this purpose, the LULC changes were analyzed using post-classification comparison technique, following to the maximum likelihood supervised classification, between two multi-temporal Landsat images of ETM+ and OLI, which were acquired on April 7th 2000 and April 6th 2014, respectively. Results highlighted irreversible human-induced changes, where the rapid growth of built-up areas exhibited 20 times from its initial area, because of the anthropogenic pressure of surrounding population. In addition, major changes occurred mainly in forested area with the loss of 9.77% of its initial area. During the classification process, the use of collateral data, such as GPS coordinates and high resolution images retrieved from ground survey and Google Earth, were extremely relevant to enhancement of sample selection of ROSs and for the validation of classification map as well. However, this study provided relevant findings which could be used as a reference for decision makers while developing conservation policies in order to generate sustainable LULC management practices

Online change detection techniques in time series: an overview

Time-series change detection has been studied in several fields. From sensor data, engineering systems, medical diagnosis, and financial markets to user actions on a network, huge amounts of temporal data are generated. There is a need for a clear separation between normal and abnormal behaviour of the system in order to investigate causes or forecast change. Characteristics include irregularities, deviations, anomalies, outliers, novelties or surprising patterns. The efficient detection of such patterns is challenging, especially when constraints need to be taken into account, such as the data velocity, volume, limited time for reacting to events, and the details of the temporal sequence.This paper reviews the main techniques for time series change point detection, focusing on online methods. Performance criteria including complexity, time granularity, and robustness is used to compare techniques, followed by a discussion about current challenges and open issue

Object detection for single tree species identification with high resolution aerial images

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesObject recognition is one of the computer vision tasks developing rapidly with the invention of Region-based Convolutional Neural Network (RCNN). This thesis contains a study conducted using RCNN base object detection technique to identify palm trees in three datasets having RGB images taken by Unnamed Aerial Vehicles (UAVs). The method was entirely implemented using TensorFlow object detection API to compare the performance of pre-trained faster RCNN object detection models. According to the results, best performance was recorded with the highest overall accuracy of 93.1 ± 4.5 % and the highest speed of 9m 57s from faster RCNN model which was having inceptionv2 as feature extractor. The poorest performance was recorded with the lowest overall accuracy of 65.2 ± 10.9% and the lowest speed of 5h 39m 15s from faster RCNN model which was having inception_resnetv2 as feature extractor

The Use of Landsat Imagery and Spatial Analysis to Detect Forest Cover Change and Degradation, and Determine Forest Management Suitability Indices in the Bago Mountain Region of Myanmar

The Bago Mountain region in Myanmar is known as the “Home of Teak” (Tectona grandis) due to the occurrence of natural teak forests. Nowadays, the composition of this valuable timber species is declining in the region. Thus, the first objective of this study was to quantify forest cover changes between 2000 and 2017. The second objective was to develop GIS models and determine potential sites for reforestation activities. The results revealed that between 2000 and 2017, the annual deforestation rate was 0.78%, and annual forest degradation rate was 1.35%. In addition to reporting the forest cover changes, this GIS land suitability analysis could provide important spatial information for immediate teak restoration planning and investments. The steps employed in this study can be referred to as a protocol for locating candidate sites for reforestation in other geographic areas

The Contribution of Indigenous Ecological Knowledge in Conservation of Enguserosambu Community Forest, Tanzania

Community managed forests constitute a significant proportion of the world\u27s forests, however, little is known regarding their condition or the details of how they are managed. Documented benefits of community managed forest include poverty alleviation and in some places a decrease in the rate of deforestation. Although some community based forests do not satisfy the IUCN definition of a protected areas, they provide valuable long term sustainability of forest products and many are also rich in biodiversity and support landscape conservation strategies. Forests are also home to many cultures including the indigenous people. Indigenous communities surrounding forest areas and other protected areas have developed patterns of resource use and management that reflect their intimate knowledge of local environments and ecosystems. However, indigenous knowledge is rarely documented or incorporated into science based or government run conservation planning. It is therefore the aim of this research to examine the contribution of indigenous ecological knowledge in the conservation of Enguserosambu Community Forest and surrounding rangelands. Specifically, the research aimed to; understand social mechanisms supporting indigenous ecological knowledge generation, accumulation and transmission, to examine the role of local indigenous institutions in supporting conservation of Enguserosambu Community Forest, and to assess if time-series aerial imagery support historical forest management practices shared as oral histories about land-use change by the communities. Case study design was used to explore the phenomenon in detail. Purposeful sampling was used to recruit research participants that could provide information rich in detail about indigenous forest management practices in the study area. Four villages were surveyed. Individual and group semi-structured interviews were conducted with customary elders, village leaders, forest user groups, NGO\u27s, and forest officers. One focus group discussion was conducted with a community conservation trust. A total of 57 individuals were interviewed, of which 19 were females. Interviews session lasted between 30 minutes and 2 hours. Most of the interviews were audio recorded. Interviews were conducted in either Swahili or Maa language. In case of the latter, translator was used during the interview process. Field noted were also recorded each time the researcher visited the villages. Thematic analysis was carried out for qualitative information using NVivo 10. To compare oral history with land cover change, satellite images with 30m spatial resolution were acquired from Landsat 7 and 8 for land cover change analysis. Satellite Imagery from February 2000 and February 2015 were selected for analysis. ArcGIS 10.2 was used to analyze satellite images for forest cover change

Integrative Assessment and Modelling of the Non Timber Forest Products Potential in Nuba Mountains of Sudan by Field Methods, Remote Sensing and GIS

Pressure imposed at any one place or point in time results in a complexity of spatial and temporal interactions within topographical ecosystems. It can be propagated through the system and may have implications for future ecosystem functions over a wide array of various spatial and temporal scales. Under conditions of wars and other socio-economic conflicts, these processes are most forceful in developing countries amidst declining economic growth, lack of awareness, deterioration of ecosystem services, loss of existing traditional knowledge bases and weak governance structures. Forests are an essential part of ecosystem services, not only as a resource but as a contributor to biological systems as well. They represent one of the most important sectors in the context of Environmental Change (EC), both from the point of mitigation as well as adaptation. While forests are projected to be adversely impacted under EC, they are also providing opportunities to mitigate these changes. Yet this is one of the least understood sectors, especially at the regional level - many of its fundamental metrics such as mitigation potential, vulnerability and the likely impacts of EC are still not well understood until now. Thus, there is a need for research and field investigations into the synergy of mitigation and adaptation so that the cost of addressing EC impacts can be reduced and the co-benefits can be increased. The aim of this study is to focus particularly on forest-based ecosystem services and to use forests as a strategy for inducing environmental change within the Nuba Mountains in Sudan, specifically for systems in poor condition under EC, and furthermore to explore forests as an entry point for investigating the relationship between urban and rural development and ecosystem services. In addition, the aim is also to raise understanding of the relations between patterns of local-level economic and demographic changes, the nature and value of local ecosystem services, and the role of such services in increasingly interlinked urban and rural livelihood systems. The methodology applied in the current research is three-pronged: a formal literature review, a socio–economic survey (based on semi-structured interviews of household heads via Rapid Rural Appraisal (RRA), with a focus on group discussions, informal meetings, free listening and key informant techniques), and multitemporal optical satellite data analysis (i.e. Landsat and RapidEye). Landsat imagery was utilized to gather the spatial characteristics of the region and to study the Land Use/Land Cover (LU/LC) changes during the period from 1984 to 2014. Meanwhile, RapidEye imagery was used to generate the tree species distribution map. Qualitative and quantitative techniques were applied to analyze socio-economic data. Moreover, Food Consumption Score (FCS) was used to gauge both diversity and frequency of food consumption in surveyed areas. Geographic object-based image analysis (i.e. K-Nearest Neighbour classifier and knowledge-based classifiers) based on a developed model of integrated features (such as vegetation indices, DEM, thematic layers and meteorological information) was applied. Post Classification Analysis (PCA) as well as Post Change Detection (PCD) techniques were used. Hotspot analysis was conducted to detect the areas affected by deforestation. Furthermore, Ordinary Least Squares regression (OLS), Autocorrelation (Moran's) analysis, and Geographically Weighted Regression analyses (GWR) were applied to address the interaction of the different socioeconomic/ecological factors on Non Timber Forest Products (NTFPs) collection and to simulate the dependency scenarios of NTFPs along with their impact on poverty alleviation. Additionally, simulation was performed to estimate the future forest density and predict the dependency on forest services. An increasing impact of intensive interactions between the rural and urban areas has long been acknowledged. However, recent changes in the global political economy and environmental systems, as well as local dynamics of the study area driven by war, drought and deforestation, have led to an increasing rapidity and depth in rural transformation, as well as to a significant impact on urban areas. Like most environmental problems, the effects of these drivers are complex and are stressed diversely across different geographic regions by the socio-political processes that underlie recent economic and cultural globalization. These interactions and processes have increasingly brought rapid changes in land cover, social, institutional and livelihood transformation across broad areas of South Kordofan. Moreover, the study unveils new dynamics such as high rates of migration and mobility by the indigenous population and the increasing domination of market-centric livelihoods in many villages that were once dominated by rural agricultural and natural resourcesbased socio-economic systems. Furthermore, the research highlights the significant roles of NTFPs and trees in contributing to Nuba Mountains’ economic development, food security and environmental health, indicating which requirements need to be addressed in order to improve these potentials. The study proves that drawing on a wide range of these products for livelihood strengthens rural people’s ability to deal with and adapt to both EC and extreme events. Moreover, the results underline the importance of participatory approaches of rural women and their impact on NTFPs management with recommendations of more emphasis on potential roles and the ability of women to participate in public fora. Furthermore, the study shows that the use of high-resolution satellite imagery, integrated with model-based terrestrial information, provides a precise knowledge about the magnitude and distribution of LU/LC patterns. These methods can make an important contribution towards a better understanding of EC dynamics over time. The study reveals that more information exchange is needed to inform actors and decision makers regarding specific experiences, capacity gaps and knowledge to address EC. Subsequently, new policies and strategies are required to much more specifically focus on how to deal with consequences of longer-term EC rather than with the impacts of sudden natural disasters

Respuesta hidrológica ante los cambios de uso y cobertura del suelo en la cuenca del río Chinchiná

Desde el punto de vista antrópico, actividades como la agricultura, la minería, la producción maderera y la ganadería, son invasivos y modifican su estructura. El conocimiento de la dinámica del espacio–temporal de la tierra, y como ésta puede condicionar el comportamiento hidrológico de los ríos, podría ser una herramienta de planificación del territorio. El régimen hidrológio de las cuencas está determinado por la interrelación sueloclima, la afectación de estos parámetros tiene consecuencias en la producción de caudal; el clima en la cuenca del río Chinchiná está influenciado por el fenómeno del ENSO, en el periodo 1981-2014 (Línea Base) la precipitación se incrementó en un 24% durante La Niña y se redujo 11% en el Niño, con relación al caudal el aumento es del 34% en los episodios fríos y la disminución fue del 22% en los cálidos. La caracterización del suelo de la cuenca se realiza por medio de la construcción de mapas de uso y cobertura a partir de imágenes satelitales Landsat 5, 7 y 8, de los años 1987, 1999 y 2014, en estos periodos se presenta una disminución de la cobertura boscosa y aumento de pastos y áreas agrícolas, en 1987 representaban el 45% (Bosques) - 22% (Cultivos), y en 2014 pasaron a ocupar el 29% (Bosques) – 35% (Cultivos) de la superficie de la cuenca. Los cambios en las coberturas generaron una reducción en el caudal con respecto al obtenido en la línea base que fue de 35.8%, 5.4% y 1.7% para los tres años, la escorrentía directa presentó un incremento en el porcentaje de cambio respecto a la línea base de 1.0%, 5.5% y 26.3% para los años 1987, 1999 y 2014, de igual forma los procesos de evapotranspiración, infiltración y flujo base presentaron afectaciones. Los resultados y análisis basados en información satelital (o de sensores remotos), aportan los conocimientos necesarios para realizar una adecuada gestión de los recursos hídricos y edáficos de las cuencasAbstract: From the anthropic point of view, activities such as agriculture, timber production and livestock are invasive and modify its structure. The knowledge of the space and time dynamics of the soil, and how the hydrological behavior of the rivers can be conditioned, could be a tool for territorial planning. The hydrological regime of the basins is determined by the interrelation of soil and climate, the affectation of these parameters has consequences in the flow production; the climate in the Chinchiná river basin is influenced by the ENSO, in the period 1981-2014 (Base line) precipitation increases by 24% during La Niña and is reduced by 11% in El Niño, in relation to the flow the increase is 34% in the cold episodes and the decrease is 22% in the warm ones. The soil characterization of the basin is made through the construction of maps of use and coverage of satellite images Landsat 5, 7 and 8, of the years 1987, 1999 and 2014, in these periods the decrease of forest cover is presented and increase in pastures and agricultural areas, in 1987 represented 45% (Forests) - 22% (Crops), and in 2014 they occupied 29% (Forests) - 35% (Crops) of the surface of the basin. The changes in coverage generated a reduction in the flow with respect to the base line of 35.8%, 5.4% and 1.7% for the three years, the direct runoff showed an increase in the percentage of change with respect to the base line of 1.0%, 5.5% and 26.3% for the years 1987, 1999 and 2014, in the same way the processes of evapotranspiration, infiltration and base flow offer affectations. The results and analysis in satellite information (or remote sensing), provide the necessary knowledge to carry out an adequate management of the water and soil resources of the basinsMaestrí