estimating forest leaf area index using satellite images : comparison of k - nn based landsat - nFi lai with moDis - rsr based lai product for Finland

نویسنده

  • Eero Nikinmaa
چکیده

Leaf area index (LAI) is a key variable for many ecological models, but it is typically not available from basic forest inventories. In this study, we (1) construct a high-resolution LAI map using k nearest-neighbor (k-NN) imputation based on National Forest Inventory data and Landsat 5 TM images (Landsat-NFI LAI), and (2) examine a moderate-resolution LAI map produced based on reduced simple ratio derived from MODIS reflectances (MODISRSR LAI). The maps cover all the forested areas in Finland. Country-level averages of Landsat-NFI and MODIS-RSR LAI were at same level, but several geographical and land-use related differences between them were detected. Difference was the largest in the lake district of Finland and in northern Finland, and it increased with decreasing share of forests and increasing share of deciduous trees. As MODIS-RSR LAI does not take into account the subpixel variation in land use, Landsat-NFI LAI was found to produce more reliable estimates.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Evaluation of the MODIS LAI algorithm at a coniferous forest site in Finland

Leaf area index (LAI) collected in a needle-leaf forest site near Ruokolahti, Finland, during a field campaign in June 14–21, 2000, was used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) LAI algorithm. The field LAI data was first related to 30-m resolution Enhanced Thermal Mapper Plus (ETM+) images using empirical methods to create a high-resolution LAI map. The analysis of...

متن کامل

Validation of the MODIS LAI Product in Coniferous Forest of Ruokolahti, Finland

Leaf area index collected in a needle-leaf forest site near Ruokolahti, Finland, during a field campaign in June 14-21, 2000, was used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) LAI and FPAR algorithm. The field LAI data was first related to 30m resolution Enhanced Thermal Mapper Plus (ETM+) images using empirical methods to create a high resolution LAI map. It shows that...

متن کامل

Analysis of LAI in Iran based on MODIS satellite data

This study was performed to evaluate the extent of leaf area in Iran from (2002) to (2016) using Remote sensing. For this purpose, we extracted data collection and leaf area index for the Iranian territory from MODIS website. The database was established with programming in MATLAB software to perform mathematical and Statistical calculations repeated. After the analysis of the data in this soft...

متن کامل

seasonal changes in canopy leaf area index and moDis vegetation products for a boreal forest site in central Finland

Seasonal change in leaf area index (LAI) is highly important in remote sensing of land surface phenology because LAI is a main driving factor of forest reflectance. We present a time series of in situ measurements of boreal forest LAI expanding throughout the growing period from budburst to senescence. We measured the LAI of 20 stands at approximately two-week intervals between mid-May and mid-...

متن کامل

Reduced Simple Ratio Better than NDVI for Estimating LAI in Finnish Pine and Spruce Stands

Estimation of leaf area index (LAI) using spectral vegetation indices (SVIs) was studied based on data from 683 plots on two Scots pine and Norway spruce dominated sites in Finland. The SVIs studied included the normalised difference vegetation index (NDVI), the simple ratio (SR), and the reduced simple ratio (RSR), and were calculated from Landsat ETM images of the two sites. Regular grids of ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015