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Spatio-temporal changes in rice area at the northern limits of the rice cropping system in China from 1984 to 2013

Journal of Integrative Agriculture 2017年第2期16卷 360-367页

作者： LI Zhi-peng LONG Yu-qiao TANG Peng-qin TAN Jie-yang LI Zheng-guo WU Wen-bin HU Ya-nan YANG Peng Key Laboratory of Agri-informatics Ministry of Agriculture/Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural Sciences Institute of Agricultural Economics and Regional Planning Hunan Academy of Agricultural Sciences

Rice area has been expanding rapidly during the past 30 years under the influence of global change in northeastern China, which is the northernmost region of rice cultivation in China. However, the spatio-temporal dynamic changes in rice area are still unclear, although they may have important policy implications for environmental protection and adaptation to climate change. In this study, we aimed to identify the dynamic changes of the rice area in Heilongjiang Province of northeastern China by extracting data from multiple landsat images. The study used ground quadrats selected from Google Earth and the extraction of a confusion matrix to verify the accuracy of extraction. The overall accuracy of the extracted rice area was higher than 95% as a result of using the artificial neural network （ANN） classification method. The results showed that the rice area increased by approximately 2.4×10^6 ha during the past 30 years at an annual rate of 8.0×10^4 ha, and most of the increase occurred after 2000. The central latitude of the rice area shifted northwards from 46 to 47°N during the study period, and moved eastwards from 130 to 133°E. The rice expansion area accounted for 98% of the total change in rice area, and rice loss was notably rare. The rice expansion was primarily from dryland. In addition, rice cultivation in marshland and grassland played a minor role in the rice expansion in this region.

关键词： paddy rice landsat images artificial neural network Heilongjiang Province

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Erosion hotspot identified along the sandy coast of Shanwei: characteristics and origin

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Acta Oceanologica Sinica 2023年第7期42卷 91-102页

作者： Jitao Yu Yuanting Ding Lin Zhang Pei Liu Renfu Fan Hainan Academy of Ocean and Fisheries Sciences Haikou 571126China Yazhou Bay Innovation Institute Hainan Tropical Ocean UniversitySanya 572025China School of Geography and Environmental Sciences Hainan Normal UniversityHaikou 571158China

Based on the measured beach profile data of Sanzhou Bay from 2015 to 2019,an erosion hotspot was identified along the Shanwei coastline of eastern Guangdong,where the maximum retreat distance of the shoreline exceeded 80 m and the erosion rate was more than 20 m/*** determine the time at which the erosion hotspot started and the potential causes of its formation,this study used 63 landsat satellite images from 1986 to 2019 to construct a time series of shoreline positions over the past 30 years by extracting their high-tide ***,the M-K trend test method was introduced to evaluate the non-linear shoreline behavior based on the single-transect *** results showed that the time of approximately 2013 marked the start of the erosion hotspot,the erosion hotspot was characterized by erosion rates of more than 2 m/a(a maximum rate of 31.6 m/a),and the affected shoreline more than 4.3 km from 2013 to ***,this erosion hotspot was proved to be caused by artificial sand mining in the nearshore zone,which destroyed the original beach’s morphodynamic *** the aid of storm events,soil cliffs composed of loose sediment on the backshore were sacrificed to achieve a new equilibrium,resulting in an extremely significant retreat parallel to the coast on the west side of the study area,which reflects the combined effect of human and natural *** study provides a concrete example of the rapid response of shorelines to artificial sand mining activities,and the associated finding is a stark warning about the cautious development and utilization of coastal zones and the strict regulation of human activities.

关键词： erosion hotspot shoreline non-linear behavior artificial sand mining beach morphodynamic equilibrium landsat images

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Remote sensing study of wetlands in the Pearl River Delta during 1995-2015 with the support vector machine method

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Frontiers of Earth Science 2018年第3期12卷 521-531页

作者： Xiaosong HAN Jiayi PAN Adam T. DEVLIN Institute of Space and Earth Information Science The Chinese University of Hong Kong Hong Kong China

In recent years, experienced rapid economic the Pearl River Delta has growth which may create a substantial burden to its ecology. In this study, the wetlands of the Pearl River Delta are investigated. Through the use of remote sensing methods, we analyze spatial and temporal variations of wetlands in this area over the past twenty years. The support vector machine （SVM） method is proven to be an effective approach for classifying the wetlands of the Pearl River Delta, and the total classifica- tion resolution reaches 94.94% with a Kappa coefficient exceeding 0.94, higher than other comparable analysis methods. Our results show that wetland areas were reduced by 36.9% during the past twenty years. The change detection analysis method shows that there was a 95.58% intertidal zone change to other land-use types, most of which （57.12%） was converted to construction land. In addition, farmland was reduced by 54.89% during the past twenty years, 47.19% of which was changed to construction land use. The inland water area increased 19.02%, but most of this growth （18.77%） was converted from the intertidal zone.

关键词： wetland Pearl River Delta support vector machine method landsat images

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Lineament analysis as a seismic precursor:The El Mayor Cucapah earthquake of April 4,2010(MW7.2),Baja California,Mexico

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Geodesy and Geodynamics 2023年第2期14卷 121-129页

作者： Rosendo Romero-Andrade Manuel E.Trejo-Soto Karan Nayak Daniel Hernández-Andrade Naccieli Bojorquez-Pacheco Faculty of Earth and Space Sciences Autonomous University of Sinaloa80013Culiacan RosalesSinaloaMexico

An earthquake called the MW7.2“El Mayor Cucapah”earthquake on April 4,2010 has been analyzed for seismic *** changes in the lineament system concerning its pattern and time intervals were analyzed during the earthquake preparation period and occurrence using the automated lineament detection *** landsat 5 TM images were processed using LESSA and ADALGEO software obtaining similar *** statistical analysis revealed the stress accumulation due to plate interaction during earthquake *** study shows that the number of extracted lineaments changes rapidly about 23 months before the earthquake,and the systems return to the initial stage after 23 *** lineaments coincide with the extension of the San Andreas Fault as NW direction is the dominant ***,it can be concluded that the featural changes within the Rose diagram corresponding to the different strokes direction along with oriented elongation lines as disclosed in the present study using satellite images could be identified as a mid-term and/or short-term precursors of the ***,even though the dynamism of the El Mayor Cucapah earthquake is found in the extracted lineaments,it is possible to isolate more significant earthquakes even if new ones appear near the ***,using two algorithms for lineament detection allows for the tectonics to corroborate the obtained lineaments and dynamism.

关键词： Lineament analysis Earthquake landsat images Seismic precursor

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Long-term coastal erosion assessment along the coast of Karnataka,west coast of India

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International Journal of Sediment Research 2019年第4期34卷 335-344页

作者： K.Sowmya M.Dhivya Sri Aparna S.Bhaskar K.S.Jayappa Department of Marine Geology Mangalore University Department of Geography University of Madras Department of Civil Engineering SRM Institute of Science and Technology

Coastal areas are always under frequent threat from various natural processes and man-induced *** erosion is recognized as the permanent loss of land along the shoreline resulting in the transformation of the coast. The current study focuses on long-term coastal erosion analysis of the entire Karnataka coast using Remote Sensing, Geographical Information System(GIS), Linear Regression Rate(LRR), and End Point Rate(EPR) techniques. Analysis of 26(1990 to 2016) years of erosion using landsat images by the use of the Digital Shoreline Analysis System(DSAS) tool has been done. The results show a high erosion rate at Ullal during this period(LRR-1.3 m/yr) and accretion at Devbagh(LRR 3.2 m/yr). The southern Karnataka coast faces severe erosion especially at Ullal, where the settlement is high. At Thanirbhavi, Mukka, Kota,and Om Beaches erosion also is noticed. Both anthropogenic activities like ports, seawalls, breakwaters, *** natural processes like long shore drift, seasonal variation, etc. are factors affecting the shoreline change along the Karnataka coast.

关键词： Karnataka coast landsat images Erosion Linear Regression Rate End Point Rate

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Coastline Change Modelling Induced by Climate Change Using Geospatial Techniques in Togo (West Africa)

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Advances in Remote Sensing 2020年第2期9卷 85-100页

作者： Yawo Konko Appollonia Okhimambe Pouwèréou Nimon Jerry Asaana Jean Paul Rudant Kouami Kokou National Environmental Observatory National Agency of Environment Management Lome Togo West African Science Service Centre on Climate Change and Adapted Land Use Federal University of Technology Minna Nigeria National Meteorological Service Lome Togo Department of Civil Engineering Bolgatanga Technical University Bolgatanga Ghana LASTIG Gustave Eiffel University ENSG IGN Champs-sur-Marne France Laboratory of Forest Research Faculty of Sciences University of Lome Lome Togo

Climate change is a major concern of humanity. One of the consequences of climate change is global warming causing melting glaciers, rising sea levels and shoreline regression. In Togo, the regression of shoreline leads to coastal erosion with significant damage on socio-economic infrastructures and human habitats. This research, basing on geospatial techniques, focuses on coastal erosion monitoring from 1988 to 2018 in Togo. It is interested in the extraction of shoreline and in the analysis of change. Various satellite images indexes have been developed for shoreline extraction but the major scientific problem concerns the precision of the different classification algorithms methods used for the extraction of the shoreline from these water index. This study used NDWI index from multisource satellite images. It assesses the performance of Otsu threshold segmentation, Iso Cluster Unsupervised Classification and Support Vector Machine (SVM) Supervised Classification methods for the extraction of the shoreline on NDWI index. The topographic morphology such as linear and non-linear coastal surfaces have been considered. The estimation of the rates of change of the shoreline was performed using the statistical linear regression method (LRR). The results revealed that the SVM Supervised Classification method showed good performance on linear and non-linear coastal surface than the other methods. For the kine

关键词： Coastal Erosion landsat images NDWI Remote Sensing Sentinel images Shoreline SVM

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A Comparative Study of Image Classification Algorithms for Landscape Assessment of the Niger Delta Region

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Journal of Geographic Information System 2016年第2期8卷 163-170页

作者： Omoleomo Olutoyin Omo-Irabor Department of Earth Sciences College of Science Federal University of Petroleum ResourcesEffurun Nigeria

A critical problem associated with the southern part of Nigeria is the rapid alteration of the landscape as a result of logging, agricultural practices, human migration and expansion, oil exploration, exploitation and production activities. These processes have had both positive and negative effects on the economic and socio-political development of the country in general. The negative impacts have led not only to the degradation of the ecosystem but also posing hazards to human health and polluting surface and ground water resources. This has created the need for the development of a rapid, cost effective and efficient land use/land cover (LULC) classification technique to monitor the biophysical dynamics in the region. Due to the complex land cover patterns existing in the study area and the occasionally indistinguishable relationship between land cover and spectral signals, this paper introduces a combined use of unsupervised and supervised image classification for detecting land use/land cover (LULC) classes. With the continuous conflict over the impact of oil activities in the area, this work provides a procedure for detecting LULC change, which is an important factor to consider in the design of an environmental decision-making framework. Results from the use of this technique on landsat TM and ETM+ of 1987 and 2002 are discussed. The results reveal the pros and cons of the two methods and the effects of their overall accuracy on post-classification change detection.

关键词： Land Cover Supervised and Unsupervised Classification Algorithms landsat images Change Detection Niger Delta

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Land Use and Land Cover Dynamics in the Eseka Alluvial Gold Mining District, Centre Region, Cameroon

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Journal of Geographic Information System 2024年第4期16卷 289-305页

作者： Shu Vejiline Lum-Ndob Fonge Beatrice Ambo Ambe Godlove Neba Ateh Kevin Ijunghi Enerst Tata Cheo Emmanuel Suh Department of Plant Science Faculty of Science University of Buea Buea Cameroon Department of Mining and Mineral Engineering National Higher Polytechnic Institute The University of Bamenda Bambili Cameroon Economic Geology Unit Department of Geology Faculty of Science University of Buea Buea Cameroon Department of Geology Mining and Environmental Science The University of Bamenda Bambili Cameroon

Local populations in Cameroon thrive on forest resources and the flow of ecosystem services they provide are pivotal in sustaining national economy, improving people’s lives, safeguarding biodiversity, and mitigating the impacts of environmental changes. The exploitation of these resources invariably leads to deforestation and forest degradation. This study was designed to evaluate land use land cover change (LULCC) in the Eseka alluvial gold mining district with the aid of landsat images. In the investigation of forest cover change, four landsat satellite images for (1990, 2002, 2015 and 2022) were used. Ground-truthing also helped to identify the activities carried out by the local population and to determine agents, drivers and pressures of land use and land cover change. Four main land cover classes namely: forest, agricultural land, settlement/mining camps and water bodies were selected. Between 1990 and 2022, the proportion of forest decreased from 98% to 34% while those of agricultural land and settlement/mining camps increased from 2% to 60% and 0.54% to 6% respectively. Analysis showed ongoing deforestation with forest cover loss of ~98,263 ha in 32 years giving a cover change percentage of 63.94%. Kappa coefficient for the study period ranged from 0.92 to 0.99. Forest cover loss could be attributed to farming activities, wood extraction and alluvial gold mining activities. Economic motives notably the need to increase household income from a frequent demand for farm and wood products in neighbouring towns and the quest for gold were the main drivers of these activities. Hence, this study assesses the impact of human activities from the mining sector on the forest ecosystem in a bid to inform mitigation policies.

关键词： Land Use and Land Cover Changes Biodiversity Alluvial Gold Mining Drivers landsat images Ground-Truthing Mitigation

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Monitoring of coastline changes along the Red Sea,Yemen based on remote sensing technique

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Global Geology 2011年第4期14卷 241-248页

作者： Aref A.Sagheer Ahmed Humade Aref M.O.Al-Jabali Marine Science and Environment Faculty Hodeidah UniversityYemen Geological Survey and Mineral Resources Board Sana'aYemen

The coastline changes along Yemen＇s the Red Sea （Al-muka, Al-khohah, Al-tiaf, Ras Katib and Al- Urji spits） were studied using a series of landsat images （MSS, TM and ETM ＋ , 1972, 1989, 2000, 2006）, coupled with geomorphological, sedimentological and meteorological findings. Comparison of satellite images provided a viable means for establishing long-term coastal changes （accretion and erosion） as observed in the studied spits （Al-Urj, Ras Sham, Ras Maemoon, Ras Katib, Al-Mandar, Nukhaylah, Mujamilah, Ras Ashab Abu-Zahr and Mukha）. The rate of the spit accretion has the greatest value up to 89 pixel/year corresponding to 72 290 m2/year in Mukha, while the spit erosion shows greatest value up to 131 pixel/year corresponding to 106 404 m2/year in Mujamilab. The patterns of accretion and erosion along the spits depend on the spit direction, natural processes mainly of wave-induced longshore currents, the sediments supply and depth of sea.

关键词： coastline change landsat images Yemen Red Sea

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The Dynamics of Urbanization and Its Effects on Rural Livelihoods:Evidence from Adama City and Adama Rural District, Ethiopia

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Chinese Journal of Urban and Environmental Studies 2024年第2期12卷 113-131页

作者： Wakitole DADI Negussie SIMIE Messay MULUGETA Center for Rural Development Studies Addis Ababa University Center for Food Security Studies Addis Ababa University

Rapid urbanization in cities brings about both opportunities and challenges for national development. This study focuses on investigating the dynamics of urbanization and its impact on livelihoods using land use/land cover change in Adama City, located in the Oromia Regional State. Various datasets from the U.S. Geological Survey(USGS), including landsat Thematic Mapper(LTM), landsat Enhanced Thematic Mapper Plus(ETH+), and Operational Land Imager(OLI), were utilized. Geographic Information System(GIS) and remote sensing tools were employed to extract relevant information from these datasets for years from 1986 to 2022. In addition, findings pertain to the impact of urbanization on income diversification and the overall welfare of farm households near Adama City was aligned with the study. The findings reveal that built-up areas and agricultural land exhibit the most significant changes over the examined ***, these changes occur in opposite directions. The built-up area has experienced a substantial increase of 60% from 1986 to 2022, while agricultural land has decreased by 40% during the same timeframe. The conversion of farmland to built-up areas negatively impacts farm households by reducing farming activities and increasing reliance on non-farm activities, resulting in lower consumption expenditures for rural households near urban areas compared to those farther from the urban center. The result underscores the need for policies that promote appropriate land management and a well-planned urbanization process to ensure sustainable urban development. Furthermore, it is vital to enhance understanding of the spatial and temporal dynamics of urban growth and its impacts on farm households residing near urban areas. By addressing these issues, sustainable food security and poverty reduction objectives can be better achieved in peri-urban areas of the region.

关键词： Agricultural land built-up area farm households landsat images urbanization

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