Decision tree classification of land cover from remotely sensed data

Decision tree classification algorithms have significant potential for land cover mapping problems and have not been tested in detail by the remote sensing community relative to more conventional pattern recognition techniques such as maximum likelihood classification. In this paper, we present several types of decision tree classification algorithms arid evaluate them on three different remote sensing data sets. The decision tree classification algorithms tested include an univariate decision tree, a multivariate decision tree, and a hybrid decision tree capable of including several different types of classification algorithms within a single decision tree structure. Classification accuracies produced by each of these decision tree algorithms are compared with both maximum likelihood and linear discriminant function classifiers. Results from this analysis show that the decision tree algorithms consistently outperform the maximum likelihood and linear discriminant function classifiers in regard to classf — cation accuracy. In particular, the hybrid tree consistently produced the highest classification accuracies for the data sets tested. More generally, the results from this work show that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure. Further, decision tree algorithms are strictly nonparametric and, therefore, make no assumptions regarding the distribution of input data, and are flexible and robust with respect to nonlinear and noisy relations among input features and class labels.

Land-cover classification of China: integrated analysis of AVHRR imagery and geophysical data

Over last two decades, numerous studies have used remotely sensed data from the Advanced Very High Resolution Radiometer (AVHRR) sensors to map land use and land cover at large spatial scales, but achieved only limited success. In this paper, we employed an approach that combines both AVHRR images and geophysical datasets (e.g. climate, elevation). Three geophysical datasets are used in this study: annual mean temperature, annual precipitation, and elevation. We first divide China into nine bio-climatic regions, using the long-term mean climate data. For each of nine regions, the three geophysical data layers are stacked together with AVHRR data and AVHRR-derived vegetation index (Normalized Difference Vegetation Index) data, and the resultant multi-source datasets were then analysed to generate land-cover maps for individual regions, using supervised classification algorithms. The nine land-cover maps for individual regions were assembled together for China. The existing land-cover dataset derived from Landsat Thematic Mapper (TM) images was used to assess the accuracy of the classification that is based on AVHRR and geophysical data. Accuracy of individual regions varies from 73% to 89%, with an overall accuracy of 81% for China. The results showed that the methodology used in this study is, in general, feasible for large-scale land-cover mapping in China.

Validating MODIS-derived land surface evapotranspiration with in situ measurements at two AmeriFlux sites in a semiarid region

Reducing uncertainties in the estimation of land surface evapotranspiration (ET) from remote-sensing data is essential to better understand earth-atmosphere interactions. This paper demonstrates the applicability of temperature-vegetation index triangle (T-s-VI) method in estimating regional ET and evaporative fraction (EF, defined as the ratio of latent heat flux to surface available energy) from MODIS/Terra and MODIS/Aqua products in a semiarid region. We have compared the satellite-based estimates of ET and EF with eddy covariance measurements made over 4 years at two semiarid grassland sites: Audubon Ranch (AR) and Kendall Grassland (KG). The lack of closure in the eddy covariance measured surface energy components is shown to be more serious at MODIS/Aqua overpass time than that at MODIS/Terra overpass time for both AR and KG sites. The T-s-VI-derived EF could reproduce in situ EF reasonably well with BIAS and root-mean-square difference (RMSD) of less than 0.07 and 0.13, respectively. Surface net radiation has been shown to be systematically overestimated by as large as about 60 W/m(2). Satisfactory validation results of the T-s-VI-derived sensible and latent heat fluxes have been obtained with RMSD within 54 W/m(2). The simplicity and yet easy use of the T-s-VI triangle method show a great potential in estimating regional ET with highly acceptable accuracy that is of critical significance in better understanding water and energy budgets on the Earth. Nevertheless, more validation work should be carried out over various climatic regions and under other different land use/land cover conditions in the future.

Industrial development and land use/cover change and their effects on local environment: a case study of Changshu in eastern coastal China

The interactions among industrial development, land use/cover change (LUCC), and environmental effects in Changshu in the eastern coastal China were analyzed using high-resolution Landsat TM data in 1990, 1995, 2000, and 2006, socio-economic data and water environmental quality monitoring data from research institutes and governmental departments. Three phases of industrial development in Changshu were examined (i.e., the three periods of 1990 to 1995, 1995 to 2000, and 2000 to 2006). Besides industrial development and rapid urbanization, land use/cover in Changshu had changed drastically from 1990 to 2006. This change was characterized by major replacements of farmland by urban and rural settlements, artificial ponds, forested and constructed land. Industrialization, urbanization, agricultural structure adjustment, and rural housing construction were the major socio-economic driving forces of LUCC in Changshu. In addition, the annual value of ecosystem services in Changshu decreased slightly during 1990-2000, but increased significantly during 2000-2006. Nevertheless, the local environmental quality in Changshu, especially in rural areas, has not yet been improved significantly. Thus, this paper suggests an increased attention to fully realize the role of land supply in adjustment of environment-friendly industrial structure and urban-rural spatial restructuring, and translating the land management and environmental protection policies into an optimized industrial distribution and land-use pattern.

Relationships between precipitation, soil water and groundwater at Chongling catchment with the typical vegetation cover in the Taihang mountainous region, China

Vegetation cover plays an important role in the process of evaporation and infiltration. To explore the relationships between precipitation, soil water and groundwater in Taihang mountainous region, China, precipitation, soil water and water table were observed from 2004 to 2006, and precipitation, soil water and groundwater were sampled in 2004 and 2005 for oxygen-18 and deuterium analysis at Chongling catchment. The soil water was sampled at three sites covered by grass (Carex humilis and Carex lanceolata), acacia and arborvitae respectively. Precipitation is mainly concentrated in rainy seasons and has no significant spatial variance in study area. The stable isotopic compositions are enriched in precipitation and soil water due to the evaporation. The analysis of soil water potential and isotopic profiles shows that evaporation of soil water under arborvitae cover is weaker than under grass and acacia, while soil water evaporation under grass and acacia showed no significant difference. Both delta O-18 profiles and soil water potential dynamics reveal that the soil under acacia allows the most rapid infiltration rate, which may be related to preferential flow. In the process of infiltration after a rainstorm, antecedent water still takes up over 30% of water in the topsoil. The soil water between depths of 0-115 cm under grass has a residence time of about 20 days in the rainy season. Groundwater recharge from precipitation mainly occurs in the rainy season, especially when rainstorms or successive heavy rain events happen.

Radiation-use efficiency and the harvest index of winter wheat at different nitrogen levels and their relationships to canopy spectral reflectance

Radiation-use efficiency (RUE, g/MJ) and the harvest index (HI, unitless) are two helpful characteristics in interpreting crop response to environmental and climatic changes. They are also increasingly important for accurate crop yield simulation, but they are affected by various environmental factors. In this study, the RUE and HI of winter wheat and their relationships to canopy spectral reflectance were investigated based on the massive field measurements of five nitrogen (N) treatments. Crop production can be separated into light interception and RUE. The results indicated that during a long period of slow growth from emergence to regreening, the effect of N on crop production mainly showed up in an increased light interception by the canopy. During the period of rapid growth from regreening to maturity, it was present in both light interception and RUE. The temporal variations of RUEAPAR (aboveground biomass produced per unit of photosynthetically active radiation absorbed by the canopy) during the period from regreening to maturity had different patterns corresponding to the N deficiency, N adequacy and N-excess conditions. Moreover, significant relationships were found between the RUEAPAR and the accumulative normalised difference vegetation index (NDVI) in the integrated season (R-2 = 0.68), between the HI and the accumulative NDVI after anthesis (R-2 = 0.89), and between the RUEgrain (ratio of grain yield to the total amount of photosynthetically active radiation absorbed by the canopy) and the accumulative NDVI of the whole season (R-2 = 0.89) and that after anthesis (R-2 = 0.94). It suggested that canopy spectral reflectance has the potential to reveal the spatial information of the RUEAPAR, HI and RUEgrain. It is hoped that this information will be useful in improving the accuracy of crop yield simulation in large areas.

The characteristics of land cover and macroscopical ecology changes in the source region of three rivers in Qinghai-Tibet plateau during last 30 years

We obtained four phases of land cover spatial data sets by interpreting MSS images of middle and late 1970s and three phases of TM images of late 1980s, 2004 and 2008 based on field investigation in Three Rivers' Source Region. We analyzed the temporal and spatial characteristics of land cover and macro ecological changes in Three Rivers' Source Region in Qinghai-Tibet plateau since middle and late 1970s. Indicated by land cover condition index change rate and land cover change index, land cover and macroscopical ecological condition degenerated (7090 period Zc -0.63, LCCI -0.58)-obviously degenerated (9004 period, Zc -0.94, LCCI -1.76)-slightly meliorated (0408 period, Zc 0.06, LCCI 0.33). This course was jointly driven by climate change, grassland stocking pressure and implement of ecological construction project.

Assessing the potential of VEGETATION sensor data for mapping snow and ice cover: a Normalized Difference Snow and Ice Index

The VEGETATION (VGT) sensor in SPOT 4 has four spectral bands that are equivalent to Landsat Thematic Mapper (TM) bands (blue, red, near-infrared and mid-infrared spectral bands) and provides daily images of the global land surface at a 1-km spatial resolution. We propose a new index for identifying and mapping of snow ice cover, namely the Normalized Difference Snow/Ice Index (NDSII), which uses reflectance values of red and mid-infrared spectral bands of Landsat TM and VGT. For Landsat TM data, NDSII is calculated as NDSIITM =(TM3 -TM5)/(TM3 +TM5); for VGT data, NDSII is calculated as NDSIIVGT =(B2- MIR)/(B2 + MIR). As a case study we used a Landsat TM image that covers the eastern part of the Qilian mountain range in the Qinghai-Xizang (Tibetan) plateau of China. NDSIITM gave similar estimates of the area and spatial distribution of snow/ice cover to the Normalized Difference Snow Index (NDSI=(TM2-TM5)/(TM2+TM5)) which has been proposed by Hall et al. The results indicated that the VGT sensor might have the potential for operational monitoring and mapping of snow/ice cover from regional to global scales, when using NDSIIVGT.