Characterization of land cover types in Xilin River Basin using multi-temporal Landsat images

2003 ◽  
Vol 13 (2) ◽  
pp. 131-138 ◽  
Author(s):  
Chen Siqing ◽  
Liu Jiyuan ◽  
Zhuang Dafang ◽  
Xiao Xiangming
Keyword(s):  
Land Cover ◽  
River Basin ◽  
Landsat Images ◽  
Land Cover Types ◽  
Multi Temporal

Integration of Satellite Remote Sensing Techniques and Landscape Metrics to Characterize Land Cover Change and Dynamics

2013 ◽  
pp. 228-244
Author(s):  
Carmelo Riccardo Fichera ◽  
Giuseppe Modica ◽  
Maurizio Pollino
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Landscape Metrics ◽  
Landsat Images ◽  
Aerial Photos ◽  
Multi Temporal ◽  
Urban Rural ◽  
Remote Sensing Techniques

One of the most relevant applications of Remote Sensing (RS) techniques is related to the analysis and the characterization of Land Cover (LC) and its change, very useful to efficiently undertake land planning and management policies. Here, a case study is described, conducted in the area of Avellino (Southern Italy) by means of RS in combination with GIS and landscape metrics. A multi-temporal dataset of RS imagery has been used: aerial photos (1954, 1974, 1990), Landsat images (MSS 1975, TM 1985 and 1993, ETM+ 2004), and digital orthophotos (1994 and 2006). To characterize the dynamics of changes during a fifty year period (1954-2004), the approach has integrated temporal trend analysis and landscape metrics, focusing on the urban-rural gradient. Aerial photos and satellite images have been classified to obtain maps of LC changes, for fixed intervals: 1954-1985 and 1985-2004. LC pattern and its change are linked to both natural and social processes, whose driving role has been clearly demonstrated in the case analysed. In fact, after the disastrous Irpinia earthquake (1980), the local specific zoning laws and urban plans have significantly addressed landscape changes.

scholarly journals Topography as a macroscopic index for the dissolved iron productivity of different land cover types in the Amur River Basin

2010 ◽  
Vol 4 ◽  
pp. 85-89 ◽  
Author(s):  
Takeo Onishi ◽  
Muneoki Yoh ◽  
Hideaki Shibata ◽  
Seiya Nagao ◽  
Masayuki Kawahigashi ◽  
...  
Keyword(s):  
Land Cover ◽  
River Basin ◽  
Amur River Basin ◽  
Amur River ◽  
Land Cover Types ◽  
Dissolved Iron ◽  
The Amur River

Impact of a volcanic eruption on the sediment connectivity of a Chilean river basin: the Calbuco study case

2021 ◽  
Author(s):  
Marco Andreoli ◽  
Lorenzo Martini ◽  
Marco Cavalli ◽  
Andrés Iroumé ◽  
Lorenzo Picco
Keyword(s):  
Land Cover ◽  
River Basin ◽  
Volcanic Eruption ◽  
Overland Flow ◽  
Volcanic Eruptions ◽  
Landsat 8 ◽  
Strong Impact ◽  
Low Resolution ◽  
Multi Temporal ◽  
Sediment Connectivity

<p>Volcanic eruptions are natural disturbances capable of introducing large quantities of sediment into river systems as to upset the transport regime for several years. Such a disturbance can have a strong impact on the water and sediment flows and consequently on the transport capacity. Moreover, changes in morphological settings and land cover lead to an alteration of the sediment connectivity within the catchment. This study aims to investigate the changes of sediment connectivity in a catchment affected by an explosive volcanic eruption using the Index of Connectivity (IC) with a multi-temporal approach. Potential variations were analyzed at the catchment scale over a period of 6 years, before and after the eruption. The study area, located in southern Chile, is the Blanco Este River basin (39,6 km²), affected by the eruption of the Calbuco volcano (April 2015, total volume of sediment expelled of about 0,28 km³) which profoundly changed its vegetation cover, geomorphology and hydrology. IC analyses were based on low-resolution and freely available data (i.e., GDEM, Landsat 8 satellite images). Through supervised image classification and field data survey, a Manning's n coefficient for overland flow is derived as weighting factor (W) due to its suitability to represent the impedance to sediment flows in catchments characterized by land cover variations. Following the eruption, bare soil cover on the basin doubled (from 5% to 10% of total basin area). Consequently, the multi-temporal analysis results in an overall increase of IC with the median value ranges from -3,58 to -3,26 in pre-eruptive (2015) and first post-eruptive scenario (2016), respectively. The connectivity maps show that the higher IC values (i.e. range from -1,23 to 1,66) are persistently located in three areas: at the base of the volcanic dome, on the steepest slopes near the main channel and in a sub-basin on the right side of the catchment. Moreover, the Difference of IC (DoIC) among different scenarios highlighted the major variations. Such changes are found along the volcano slopes, in a flat area located in the upper part of the basin and along the lower valley of the Rio Blanco Este. The study proposes a useful methodology to evaluate the sediment connectivity, and its evolutionary trends, in environments affected volcanic eruptions starting from low-resolution data and field survey. These results may help to better define types, location and typologies of interventions to improve the river management approaches, considering the ongoing cascading processes. This research is funded by the Fondecyt 1200079 project.</p>

scholarly journals CHARACTERIZATION OF LAND COVER SEASONALITY IN SENTINEL-1 TIME SERIES DATA

2020 ◽  
Vol V-3-2020 ◽  
pp. 97-104
Author(s):  
C. Dubois ◽  
M. M. Mueller ◽  
C. Pathe ◽  
T. Jagdhuber ◽  
F. Cremer ◽  
...  
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Time Series Data ◽  
Coniferous Forest ◽  
Series Data ◽  
Urban Land Cover ◽  
Multi Temporal ◽  
Forested Areas

Abstract. In this study, we analyze Sentinel-1 time series data to characterize the observed seasonality of different land cover classes in eastern Thuringia, Germany and to identify multi-temporal metrics for their classification. We assess the influence of different polarizations and different pass directions on the multi-temporal backscatter profile. The novelty of this approach is the determination of phenological parameters, based on a tool that has been originally developed for optical imagery. Furthermore, several additional multitemporal metrics are determined for the different classes, in order to investigate their separability for potential multi-temporal classification schemes. The results of the study show a seasonality for vegetation classes, which differs depending on the considered class: whereas pastures and broad-leaved forests show a decrease of the backscatter in VH polarization during summer, an increase of the backscatter in VH polarization is observed for coniferous forest. The observed seasonality is discussed together with meteorological information (precipitation and air temperature). Furthermore, a dependence of the backscatter of the pass direction (ascending/descending) is observed particularly for the urban land cover classes. Multi-temporal metrics indicate a good separability of principal land cover classes such as urban, agricultural and forested areas, but further investigation and use of seasonal parameters is needed for a distinct separation of specific forest sub-classes such as coniferous and deciduous.

Mapping land cover of the Yellow River source using multi-temporal Landsat images

2010 ◽  
Author(s):  
Yong Hu ◽  
Liangyun Liu ◽  
Lingling Liu ◽  
Quanjun Jiao ◽  
Jianhua Jia
Keyword(s):  
Land Cover ◽  
Yellow River ◽  
The Yellow River ◽  
Landsat Images ◽  
Multi Temporal ◽  
Yellow River Source

scholarly journals Classification of Land Use/Land Cover Changes Using GIS and Remote Sensing Technique in Lake Kenyir Basin, Terengganu, Malaysia

2018 ◽  
Vol 7 (3.14) ◽  
pp. 12 ◽  
Author(s):  
Mohd Khairul Amri Kamarudin ◽  
Kabir Abdulkadir Gidado ◽  
Mohd Ekhwan Toriman ◽  
Hafizan Juahir ◽  
Roslan Umar ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Water Body ◽  
Geographical Information ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technique ◽  
Multi Temporal ◽  
Vegetation Water

Geographical information system (GIS) techniques and Remote Sensing (RS) data are fundamental in the study of land use (LU) and land cover (LC) changes and classification. The aim of this study is to map and classify the LU and LC change of Lake Kenyir Basin within 40 years’ period (1976 to 2016). Multi-temporal Landsat images used are MSS 1976, 1989, ETM+ 2001 and OLI 8 2016. Supervised Classification on Maximum Likelihood Algorithm method was used in ArcGIS 10.3. The result shows three classes of LU and LC via vegetation, water body and built up area. Vegetation, which is the dominant LC found to be 100%, 88.83%, 86.15%, 81.91% in 1976, 1989, 2001 and 2016 respectively. While water body accounts for 0%, 11.17%, 12.36% and 13.62% in the years 1976, 1989, 2001 and 2016 respectively and built-up area 1.49% and 4.47 in 2001 and 2016 respectively. The predominant LC changes in the study are the water body and vegetation, the earlier increasing rapidly at the expense of the later. Therefore, proper monitoring, policies that integrate conservation of the environment are strongly recommended. 

scholarly journals Spatial and Temporal Characteristics and Driving Forces of Vegetation Changes in the Huaihe River Basin from 2003 to 2018

2020 ◽  
Vol 12 (6) ◽  
pp. 2198 ◽  
Author(s):  
Zhenzhen Liu ◽  
Hang Wang ◽  
Ning Li ◽  
Jun Zhu ◽  
Ziwu Pan ◽  
...  
Keyword(s):  
Land Cover ◽  
River Basin ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Changes ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Land Cover Types ◽  
The Huaihe River

In this study, MODIS normalized difference vegetation index (NDVI), TRMM3B43 precipitation, and MOD11A2 land-surface temperature (LST) data were used as data sources in an analysis of temporal and spatial characteristics of vegetation changes and ecological environmental quality in the Huaihe River basin, China, from 2003 to 2018. The Mann–Kendall (MK) non-parametric test and the Theil–Sen slope test were combined for this analysis; then, when combined with the results of the MK mutation test and two introduced indexes, the kurtosis coefficient (KU) and skewness (SK) and correlations between NDVI, precipitation (TRMM), and land-surface temperature (LST) in different time scales were revealed. The results illustrate that the mean NDVI in the Huaihe River basin was 0.54. The annual NDVImax curve fluctuations for different land cover types were almost the same. The main reasons for the decrease in or disappearance of vegetation cover in the Huaihe River basin were the expansion of towns and impact of human activities. Furthermore, vegetation cover around water areas was obviously degraded and wetland protections need to be strengthened urgently. On the same time scale, change trends of NDVI, TRMM, and LST after abrupt changes became consistent within a short time period. Vegetation growth was favored when the KU and SK of TRMM had a close to normal distribution within one year. Monthly TRMM and LST can better reflect NDVI fluctuations compared with seasonal and annual scales. When the precipitation (TRMM) is less than 767 mm, the average annual NDVI of different land cover types is not ideal. Compared with other land cover types, dry land has stronger adaptability to changes in the LST when the LST is between 19 and 22.6 °C. These trends can serve as scientific reference for protecting and managing the ecological environment in the Huaihe River basin.

scholarly journals Spatial Representativeness of Gross Primary Productivity from Carbon Flux Sites in the Heihe River Basin, China

2021 ◽  
Vol 13 (24) ◽  
pp. 5016
Author(s):  
Tao Yu ◽  
Qiang Zhang ◽  
Rui Sun
Keyword(s):  
Land Cover ◽  
River Basin ◽  
Primary Productivity ◽  
Carbon Flux ◽  
Multiple Scale ◽  
Heihe River Basin ◽  
Heihe River ◽  
Field Scale ◽  
Land Cover Types ◽  
The Heihe River Basin

Studying the spatial representativeness of carbon flux measurement data for typical land cover types can provide important information for benchmarking Earth system models and validating multiple-scale remote sensing products. In our study, daily gross primary productivity (GPP) was firstly derived from eddy covariance observation systems and seasonal variations in field GPP were analyzed at nine flux tower sites for typical land cover types in the Heihe River Basin, China. Then, the real-time footprint distance and climate footprint distance of the field GPP were obtained by using a footprint source area model. Lastly, multiple-scale GPP products were validated at footprint scale, and the impacts (measurement height, surface roughness and turbulent state of the atmosphere) on the footprint distance of field GPP were analyzed. The results of this paper demonstrated that climate footprint distances ranged from about 500 m to 1500 m for different land cover types in the Heihe River Basin. The accuracy was higher when validating MODIS GPP products at footprint scale (R2 = 0.56, RMSE = 3.07 g C m−2 d−1) than at field scale (R2 = 0.51, RMSE = 3.34 g C m−2 d−1), and the same situation occurred in the validation of high-resolution downscaled GPP (R2 = 0.85, RMSE = 1.34 g C m−2 d−1 when validated at footprint scale; R2 = 0.82, RMSE = 1.47 g C m−2 d−1 when validated at field scale). The results of this study provide information about the footprints of field GPP for typical land cover types in arid and semi-arid areas in Northwestern China, and reveal that precision may be higher when validating multiple-scale remote sensing GPP products at the footprint scale than at the field scale.

scholarly journals Specific features of NDVI, NDWI and MNDWI as reflected in land cover categories

2016 ◽  
Vol 10 (3-4) ◽  
pp. 194-202 ◽  
Author(s):  
Szilárd Szabó ◽  
Zoltán Gácsi ◽  
Boglárka Balázs
Keyword(s):  
Land Cover ◽  
Global Scale ◽  
Spectral Indices ◽  
Landsat Images ◽  
Land Cover Types ◽  
Environmental Processes ◽  
Landsat 7 ◽  
Great Possibility ◽  
Remote Sensing Techniques ◽  
Cover Class

The remote sensing techniques provide a great possibility to analyze the environmental processes inlocal or global scale. Landsat images with their 30 m resolution are suitable among others for landcover mapping and change monitoring. In this study three spectral indices (NDVI, NDWI, MNDWI) wereinvestigated from the aspect of land cover types: water body (W); plough land (PL); forest (F); vineyard(V); grassland (GL) and built-up areas (BU) using Landsat-7 ETM+ data. The range, the dissimilaritiesand the correlation of spectral indices were examined. In BU – GL – F categories similar NDVI valueswere calculated, but the other land cover types differed significantly. The water related indices (NDWI,MNDWI) were more effective (especially the MNDWI) to enhance water features, but the values of othercategories ranged from narrower interval. Weak correlation were found among the indices due to thedifferences caused by the water land cover class. Statistically, most land cover types differed from eachother, but in several cases similarities can be found when delineating vegetation with various watercontent. MNDWI was found as the most effective in highlighting water bodies.

scholarly journals Land Use and Land Cover Dynamics and Assessing the Ecosystem Service Values in the Trans-Boundary Gandaki River Basin, Central Himalayas

2018 ◽  
Vol 10 (9) ◽  
pp. 3052 ◽  
Author(s):  
Raju Rai ◽  
Yili Zhang ◽  
Basanta Paudel ◽  
Bipin Acharya ◽  
Laxmi Basnet
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Cover ◽  
River Basin ◽  
Ecosystem Service ◽  
Satellite Image ◽  
Landsat 8 ◽  
Barren Land ◽  
Central Himalayas ◽  
Land Cover Types

Land use and land cover is a fundamental variable that affects many parts of social and physical environmental aspects. Land use and land cover changes (LUCC) has been known as one of the key drivers of affecting in ecosystem services. The trans-boundary Gandaki River Basin (GRB) is the part of Central Himalayas, a tributary of Ganges mega-river basin plays a crucial role on LUCC and ecosystem services. Due to the large topographic variances, the basin has existed various land cover types including cropland, forest cover, built-up area, river/lake, wetland, snow/glacier, grassland, barren land and bush/shrub. This study used Landsat 5-TM (1990), Landsat 8-OLI (2015) satellite image and existing national land cover database of Nepal of the year 1990 to analyze LUCC and impact on ecosystem service values between 1990 and 2015. Supervised classification with maximum likelihood algorithm was applied to obtain the various land cover types. To estimate the ecosystem services values, this study used coefficients values of ecosystem services delivered by each land cover class. The combined use of GIS and remote sensing analysis has revealed that grassland and snow cover decreased from 10.62% to 7.62% and 9.55% to 7.27%, respectively compared to other land cover types during the 25 years study period. Conversely, cropland, forest and built-up area have increased from 31.78% to 32.67%, 32.47–33.22% and 0.19–0.59%, respectively in the same period. The total ecosystem service values (ESV) was increased from 50.16 × 108 USD y−1 to 51.84 × 108 USD y−1 during the 25 years in the GRB. In terms of ESV of each of land cover types, the ESV of cropland, forest, water bodies, barren land were increased, whereas, the ESV of snow/glacier and grassland were decreased. The total ESV of grassland and snow/glacier cover were decreased from 3.12 × 108 USD y−1 to 1.93 × 108 USD y−1 and 0.26 × 108 USD y−1 to 0.19 × 108 USD y−1, respectively between 1990 and 2015. The findings of the study could be a scientific reference for the watershed management and policy formulation to the trans-boundary watershed.

Sign in / Sign up

Export Citation Format

Share Document