Spatial and spectral remote sensing features to detect deforestation in Brazilian Savannas

The Brazilian Savannas have been under increasing anthropic pressure for many years, and land-use/land-cover changes (LULCC) have been largely neglected. Remote sensing provides useful tools to detect changes, but previous studies have not attempted to separate the effects of phenology from deforestation, clearing or fires to improve the accuracy of change detection without a dense time series. The scientific questions addressed in this study were: how well can we differentiate seasonal changes from deforestation processes combining the spatial and spectral information of bi-temporal (normalized difference vegetation index) NDVI images? Which feature best contribute to increase the separability on classification assessment? We applied an object-based remote sensing method that is able to separate seasonal changes due to phenology effects from LULCC by combining spectral and the spatial context using traditional spectral features and semivariogram indices, exploring the full capability of NDVI image difference to train random forest (RF) algorithm. We found that the spatial variability of NDVI values is not affect by vegetation seasonality and, therefore, the combination of spectral features and semivariogram indices provided high global accuracy (97.73%) to separate seasonal changes and deforestation or fires. From the total of 13 features, 6 provided the best combination to increase the separability on classification assessment (4 spatial and 2 spectral features). How to accurately extract LULCC while disregarding the ones caused by phenological differences in Brazilian seasonal biomes undergoing rapid land-cover changes can be achieved by adding semivariogram indices in combination with spectral features as input data to train RF algorithm.

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Spatial variability of evapotranspiration of old-growth cypress forest using remote sensing — a case study of Chilan Mountain cypress forest in Taiwan

Canadian Journal of Forest Research ◽

10.1139/x2012-066 ◽

2012 ◽

Vol 42 (6) ◽

pp. 1060-1071

Author(s):

Chih-Da Wu ◽

Chi-Chuan Cheng ◽

Yung-Chung Chuang

Keyword(s):

Remote Sensing ◽

Land Cover ◽

Spatial Variability ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Environmental Parameters ◽

Habitat Characteristics ◽

Old Growth ◽

Mountain Area ◽

Watershed Divisions

The Chilan Mountain cypress forest, northeastern Taiwan, is the only one where the genus Chamaecyparis is situated in a subtropical region. The health of a forest ecosystem is closely tied to the evapotranspiration (ET) of water through forests. This study focused on estimating the ET of old-growth cypress in the Chilan Mountain area and investigated its spatial variability in different watershed divisions using remote sensing. Our methods included applying hybrid image classification to generate land cover maps using Landsat-5 images, calculating habitat characteristics of old-growth using the Surface Energy Balance Algorithm for Land (SEBAL), investigating spatial variability of ET in relation to environmental parameters, and examining the gap-snag effect on old-growth cypress ET. The results indicated that the study area was classified into three land cover types (i.e., old-growth, non-old growth, and others). Old-growth had lower values in net radiance, the normalized difference vegetation index (NDVI), and daily ET than did non-old-growth. Watershed divisions at various scales did cause the variation on old-growth ET characteristics according to the selected parameters and the number of parameters for predicting the value of ET. Finally, ET between gap-snag and non-gap-snag habitats was statistically different. A higher proportion in gap-snag composition would lead to a lower value in daily ET and the NDVI.

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CHARACTERIZING LANDSCAPE SPATIAL HETEROGENEITY USING SEMIVARIOGRAM PARAMETERS DERIVED FROM NDVI IMAGES

CERNE ◽

10.1590/01047760201723042370 ◽

2017 ◽

Vol 23 (4) ◽

pp. 413-422 ◽

Cited By ~ 1

Author(s):

Eduarda Martiniano de Oliveira Silveira ◽

José Márcio de Mello ◽

Fausto Weimar Acerbi Júnior ◽

Aliny Aparecida dos Reis ◽

Kieran Daniel Withey ◽

...

Keyword(s):

Remote Sensing ◽

Spatial Heterogeneity ◽

Spatial Resolution ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Landscape Heterogeneity ◽

Landsat 8 ◽

Remotely Sensed Data ◽

Object Based ◽

Geostatistical Techniques

ABSTRACT Assuming a relationship between landscape heterogeneity and measures of spatial dependence by using remotely sensed data, the aim of this work was to evaluate the potential of semivariogram parameters, derived from satellite images with different spatial resolutions, to characterize landscape spatial heterogeneity of forested and human modified areas. The NDVI (Normalized Difference Vegetation Index) was generated in an area of Brazilian amazon tropical forest (1,000 km²). We selected samples (1 x 1 km) from forested and human modified areas distributed throughout the study area, to generate the semivariogram and extract the sill (σ²-overall spatial variability of the surface property) and range (φ-the length scale of the spatial structures of objects) parameters. The analysis revealed that image spatial resolution influenced the sill and range parameters. The average sill and range values increase from forested to human modified areas and the greatest between-class variation was found for LANDSAT 8 imagery, indicating that this image spatial resolution is the most appropriate for deriving sill and range parameters with the intention of describing landscape spatial heterogeneity. By combining remote sensing and geostatistical techniques, we have shown that the sill and range parameters of semivariograms derived from NDVI images are a simple indicator of landscape heterogeneity and can be used to provide landscape heterogeneity maps to enable researchers to design appropriate sampling regimes. In the future, more applications combining remote sensing and geostatistical features should be further investigated and developed, such as change detection and image classification using object-based image analysis (OBIA) approaches.

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Land use and Land cover Mapping Based on Normalized Difference Vegetation Index using Remote Sensing and Geographical Information System in Banjar River Watershed of Narmada Basin

Current World Environment ◽

10.12944/cwe.12.3.19 ◽

2017 ◽

Vol 12 (3) ◽

pp. 678-684

Author(s):

Jagriti Tiwari ◽

S.K. Sharma ◽

R.J. Patil

Keyword(s):

Remote Sensing ◽

Land Use ◽

Information System ◽

Land Cover ◽

Geographical Information System ◽

Water Body ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Geographical Information ◽

River Watershed

The spatial analysis of land use and land cover (LULC) dynamics is necessary for sustainable utilization and management of the land resources of an area. Remote sensing along with Geographical Information System emerged as an effective technique for mapping the LU/LC categories of an area in an efficient and cost-effective manner. The present study was conducted in Banjar river watershed located in Balaghat and Mandla district of Madhya Pradesh, India. The Normalized Difference Vegetation Index (NDVI) approach was adopted for LU/LC classification of study area. The Landsat-8 satellite data of year 2013 was selected for the classification purpose. The NDVI values were generated in ERDAS Imagine 2011 software and LU/LC map was prepared in ARC GIS environment. On the basis of NDVI values five LU/LC classes were recognized in the study area namely river & water body, waste land & habitation, forest, agriculture/other vegetation, open land/fallow land/barren land. The forest cover was found to be highly distributed in the study area with an extent of 115811 ha and least area was found to be covered under river and water body (4057.28 ha). This research work will be helpful for the policy makers for proper formulation and implementation of watershed developmental plans.

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Monitoring Land Cover Change Using Remote Sensing and GIS Techniques: a Case Study of Al-Dalmaj Marsh, Iraq

Journal of Engineering ◽

10.31026/j.eng.2018.09.07 ◽

2018 ◽

Vol 24 (9) ◽

pp. 96 ◽

Cited By ~ 1

Author(s):

Marwah Moojid Kadhim

Keyword(s):

Remote Sensing ◽

Land Cover ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Accurate Information ◽

Past Century ◽

Landsat Images ◽

Gis And Remote Sensing ◽

Vegetation Water ◽

Set Up

Al-Dalmaj marsh and the near surrounding area is a very promising area for energy resources, tourism, agricultural and industrial activities. Over the past century, the Al-Dalmaje marsh and near surroundings area endrous from a number of changes. The current study highlights the spatial and temporal changes detection in land cover for Al-Dalmaj marsh and near surroundings area using different analyses methods the supervised maximum likelihood classification method, the Normalized Difference Vegetation Index (NDVI), Geographic Information Systems(GIS), and Remote Sensing (RS). Techniques spectral indices were used in this study to determine the change of wetlands and drylands area and of other land classes, through analyses Landsat images for different three years (1990, 2003, 2016). The results indicated that there was an annual increase in vegetation was from 1990 with 980.68 km2, and 1420.35km2 in 2003 to 2072.98km2 in 2016. Whereas, the annual water coverage was about 185.95km2 in 1990 then dropped to 68.27km2 in 2003, and rose to 180.23 km2 in 2016. The water coverage increasing was on the account of barren lands areas, which were significantly decreased. These collected data can be used to deliver accurate information of the values of vegetation,water, wetlands and drylands sustainability of resources which can be used to make plans to increase tourism and protected areas by using barren lands which cannot be reclaimed for agriculture, and cultivate a new renewable energy can be set up as solar power stations.

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Applications of Satellite Remote Sensing for Archaeological Survey: A Case Study from the Sinis Archaeological Project, Sardinia

Advances in Archaeological Practice ◽

10.1017/aap.2020.1 ◽

2020 ◽

Vol 8 (2) ◽

pp. 192-205

Author(s):

Daniel Plekhov ◽

Linda R. Gosner ◽

Alexander J. Smith ◽

Jessica Nowlin

Keyword(s):

Remote Sensing ◽

Land Cover ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Daily Basis ◽

Archaeological Survey ◽

Short Term ◽

Spectral Bands ◽

Archaeological Project

ABSTRACTSatellite imagery has long been recognized as well suited for the regional and ecological questions of many archaeological surveys. One underexplored aspect of such data is their temporal resolution. It is now possible for areas to be imaged on an almost daily basis, and this resolution offers new opportunities for studying landscapes through remote sensing in parallel with ground-based survey. This article explores the applications of these data for visibility assessment and land-cover change detection in the context of the Sinis Archaeological Project, a regional archaeological survey of west-central Sardinia. We employ imagery provided by Planet, which has a spatial resolution of 3 m, in four spectral bands, and is collected daily. Using Normalized Difference Vegetation Index (NDVI) values calculated for each survey unit, we find that there is a relationship between NDVI values and field-reported visibility in general, though the strength of this correlation differs according to land-cover classes. We also find the data to be effective at tracking short-term changes in field conditions that allow us to differentiate fields of similar land cover and visibility. We consider limitations and potentials of these data and encourage further experimentation and development.

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Monitoring NDVI Inter-Annual Behavior in Mountain Areas of Mainland Spain (2001–2016)

Sustainability ◽

10.3390/su10124363 ◽

2018 ◽

Vol 10 (12) ◽

pp. 4363 ◽

Cited By ~ 1

Author(s):

Patricia Arrogante-Funes ◽

Carlos Novillo ◽

Raúl Romero-Calcerrada

Keyword(s):

Land Cover ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Agricultural Land ◽

Land Cover Changes ◽

Mountainous Area ◽

Statistical Association ◽

Mountain Areas ◽

Mountain Ranges ◽

Statistical Trends

Currently, there exists growing evidence that warming is amplified with elevation resulting in rapid changes in temperature, humidity and water in mountainous areas. The latter might result in considerable damage to forest and agricultural land cover, affecting all the ecosystem services and the socio-economic development that these mountain areas provide. The Mediterranean mountains, moreover, which host a high diversity of natural species, are more vulnerable to global change than other European ecosystems. The protected areas of the mountain ranges of peninsular Spain could help preserve natural resources and landscapes, as well as promote scientific research and the sustainable development of local populations. The temporal statistical trends (2001–2016) of the MODIS13Q1 Normalized Difference Vegetation Index (NDVI) interannual dynamics are analyzed to explore whether the NDVI trends are found uniformly within the mountain ranges of mainland Spain (altitude > 1000 m), as well as in the protected or non-protected mountain areas. Second, to determine if there exists a statistical association between finding an NDVI trend and the specific mountain ranges, protected or unprotected areas are studied. Third, a possible association between cover types in pure pixels using CORINE (Co-ordination of Information on the Environment) land cover cartography is studied and land cover changes between 2000 and 2006 and between 2006 and 2012 are calculated for each mountainous area. Higher areas are observed to have more positive NDVI trends than negative in mountain areas located in mainland Spain during the 2001–2016 period. The growing of vegetation, therefore, was greater than its decrease in the study area. Moreover, differences in the size of the area between growth and depletion of vegetation patterns along the different mountains are found. Notably, more negatives than expected are found, and fewer positives are found than anticipated in the mountains, such as the Cordillera Cantábrica (C.Cant.) or Montes de Murcia y Alicante (M.M.A). Quite the reverse happened in Pirineos (Pir.) and Montes de Cádiz y Málaga (M.C.M.), among others. The statistical association between the trends found and the land cover types is also observed. The differences observed can be explained since the mountain ranges in this study are defined by climate, land cover, human usage and, to a small degree, by land cover changes, but further detailed research is needed to get in-depth detailed conclusions. Conversely, it is found that, in protected mountain areas, a lower NDVI pixels trend than expected (>20%) occurs, whereas it is less than anticipated in unprotected mountain areas. This could be caused by management and the land cover type.

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Response of vegetation to the 2003 European drought was mitigated by height

Biogeosciences Discussions ◽

10.5194/bgd-10-16075-2013 ◽

2013 ◽

Vol 10 (10) ◽

pp. 16075-16100

Author(s):

S. L. Bevan ◽

S. O. Los ◽

P. R. J. North

Keyword(s):

Land Cover ◽

Land Surface ◽

Diurnal Temperature Range ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Land Cover Changes ◽

High Latitudes ◽

Vegetation Height ◽

Direct Measurements ◽

Surface Models

Abstract. The effects on climate of land-cover change, predominantly from forests to crops or grassland, are reasonably well understood for low and high latitudes but are largely unknown for temperate latitudes. The main reason for this gap in our knowledge is that there are compensating effects on the energy and water balance when land cover changes. To obtain a better understanding of the direction of this response, we analyse the differential response of tall and short vegetation to the 2003 European drought. We analyse precipitation, temperature and normalized difference vegetation index data and compare these with direct measurements of vegetation height. At the height of the 2003 drought we find for tall vegetation a significantly smaller decrease in vegetation index and a smaller diurnal temperature range, indicating less water stress on tall vegetation, which can be explained by access of tall vegetation to deeper soil water. Based on these results we question the current parameterizations of short and tall vegetation in some land-surface models.

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Monitoring the Land Cover Changes in Mangrove Areas and Urbanization using Normalized Difference Vegetation Index and Normalized Difference Built-up Index in Krabi Estuary Wetland, Krabi Province, Thailand

Applied Environmental Research ◽

10.35762/aer.2021.43.3.1 ◽

2021 ◽

pp. 1-16

Author(s):

Katawut Waiyasusri

Keyword(s):

Land Cover ◽

Mangrove Forest ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Accuracy Assessment ◽

Forest Degradation ◽

Tourism Industry ◽

Land Cover Changes ◽

Band Ratio ◽

The Impact

Krabi Estuary Wetland (KEW) is an outstanding wetland with an estuary environment. At present, the tourism industry has rapidly grown, resulting in the impact of land cover changes. This research aims to assess the changes that have occurred in the KEW from 1999 to 2020 using NDVI and NDBI for monitoring changes in mangrove areas and urbanization in Krabi Province, Thailand. Landsat satellite images in years 1999, 2009 and 2020 were classified by using a band ratio to create land cover maps. The results show that NDVI between 0.41–1.00 clearly shows the mangrove forest area, while NDBI between 0.01–0.40 shows urban and built-up land, and 0.41–1.00 appears as bare land. The NDVI overall accuracy assessment is 82.88%, 97.46% and 88.25% with Kappa values of 0.64, 0.92, and 0.85 for year 1999, 2009 and 2020, respectively. The NDBI overall accuracy assessment is 92.81%, 77.11% and 64% with Kappa values of 0.93, 0.77, and 0.63 for year 1999, 2009 and 2020, respectively. In addition, areas that are sensitive to land-cover change appear around the Chi rat River, Pak Nam Krabi River, and Yuan River, which are tourist areas close to the Krabi and Ao Nang communities. Therefore, it is necessary to speed up the problem solving and find measures to prevent mangrove forest degradation in these 3 mangrove forest areas so that the mangrove forest areas will not decrease rapidly in the future. This research can be valuable for land-cover management in the KEW by policy and decision makers.

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Intersection of Physical and Anthropogenic Effects on Land-Use/Land-Cover Changes in Coastal China of Jiangsu Province

Sustainability ◽

10.3390/su11082370 ◽

2019 ◽

Vol 11 (8) ◽

pp. 2370 ◽

Cited By ~ 1

Author(s):

Xiaowei Chuai ◽

Jiqun Wen ◽

Dachang Zhuang ◽

Xiaomin Guo ◽

Ye Yuan ◽

...

Keyword(s):

Land Use ◽

Land Cover ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Driving Forces ◽

Land Use Changes ◽

Temporal Analysis ◽

Jiangsu Province ◽

Land Cover Changes ◽

Land Use Type

China is experiencing substantial land-use and land-cover change (LUCC), especially in coastal regions, and these changes have caused many ecological problems. This study selected a typical region of Jiangsu Province and completed a comprehensive and detailed spatial-temporal analysis regarding LUCC and the driving forces. The results show that the rate of land-use change has been accelerating, with land-use experiencing the most substantial changes from 2005 to 2010 for most land-use types and the period from 2010 to 2015 showing a reversed changing trend. Built-up land that occupies cropland was the main characteristic of land-use type change. Southern Jiangsu and the coastline region presented more obvious land-use changes. Social-economic development was the main factor driving increased built-up land expansion and cropland reduction. In addition, land-use policy can significantly affect land-use type changes. For land-cover changes, the normalized difference vegetation index (NDVI) for the land area without land-use type changes increased by 0.005 per year overall. Areas with increasing trends accounted for 82.43% of the total area. Both precipitation and temperature displayed more areas that were positively correlated with NDVI, especially for temperature. Temperature correlated more strongly with NDVI change than precipitation for most vegetation types. Our study can be used as a reference for land-use managers to ensure sustainable and ecological land-use and coastal management.

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APPLICATION OF REMOTE SENSING AND GIS FOR ASSESSING LAND COVER RESOURCES VARIABILITY IN THE SELOUS GAME RESERVE, TANZANIA

European Journal of Technology ◽

10.47672/ejt.227 ◽

2017 ◽

Vol 1 (2) ◽

pp. 74

Author(s):

Phillip W. Mambo ◽

John E. Makunga

Keyword(s):

Remote Sensing ◽

Land Cover ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Remote Sensing And Gis ◽

Vegetation Density ◽

Landsat Images ◽

Gis And Remote Sensing ◽

Game Reserve ◽

Year 2000

Purpose: The study was conducted in Selous Game Reserve, with intention of developing GIS and Remote Sensing based wildlife management system in the protected area.Methodology: All habitats were digitised using ArcGIS9.3 in which five scenes of Landsat TM and ETM+ digital images were acquired during dry seasons of the year 2000 and 2010. Band 3 and 4 of the Landsat images were used for calculation of normalized difference vegetation index (NDVI) for determination of vegetation spatial distributionResults: The NDVI maps of year 2000 to 2010 revealed the vegetation density depletion from 0.72 (obtained in 0.46─0.72 value interval and covering 46.5% pixel area) in 2000 as compared to 0.56 ( found in 0.38─0.56 value interval and covering 8.04% pixel area) in 2010 NDVI maps.Unique contribution to theory, practice and policy: It was recommended that there was a necessity to integrate applications of remote sensing and GIS techniques for the assessment and monitoring of the natural land cover variability to detect fragmentation and loss of wildlife species.

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