Feature extraction and analysis of reclaimed vegetation in ecological restoration area of abandoned mines based on hyperspectral remote sensing images

The vegetation growth status largely represents the ecosystem function and environmental quality.Hyperspectral remote sensing data can effectively eliminate the effects of surface spectral reflectance and atmospheric scattering and directly reflect the vegetation parameter information.In this study,the abandoned mining area in the Helan Mountains,China was taken as the study area.Based on hyperspectral remote sensing images of Zhuhai No.1 hyperspectral satellite,we used the pixel dichotomy model,which was constructed using the normalized difference vegetation index(NDVI),to estimate the vegetation coverage of the study area,and evaluated the vegetation growth status by five vegetation indices(NDVI,ratio vegetation index(RVI),photochemical vegetation index(PVI),red-green ratio index(RGI),and anthocyanin reflectance index 1(ARI1)).According to the results,the reclaimed vegetation growth status in the study area can be divided into four levels(unhealthy,low healthy,healthy,and very healthy).The overall vegetation growth status in the study area was generally at low healthy level,indicating that the vegetation growth status in the study area was not good due to short-time period restoration and harsh damaged environment such as high and steep rock slopes.Furthermore,the unhealthy areas were mainly located in Dawukougou where abandoned mines were concentrated,indicating that the original mining activities have had a large effect on vegetation ecology.After ecological restoration of abandoned mines,the vegetation coverage in the study area has increased to a certain extent,but the amplitude was not large.The situation of vegetation coverage in the northern part of the study area was worse than that in the southern part,due to abandoned mines mainly concentrating in the northern part of the Helan Mountains.The combination of hyperspectral remote sensing data and vegetation indices can comprehensively extract the characteristics of vegetation,accurately analyze the plant growth status,and provide technical support for vegetation health evaluation.

Stem Respiration of a Larch (Larix gmelini) Plantation in Northeast China

Stem respiration is an important part of the activity of a tree and is an important source of CO2 evolution from a forest ecosystem. Presently, no standard methods are available for the accurate estimation of total stem CO2 efflux from a forest. In the current study, a 33-year-old (by the year 2001) larch (Larix gmelini Rupr.) plantation was measured throughout 2001-2002 to analyze its monthly and seasonal patterns of stem respiration. Stem respiration rate was also measured at different heights, at different daily intervals and any variation in the larch plantation was recorded. The relationship between stem temperature, growth status and respiration rate was analyzed. Higher respiration rates were recorded in upper reaches of the larch tree throughout the season and these were affected partially by temperature difference. Midday depression was found in the diurnal changes in stem respiration. In the morning, but not in the afternoon, stem respiration was positively correlated with stem temperature. The reason for this variation may be attributed to water deficit, which was stronger in the afternoon. In the larch plantation, a maximum 7-fold variation in stem respiration was found. The growth status (such as mean growth rate of stem and canopy projection area) instead of stem temperature difference was positively correlated with this large variation. An S-model (sigmoid curve) or Power model shows the greatest regression of the field data. In the courses of seasonal and annual changes of stem respiration, peak values were observed in July of both years, but substantial interannual differences in magnitude were observed. An exponential model can clearly show this regression of the temperature-respiration relationship. In our results, Q(10) values ranged from 2.22 in 2001 to 3.53 in 2002. Therefore, estimation of total stem CO2 efflux only by a constant Q(10) value may give biased results. More parameters of growth status and water status should be considered for more accurate estimation.

Development and application of crop monitoring system for detecting chlorophyll content of tomato seedlings

A crop monitoring system was developed to nondestructively monitor the crop growth status in the field.With a two channel multispectral camera with one lens,controlling platform,wireless remote control module and control software,the system was able to synchronously acquire visible image(red(R),green(G),blue(B):400-700 nm)and near-infrared(NIR)image(760-1000 nm).The tomato seedlings multi-spectral images collection experiment in the greenhouse was conducted by using the developed system from the seeding stage to fruiting stage.More than 240 couples of tomato seedlings pictures were acquired with the Soil and Plant Analyzer Development(SPAD)value measured at the same time.The obtained images were available to process,and some vegetation indexes,such as normalized difference vegetation index(NDVI),ratio vegetation index(RVI)and normalized difference green index(NDGI),were calculated.Considering the SPAD value and the correlation coefficient between SPAD and other parameters in different fertilization treatments,the multiple linear regressions(MLR)model for estimating tomato seedlings chlorophyll content was built based on the average gray value in red,green,blue and NIR,vegetable indexes,NDVI,RVI and NDGI in the 33.3%(N1),66.6%(N2),and 100%(N3)nutrient levels during seeding stage and blossom and fruit stage.The R2 of the model is 0.88.The results revealed that the developed crop monitoring system provided a feasible tool to detect the growth status of tomato.More filed experiments and multi-spectral image analysis will be investigated to evaluate the crop growth status in the near future.