Estimation of shrub height for fuel-type mapping combining airborne LiDAR and simultaneous color infrared ortho imaging

2007 ◽  
Vol 16 (3) ◽  
pp. 341 ◽  
Author(s):  
David Riaño ◽  
Emilio Chuvieco ◽  
Susan L. Ustin ◽  
Javier Salas ◽  
José R. Rodríguez-Pérez ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Ground Improvement ◽  
Accurate Estimate ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Fuel Type ◽  
Vegetation Height ◽  
Shrub Canopy ◽  
Central Portugal

A fuel-type map of a predominantly shrub-land area in central Portugal was generated for a fire research experimental site, by combining airborne light detection and ranging (LiDAR), and simultaneous color infrared ortho imaging. Since the vegetation canopy and the ground are too close together to be easily discerned by LiDAR pulses, standard methods of processing LiDAR data did not provide an accurate estimate of shrub height. It was demonstrated that the standard process to generate the digital ground model (DGM) sometimes contained height values for the top of the shrub canopy rather than from the ground. Improvement of the DGM was based on separating canopy from ground hits using color infrared ortho imaging to detect shrub cover, which was measured simultaneously with the LiDAR data. Potentially erroneous data in the DGM was identified using two criteria: low vegetation height and high Normalized Difference Vegetation Index (NDVI), a commonly used spectral index to identify vegetated areas. Based on the height of surrounding pixels, a second interpolation of the DGM was performed to extract those erroneously identified as ground in the standard method. The estimation of the shrub height improved significantly after this correction, and increased determination coefficients from R2 = 0.48 to 0.65. However, the estimated shrub heights were still less than those observed in the field.

scholarly journals Post-fire vegetation recovery in Portugal based on spot/vegetation data

2010 ◽  
Vol 10 (4) ◽  
pp. 673-684 ◽  
Author(s):  
C. Gouveia ◽  
C. C. DaCamara ◽  
R. M. Trigo
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Soil Surface ◽  
Recovery Process ◽  
Vegetation Recovery ◽  
Fire Season ◽  
Burned Area ◽  
Vegetation Density ◽  
Fire Event ◽  
Central Portugal

Abstract. A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI), with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation indices.

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

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.

scholarly journals Assessing Potential Safety Zone Suitability Using a New Online Mapping Tool

Fire ◽  
2022 ◽  
Vol 5 (1) ◽  
pp. 5
Author(s):  
Michael J. Campbell ◽  
Philip E. Dennison ◽  
Matthew P. Thompson ◽  
Bret W. Butler
Keyword(s):  
Burn Injury ◽  
Wildland Fire ◽  
Satellite Image ◽  
Safety Information ◽  
Separation Distance ◽  
Airborne Lidar ◽  
Ecosystem Dynamics ◽  
Lidar Data ◽  
Landsat 8 ◽  
Vegetation Height

Safety zones (SZs) are critical tools that can be used by wildland firefighters to avoid injury or fatality when engaging a fire. Effective SZs provide safe separation distance (SSD) from surrounding flames, ensuring that a fire’s heat cannot cause burn injury to firefighters within the SZ. Evaluating SSD on the ground can be challenging, and underestimating SSD can be fatal. We introduce a new online tool for mapping SSD based on vegetation height, terrain slope, wind speed, and burning condition: the Safe Separation Distance Evaluator (SSDE). It allows users to draw a potential SZ polygon and estimate SSD and the extent to which that SZ polygon may be suitable, given the local landscape, weather, and fire conditions. We begin by describing the algorithm that underlies SSDE. Given the importance of vegetation height for assessing SSD, we then describe an analysis that compares LANDFIRE Existing Vegetation Height and a recent Global Ecosystem Dynamics Investigation (GEDI) and Landsat 8 Operational Land Imager (OLI) satellite image-driven forest height dataset to vegetation heights derived from airborne lidar data in three areas of the Western US. This analysis revealed that both LANDFIRE and GEDI/Landsat tended to underestimate vegetation heights, which translates into an underestimation of SSD. To rectify this underestimation, we performed a bias-correction procedure that adjusted vegetation heights to more closely resemble those of the lidar data. SSDE is a tool that can provide valuable safety information to wildland fire personnel who are charged with the critical responsibility of protecting the public and landscapes from increasingly intense and frequent fires in a changing climate. However, as it is based on data that possess inherent uncertainty, it is essential that all SZ polygons evaluated using SSDE are validated on the ground prior to use.

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

2014 ◽  
Vol 11 (11) ◽  
pp. 2897-2908 ◽  
Author(s):  
S. L. Bevan ◽  
S. O. Los ◽  
P. R. J. North
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rooting Depth ◽  
Laser Altimeter ◽  
Data Set ◽  
Ice Cloud ◽  
Vegetation Height ◽  
Surface Models ◽  
Height Data

Abstract. The effects on climate of land-cover change, predominantly from the conversion of 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 that are related to changes in land-surface albedo, soil evaporation and plant transpiration. We analyse how vegetation height affected the response of vegetation during the 2003 European drought using precipitation data, temperature data, normalized difference vegetation index data and a new vegetation height data set obtained from the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat). At the height of the 2003 drought we find for tall vegetation a significantly smaller decrease in vegetation index and a smaller diurnal temperature (DTR) range, indicating less water stress and drought impacts on tall vegetation. Over Germany for example, 98% of significant correlations showed a smaller anomaly in vegetation index anomaly with greater height, and 95% of significant correlations showed a smaller DTR with greater vegetation height. Over France the equivalent percentages were 94 and 88%, respectively. Vegetation height is likely associated with greater rooting depth, canopy heat capacity or both. Our results suggest that land-surface models can be improved by better estimates of vegetation height and associated with this a more realistic response to drought.

scholarly journals A DIMENSION REDUCTION-BASED METHOD FOR CLASSIFICATION OF HYPERSPECTRAL AND LIDAR DATA

2015 ◽  
Vol XL-1-W5 ◽  
pp. 1-4
Author(s):  
B. Abbasi ◽  
H. Arefi ◽  
B. Bigdeli
Keyword(s):  
Dimension Reduction ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Principal Component ◽  
Decision Fusion ◽  
Object Identification ◽  
Hyperspectral Data ◽  
Majority Voting ◽  
Svm Classifier ◽  
Lidar Data

The existence of various natural objects such as grass, trees, and rivers along with artificial manmade features such as buildings and roads, make it difficult to classify ground objects. Consequently using single data or simple classification approach cannot improve classification results in object identification. Also, using of a variety of data from different sensors; increase the accuracy of spatial and spectral information. In this paper, we proposed a classification algorithm on joint use of hyperspectral and Lidar (Light Detection and Ranging) data based on dimension reduction. First, some feature extraction techniques are applied to achieve more information from Lidar and hyperspectral data. Also Principal component analysis (PCA) and Minimum Noise Fraction (MNF) have been utilized to reduce the dimension of spectral features. The number of 30 features containing the most information of the hyperspectral images is considered for both PCA and MNF. In addition, Normalized Difference Vegetation Index (NDVI) has been measured to highlight the vegetation. Furthermore, the extracted features from Lidar data calculated based on relation between every pixel of data and surrounding pixels in local neighbourhood windows. The extracted features are based on the Grey Level Co-occurrence Matrix (GLCM) matrix. In second step, classification is operated in all features which obtained by MNF, PCA, NDVI and GLCM and trained by class samples. After this step, two classification maps are obtained by SVM classifier with MNF+NDVI+GLCM features and PCA+NDVI+GLCM features, respectively. Finally, the classified images are fused together to create final classification map by decision fusion based majority voting strategy.

Pemetaan Pulau Kecil Gelasa Kabupaten Bangka Tengah

2019 ◽  
Vol 2 (1) ◽  
pp. 11-14
Author(s):  
Wahyu Adi
Keyword(s):  
Coral Reefs ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Image Interpretation ◽  
Vegetation Coverage ◽  
Small Island ◽  
Shallow Waters ◽  
Small Islands ◽  
Seagrass Beds ◽  
Cover Density

Pulau Kecil Gelasa merupakan daerah yang belum banyak diteliti. Pemetaan ekosistem di pulau kecil dilakukan dengan bantuan citra Advanced Land Observing Satellite (ALOS). Penelitian terdahulu diketahui bahwa ALOS memiliki kemampuan memetakan terumbu karang dan padang lamun di perairan dangkal serta mampu memetakan kerapatan penutupan vegetasi. Metode interpretasi citra menggunakan alogaritma indeks vegetasi pada citra ALOS yaitu NDVI (Normalized Difference Vegetation Index), serta pendekatan Lyzengga untuk mengkoreksi kolom perairan. Hasil penelitian didapatkan luasan Padang Lamun di perairan dangkal 41,99 Ha, luasan Terumbu Karang 125,57 Ha. Hasil NDVI di daratan/ pulau kecil Gelasa untuk Vegetasi Rapat seluas 47,62 Ha; luasan penutupan Vegetasi Sedang 105,86 Ha; dan penutupan Vegetasi Jarang adalah 34,24 Ha.   Small Island Gelasa rarely studied. Mapping ecosystems on small islands with the image of Advanced Land Observing Satellite (ALOS). Previous research has found that ALOS has the ability to map coral reefs and seagrass beds in shallow water, and is able to map vegetation cover density. The method of image interpretation uses the vegetation index algorithm in the ALOS image, NDVI (Normalized Difference Vegetation Index), and the Lyzengga approach to correct the water column. The results of the study were obtained in the area of Seagrass Padang in the shallow waters of 41.99 ha, the area of coral reefs was 125.57 ha. NDVI results on land / small islands Gelasa for dense vegetation of 47.62 ha; area of Medium Vegetation coverage 105.86 Ha; and the coverage of Rare Vegetation is 34.24 Ha.

HEALTHINESS OF OIL PALM PLANTATION TOWARDS SUSTAINABILITY OF ENVIRONMENT

2020 ◽  
Vol 7 (1) ◽  
pp. 21
Author(s):  
Faradina Marzukhi ◽  
Nur Nadhirah Rusyda Rosnan ◽  
Md Azlin Md Said
Keyword(s):  
Oil Palm ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Vegetation Indices ◽  
Soil Nutrient ◽  
Oil Palm Plantation ◽  
Sustainable Environment ◽  
Moisture Analysis ◽  
The Relationship

The aim of this study is to analyse the relationship between vegetation indices of Normalized Difference Vegetation Index (NDVI) and soil nutrient of oil palm plantation at Felcra Nasaruddin Bota in Perak for future sustainable environment. The satellite image was used and processed in the research. By Using NDVI, the vegetation index was obtained which varies from -1 to +1. Then, the soil sample and soil moisture analysis were carried in order to identify the nutrient values of Nitrogen (N), Phosphorus (P) and Potassium (K). A total of seven soil samples were acquired within the oil palm plantation area. A regression model was then made between physical condition of the oil palms and soil nutrients for determining the strength of the relationship. It is hoped that the risk map of oil palm healthiness can be produced for various applications which are related to agricultural plantation.

ANALISIS SPEKTRAL CITRA SPOT 7 UNTUK IDENTIFIKASI KAWASAN MANGROVE DI PANTAI TIMUR KABUPATEN LAMPUNG SELATAN

2019 ◽  
Vol 3 ◽  
pp. 1213
Author(s):  
Nirmawana Simarmata ◽  
Fitralia Elyza ◽  
Rezalian Vatiady
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index

Konversi hutan manggrove merupakan sumber utama emisi CO dengan jumlah sebesar 1,7 ± 0,6 Pg karbon per tahun. Kegiatan konversi hutan mangrove menjadi lahan tambak melepaskan cadangan karbon ke atmosfir dalam jumlah yang cukup berarti. Ekspansi usaha pertambakan udang di kawasan pesisir Provinsi Lampung semakin meluas dari tahun ke tahun yang berdampak serius pada kondisi hutan mangrove. Kebijakan pembukaan tambak baru telah mengubah bentang hutan mangrove dan akan menimbulkan kerugian sosial yang jauh lebih besar. Menanggapi permasalahan tersebut, Indonesia menjadi salah satu negara yang mengikuti program Reduce Emission from Deforestation and Degradation atau REDD+ dalam melakukan inventarisasi karbon hutan. Indonesia memiliki potensi sumberdaya hutan mangrove yang sangat melimpah. Potensi hutan mangrove Indonesia cukup besar, Indonesia memiliki luas hutan mangrove terbesar di dunia. Salah satunya di Kabupaten Lampung Selatan merupakan kawasan dengan tutupan yang relatif luas di Provinsi Lampung. Karakteristik hutan mangrove dianalisis berdasarkan nilai spektral nya dengan menggunakan indeks vegetasi. Jenis data penginderaan jauh yang digunakan untuk penelitian ini adalah citra SPOT 7. Citra SPOT 7 dianalisis menggunakan Normalized Difference Vegetation Index (NDVI) sehingga diperoleh nilai kehijauan objek mangrove. Nilai indeks vegetasi pada kawasan penelitian mempunyai range antara 0.2 – 0.7. Nilai indeks vegetasi digunakan sebagai parameter untuk memetakan kawasan hutan mangrove di Kabupaten Lampung Selatan.

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