Towards understanding climate change impacts: monitoring the vegetation dynamics of terrestrial national parks in Indonesia.

Monitoring vegetation dynamics in terrestrial national parks (TNPs) is crucial for ensuring sustainable environmental management and mitigating the potential negative impacts of short- and long-term disturbances understanding the effect of climate change within natural and protected areas. This study aims to monitor the vegetation dynamics of TNPs in Indonesia by first categorizing them into the regions of Sumatra, Jawa, Kalimantan, Sulawesi, and Eastern Indonesia and then applying ready-to-use MODIS EVI time-series imageries (MOD13Q1) taken from 2000 to 2022 on the GEE cloud-computing platform. Specifically, this research investigates the greening and browning fraction trends using Sen's slope, considers seasonality by analyzing the maximum and minimum EVI values, and assesses anomalous years by comparing the annual time series and long-term median EVI value. The findings reveal significantly increasing greening trends in most TNPs, except Danau Sentarum, from 2000 to 2022. The seasonality analysis shows that most TNPs exhibit peak and trough greenness at the end of the rainy and dry seasons, respectively, as the vegetation response to precipitation increases and decreases. Anomalies in seasonality that is affected by climate change was detected in all of the regions. To increase TNPs resilience, suggested measures include active reforestation and implementation of Assisted Natural Regeneration, strengthen the enforcement of fundamental managerial task, and forest fire management.

Temporal variation of normalized difference vegetation index (NDVI) and calculation of the crop coefficient (Kc ) from NDVI in areas cultivated with irrigated soybean / Variação temporal do Índice de Vegetação por Diferença Normalizada (NDVI) e obtenção do coeficiente de cultura (Kc ) a partir do NDVI em áreas cultivadas com soja irrigada

ABSTRACT: Vegetation indices obtained by remote sensing products have various applications in agriculture. An important application of the Normalized Difference Vegetation Index (NDVI) is obtaining the crop coefficient (Kc). The aims of this study were to analyze NDVI temporal profiles and to obtain Kc from the NDVI vegetation index product MOD13Q1. The analysis is based on the phenological stages of irrigated soybean crops in the municipality of Planura/MG during the 2010/2011 growing season. Areas planted with irrigated soybean were identified through fieldwork. Temporal series of the MOD13Q1 products were used to analyze NDVI, allowing the extraction of NDVI values for all points in the period studied. The NDVI temporal profiles showed a similar pattern to each other and corresponded to the crop cycle. The KcNDVI values for the MOD13Q1 products were well correlated to the FAO Kc values (r2=0.72). Thus, NDVI can be used as an alternative for obtaining crop coefficient (Kc).

RESUMO: Os índices de vegetação obtidos a partir de produtos de sensoriamento remoto apresentam várias aplicações na agricultura. Uma importante aplicação do índice de vegetação Normalized Difference Vegetation Index (NDVI) está relacionada à obtenção do coeficiente de cultura (Kc). Assim, o objetivo deste trabalho foi analisar os perfis temporais de NDVI e obter o Kc a partir do produto de índice de vegetação NDVI (MOD13Q1), baseado na análise dos estádios fenológicos da cultura de soja irrigada, no município de Planura/MG, safra 2010/2011. A identificação das áreas plantadas com soja irrigada foi feita através de pesquisa de campo. As séries temporais do produto MOD13Q1 foram utilizadas para analisar o NDVI, permitindo a extração dos valores de NDVI para todos os pontos no período estudado. Os perfis temporais de NDVI apresentaram um padrão semelhante entre si e quanto ao ciclo da cultura. Os valores de KcNDVI variaram, em média, de acordo com os valores de Kc FAO, representando uma correlação linear (r2) de 0,72 para o produto MOD13Q1. Assim, o NDVI pode ser usado como uma alternativa na obtenção do Kc.

Effectiveness of China's National Forest Protection Program and nature reserves.

There is profound interest in knowing the degree to which China's institutions are capable of protecting its natural forests and biodiversity in the face of economic and political change. China's 2 most important forest-protection policies are its National Forest Protection Program (NFPP) and its national-level nature reserves (NNRs). The NFPP was implemented in 2000 in response to deforestation-caused flooding. We undertook the first national, quantitative assessment of the NFPP and NNRs to examine whether the NFPP achieved its deforestation-reduction target and whether the NNRs deter deforestation altogether. We used MODIS data to estimate forest cover and loss across mainland China (2000-2010). We also assembled the first-ever polygon dataset for China's forested NNRs (n = 237, 74,030 km(2) in 2000) and used both conventional and covariate-matching approaches to compare deforestation rates inside and outside NNRs (2000-2010). In 2000, 1.765 million km(2) or 18.7% of mainland China was forested (12.3% with canopy cover of ≥70%)) or woodland (6.4% with canopy cover <70% and tree plus shrub cover ≥40%). By 2010, 480,203 km(2) of forest and woodland had been lost, an annual deforestation rate of 2.7%. Forest-only loss was 127,473 km(2) (1.05% annually). In the NFPP provinces, the forest-only loss rate was 0.62%, which was 3.3 times lower than in the non-NFPP provinces. Moreover, the Landsat data suggest that these loss rates are overestimates due to large MODIS pixel size. Thus, China appears to have achieved, and even exceeded, its target of reducing deforestation to 1.1% annually in the NFPP provinces. About two-thirds of China's NNRs were effective in protecting forest cover (prevented loss 4073 km(2) unmatched approach; 3148 km(2) matched approach), and within-NNR deforestation rates were higher in provinces with higher overall deforestation. Our results indicate that China's existing institutions can protect domestic forest cover.