Monitoring post-fire vegetation recovery in the Mediterranean using SPOT and ERS imagery

2014 ◽  
Vol 23 (5) ◽  
pp. 631 ◽  
Author(s):  
A. Polychronaki ◽  
I. Z. Gitas ◽  
A. Minchella
Keyword(s):  
Land Cover ◽  
Forest Regeneration ◽  
Vegetation Index ◽  
Backscatter Coefficient ◽  
Understorey Vegetation ◽  
Regeneration Rate ◽  
Land Cover Types ◽  
Normalised Difference Vegetation Index ◽  
Forested Areas ◽  
The Mediterranean

This study examined the effect of two different forest fires 19 and 23 years ago on the Mediterranean island of Thasos. An object-based classification scheme was developed to map the major land-cover types using multi-temporal Système Pour l’Observation de la Terre (SPOT) and European Remote-Sensing (ERS) (C-band VV) images covering the time period from 1993 to 2007. The developed scheme mapped the post-fire land-cover types accurately: 0.84 Kappa coefficient and 90.5% overall accuracy. The use of the ERS backscatter coefficient contributed to decreasing the commission errors related to the mapping of forested areas and to overcoming misclassifications that occurred between forested areas and shrublands located in shadowed areas. Results indicated that the forest regeneration rate is rather slow, especially in areas where the degree of burn severity was high while the largest part of the burned area is, to date, covered by low vegetation and shrubs. Nevertheless, a gradual shift from low vegetation to shrubland was observed. A preliminary investigation on the use of the ERS backscatter coefficient and the Normalised Difference Vegetation Index to monitor forest regeneration revealed that the backscatter coefficient could provide information related to changes in dense regenerating pine forests for the first 18 years after the fire event, whereas the Normalised Difference Vegetation Index was found to be sensitive to the regenerating forest understorey vegetation. However, further investigation is needed to confirm these findings.

scholarly journals Stretching the Habitat Envelope: Insectivorous Bat Guilds Can Use Rubber Plantations, but Need Understorey Vegetation and Forest Buffers

2021 ◽  
Vol 2 ◽  
Author(s):  
Kadambari Deshpande ◽  
Nachiket Kelkar ◽  
Jagdish Krishnaswamy ◽  
Mahesh Sankaran
Keyword(s):  
Land Cover ◽  
Management Practices ◽  
Forest Cover ◽  
Foraging Strategies ◽  
Insectivorous Bats ◽  
Understorey Vegetation ◽  
Land Cover Types ◽  
Rubber Plantations ◽  
Bat Activity ◽  
Western Ghats Of India

Effects of land-cover change on insectivorous bat activity can be negative, neutral or positive, depending on foraging strategies of bats. In tropical agroforestry systems with high bat diversity, these effects can be complex to assess. We investigated foraging habitat use by three insectivorous bat guilds in forests and rubber plantations in the southern Western Ghats of India. Specifically, we monitored acoustic activity of bats in relation to (1) land-cover types and vegetation structure, and (2) plantation management practices. We hypothesized that activity of open-space aerial (OSA) and edge-space aerial (ESA) bat guilds would not differ; but narrow-space, flutter-detecting (NSFD) bat guild activity would be higher, in structurally heterogeneous forest habitats than monoculture rubber plantations. We found that bat activity of all guilds was highest in areas with high forest cover and lowest in rubber plantations. Higher bat activity was associated with understorey vegetation in forests and plantations, which was expected for NSFD bats, but was a surprise finding for OSA and ESA bats. Within land-cover types, open areas and edge-habitats had higher OSA and ESA activity respectively, while NSFD bats completely avoided open habitats. In terms of management practices, intensively managed rubber plantations with regular removal of understorey vegetation had the lowest bat activity for all guilds. Intensive management can undermine potential ecosystem services of insectivorous bats (e.g., insect pest-control in rubber plantations and surrounding agro-ecosystems), and magnify threats to bats from human disturbances. Low-intensity management and maintenance of forest buffers around plantations can enable persistence of insectivorous bats in tropical forest-plantation landscapes.

scholarly journals Simplified Priestley–Taylor Model to Estimate Land-Surface Latent Heat of Evapotranspiration from Incident Shortwave Radiation, Satellite Vegetation Index, and Air Relative Humidity

2021 ◽  
Vol 13 (5) ◽  
pp. 902
Author(s):  
Yunjun Yao ◽  
Zhenhua Di ◽  
Zijing Xie ◽  
Zhiqiang Xiao ◽  
Kun Jia ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Land Cover ◽  
Latent Heat ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Mainland China ◽  
Shortwave Radiation ◽  
Land Cover Types

An operational and accurate model for estimating global or regional terrestrial latent heat of evapotranspiration (ET) across different land-cover types from satellite data is crucial. Here, a simplified Priestley–Taylor (SPT) model was developed without surface net radiation (Rn) by combining incident shortwave radiation (Rs), satellite vegetation index, and air relative humidity (RH). Ground-measured ET for 2000–2009 collected by 100 global FLUXNET eddy covariance (EC) sites was used to calibrate and evaluate the SPT model. A series of cross-validations demonstrated the reasonable performance of the SPT model to estimate seasonal and spatial ET variability. The coefficients of determination (R2) of the estimated versus observed daily (monthly) ET ranged from 0.42 (0.58) (p < 0.01) at shrubland (SHR) flux sites to 0.81 (0.86) (p < 0.01) at evergreen broadleaf forest (EBF) flux sites. The SPT model was applied to estimate agricultural ET at high spatial resolution (16 m) from Chinese Gaofen (GF)-1 data and monitor long-term (1982–2018) ET variations in the Three-River Headwaters Region (TRHR) of mainland China using the Global LAnd-Surface Satellite (GLASS) normalized difference vegetation index (NDVI) product. The proposed SPT model without Rn provides an alternative model for estimating regional terrestrial ET across different land-cover types.

scholarly journals Assessing the Relationship of LST, NDVI and EVI with Land Cover Changes in the Lagos Lagoon Environment

2020 ◽  
Vol 39 (3) ◽  
pp. 87-109 ◽  
Author(s):  
Alfred S. Alademomi ◽  
Chukwuma J. Okolie ◽  
Olagoke E. Daramola ◽  
Raphael O. Agboola ◽  
Tosin J. Salami
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Urban Expansion ◽  
Normalised Difference Vegetation Index ◽  
Lagos Lagoon ◽  
The Mean ◽  
Lagoon Environment ◽  
The Relationship ◽  
Derived Data

AbstractThe Lagos Lagoon is under increased pressure from growth in human population, growing demands for natural resources, human activities, and socioeconomic factors. The degree of these activities and the impacts are directly proportional to urban expansion and growth. In the light of this situation, the objectives of this study were: (i) to estimate through satellite imagery analysis the extent of changes in the Lagos Lagoon environment for the periods 1984, 2002, 2013 and 2019 using Landsat-derived data on land cover, Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI); and (ii) to evaluate the relationship between the derived data and determine their relative influence on the lagoon environment. The derived data were subjected to descriptive statistics, and relationships were explored using Pearson's correlation and regression analysis. The effect of land cover on LST was measured using the Contribution Index and a trend analysis was carried out. From the results, the mean LSTs for the four years were 22.68°C (1984), 24.34°C (2002), 26.46°C (2013) and 28.40°C (2019). Generally, the mean LSTs is in opposite trend with the mean NDVIs and EVIs as associated with their dominant land cover type. The strongest positive correlations were observed between NDVI and EVI while NDVI had the closest fit with LST in the regression. Built-up areas have the highest contributions to LST while vegetation had a cooling influence. The depletion in vegetative cover has compromised the biodiversity of this environment and efforts are required to reverse this trend.

scholarly journals Land Covers and Climate Impacts on Land Surface Temperature in Putrajaya, Malaysia

2018 ◽  
Vol 3 (10) ◽  
pp. 78-88
Author(s):  
Siti Aekbal Salleh ◽  
Zulkiflee Abd.Latif ◽  
Wan Mohd. Naim Wan Mohd ◽  
Andy Chan
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Publishing House ◽  
Urban Climate ◽  
Climate Impacts ◽  
Climate Data ◽  
Normalised Difference Vegetation Index

This study investigates the influence of surface heterogeneity to the land surface temperature (LST). The land cover changes evaluation and historical climate data comparison were used in this study. Land cover, Normalised Difference Vegetation Index (NDVI), Normalised Difference Built-up Index (NDBI) and LST maps are produced to quantify the impacts of urbanization towards the surface thermal behaviour. The urbanization was set on years 1999 to 2006. While urbanization continued in 2009, the surface temperature was lower than that of 2006. The sea level was notably high during 2006, suggesting the lost of ice extent and evident to the climate change effects. Therefore, the fluctuation of temperature in 1999 to 2009 manifestly influenced by green space and climatic response and not solely caused by urbanization. Keywords: Land surface temperature, Land cover, Urban, Climate. eISSN 2514-751X © 2018. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/aje-bs.v3i10.315     

Biological and Environmental Controls on Evaporative Fractions at AmeriFlux Sites

2016 ◽  
Vol 55 (1) ◽  
pp. 145-161 ◽  
Author(s):  
Chunlüe Zhou ◽  
Kaicun Wang
Keyword(s):  
Land Cover ◽  
Latent Heat ◽  
Air Temperature ◽  
Vegetation Index ◽  
Meteorological Data ◽  
Heat Fluxes ◽  
Vegetation Coverage ◽  
Land Cover Types ◽  
Environmental Controls ◽  
Mean Square Errors

AbstractKnowledge of the evaporative fraction (EF: the ratio of latent heat flux to the sum of sensible and latent heat fluxes) and its controls is particularly important for accurate estimates of water flux, heat exchange, and ecosystem response to climatic changes. In this study, the biological and environmental controls on monthly EF were evaluated across 81 AmeriFlux sites, mainly in North America, for 2000–12. The land-cover types of these sites include forest, shrubland, grassland, and cropland, and the local climates vary from humid to arid. The results show that vegetation coverage, indicated by the normalized difference vegetation index (NDVI), has the best agreement with EF (site-averaged partial correlation coefficient ρ = 0.53; significance level p < 0.05) because of vegetation transpiration demand. The minimum air temperature is closely related to EF (site-averaged ρ = 0.51; p < 0.05) because of the inhibition of respiratory enzyme activity. Relative humidity, an indicator of surface aridity, shows a significant positive correlation with EF (site-averaged ρ = 0.46; p < 0.05). The impacts of wind speed and diurnal air temperature range on EF depend on land-cover types and are strong over grasslands and cropland. From these findings, empirical methods were established to predict monthly EF using meteorological data and NDVI. Correlation coefficients between EF estimates and observations range from 0.80 to 0.93, with root-mean-square errors varying from 0.09 to 0.12. This study demonstrates the varying controls on EF across different landscapes and enhances understanding of EF and its dynamics under changing climates.

Trend analysis of medium- and coarse-resolution time series image data for burned area mapping in a Mediterranean ecosystem

2014 ◽  
Vol 23 (5) ◽  
pp. 668 ◽  
Author(s):  
Thomas Katagis ◽  
Ioannis Z. Gitas ◽  
Pericles Toukiloglou ◽  
Sander Veraverbeke ◽  
Rudi Goossens
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Trend Analysis ◽  
Vegetation Index ◽  
Probability Of Detection ◽  
Vegetation Recovery ◽  
Burned Area ◽  
Mediterranean Ecosystem ◽  
Normalised Difference Vegetation Index ◽  
Induced Changes

In this study, the Breaks for Additive Seasonal and Trend (BFAST), a recently introduced trend analysis technique, was employed for the detection of fire-induced changes in a Mediterranean ecosystem. BFAST enables the decomposition of time series into trend, seasonal and noise components, resulting in the detection of gradual and rapid land cover changes. Normalised Difference Vegetation Index (NDVI) time series derived from the MODIS and VEGETATION (VGT) standard products were analysed. The time series decomposition resulted in the mapping of the burned area and the demonstration of the post-fire vegetation recovery trend. The observed gradual changes revealed an increase of NDVI values over time, indicating post-fire vegetation recovery. Spatial validation of the generated burned area maps with a higher resolution reference map was performed and probability statistics were derived. Both maps achieved a high probability of detection – 0.90 for MODIS and 0.87 for VGT – and a low probability of false alarms, 0.01 for MODIS and 0.02 for VGT. In addition, the Pareto boundary theory was implemented to account for the low-resolution bias of the maps. BFAST facilitated detection of fire-induced changes using image time series, without having to set thresholds, select specific seasons or adjust to certain land cover types. Further evaluation of the approach should focus on a more comprehensive assessment across regions and time.

scholarly journals Investigating Decadal Changes of Multiple Hydrological Products and Land-Cover Changes in the Mediterranean Region for 2009–2018

2021 ◽  
Author(s):  
Wenzhao Li ◽  
Sachi Perera ◽  
Erik Linstead ◽  
Rejoice Thomas ◽  
Hesham El-Askary ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Cover ◽  
Mediterranean Region ◽  
Vegetation Index ◽  
Surface Soil ◽  
The North ◽  
Land Data Assimilation ◽  
The Mediterranean ◽  
Land Data Assimilation System ◽  
Data Assimilation System

AbstractLand-cover change is a critical concern due to its climatic, ecological, and socioeconomic consequences. In this study, we used multiple variables including precipitation, vegetation index, surface soil moisture, and evapotranspiration obtained from different satellite sources to study their association with land-cover changes in the Mediterranean region. Both observational and modeling data were used for climatology and correlation analysis. Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) and Global Land Data Assimilation System (GLDAS) were used to extract surface soil moisture and evapotranspiration data. Intercomparing the results of FLDAS and GLDAS suggested that FLDAS data had better accuracy compared to GLDAS for its better coherence with observational data. Climate Hazards Group Infra-Red Precipitation with Station Data (version 2.0 final) (CHIRPS Pentad) were used to extract precipitation data while Moderate Resolution Imaging Spectroradiometer (MODIS) products were used to extract the vegetation indices used in this study. The land-cover change detection was demonstrated during the 2009–2018 period using MODIS Land-Cover data. Some of the barren and crop lands in Euphrates-Tigris and Algeria have converted to low-vegetated shrublands over the time, while shrublands and barren areas in Egypt’s southwestern Delta region became grasslands. These observations were well explained by changing trends of hydrological variables which showed that precipitation and soil moisture had higher values in the countries located to the east of the Mediterranean region compared to the ones on the west. For evapotranspiration, the countries in the north had lower values except for countries in Europe such as Bosnia, Romania, Slovenia, and countries in Africa such as Egypt and Libya. The enhanced vegetation index appeared to be decreasing from north to south, with countries in the north such as Germany, Romania, and Czechia having higher values, while countries in the south such as Libya, Egypt, and Iraq having lower trends. Time series analysis for selected countries was also done to understand the change in hydrological parameters, including Enhanced Vegetation Index, evapotranspiration, and soil moisture, which showed alternating drop and rise as well as stagnant values for different parameters in each country.

scholarly journals Selecting appropriate variables for detecting grassland to cropland changes using high resolution satellite data

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5487 ◽  
Author(s):  
Tomáš Klouček ◽  
David Moravec ◽  
Jan Komárek ◽  
Ondřej Lagner ◽  
Přemysl Štych
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Change Detection ◽  
Spatial Data ◽  
Vegetation Index ◽  
Identification System ◽  
Landsat 8 ◽  
Economic Point ◽  
Normalised Difference Vegetation Index ◽  
Cropland Change

Grassland is one of the most represented, while at the same time, ecologically endangered, land cover categories in the European Union. In view of the global climate change, detecting its change is growing in importance from both an environmental and a socio-economic point of view. A well-recognised tool for Land Use and Land Cover (LULC) Change Detection (CD), including grassland changes, is Remote Sensing (RS). An important aspect affecting the accuracy of change detection is finding the optimal indicators of LULC changes (i.e., variables). Inappropriately selected variables can produce inaccurate results burdened with a number of uncertainties. The aim of our study is to find the most suitable variables for the detection of grassland to cropland change, based on a pair of high resolution images acquired by the Landsat 8 satellite and from the vector database Land Parcel Identification System (LPIS). In total, 59 variables were used to create models using Generalised Linear Models (GLM), the quality of which was verified through multi-temporal object-based change detection. Satisfactory accuracy for the detection of grassland to cropland change was achieved using all of the statistically identified models. However, a three-variable model can be recommended for practical use, namely by combining the Normalised Difference Vegetation Index (NDVI), Wetness and Fifth components of Tasselled Cap. Increasing number of variables did not significantly improve the accuracy of detection, but rather complicated the interpretation of the results and was less accurate than detection based on the original Landsat 8 images. The results obtained using these three variables are applicable in landscape management, agriculture, subsidy policy, or in updating existing LULC databases. Further research implementing these variables in combination with spatial data obtained by other RS techniques is needed.

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