scholarly journals Spatio-Temporal Variations of Land-Cover Types in Osho Forest Reserve, Southwestern Nigeria

2019 ◽  
Vol 7 (5) ◽  
pp. 168
Author(s):  
Olufunke Olubusayo Olayode
Keyword(s):  
Land Cover ◽  
Temporal Variations ◽  
Southwestern Nigeria ◽  
Forest Reserve ◽  
Land Cover Types ◽  
Spatio Temporal

Remote sensing and GIS forest landscape assessment for sustainable forest management

2021 ◽  
Vol 17 (1) ◽  
pp. 12-26
Author(s):  
A.F. Chukwuka ◽  
A. Alo ◽  
O.J. Aigbokhan
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Forest Cover ◽  
Sustainable Forest Management ◽  
Markov Chain Model ◽  
Remote Sensing Data ◽  
Chain Model ◽  
Spatial Metrics ◽  
Forest Reserve ◽  
Land Cover Types

This study set out to assess the dynamic characteristics of the Ikere forest reserve landscape between 1985 and 2017 using remote sensing data and spatial metrics. Landscape of the study area maintained complex patterns of spatial heterogeneity over the years. Forest cover loss to other land cover types results in new large non-forest area at increasing rate. As at the year 2017, the changes in land cover types were not yet at equilibrium, thus the need to determine the future forest cover extent using a three-way markov Chain model. The decrease in number of patches of forest land (NumP) with increase in its mean patch size (MPS) shows that the forest is becoming a single unit probably due to clearing of existing patches of forest trees. The decrease in class diversity and evenness (SDI and SEI) of the general landscape over the years strengthens this assertion. The findings of this study would be very helpful to government and other stakeholders responsible for ensuring sustainable forest and general environment. Keyword: Landscape, Spatial metrics, sustainable forest and Environment

scholarly journals Spatio-temporal variations in soil hydrology of a typical semiarid sand-meadow-desert landscape

2011 ◽  
Vol 8 (1) ◽  
pp. 1895-1928 ◽  
Author(s):  
L. Duan ◽  
T. Liu ◽  
X. Wang ◽  
G. Wang ◽  
L. Ma ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Cover ◽  
Physicochemical Properties ◽  
Fine Particles ◽  
Temporal Variations ◽  
P Value ◽  
Horqin Sandy Land ◽  
Sandy Land ◽  
Spatio Temporal ◽  
Semiarid Land

Abstract. A good understanding of the interrelations between land cover alteration and changes in hydrologic conditions (e.g., soil moisture) as well as soil physicochemical properties (e.g., fine particles and nutrients) is crucial for maintaining the fragile hydrologic and environmental conditions of semiarid land, such as the Horqin Sandy Land in China, but is lacking in existing literature. The objectives of this study were to examine: (1) spatio-temporal variations of soil moisture and physicochemical properties in semiarid land; and (2) how those variations are influenced by land cover alteration. Using the data collected in a 9.71 km2 well-instrumented area of the Horqin Sandy Land, this study examined by visual examination and statistical analyses the spatio-temporal variations of soil moisture and physicochemical properties. The results indicated that for the study area, the soil moisture and physicochemical properties were dependent on local topography, soil texture, vegetation density, and human activity. Long-term reclamation for agriculture was found to reduce soil moisture by over 23% and significantly (p-value < 0.05) lower the contents of soil organic matter, fine particles, and nutrients.

scholarly journals ANALYZING THE EFFECTS OF LAND COVER CHANGE ON SURFACE TEMPERATURE IN MOUNT MAKILING FOREST RESERVE (MMFR) AND ITS NEIGHBORING MUNICIPALITIES USING LANDSAT DATA

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 165-172
Author(s):  
V. K. M. Del Mundo ◽  
C. L. Tiburan Jr.
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Cover Change ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Centers ◽  
Forest Reserve ◽  
Land Cover Types ◽  
Rapid Economic Growth ◽  
Supervised Image Classification

Abstract. Land Surface Temperature (LST) is said to be affected by frequent changes in the land cover. Over the years, the immediate environs of Mount Makiling Forest Reserve (MMFR) have experienced such kind of change due to rapid economic growth of the area that also led to the expansion of urban centers. The study utilized Landsat imageries to determine the possible effects of land cover change on surface temperature using the integration of remote sensing and GIS technologies. Initially, the multispectral bands were radiometrically corrected using Dark Object Subtraction (DOS) while the thermal bands were corrected using Land Surface Emissivity (LSE). After these corrections were applied, the images were classified using supervised image classification technique where seven land cover types have been identified. The classified images were then validated using 200 reference data and this revealed an overall accuracy of 87.5% and 86.0% for the May 2003 and July 2015 images, respectively. Results showed that changes in land cover resulted to a significant change in Land Surface Temperature (LST). The LST in 2003 (16.49°C – 40.44°C) was found higher than that of 2015 which was observed between 13.35°C and 33.83°C only. The reason behind this is the increase in green spaces from 2003 to 2015. Among the major land cover types, forest lands exhibited the lowest mean surface temperature for both years having 27.27°C in 2003 and 21.35°C in 2015 while built-up areas had the highest surface temperature having 32.60°C in 2003 and 26.00°C in 2015.

scholarly journals A Spatio-Temporal Analysis of Active Fires over China during 2003–2016

2020 ◽  
Vol 12 (11) ◽  
pp. 1787
Author(s):  
Xikun Wei ◽  
Guojie Wang ◽  
Tiexi Chen ◽  
Daniel Fiifi Tawia Hagan ◽  
Waheed Ullah
Keyword(s):  
Land Cover ◽  
Seasonal Variations ◽  
Urban Areas ◽  
Atmospheric Environment ◽  
Economic Losses ◽  
Change Analysis ◽  
Land Cover Types ◽  
North East ◽  
Spatio Temporal

Fire is a common circumstance in the world. It causes direct casualties and economic losses, and also brings severe negative influences on the atmospheric environment. In the background of climate warming and rising population, it is important to understand the fire responses regarding the spatio-temporal changes. Thus, a long-term change analysis of fires is needed in China. We use the remote sensed MOD14A1/MYD14A1 fire products to analyze the seasonal variations and long-term trends, based on five main land cover types (forest, cropland, grassland, savannas and urban areas). The fires are found to have clear seasonal variations; there are more fires in spring and autumn in vegetated lands, which are related to the amount of dry biomass and temperature. The fire numbers have significantly increased during the study period, especially from spring to autumn, and those have decreased in winter. The long-term fire trends are different when delineated into different land cover types. There are significant increasing fire trends in grasslands and croplands in North, East and Northeast China during the study period. The urban fires also show increasing trends. On the contrary, there are significant decreasing fire trends in forests and savannas in South China where it is most densely vegetated. This study provides an overall analysis of the spatio-temporal fire changes from satellite products, and it may help to understand the fire risk in the changing climate for a better risk management.

scholarly journals Extracting the spatio-temporal linkages between land use/land cover and water quality parameters using spatio-temporal weighted regression

2018 ◽  
Vol 53 (4) ◽  
pp. 205-218
Author(s):  
Farid Karimipour ◽  
Arash Madadi ◽  
Mohammad Hosein Bashough
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Land Cover ◽  
Temporal Variations ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Spatial And Temporal Variations ◽  
Weighted Regression ◽  
Land Use Land Cover ◽  
Spatio Temporal

Abstract Studies in water quality management have indicated significant relationships between land use/land cover (LULC) variables and water quality parameters. Thus, understanding this linkage is essential in protecting and developing water resources. This article extends the conventional geographical weighted regression (GWR) to a temporal version in order to take both spatial and temporal variations of such linkages into account, which has been ignored by many of the previous efforts. The approach has been evaluated for total nitrates and nitrites' concentration as the case study. For this, observations of 45 water quality sampling stations were examined in a time interval of 20 years (1992–2011), and the linkages between LULC variables and NO2 + NO3 concentration were extracted through Pearson correlation coefficient as a global regression model, the conventional geographic weighted regression, and the proposed spatio-temporal weighted regression (STWR). Comparing the results based on two global criteria of goodness-of-fitness (R2) and residual sum of squares (RSS) verifies that the simultaneous consideration of spatial and temporal variations by STWR substantially improves the results.

scholarly journals ESTIMATION OF BVOC EMISSIONS IN GUANGZHOU AND ITS SPATIAL-TEMPORAL VARIATIONS: PRELIMINARY RESULTS FROM GLOBEIS

2018 ◽  
Vol XLII-3/W5 ◽  
pp. 33-38
Author(s):  
L. Li ◽  
Y. Wang ◽  
Y. Zheng ◽  
T. Chen
Keyword(s):  
Land Cover ◽  
Meteorological Data ◽  
Seasonal Pattern ◽  
Temporal Variations ◽  
Emission Rates ◽  
Area Index ◽  
Land Cover Types ◽  
The North ◽  
Result Show ◽  
High Emission

<p><strong>Abstract.</strong> Biogenic VOC emissions greatly exceed anthropogenic emissions and are regarded as significant precursors to secondary organic aerosol (SOA) and ozone. Using the Global Biosphere Emission and Interactions System (GloBEIS) model, 1<span class="thinspace"></span>&amp;times;<span class="thinspace"></span>1<span class="thinspace"></span>km gridded and hourly BVOC emissions in Guangzhou were estimated for the year of 2012. This study used satellite-retrieved land cover data, cloud product and leaf area index (LAI), observed meteorological data and local emission rates for land cover types in South China. The result show that the total BVOC emission in Guangzhou, 2012 was 4.39<span class="thinspace"></span>kt and the average area emission was 5.93<span class="thinspace"></span>t/(km<sup>2</sup>&amp;sdot;a), of which isoprene contributed about 55.7% (2.44<span class="thinspace"></span>kt)), monoterpenes about 11.9% (0.52<span class="thinspace"></span>kt) and OVOC about 32.4% (1.42<span class="thinspace"></span>kt). Emission factors of land cover types and correction parameters including LAI, wind speed and relative humidity have great effects on the estimation results of the model. BVOC emissions in Guangzhou exhibit a marked monthly and seasonal pattern with the peak emission in July to August and the lowest emission in January and are mainly distributed in the east-western of Conghua, the north of Zengcheng and the border of Huadu and Conghua, mostly covered by evergreen broadleaf forest with high emission factor, while areas of BVOC emission below 50<span class="thinspace"></span>kg/(km<sup>2</sup>&amp;sdot;a) are distributed in highly urbanized areas like Tianhe, Yuexiu, Liwan and Haizhu district.</p>

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